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1,802.0406
Notable Characteristics Search through Knowledge Graphs
Query answering routinely employs knowledge graphs to assist the user in the search process. Given a knowledge graph that represents entities and relationships among them, one aims at complementing the search with intuitive but effective mechanisms. In particular, we focus on the comparison of two or more entities and the detection of unexpected, surprising properties, called notable characteristics. Such characteristics provide intuitive explanations of the peculiarities of the selected entities with respect to similar entities. We propose a solid probabilistic approach that first retrieves entity nodes similar to the query nodes provided by the user, and then exploits distributional properties to understand whether a certain attribute is interesting or not. Our preliminary experiments demonstrate the solidity of our approach and show that we are able to discover notable characteristics that are indeed interesting and relevant for the user.
cs.DB
query answering routinely employs knowledge graphs to assist the user in the search process given a knowledge graph that represents entities and relationships among them one aims at complementing the search with intuitive but effective mechanisms in particular we focus on the comparison of two or more entities and the detection of unexpected surprising properties called notable characteristics such characteristics provide intuitive explanations of the peculiarities of the selected entities with respect to similar entities we propose a solid probabilistic approach that first retrieves entity nodes similar to the query nodes provided by the user and then exploits distributional properties to understand whether a certain attribute is interesting or not our preliminary experiments demonstrate the solidity of our approach and show that we are able to discover notable characteristics that are indeed interesting and relevant for the user
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1,802.04061
Abelian extensions and crossed modules of Hom-Lie algebras
In this paper we study the low dimensional cohomology groups of Hom-Lie algebras and their relation with derivations, abelian extensions and crossed modules. On one hand, we introduce the notion of $\alpha$-abelian extensions and we obtain a five term exact sequence in cohomology. On the other hand, we introduce crossed modules of Hom-Lie algebras showing their equivalence with cat$^1$-Hom-Lie algebras, and we introduce $\alpha$-crossed modules to have a better understanding of the third cohomology group.
math.RA
in this paper we study the low dimensional cohomology groups of homlie algebras and their relation with derivations abelian extensions and crossed modules on one hand we introduce the notion of alphaabelian extensions and we obtain a five term exact sequence in cohomology on the other hand we introduce crossed modules of homlie algebras showing their equivalence with cat1homlie algebras and we introduce alphacrossed modules to have a better understanding of the third cohomology group
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1,802.04062
Elastic modeling of point-defects and their interaction
Different descriptions used to model a point-defect in an elastic continuum are reviewed. The emphasis is put on the elastic dipole approximation, which is shown to be equivalent to the infinitesimal Eshelby inclusion and to the infinitesimal dislocation loop. Knowing this elastic dipole, a second rank tensor fully characterizing the point-defect, one can directly obtain the long-range elastic field induced by the point-defect and its interaction with other elastic fields. The polarizability of the point-defect, resulting from the elastic dipole dependence with the applied strain, is also introduced. Parameterization of such an elastic model, either from experiments or from atomic simulations, is discussed. Different examples, like elastodiffusion and bias calculations, are finally considered to illustrate the usefulness of such an elastic model to describe the evolution of a point-defect in a external elastic field.
cond-mat.mtrl-sci
different descriptions used to model a pointdefect in an elastic continuum are reviewed the emphasis is put on the elastic dipole approximation which is shown to be equivalent to the infinitesimal eshelby inclusion and to the infinitesimal dislocation loop knowing this elastic dipole a second rank tensor fully characterizing the pointdefect one can directly obtain the longrange elastic field induced by the pointdefect and its interaction with other elastic fields the polarizability of the pointdefect resulting from the elastic dipole dependence with the applied strain is also introduced parameterization of such an elastic model either from experiments or from atomic simulations is discussed different examples like elastodiffusion and bias calculations are finally considered to illustrate the usefulness of such an elastic model to describe the evolution of a pointdefect in a external elastic field
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1,802.04063
Taking gradients through experiments: LSTMs and memory proximal policy optimization for black-box quantum control
In this work we introduce the application of black-box quantum control as an interesting rein- forcement learning problem to the machine learning community. We analyze the structure of the reinforcement learning problems arising in quantum physics and argue that agents parameterized by long short-term memory (LSTM) networks trained via stochastic policy gradients yield a general method to solving them. In this context we introduce a variant of the proximal policy optimization (PPO) algorithm called the memory proximal policy optimization (MPPO) which is based on this analysis. We then show how it can be applied to specific learning tasks and present results of nu- merical experiments showing that our method achieves state-of-the-art results for several learning tasks in quantum control with discrete and continouous control parameters.
cs.LG quant-ph
in this work we introduce the application of blackbox quantum control as an interesting rein forcement learning problem to the machine learning community we analyze the structure of the reinforcement learning problems arising in quantum physics and argue that agents parameterized by long shortterm memory lstm networks trained via stochastic policy gradients yield a general method to solving them in this context we introduce a variant of the proximal policy optimization ppo algorithm called the memory proximal policy optimization mppo which is based on this analysis we then show how it can be applied to specific learning tasks and present results of nu merical experiments showing that our method achieves stateoftheart results for several learning tasks in quantum control with discrete and continouous control parameters
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1,802.04064
A Contextual Bandit Bake-off
Contextual bandit algorithms are essential for solving many real-world interactive machine learning problems. Despite multiple recent successes on statistically and computationally efficient methods, the practical behavior of these algorithms is still poorly understood. We leverage the availability of large numbers of supervised learning datasets to empirically evaluate contextual bandit algorithms, focusing on practical methods that learn by relying on optimization oracles from supervised learning. We find that a recent method (Foster et al., 2018) using optimism under uncertainty works the best overall. A surprisingly close second is a simple greedy baseline that only explores implicitly through the diversity of contexts, followed by a variant of Online Cover (Agarwal et al., 2014) which tends to be more conservative but robust to problem specification by design. Along the way, we also evaluate various components of contextual bandit algorithm design such as loss estimators. Overall, this is a thorough study and review of contextual bandit methodology.
stat.ML cs.LG
contextual bandit algorithms are essential for solving many realworld interactive machine learning problems despite multiple recent successes on statistically and computationally efficient methods the practical behavior of these algorithms is still poorly understood we leverage the availability of large numbers of supervised learning datasets to empirically evaluate contextual bandit algorithms focusing on practical methods that learn by relying on optimization oracles from supervised learning we find that a recent method foster et al 2018 using optimism under uncertainty works the best overall a surprisingly close second is a simple greedy baseline that only explores implicitly through the diversity of contexts followed by a variant of online cover agarwal et al 2014 which tends to be more conservative but robust to problem specification by design along the way we also evaluate various components of contextual bandit algorithm design such as loss estimators overall this is a thorough study and review of contextual bandit methodology
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1,802.04065
Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders
In this paper, we study the ability to make the short-term prediction of the exchange price fluctuations towards the United States dollar for the Bitcoin market. We use the data of realized volatility collected from one of the largest Bitcoin digital trading offices in 2016 and 2017 as well as order information. Experiments are performed to evaluate a variety of statistical and machine learning approaches.
stat.ML cs.LG
in this paper we study the ability to make the shortterm prediction of the exchange price fluctuations towards the united states dollar for the bitcoin market we use the data of realized volatility collected from one of the largest bitcoin digital trading offices in 2016 and 2017 as well as order information experiments are performed to evaluate a variety of statistical and machine learning approaches
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1,802.04066
Accessible bounds for general quantum resources
The recent development of general quantum resource theories has given a sound basis for the quantification of useful quantum effects. Nevertheless, the evaluation of a resource measure can be highly non-trivial, involving an optimisation that is often intractable analytically or intensive numerically. In this paper, we describe a general framework that provides quantitative lower bounds to any resource quantifier that satisfies the essential property of monotonicity under the corresponding set of free operations. Our framework relies on projecting all quantum states onto a restricted subset using a fixed resource non-increasing operation. The resources of the resultant family can then be evaluated using a simplified optimisation, with the result providing lower bounds on the resource contents of any state. This approach also reduces the experimental overhead, requiring only the relevant statistics of the restricted family of states. We illustrate the application of our framework by focusing on the resource of multiqubit entanglement and outline applications to other quantum resources.
quant-ph cond-mat.stat-mech hep-th math-ph math.MP
the recent development of general quantum resource theories has given a sound basis for the quantification of useful quantum effects nevertheless the evaluation of a resource measure can be highly nontrivial involving an optimisation that is often intractable analytically or intensive numerically in this paper we describe a general framework that provides quantitative lower bounds to any resource quantifier that satisfies the essential property of monotonicity under the corresponding set of free operations our framework relies on projecting all quantum states onto a restricted subset using a fixed resource nonincreasing operation the resources of the resultant family can then be evaluated using a simplified optimisation with the result providing lower bounds on the resource contents of any state this approach also reduces the experimental overhead requiring only the relevant statistics of the restricted family of states we illustrate the application of our framework by focusing on the resource of multiqubit entanglement and outline applications to other quantum resources
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1,802.04067
Alternating Nonzero Automata
We introduce a new class of automata on infinite trees called \emph{alternating nonzero automata}, which extends the class of non-deterministic nonzero automata. We reduce the emptiness problem for alternating nonzero automata to the same problem for non-deterministic ones, which implies decidability. We obtain as a corollary algorithms for the satisfiability of a probabilistic temporal logic extending both CTL* and the qualitative fragment of pCTL*.
cs.LO cs.FL
we introduce a new class of automata on infinite trees called emphalternating nonzero automata which extends the class of nondeterministic nonzero automata we reduce the emptiness problem for alternating nonzero automata to the same problem for nondeterministic ones which implies decidability we obtain as a corollary algorithms for the satisfiability of a probabilistic temporal logic extending both ctl and the qualitative fragment of pctl
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1,802.04068
Towards an Open Science Platform for the Evaluation of Data Fusion
Combining the results of different search engines in order to improve upon their performance has been the subject of many research papers. This has become known as the "Data Fusion" task, and has great promise in dealing with the vast quantity of unstructured textual data that is a feature of many Big Data scenarios. However, no universally-accepted evaluation methodology has emerged in the community. This makes it difficult to make meaningful comparisons between the various proposed techniques from reading the literature alone. Variations in the datasets, metrics, and baseline results have all contributed to this difficulty. This paper argues that a more unified approach is required, and that a centralised software platform should be developed to aid researchers in making comparisons between their algorithms and others. The desirable qualities of such a system have been identified and proposed, and an early prototype has been developed. Re-implementing algorithms published by other researchers is a great burden on those proposing new techniques. The prototype system has the potential to greatly reduce this burden and thus encourage more comparable results being generated and published more easily.
cs.IR
combining the results of different search engines in order to improve upon their performance has been the subject of many research papers this has become known as the data fusion task and has great promise in dealing with the vast quantity of unstructured textual data that is a feature of many big data scenarios however no universallyaccepted evaluation methodology has emerged in the community this makes it difficult to make meaningful comparisons between the various proposed techniques from reading the literature alone variations in the datasets metrics and baseline results have all contributed to this difficulty this paper argues that a more unified approach is required and that a centralised software platform should be developed to aid researchers in making comparisons between their algorithms and others the desirable qualities of such a system have been identified and proposed and an early prototype has been developed reimplementing algorithms published by other researchers is a great burden on those proposing new techniques the prototype system has the potential to greatly reduce this burden and thus encourage more comparable results being generated and published more easily
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1,802.04069
Searchers adjust their eye movement dynamics to the target characteristics in natural scenes
When searching a target in a natural scene, both the target's visual properties and similarity to the background influence whether (and how fast) humans are able to find it. However, thus far it has been unclear whether searchers adjust the dynamics of their eye movements (e.g., fixation durations, saccade amplitudes) to the target they search for. In our experiment participants searched natural scenes for six artificial targets with different spatial frequency throughout eight consecutive sessions. High-spatial frequency targets led to smaller saccade amplitudes and shorter fixation durations than low-spatial frequency targets if target identity was known before the trial. If a saccade was programmed in the same direction as the previous saccade (saccadic momentum), fixation durations and successive saccade amplitudes were not influenced by target type. Visual saliency and empirical density at the endpoints of saccadic momentum saccades were comparatively low, indicating that these saccades were less selective. Our results demonstrate that searchers adjust their eye movement dynamics to the search target in a sensible fashion, since low-spatial frequencies are visible farther into the periphery than high-spatial frequencies. Additionally, the saccade direction specificity of our effects suggests a separation of saccades into a default scanning mechanism and a selective, target-dependent mechanism.
q-bio.NC
when searching a target in a natural scene both the targets visual properties and similarity to the background influence whether and how fast humans are able to find it however thus far it has been unclear whether searchers adjust the dynamics of their eye movements eg fixation durations saccade amplitudes to the target they search for in our experiment participants searched natural scenes for six artificial targets with different spatial frequency throughout eight consecutive sessions highspatial frequency targets led to smaller saccade amplitudes and shorter fixation durations than lowspatial frequency targets if target identity was known before the trial if a saccade was programmed in the same direction as the previous saccade saccadic momentum fixation durations and successive saccade amplitudes were not influenced by target type visual saliency and empirical density at the endpoints of saccadic momentum saccades were comparatively low indicating that these saccades were less selective our results demonstrate that searchers adjust their eye movement dynamics to the search target in a sensible fashion since lowspatial frequencies are visible farther into the periphery than highspatial frequencies additionally the saccade direction specificity of our effects suggests a separation of saccades into a default scanning mechanism and a selective targetdependent mechanism
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1,802.0407
Compact embedded surfaces with constant mean curvature in $\mathbb{S}^2\times\mathbb{R}$
We obtain compact orientable embedded surfaces with constant mean curvature $0<H<\frac{1}{2}$ and arbitrary genus in $\mathbb{S}^2\times\mathbb{R}$. These surfaces have dihedral symmetry and desingularize a pair of spheres with mean curvature $\frac{1}{2}$ tangent along an equator. This is a particular case of a conjugate Plateau construction of doubly periodic surfaces with constant mean curvature in $\mathbb{S}^2\times\mathbb{R}$, $\mathbb{H}^2\times\mathbb{R}$, and $\mathbb{R}^3$ with bounded height and enjoying the symmetries of certain tessellations of $\mathbb{S}^2$, $\mathbb{H}^2$, and $\mathbb{R}^2$ by regular polygons.
math.DG
we obtain compact orientable embedded surfaces with constant mean curvature 0hfrac12 and arbitrary genus in mathbbs2timesmathbbr these surfaces have dihedral symmetry and desingularize a pair of spheres with mean curvature frac12 tangent along an equator this is a particular case of a conjugate plateau construction of doubly periodic surfaces with constant mean curvature in mathbbs2timesmathbbr mathbbh2timesmathbbr and mathbbr3 with bounded height and enjoying the symmetries of certain tessellations of mathbbs2 mathbbh2 and mathbbr2 by regular polygons
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1,802.04071
pyGDM -- A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures
pyGDM is a python toolkit for electro-dynamical simulations in nano-optics based on the Green Dyadic Method (GDM). In contrast to most other coupled-dipole codes, pyGDM uses a generalized propagator, which allows to cost-efficiently solve large monochromatic problems such as polarization-resolved calculations or raster-scan simulations with a focused beam or a quantum-emitter probe. A further peculiarity of this software is the possibility to very easily solve 3D problems including a dielectric or metallic substrate. Furthermore, pyGDM includes tools to easily derive several physical quantities such as far-field patterns, extinction and scattering cross-section, the electric and magnetic near-field in the vicinity of the structure, the decay rate of quantum emitters and the LDOS or the heat deposited inside a nanoparticle. Finally, pyGDM provides a toolkit for efficient evolutionary optimization of nanoparticle geometries in order to maximize (or minimize) optical properties such as a scattering at selected resonance wavelengths.
physics.comp-ph cond-mat.mes-hall physics.optics
pygdm is a python toolkit for electrodynamical simulations in nanooptics based on the green dyadic method gdm in contrast to most other coupleddipole codes pygdm uses a generalized propagator which allows to costefficiently solve large monochromatic problems such as polarizationresolved calculations or rasterscan simulations with a focused beam or a quantumemitter probe a further peculiarity of this software is the possibility to very easily solve 3d problems including a dielectric or metallic substrate furthermore pygdm includes tools to easily derive several physical quantities such as farfield patterns extinction and scattering crosssection the electric and magnetic nearfield in the vicinity of the structure the decay rate of quantum emitters and the ldos or the heat deposited inside a nanoparticle finally pygdm provides a toolkit for efficient evolutionary optimization of nanoparticle geometries in order to maximize or minimize optical properties such as a scattering at selected resonance wavelengths
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1,802.04072
Higher structures, quantum groups, and genus zero modular operad
In my Montreal lecture notes of 1988, it was suggested that the theory of linear quantum groups can be presented in the framework of the category of {\it quadratic algebras} (imagined as algebras of functions on "quantum linear spaces"), and quadratic algebras of their inner (co)homomorphisms. Soon it was understood (E. Getzler and J. Jones, V. Ginzburg, M. Kapranov, M. Kontsevich, M. Markl, B. Vallette et al.) that the class of {\it quadratic operads} can be introduced and the main theorems about quadratic algebras can be generalised to the level of such operads, if their components are {\it linear spaces} (or objects of more general monoidal categories.) When quantum cohomology entered the scene, it turned out that the basic tree level (genus zero) (co)operad of quantum cohomology not only is {\it quadratic} one, but its {\it components are themselves quadratic algebras.} In this short note, I am studying the interaction of quadratic algebras structure with operadic structure in the context of enriched category formalism due to G. M. Kelly et al.
math.CT
in my montreal lecture notes of 1988 it was suggested that the theory of linear quantum groups can be presented in the framework of the category of it quadratic algebras imagined as algebras of functions on quantum linear spaces and quadratic algebras of their inner cohomomorphisms soon it was understood e getzler and j jones v ginzburg m kapranov m kontsevich m markl b vallette et al that the class of it quadratic operads can be introduced and the main theorems about quadratic algebras can be generalised to the level of such operads if their components are it linear spaces or objects of more general monoidal categories when quantum cohomology entered the scene it turned out that the basic tree level genus zero cooperad of quantum cohomology not only is it quadratic one but its it components are themselves quadratic algebras in this short note i am studying the interaction of quadratic algebras structure with operadic structure in the context of enriched category formalism due to g m kelly et al
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1,802.04073
Blind Image Deconvolution using Deep Generative Priors
This paper proposes a novel approach to regularize the \textit{ill-posed} and \textit{non-linear} blind image deconvolution (blind deblurring) using deep generative networks as priors. We employ two separate generative models --- one trained to produce sharp images while the other trained to generate blur kernels from lower-dimensional parameters. To deblur, we propose an alternating gradient descent scheme operating in the latent lower-dimensional space of each of the pretrained generative models. Our experiments show promising deblurring results on images even under large blurs, and heavy noise. To address the shortcomings of generative models such as mode collapse, we augment our generative priors with classical image priors and report improved performance on complex image datasets. The deblurring performance depends on how well the range of the generator spans the image class. Interestingly, our experiments show that even an untrained structured (convolutional) generative networks acts as an image prior in the image deblurring context allowing us to extend our results to more diverse natural image datasets.
cs.CV
this paper proposes a novel approach to regularize the textitillposed and textitnonlinear blind image deconvolution blind deblurring using deep generative networks as priors we employ two separate generative models one trained to produce sharp images while the other trained to generate blur kernels from lowerdimensional parameters to deblur we propose an alternating gradient descent scheme operating in the latent lowerdimensional space of each of the pretrained generative models our experiments show promising deblurring results on images even under large blurs and heavy noise to address the shortcomings of generative models such as mode collapse we augment our generative priors with classical image priors and report improved performance on complex image datasets the deblurring performance depends on how well the range of the generator spans the image class interestingly our experiments show that even an untrained structured convolutional generative networks acts as an image prior in the image deblurring context allowing us to extend our results to more diverse natural image datasets
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1,802.04074
Nuclear emulsions for the detection of micrometric-scale fringe patterns: an application to positron interferometry
Nuclear emulsions are capable of very high position resolution in the detection of ionizing particles. This feature can be exploited to directly resolve the micrometric-scale fringe pattern produced by a matter-wave interferometer for low energy positrons (in the 10-20 keV range). We have tested the performance of emulsion films in this specific scenario. Exploiting silicon nitride diffraction gratings as absorption masks, we produced periodic patterns with features comparable to the expected interferometer signal. Test samples with periodicities of 6, 7 and 20 {\mu}m were exposed to the positron beam, and the patterns clearly reconstructed. Our results support the feasibility of matter-wave interferometry experiments with positrons.
physics.ins-det hep-ex
nuclear emulsions are capable of very high position resolution in the detection of ionizing particles this feature can be exploited to directly resolve the micrometricscale fringe pattern produced by a matterwave interferometer for low energy positrons in the 1020 kev range we have tested the performance of emulsion films in this specific scenario exploiting silicon nitride diffraction gratings as absorption masks we produced periodic patterns with features comparable to the expected interferometer signal test samples with periodicities of 6 7 and 20 mum were exposed to the positron beam and the patterns clearly reconstructed our results support the feasibility of matterwave interferometry experiments with positrons
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1,802.04075
On effects of inhomogeneity on anisotropy in Backus average
In general, the Backus average of an inhomogeneous stack of isotropic layers is a transversely isotropic medium. Herein, we examine a relation between this inhomogeneity and the strength of resulting anisotropy, and show that, in general, they are proportional to one another. There is an important case, however, in which the Backus average of isotropic layers results in an isotropic -- as opposed to a transversely isotropic -- medium. We show that it is a consequence of the same rigidity of layers, regardless of their compressibility. Thus, in general, the strength of anisotropy of the Backus average increases with the degree of inhomogeneity among layers, except for the case in which all layers exhibit the same rigidity.
physics.geo-ph
in general the backus average of an inhomogeneous stack of isotropic layers is a transversely isotropic medium herein we examine a relation between this inhomogeneity and the strength of resulting anisotropy and show that in general they are proportional to one another there is an important case however in which the backus average of isotropic layers results in an isotropic as opposed to a transversely isotropic medium we show that it is a consequence of the same rigidity of layers regardless of their compressibility thus in general the strength of anisotropy of the backus average increases with the degree of inhomogeneity among layers except for the case in which all layers exhibit the same rigidity
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1,802.04076
Performance Analysis of Low Latency Multiple Full-Duplex Selective Decode and Forward Relays
In order to follow up with mission-critical applications, new features need to be carried to satisfy a reliable communication with reduced latency. With this regard, this paper proposes a low latency cooperative transmission scheme, where multiple full-duplex relays, simultaneously, assist the communication between a source node and a destination node. First, we present the communication model of the proposed transmission scheme. Then, we derive the outage probability closed-form for two cases: asynchronous transmission (where all relays have different processing delay) and synchronous transmissions (where all relays have the same processing delay). Finally, using simulations, we confirm the theoretical results and compare the proposed multi-relays transmission scheme with relay selection schemes.
cs.IT cs.PF eess.SP math.IT
in order to follow up with missioncritical applications new features need to be carried to satisfy a reliable communication with reduced latency with this regard this paper proposes a low latency cooperative transmission scheme where multiple fullduplex relays simultaneously assist the communication between a source node and a destination node first we present the communication model of the proposed transmission scheme then we derive the outage probability closedform for two cases asynchronous transmission where all relays have different processing delay and synchronous transmissions where all relays have the same processing delay finally using simulations we confirm the theoretical results and compare the proposed multirelays transmission scheme with relay selection schemes
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1,802.04077
Compact operators on the sets of fractional difference sequences
Fractional difference sequence spaces have been studied in the literature recently. In this work, some identities or estimates for the operator norms and the Hausdorff measures of noncompactness of certain operators on some difference sequence spaces of fractional orders are established. Some classes of compact operators on those spaces are characterized. The results of this work are more general and comprehensive then many other studies in literature.
math.FA
fractional difference sequence spaces have been studied in the literature recently in this work some identities or estimates for the operator norms and the hausdorff measures of noncompactness of certain operators on some difference sequence spaces of fractional orders are established some classes of compact operators on those spaces are characterized the results of this work are more general and comprehensive then many other studies in literature
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1,802.04078
A concept of biopharmaceutical nanosatellite
The article is a short overview of a proposal of a CubeSat type nanosatellite designed to conduct biopharmaceutical tests on the low earth orbit. Motivations behind the emerging demand for such solution nowadays and in the close future are emphasized. The possible objectives and challenges to be addressed in the planned biopharmaceutical CubeSat missions are discussed. In particular, it is hard to imagine progress of the space tourism and colonization of Mars without a wide-ranging development of pharmaceutics dedicated to be used in space. Finally, an exemplary layout of a 3U type CubeSat is presented. We stress that, thanks to recent development in both nanosatellite technologies and lab-on-a-chip type biofluidic systems the proposed idea becomes now both feasible and relatively affordable.
physics.bio-ph physics.space-ph
the article is a short overview of a proposal of a cubesat type nanosatellite designed to conduct biopharmaceutical tests on the low earth orbit motivations behind the emerging demand for such solution nowadays and in the close future are emphasized the possible objectives and challenges to be addressed in the planned biopharmaceutical cubesat missions are discussed in particular it is hard to imagine progress of the space tourism and colonization of mars without a wideranging development of pharmaceutics dedicated to be used in space finally an exemplary layout of a 3u type cubesat is presented we stress that thanks to recent development in both nanosatellite technologies and labonachip type biofluidic systems the proposed idea becomes now both feasible and relatively affordable
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1,802.04079
Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization
We present the first accelerated randomized algorithm for solving linear systems in Euclidean spaces. One essential problem of this type is the matrix inversion problem. In particular, our algorithm can be specialized to invert positive definite matrices in such a way that all iterates (approximate solutions) generated by the algorithm are positive definite matrices themselves. This opens the way for many applications in the field of optimization and machine learning. As an application of our general theory, we develop the {\em first accelerated (deterministic and stochastic) quasi-Newton updates}. Our updates lead to provably more aggressive approximations of the inverse Hessian, and lead to speed-ups over classical non-accelerated rules in numerical experiments. Experiments with empirical risk minimization show that our rules can accelerate training of machine learning models.
math.OC cs.NA
we present the first accelerated randomized algorithm for solving linear systems in euclidean spaces one essential problem of this type is the matrix inversion problem in particular our algorithm can be specialized to invert positive definite matrices in such a way that all iterates approximate solutions generated by the algorithm are positive definite matrices themselves this opens the way for many applications in the field of optimization and machine learning as an application of our general theory we develop the em first accelerated deterministic and stochastic quasinewton updates our updates lead to provably more aggressive approximations of the inverse hessian and lead to speedups over classical nonaccelerated rules in numerical experiments experiments with empirical risk minimization show that our rules can accelerate training of machine learning models
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1,802.0408
Seeding of the Self-Modulation in a Long Proton Bunch by Charge Cancellation with a Short Electron Bunch
In plasma wakefield accelerators (e.g. AWAKE) the proton bunch self-modulation is seeded by the ionization front of a high-power laser pulse ionizing a vapour and by the resulting steep edge of the driving bunch profile inside the created plasma. In this paper, we present calculations in 2D linear theory for a concept of a different self-modulation seeding mechanism based on electron injection. The whole proton bunch propagates through a preformed plasma and the effective beam current is modulated by the external injection of a short electron bunch at the centre of the proton beam. The resulting sharp edge in the effective beam current in the trailing part of the proton bunch is driving large wakefields that can lead to a growth of the seeded self-modulation (SSM). Furthermore, we discuss the feasibility for applications in AWAKE Run 2.
physics.plasm-ph physics.acc-ph
in plasma wakefield accelerators eg awake the proton bunch selfmodulation is seeded by the ionization front of a highpower laser pulse ionizing a vapour and by the resulting steep edge of the driving bunch profile inside the created plasma in this paper we present calculations in 2d linear theory for a concept of a different selfmodulation seeding mechanism based on electron injection the whole proton bunch propagates through a preformed plasma and the effective beam current is modulated by the external injection of a short electron bunch at the centre of the proton beam the resulting sharp edge in the effective beam current in the trailing part of the proton bunch is driving large wakefields that can lead to a growth of the seeded selfmodulation ssm furthermore we discuss the feasibility for applications in awake run 2
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1,802.04081
Characterizations of Compact Operators on $\ell_{p}$ Type Fractional Sets of Sequences
Among the sets of sequences studied, difference sets of sequences are probably the most common type of sets. This paper considers some $\ell_{p}$ type fractional difference sequence spaces via Euler gamma function. Although we characterize compactness conditions on those spaces using the main tools of Hausdorff measure of noncompactness, we can only obtain sufficient conditions when the final space is $\ell _{\infty }$. However, we use some recent results to exactly characterize the classes of compact matrix operators when the final space is the set of bounded sequences.
math.FA
among the sets of sequences studied difference sets of sequences are probably the most common type of sets this paper considers some ell_p type fractional difference sequence spaces via euler gamma function although we characterize compactness conditions on those spaces using the main tools of hausdorff measure of noncompactness we can only obtain sufficient conditions when the final space is ell _infty however we use some recent results to exactly characterize the classes of compact matrix operators when the final space is the set of bounded sequences
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1,802.04082
Towards self-adaptable robots: from programming to training machines
We argue that hardware modularity plays a key role in the convergence of Robotics and Artificial Intelligence (AI). We introduce a new approach for building robots that leads to more adaptable and capable machines. We present the concept of a self-adaptable robot that makes use of hardware modularity and AI techniques to reduce the effort and time required to be built. We demonstrate in simulation and with a real robot how, rather than programming, training produces behaviors in the robot that generalize fast and produce robust outputs in the presence of noise. In particular, we advocate for mammals.
cs.RO
we argue that hardware modularity plays a key role in the convergence of robotics and artificial intelligence ai we introduce a new approach for building robots that leads to more adaptable and capable machines we present the concept of a selfadaptable robot that makes use of hardware modularity and ai techniques to reduce the effort and time required to be built we demonstrate in simulation and with a real robot how rather than programming training produces behaviors in the robot that generalize fast and produce robust outputs in the presence of noise in particular we advocate for mammals
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1,802.04083
On parameterised toric codes
Let $X$ be a complete simplicial toric variety over a finite field with a split torus $T_X$. For any matrix $Q$, we are interested in the subgroup $Y_Q$ of $T_X$ parameterized by the columns of $Q$. We give an algorithm for obtaining a basis for the unique lattice $L$ whose lattice ideal $I_L$ is $I(Y_Q)$. We also give two direct algorithmic methods to compute the order of $Y_Q$, which is the length of the corresponding code ${\cC}_{\aa,Y_Q}$. We share procedures implementing them in \verb|Macaulay2|. Finally, we give a lower bound for the minimum distance of ${\cC}_{\aa,Y_Q}$, taking advantage of the parametric description of the subgroup $Y_Q$. As an application, we compute the main parameters of the toric codes on Hirzebruch surfaces $\cl H_{\ell}$ generalizing the corresponding result given by Hansen.
math.AG
let x be a complete simplicial toric variety over a finite field with a split torus t_x for any matrix q we are interested in the subgroup y_q of t_x parameterized by the columns of q we give an algorithm for obtaining a basis for the unique lattice l whose lattice ideal i_l is iy_q we also give two direct algorithmic methods to compute the order of y_q which is the length of the corresponding code cc_aay_q we share procedures implementing them in verbmacaulay2 finally we give a lower bound for the minimum distance of cc_aay_q taking advantage of the parametric description of the subgroup y_q as an application we compute the main parameters of the toric codes on hirzebruch surfaces cl h_ell generalizing the corresponding result given by hansen
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1,802.04084
Randomized Block Cubic Newton Method
We study the problem of minimizing the sum of three convex functions: a differentiable, twice-differentiable and a non-smooth term in a high dimensional setting. To this effect we propose and analyze a randomized block cubic Newton (RBCN) method, which in each iteration builds a model of the objective function formed as the sum of the natural models of its three components: a linear model with a quadratic regularizer for the differentiable term, a quadratic model with a cubic regularizer for the twice differentiable term, and perfect (proximal) model for the nonsmooth term. Our method in each iteration minimizes the model over a random subset of blocks of the search variable. RBCN is the first algorithm with these properties, generalizing several existing methods, matching the best known bounds in all special cases. We establish ${\cal O}(1/\epsilon)$, ${\cal O}(1/\sqrt{\epsilon})$ and ${\cal O}(\log (1/\epsilon))$ rates under different assumptions on the component functions. Lastly, we show numerically that our method outperforms the state-of-the-art on a variety of machine learning problems, including cubically regularized least-squares, logistic regression with constraints, and Poisson regression.
math.OC
we study the problem of minimizing the sum of three convex functions a differentiable twicedifferentiable and a nonsmooth term in a high dimensional setting to this effect we propose and analyze a randomized block cubic newton rbcn method which in each iteration builds a model of the objective function formed as the sum of the natural models of its three components a linear model with a quadratic regularizer for the differentiable term a quadratic model with a cubic regularizer for the twice differentiable term and perfect proximal model for the nonsmooth term our method in each iteration minimizes the model over a random subset of blocks of the search variable rbcn is the first algorithm with these properties generalizing several existing methods matching the best known bounds in all special cases we establish cal o1epsilon cal o1sqrtepsilon and cal olog 1epsilon rates under different assumptions on the component functions lastly we show numerically that our method outperforms the stateoftheart on a variety of machine learning problems including cubically regularized leastsquares logistic regression with constraints and poisson regression
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1,802.04085
Empirical Risk Minimization in Non-interactive Local Differential Privacy: Efficiency and High Dimensional Case
In this paper, we study the Empirical Risk Minimization problem in the non-interactive local model of differential privacy. In the case of constant or low dimensionality ($p\ll n$), we first show that if the ERM loss function is $(\infty, T)$-smooth, then we can avoid a dependence of the sample complexity, to achieve error $\alpha$, on the exponential of the dimensionality $p$ with base $1/\alpha$ (i.e., $\alpha^{-p}$), which answers a question in [smith 2017 interaction]. Our approach is based on polynomial approximation. Then, we propose player-efficient algorithms with $1$-bit communication complexity and $O(1)$ computation cost for each player. The error bound is asymptotically the same as the original one. Also with additional assumptions we show a server efficient algorithm. Next we consider the high dimensional case ($n\ll p$), we show that if the loss function is Generalized Linear function and convex, then we could get an error bound which is dependent on the Gaussian width of the underlying constrained set instead of $p$, which is lower than that in [smith 2017 interaction].
cs.LG cs.CR stat.ML
in this paper we study the empirical risk minimization problem in the noninteractive local model of differential privacy in the case of constant or low dimensionality pll n we first show that if the erm loss function is infty tsmooth then we can avoid a dependence of the sample complexity to achieve error alpha on the exponential of the dimensionality p with base 1alpha ie alphap which answers a question in smith 2017 interaction our approach is based on polynomial approximation then we propose playerefficient algorithms with 1bit communication complexity and o1 computation cost for each player the error bound is asymptotically the same as the original one also with additional assumptions we show a server efficient algorithm next we consider the high dimensional case nll p we show that if the loss function is generalized linear function and convex then we could get an error bound which is dependent on the gaussian width of the underlying constrained set instead of p which is lower than that in smith 2017 interaction
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1,802.04086
The Complex Event Recognition Group
The Complex Event Recognition (CER) group is a research team, affiliated with the National Centre of Scientific Research "Demokritos" in Greece. The CER group works towards advanced and efficient methods for the recognition of complex events in a multitude of large, heterogeneous and interdependent data streams. Its research covers multiple aspects of complex event recognition, from efficient detection of patterns on event streams to handling uncertainty and noise in streams, and machine learning techniques for inferring interesting patterns. Lately, it has expanded to methods for forecasting the occurrence of events. It was founded in 2009 and currently hosts 3 senior researchers, 5 PhD students and works regularly with under-graduate students.
cs.AI
the complex event recognition cer group is a research team affiliated with the national centre of scientific research demokritos in greece the cer group works towards advanced and efficient methods for the recognition of complex events in a multitude of large heterogeneous and interdependent data streams its research covers multiple aspects of complex event recognition from efficient detection of patterns on event streams to handling uncertainty and noise in streams and machine learning techniques for inferring interesting patterns lately it has expanded to methods for forecasting the occurrence of events it was founded in 2009 and currently hosts 3 senior researchers 5 phd students and works regularly with undergraduate students
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1,802.04087
Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms
Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables analyzing the native structures of macromolecular complexes and their spatial organization inside single cells. However, due to the high degree of structural complexity and practical imaging limitations, systematic macromolecular structural recovery inside CECT images remains challenging. Particularly, the recovery of a macromolecule is likely to be biased by its neighbor structures due to the high molecular crowding. To reduce the bias, here we introduce a novel 3D convolutional neural network inspired by Fully Convolutional Network and Encoder-Decoder Architecture for the supervised segmentation of macromolecules of interest in subtomograms. The tests of our models on realistically simulated CECT data demonstrate that our new approach has significantly improved segmentation performance compared to our baseline approach. Also, we demonstrate that the proposed model has generalization ability to segment new structures that do not exist in training data.
q-bio.QM cs.CV stat.ML
cellular electron cryotomography cect is a powerful imaging technique for the 3d visualization of cellular structure and organization at submolecular resolution it enables analyzing the native structures of macromolecular complexes and their spatial organization inside single cells however due to the high degree of structural complexity and practical imaging limitations systematic macromolecular structural recovery inside cect images remains challenging particularly the recovery of a macromolecule is likely to be biased by its neighbor structures due to the high molecular crowding to reduce the bias here we introduce a novel 3d convolutional neural network inspired by fully convolutional network and encoderdecoder architecture for the supervised segmentation of macromolecules of interest in subtomograms the tests of our models on realistically simulated cect data demonstrate that our new approach has significantly improved segmentation performance compared to our baseline approach also we demonstrate that the proposed model has generalization ability to segment new structures that do not exist in training data
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1,802.04088
On the number of Bose-selected modes in driven-dissipative ideal Bose gases
In an ideal Bose gas that is driven into a steady state far from thermal equilibrium, a generalized form of Bose condensation can occur. Namely, the single-particle states unambiguously separate into two groups: the group of Bose-selected states, whose occupations increase linearly with the total particle number, and the group of all other states whose occupations saturate [Phys. Rev. Lett. 111, 240405 (2013)]. However, so far very little is known about how the number of Bose-selected states depends on the properties of the system and its coupling to the environment. The answer to this question is crucial since systems hosting a single, a few, or an extensive number of Bose-selected states will show rather different behavior. While in the former two scenarios each selected mode acquires a macroscopic occupation, corresponding to (fragmented) Bose condensation, the latter case rather bears resemblance to a high-temperature state of matter. In this paper, we systematically investigate the number of Bose-selected states, considering different classes of the rate matrices that characterize the driven-dissipative ideal Bose gases in the limit of weak system-bath coupling. These include rate matrices with continuum limit, rate matrices of chaotic driven systems, random rate matrices, and rate matrices resulting from thermal baths that couple to a few observables only.
cond-mat.quant-gas cond-mat.stat-mech quant-ph
in an ideal bose gas that is driven into a steady state far from thermal equilibrium a generalized form of bose condensation can occur namely the singleparticle states unambiguously separate into two groups the group of boseselected states whose occupations increase linearly with the total particle number and the group of all other states whose occupations saturate phys rev lett 111 240405 2013 however so far very little is known about how the number of boseselected states depends on the properties of the system and its coupling to the environment the answer to this question is crucial since systems hosting a single a few or an extensive number of boseselected states will show rather different behavior while in the former two scenarios each selected mode acquires a macroscopic occupation corresponding to fragmented bose condensation the latter case rather bears resemblance to a hightemperature state of matter in this paper we systematically investigate the number of boseselected states considering different classes of the rate matrices that characterize the drivendissipative ideal bose gases in the limit of weak systembath coupling these include rate matrices with continuum limit rate matrices of chaotic driven systems random rate matrices and rate matrices resulting from thermal baths that couple to a few observables only
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1,802.04089
Threshold phenomena for high-dimensional random polytopes
Let $X_1,\ldots,X_N$, $N>n$, be independent random points in $\mathbb{R}^n$, distributed according to the so-called beta or beta-prime distribution, respectively. We establish threshold phenomena for the volume, intrinsic volumes, or more general measures of the convex hulls of these random point sets, as the space dimension $n$ tends to infinity. The dual setting of polytopes generated by random halfspaces is also investigated.
math.MG math.PR
let x_1ldotsx_n nn be independent random points in mathbbrn distributed according to the socalled beta or betaprime distribution respectively we establish threshold phenomena for the volume intrinsic volumes or more general measures of the convex hulls of these random point sets as the space dimension n tends to infinity the dual setting of polytopes generated by random halfspaces is also investigated
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1,802.0409
Don't Leave Me Alone: Retrospective Think Aloud supported by Real-time Monitoring of Participant's Physiology
Think aloud protocols are widely applied in user experience studies. In this paper, the effect of two different applications of the Retrospective Think Aloud (RTA) protocol on the number of user-reported usability issues is examined. To this end, 30 users were asked to use the National Cadastre and Mapping Agency web application and complete a set of tasks, such as measuring the land area of a square in their hometown. The order of tasks was randomized per participant. Next, participants were involved in RTA sessions. Each participant was involved in two different RTA modes: (a) the strict guidance, in which the facilitator stayed in the background and prompted participants to keep thinking aloud based on his judgement and experience, and (b) the physiology-supported interventions, in which the facilitator intervened based on real-time monitoring of user's physiological signals. During each session, three participant's physiological signals were recorded: skin conductance, skin temperature and blood volume pulse. Participants were also asked to provide valence-arousal ratings for each self-reported usability issue. Analysis of the collected data showed that participants in the physiology-supported RTA mode reported significantly more usability issues. No significant effect of the RTA mode was found on the va-lence-arousal ratings for the reported usability issues. Participants' physiological signals during the RTA sessions did not also differ significantly between the two modes.
cs.HC cs.CY
think aloud protocols are widely applied in user experience studies in this paper the effect of two different applications of the retrospective think aloud rta protocol on the number of userreported usability issues is examined to this end 30 users were asked to use the national cadastre and mapping agency web application and complete a set of tasks such as measuring the land area of a square in their hometown the order of tasks was randomized per participant next participants were involved in rta sessions each participant was involved in two different rta modes a the strict guidance in which the facilitator stayed in the background and prompted participants to keep thinking aloud based on his judgement and experience and b the physiologysupported interventions in which the facilitator intervened based on realtime monitoring of users physiological signals during each session three participants physiological signals were recorded skin conductance skin temperature and blood volume pulse participants were also asked to provide valencearousal ratings for each selfreported usability issue analysis of the collected data showed that participants in the physiologysupported rta mode reported significantly more usability issues no significant effect of the rta mode was found on the valencearousal ratings for the reported usability issues participants physiological signals during the rta sessions did not also differ significantly between the two modes
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1,802.04091
On the contact geometry and the Poisson geometry of the ideal gas
We elaborate on existing notions of contact geometry and Poisson geometry as applied to the classical ideal gas. Specifically we observe that it is possible to describe its dynamics using a 3-dimensional contact submanifold of the standard 5-dimensional contact manifold used in the literature. This reflects the fact that the internal energy of the ideal gas depends exclusively on its temperature. We also present a Poisson algebra of thermodynamic operators for a quantum-like description of the classical ideal gas. The central element of this Poisson algebra is proportional to Boltzmann's constant. A Hilbert space of states is identified and a system of wave equations governing the wavefunction is found. Expectation values for the operators representing pressure, volume and temperature are found to satisfy the classical equations of state.
math-ph math.MP quant-ph
we elaborate on existing notions of contact geometry and poisson geometry as applied to the classical ideal gas specifically we observe that it is possible to describe its dynamics using a 3dimensional contact submanifold of the standard 5dimensional contact manifold used in the literature this reflects the fact that the internal energy of the ideal gas depends exclusively on its temperature we also present a poisson algebra of thermodynamic operators for a quantumlike description of the classical ideal gas the central element of this poisson algebra is proportional to boltzmanns constant a hilbert space of states is identified and a system of wave equations governing the wavefunction is found expectation values for the operators representing pressure volume and temperature are found to satisfy the classical equations of state
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1,802.04092
Linear combination of composition operators on $H^\infty$ and the Bloch space
Let $\lambda_i (i=1,...,k)$ be any nonzero complex scalars and $\varphi_i (i=1,..,k)$ be any analytic self-maps of the unit disk $\mathbb{D}$. We show that the operator $\sum_{i=1}^k\lambda_iC_{\varphi_i}$ is compact on the Bloch space $\mathcal{B}$ if and only if $$\lim_{n\to\infty}\|\lambda_1\varphi_1^n+\lambda_2\varphi_2^n+...+\lambda_k\varphi_k^n\|_{\mathcal{B}}=0.$$ We also study the linear combination of composition operators on the Banach algebra of bounded analytic functions.
math.CV math.FA
let lambda_i i1k be any nonzero complex scalars and varphi_i i1k be any analytic selfmaps of the unit disk mathbbd we show that the operator sum_i1klambda_ic_varphi_i is compact on the bloch space mathcalb if and only if lim_ntoinftylambda_1varphi_1nlambda_2varphi_2nlambda_kvarphi_kn_mathcalb0 we also study the linear combination of composition operators on the banach algebra of bounded analytic functions
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1,802.04093
Reasoning in a Hierarchical System with Missing Group Size Information
The paper analyzes the problem of judgments or preferences subsequent to initial analysis by autonomous agents in a hierarchical system where the higher level agents does not have access to group size information. We propose methods that reduce instances of preference reversal of the kind encountered in Simpson's paradox.
cs.AI
the paper analyzes the problem of judgments or preferences subsequent to initial analysis by autonomous agents in a hierarchical system where the higher level agents does not have access to group size information we propose methods that reduce instances of preference reversal of the kind encountered in simpsons paradox
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1,802.04094
A rational QZ method
We propose a rational QZ method for the solution of the dense, unsymmetric generalized eigenvalue problem. This generalization of the classical QZ method operates implicitly on a Hessenberg, Hessenberg pencil instead of on a Hessenberg, triangular pencil. Whereas the QZ method performs nested subspace iteration driven by a polynomial, the rational QZ method allows for nested subspace iteration driven by a rational function, this creates the additional freedom of selecting poles. In this article we study Hessenberg, Hessenberg pencils, link them to rational Krylov subspaces, propose a direct reduction method to such a pencil, and introduce the implicit rational QZ step. The link with rational Krylov subspaces allows us to prove essential uniqueness (implicit Q theorem) of the rational QZ iterates as well as convergence of the proposed method. In the proofs, we operate directly on the pencil instead of rephrasing it all in terms of a single matrix. Numerical experiments are included to illustrate competitiveness in terms of speed and accuracy with the classical approach. Two other types of experiments exemplify new possibilities. First we illustrate that good pole selection can be used to deflate the original problem during the reduction phase, and second we use the rational QZ method to implicitly filter a rational Krylov subspace in an iterative method.
math.NA
we propose a rational qz method for the solution of the dense unsymmetric generalized eigenvalue problem this generalization of the classical qz method operates implicitly on a hessenberg hessenberg pencil instead of on a hessenberg triangular pencil whereas the qz method performs nested subspace iteration driven by a polynomial the rational qz method allows for nested subspace iteration driven by a rational function this creates the additional freedom of selecting poles in this article we study hessenberg hessenberg pencils link them to rational krylov subspaces propose a direct reduction method to such a pencil and introduce the implicit rational qz step the link with rational krylov subspaces allows us to prove essential uniqueness implicit q theorem of the rational qz iterates as well as convergence of the proposed method in the proofs we operate directly on the pencil instead of rephrasing it all in terms of a single matrix numerical experiments are included to illustrate competitiveness in terms of speed and accuracy with the classical approach two other types of experiments exemplify new possibilities first we illustrate that good pole selection can be used to deflate the original problem during the reduction phase and second we use the rational qz method to implicitly filter a rational krylov subspace in an iterative method
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1,802.04095
A New Multi Criteria Decision Making Method: Approach of Logarithmic Concept (APLOCO)
The primary aim of the study is to introduce APLOCO method which is developed for the solution of multicriteria decision making problems both theoretically and practically. In this context, application subject of APLACO constitutes evaluation of investment potential of different cities in metropolitan status in Turkey. The secondary purpose of the study is to identify the independent variables affecting the factories in the operating phase and to estimate the effect levels of independent variables on the dependent variable in the organized industrial zones (OIZs), whose mission is to reduce regional development disparities and to mobilize local production dynamics. For this purpose, the effect levels of independent variables on dependent variables have been determined using the multilayer perceptron (MLP) method, which has a wide use in artificial neural networks (ANNs). The effect levels derived from MLP have been then used as the weight levels of the decision criteria in APLOCO. The independent variables included in MLP are also used as the decision criteria in APLOCO. According to the results obtained from APLOCO, Istanbul city is the best alternative in term of the investment potential and other alternatives are Manisa, Denizli, Izmir, Kocaeli, Bursa, Ankara, Adana, and Antalya, respectively. Although APLOCO is used to solve the ranking problem in order to show application process in the paper, it can be employed easily in the solution of classification and selection problems. On the other hand, the study also shows a rare example of the nested usage of APLOCO which is one of the methods of operation research as well as MLP used in determination of weights.
cs.AI
the primary aim of the study is to introduce aploco method which is developed for the solution of multicriteria decision making problems both theoretically and practically in this context application subject of aplaco constitutes evaluation of investment potential of different cities in metropolitan status in turkey the secondary purpose of the study is to identify the independent variables affecting the factories in the operating phase and to estimate the effect levels of independent variables on the dependent variable in the organized industrial zones oizs whose mission is to reduce regional development disparities and to mobilize local production dynamics for this purpose the effect levels of independent variables on dependent variables have been determined using the multilayer perceptron mlp method which has a wide use in artificial neural networks anns the effect levels derived from mlp have been then used as the weight levels of the decision criteria in aploco the independent variables included in mlp are also used as the decision criteria in aploco according to the results obtained from aploco istanbul city is the best alternative in term of the investment potential and other alternatives are manisa denizli izmir kocaeli bursa ankara adana and antalya respectively although aploco is used to solve the ranking problem in order to show application process in the paper it can be employed easily in the solution of classification and selection problems on the other hand the study also shows a rare example of the nested usage of aploco which is one of the methods of operation research as well as mlp used in determination of weights
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1,802.04096
Indole moiety induced biological potency in pseudo- peptides derived from 2-amino-2-(1H-indole-2-yl) based acetamides: synthesis, structure and computational investigations
We report the synthesis and theoretical investigations of three novel pseudo-peptide molecules derived from 2-amino-2-(1H-indole-2-yl) acetamides. The compounds were subjected to spectroscopic characterization ($^1$H, $^{13}$C-NMR and MS) and their chemical, electronic, and optical properties have been investigated. To ascertain their potential pharmacological applicability, the prospective reactive centers and molecular sites prone to interaction with water were identified along with possible sensitivity to autoxidation. Further, we have studied the optical response in the presence of different solvents and compared the electronic and optical properties of the pristine molecules. We highlight the subtle dependence of the properties on the structure and composition of these pseudo-peptides. Our results indicate that these molecules have high pharmaceutical potential and could serve as lead components in new drug formulations.
cond-mat.mtrl-sci
we report the synthesis and theoretical investigations of three novel pseudopeptide molecules derived from 2amino21hindole2yl acetamides the compounds were subjected to spectroscopic characterization 1h 13cnmr and ms and their chemical electronic and optical properties have been investigated to ascertain their potential pharmacological applicability the prospective reactive centers and molecular sites prone to interaction with water were identified along with possible sensitivity to autoxidation further we have studied the optical response in the presence of different solvents and compared the electronic and optical properties of the pristine molecules we highlight the subtle dependence of the properties on the structure and composition of these pseudopeptides our results indicate that these molecules have high pharmaceutical potential and could serve as lead components in new drug formulations
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1,802.04097
The discreet charm of higgsino dark matter - a pocket review
We give a brief review of the current constraints and prospects for detection of higgsino dark matter in low-scale supersymmetry. In the first part we argue, after performing a survey of all potential dark matter particles in the MSSM, that the (nearly) pure higgsino is the only candidate emerging virtually unscathed from the wealth of observational data of recent years. In doing so by virtue of its gauge quantum numbers and electroweak symmetry breaking only, it maintains at the same time a relatively high degree of model-independence. In the second part we properly review the prospects for detection of a higgsino-like neutralino in direct underground dark matter searches, collider searches, and indirect astrophysical signals. We provide estimates for the typical scale of the superpartners and fine tuning in the context of traditional scenarios where the breaking of supersymmetry is mediated at about the scale of Grand Unification and where strong expectations for a timely detection of higgsinos in underground detectors are closely related to the measured 125 GeV mass of the Higgs boson at the LHC.
hep-ph astro-ph.HE hep-ex
we give a brief review of the current constraints and prospects for detection of higgsino dark matter in lowscale supersymmetry in the first part we argue after performing a survey of all potential dark matter particles in the mssm that the nearly pure higgsino is the only candidate emerging virtually unscathed from the wealth of observational data of recent years in doing so by virtue of its gauge quantum numbers and electroweak symmetry breaking only it maintains at the same time a relatively high degree of modelindependence in the second part we properly review the prospects for detection of a higgsinolike neutralino in direct underground dark matter searches collider searches and indirect astrophysical signals we provide estimates for the typical scale of the superpartners and fine tuning in the context of traditional scenarios where the breaking of supersymmetry is mediated at about the scale of grand unification and where strong expectations for a timely detection of higgsinos in underground detectors are closely related to the measured 125 gev mass of the higgs boson at the lhc
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1,802.04098
Cohesive fracture with irreversibility: quasistatic evolution for a model subject to fatigue
In this paper we prove the existence of quasistatic evolutions for a cohesive fracture on a prescribed crack surface, in small-strain antiplane elasticity. The main feature of the model is that the density of the energy dissipated in the fracture process depends on the total variation of the amplitude of the jump. Thus, any change in the crack opening entails a loss of energy, until the crack is complete. In particular this implies a fatigue phenomenon, i.e., a complete fracture may be produced by oscillation of small jumps. The first step of the existence proof is the construction of approximate evolutions obtained by solving discrete-time incremental minimum problems. The main difficulty in the passage to the continuous-time limit is that we lack of controls on the variations of the jump of the approximate evolutions. Therefore we resort to a weak formulation where the variation of the jump is replaced by a Young measure. Eventually, after proving the existence in this weak formulation, we improve the result by showing that the Young measure is concentrated on a function and coincides with the variation of the jump of the displacement.
math.AP math.FA
in this paper we prove the existence of quasistatic evolutions for a cohesive fracture on a prescribed crack surface in smallstrain antiplane elasticity the main feature of the model is that the density of the energy dissipated in the fracture process depends on the total variation of the amplitude of the jump thus any change in the crack opening entails a loss of energy until the crack is complete in particular this implies a fatigue phenomenon ie a complete fracture may be produced by oscillation of small jumps the first step of the existence proof is the construction of approximate evolutions obtained by solving discretetime incremental minimum problems the main difficulty in the passage to the continuoustime limit is that we lack of controls on the variations of the jump of the approximate evolutions therefore we resort to a weak formulation where the variation of the jump is replaced by a young measure eventually after proving the existence in this weak formulation we improve the result by showing that the young measure is concentrated on a function and coincides with the variation of the jump of the displacement
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1,802.04099
Rortex A New Vortex Vector Definition and Vorticity Tensor and Vector Decompositions
A vortex is intuitively recognized as the rotational/swirling motion of the fluids. However, an unambiguous and universally-accepted definition for vortex is yet to be achieved in the field of fluid mechanics, which is probably one of the major obstacles causing considerable confusions and misunderstandings in turbulence research. In our previous work, a new vector quantity which is called vortex vector was proposed to accurately describe the local fluid rotation and clearly display vortical structures. In this paper, the definition of the vortex vector, named Rortex here, is revisited from the mathematical perspective. The existence of the rotational axis is proved through real Schur decomposition. Based on real Schur decomposition, a fast algorithm for calculating Rortex is also presented. In addition, new vorticity tensor and vector decompositions are introduced: the vorticity tensor is decomposed to a rigidly rotational part and an anti-symmetric deformation part, and the vorticity vector is decomposed to a rigidly rotational vector and a non-rotational vector. Several cases, including 2D Couette flow, 2D rigid rotational flow and 3D boundary layer transition on a flat plate, are studied to demonstrate the justification of the definition of Rortex. It can be observed that Rortex identifies both the precise swirling strength and the rotational axis, and thus it can reasonably represent the local fluid rotation and provide a new powerful tool for vortex dynamics and turbulence research.
physics.flu-dyn
a vortex is intuitively recognized as the rotationalswirling motion of the fluids however an unambiguous and universallyaccepted definition for vortex is yet to be achieved in the field of fluid mechanics which is probably one of the major obstacles causing considerable confusions and misunderstandings in turbulence research in our previous work a new vector quantity which is called vortex vector was proposed to accurately describe the local fluid rotation and clearly display vortical structures in this paper the definition of the vortex vector named rortex here is revisited from the mathematical perspective the existence of the rotational axis is proved through real schur decomposition based on real schur decomposition a fast algorithm for calculating rortex is also presented in addition new vorticity tensor and vector decompositions are introduced the vorticity tensor is decomposed to a rigidly rotational part and an antisymmetric deformation part and the vorticity vector is decomposed to a rigidly rotational vector and a nonrotational vector several cases including 2d couette flow 2d rigid rotational flow and 3d boundary layer transition on a flat plate are studied to demonstrate the justification of the definition of rortex it can be observed that rortex identifies both the precise swirling strength and the rotational axis and thus it can reasonably represent the local fluid rotation and provide a new powerful tool for vortex dynamics and turbulence research
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1,802.041
Agile development for vulnerable populations: lessons learned and recommendations
In this paper we draw attention to the challenges of managing software projects for vulnerable populations, i.e., people potentially exposed to harm or not capable of protecting their own interests. The focus on human aspects, and particularly, the inclusion of human-centered approaches, has been a popular topic in the software engineering community. We argue, however, that current literature provides little understanding and guidance on how to approach these type of scenarios. Here, we shed some light on the topic by reporting on our experiences in developing innovative solutions for the residential care scenario, outlining potential issues and recommendations.
cs.CY
in this paper we draw attention to the challenges of managing software projects for vulnerable populations ie people potentially exposed to harm or not capable of protecting their own interests the focus on human aspects and particularly the inclusion of humancentered approaches has been a popular topic in the software engineering community we argue however that current literature provides little understanding and guidance on how to approach these type of scenarios here we shed some light on the topic by reporting on our experiences in developing innovative solutions for the residential care scenario outlining potential issues and recommendations
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1,802.04101
A New Approach for Higher Order Difference Equations and Eigenvalue problems via Physical Potentials
In this study, we give the variation of parameters method from a different viewpoint for the Nth order inhomogeneous linear ordinary difference equations with constant coefficient by means of delta exponential function . Advantage of this new approachment is to enable us to investigate the solution of difference equations in the closed form. Also, the method is supported with three difference eigenvalue problems, the second-order Sturm-Liouville problem, which is called also one dimensional Schr\"odinger equation, having Coulomb potential, hydrogen atom equation, and the fourth-order relaxation difference equations. We find sum representation of solution for the second order discrete Sturm-Liouville problem having Coulomb potential, hydrogen atom equation, and analytical solution of the fourth order discrete relaxation problem by the variation of parameters method via delta exponential and delta trigonometric functions .
math.CA
in this study we give the variation of parameters method from a different viewpoint for the nth order inhomogeneous linear ordinary difference equations with constant coefficient by means of delta exponential function advantage of this new approachment is to enable us to investigate the solution of difference equations in the closed form also the method is supported with three difference eigenvalue problems the secondorder sturmliouville problem which is called also one dimensional schrodinger equation having coulomb potential hydrogen atom equation and the fourthorder relaxation difference equations we find sum representation of solution for the second order discrete sturmliouville problem having coulomb potential hydrogen atom equation and analytical solution of the fourth order discrete relaxation problem by the variation of parameters method via delta exponential and delta trigonometric functions
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1,802.04102
Advertising in the IoT Era: Vision and Challenges
The Internet of Things (IoT) extends the idea of interconnecting computers to a plethora of different devices, collectively referred to as smart devices. These are physical items - i.e., "things" - such as wearable devices, home appliances, and vehicles, enriched with computational and networking capabilities. Due to the huge set of devices involved - and therefore, its pervasiveness - IoT is a great platform to leverage for building new applications and services or extending existing ones. In this regard, expanding online advertising into the IoT realm is an under-investigated yet promising research direction, especially considering that traditional Internet advertising market is already worth hundreds of billions of dollars. In this paper, we first propose the architecture of an IoT advertising platform inspired by the well-known business ecosystem, which the traditional Internet advertising is based on. Additionally, we discuss the key challenges to implement such a platform with a special focus on issues related to architecture, advertisement content delivery, security, and privacy of the users.
cs.CY cs.SI
the internet of things iot extends the idea of interconnecting computers to a plethora of different devices collectively referred to as smart devices these are physical items ie things such as wearable devices home appliances and vehicles enriched with computational and networking capabilities due to the huge set of devices involved and therefore its pervasiveness iot is a great platform to leverage for building new applications and services or extending existing ones in this regard expanding online advertising into the iot realm is an underinvestigated yet promising research direction especially considering that traditional internet advertising market is already worth hundreds of billions of dollars in this paper we first propose the architecture of an iot advertising platform inspired by the wellknown business ecosystem which the traditional internet advertising is based on additionally we discuss the key challenges to implement such a platform with a special focus on issues related to architecture advertisement content delivery security and privacy of the users
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1,802.04103
Ethical and Social Aspects of Self-Driving Cars
As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.
cs.CY
as an envisaged future of transportation selfdriving cars are being discussed from various perspectives including social economical engineering computer science design and ethics on the one hand selfdriving cars present new engineering problems that are being gradually successfully solved on the other hand social and ethical problems are typically being presented in the form of an idealized unsolvable decisionmaking problem the socalled trolley problem which is grossly misleading we argue that an applied engineering ethical approach for the development of new technology is what is needed the approach should be applied meaning that it should focus on the analysis of complex realworld engineering problems software plays a crucial role for the control of selfdriving cars therefore software engineering solutions should seriously handle ethical and social considerations in this paper we take a closer look at the regulative instruments standards design and implementations of components systems and services and we present practical social and ethical challenges that have to be met as well as novel expectations for software engineering
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1,802.04104
Driving Simulator Platform for Development and Evaluation of Safety and Emergency Systems
According to data from the United Nations, more than 3000 people have died each day in the world due to road traffic collision. Considering recent researches, the human error may be considered as the main responsible for these fatalities. Because of this, researchers seek alternatives to transfer the vehicle control from people to autonomous systems. However, providing this technological innovation for the people may demand complex challenges in the legal, economic and technological areas. Consequently, carmakers and researchers have divided the driving automation in safety and emergency systems that improve the driver perception on the road. This may reduce the human error. Therefore, the main contribution of this study is to propose a driving simulator platform to develop and evaluate safety and emergency systems, in the first design stage. This driving simulator platform has an advantage: a flexible software structure.This allows in the simulation one adaptation for development or evaluation of a system. The proposed driving simulator platform was tested in two applications: cooperative vehicle system development and the influence evaluation of a Driving Assistance System (\textit{DAS}) on a driver. In the cooperative vehicle system development, the results obtained show that the increment of the time delay in the communication among vehicles ($V2V$) is determinant for the system performance. On the other hand, in the influence evaluation of a \textit{DAS} in a driver, it was possible to conclude that the \textit{DAS'} model does not have the level of influence necessary in a driver to avoid an accident.
cs.CY cs.RO
according to data from the united nations more than 3000 people have died each day in the world due to road traffic collision considering recent researches the human error may be considered as the main responsible for these fatalities because of this researchers seek alternatives to transfer the vehicle control from people to autonomous systems however providing this technological innovation for the people may demand complex challenges in the legal economic and technological areas consequently carmakers and researchers have divided the driving automation in safety and emergency systems that improve the driver perception on the road this may reduce the human error therefore the main contribution of this study is to propose a driving simulator platform to develop and evaluate safety and emergency systems in the first design stage this driving simulator platform has an advantage a flexible software structurethis allows in the simulation one adaptation for development or evaluation of a system the proposed driving simulator platform was tested in two applications cooperative vehicle system development and the influence evaluation of a driving assistance system textitdas on a driver in the cooperative vehicle system development the results obtained show that the increment of the time delay in the communication among vehicles v2v is determinant for the system performance on the other hand in the influence evaluation of a textitdas in a driver it was possible to conclude that the textitdas model does not have the level of influence necessary in a driver to avoid an accident
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1,802.04105
Scalable Architecture for Personalized Healthcare Service Recommendation using Big Data Lake
The personalized health care service utilizes the relational patient data and big data analytics to tailor the medication recommendations. However, most of the health care data are in unstructured form and it consumes a lot of time and effort to pull them into relational form. This study proposes a novel data lake architecture to reduce the data ingestion time and improve the precision of healthcare analytics. It also removes the data silos and enhances the analytics by allowing the connectivity to the third-party data providers (such as clinical lab results, chemist, insurance company,etc.). The data lake architecture uses the Hadoop Distributed File System (HDFS) to provide the storage for both structured and unstructured data. This study uses K-means clustering algorithm to find the patient clusters with similar health conditions. Subsequently, it employs a support vector machine to find the most successful healthcare recommendations for the each cluster. Our experiment results demonstrate the ability of data lake to reduce the time for ingesting data from various data vendors regardless of its format. Moreover, it is evident that the data lake poses the potential to generate clusters of patients more precisely than the existing approaches. It is obvious that the data lake provides a unified storage location for the data in its native format. It can also improve the personalized healthcare medication recommendations by removing the data silos.
cs.CY
the personalized health care service utilizes the relational patient data and big data analytics to tailor the medication recommendations however most of the health care data are in unstructured form and it consumes a lot of time and effort to pull them into relational form this study proposes a novel data lake architecture to reduce the data ingestion time and improve the precision of healthcare analytics it also removes the data silos and enhances the analytics by allowing the connectivity to the thirdparty data providers such as clinical lab results chemist insurance companyetc the data lake architecture uses the hadoop distributed file system hdfs to provide the storage for both structured and unstructured data this study uses kmeans clustering algorithm to find the patient clusters with similar health conditions subsequently it employs a support vector machine to find the most successful healthcare recommendations for the each cluster our experiment results demonstrate the ability of data lake to reduce the time for ingesting data from various data vendors regardless of its format moreover it is evident that the data lake poses the potential to generate clusters of patients more precisely than the existing approaches it is obvious that the data lake provides a unified storage location for the data in its native format it can also improve the personalized healthcare medication recommendations by removing the data silos
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1,802.04106
Recent progress in subset combinatorics of groups
We systematize and analyze some results obtained in Subset Combinatorics of $G$ groups after publications the previous surveys [1-4]. The main topics: the dynamical and descriptive characterizations of subsets of a group relatively their combinatorial size, Ramsey-product subsets in connection with some general concept of recurrence in $G$-spaces, new ideals in the Boolean algebra $\mathcal{P}_{G}$ of all subsets of a group $G$ and in the Stone-$\check{C}$ech compactification $\beta G$ of $G$ , the combinatorial derivation.
math.CO math.GR
we systematize and analyze some results obtained in subset combinatorics of g groups after publications the previous surveys 14 the main topics the dynamical and descriptive characterizations of subsets of a group relatively their combinatorial size ramseyproduct subsets in connection with some general concept of recurrence in gspaces new ideals in the boolean algebra mathcalp_g of all subsets of a group g and in the stonecheckcech compactification beta g of g the combinatorial derivation
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1,802.04107
p-Laplacian Fractional Sturm-Liouville Problem for Diffusion Operator via Impulsive Condition
In this study, the existence results of solution is given for fractional p-Laplacian Stum-Liouville problem for diffusion operator of order with impulsive conditions. The derivatives are described in Riemann-Liouville and Caputo sense. The Riemann-Liouville integral operator is used to acquire the integral representation of solution. The existence of solution is demonstrate via Schaefer fixed point theorem.
math.CA
in this study the existence results of solution is given for fractional plaplacian stumliouville problem for diffusion operator of order with impulsive conditions the derivatives are described in riemannliouville and caputo sense the riemannliouville integral operator is used to acquire the integral representation of solution the existence of solution is demonstrate via schaefer fixed point theorem
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1,802.04108
Design a multicultural blended e-learning system
Most universities in developing countries are using a teaching and learning approach known as blended e-learning, however, there was no multicultural-based blended e-learning framework. Furthermore, there is no research to show the impact of multicultural blended e-learning on satisfaction of learners. This research employed two categories of students, the Iranian students and the Iraqi students studying at Razi University of Iran. These two groups were taught using the multicultural blended e-learning approach. We utilized an open source application named Claroline. Questionnaires were designed and administered to students to collect information about the level of satisfaction and the optimal mix of tools that go into blended multicultural-based e-learning. The collected information was analyzed using SPSS. We found that blended multicultural based e-learning improves the level of satisfaction of learners. In addition, the optimal mix of multicultural blended learning should be comprised 19% still pictures, audio files 23%, video files 31% and text files 27%.
cs.CY
most universities in developing countries are using a teaching and learning approach known as blended elearning however there was no multiculturalbased blended elearning framework furthermore there is no research to show the impact of multicultural blended elearning on satisfaction of learners this research employed two categories of students the iranian students and the iraqi students studying at razi university of iran these two groups were taught using the multicultural blended elearning approach we utilized an open source application named claroline questionnaires were designed and administered to students to collect information about the level of satisfaction and the optimal mix of tools that go into blended multiculturalbased elearning the collected information was analyzed using spss we found that blended multicultural based elearning improves the level of satisfaction of learners in addition the optimal mix of multicultural blended learning should be comprised 19 still pictures audio files 23 video files 31 and text files 27
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1,802.04109
Analysis of Complex System Development Based on Fuzzy Cognitive Mapping
This article represents one of the contemporary trends in the application of the latest methods of classification in business, where intense competition and the desire to expand drive this science to far-reaching prospects using the discusses months and the most recent classification and forecasting algorithms such as SVM, FFM, C4.5, which are used to build better business decision support models, including basic steps in data pre-processing such as Attributes using Information Gain Ratio and filling missing values with several algorithms:K-Means,K-NearestNeighbor,Linear Regression,Neural Network(Back Propagation)
cs.CY
this article represents one of the contemporary trends in the application of the latest methods of classification in business where intense competition and the desire to expand drive this science to farreaching prospects using the discusses months and the most recent classification and forecasting algorithms such as svm ffm c45 which are used to build better business decision support models including basic steps in data preprocessing such as attributes using information gain ratio and filling missing values with several algorithmskmeansknearestneighborlinear regressionneural networkback propagation
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1,802.0411
Means of unbounded sets
We study generalized means whose domain may contain unbounded sets as well. We investigate usual properties of this type of means and also new attributes that regard for such means only. We examine how a mean defined on bounded sets can be extended to this type of mean. We generalize some classic means and also present many new examples for means defined on unbounded sets.
math.CA
we study generalized means whose domain may contain unbounded sets as well we investigate usual properties of this type of means and also new attributes that regard for such means only we examine how a mean defined on bounded sets can be extended to this type of mean we generalize some classic means and also present many new examples for means defined on unbounded sets
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1,802.04111
TMOKE as efficient tool for the magneto-optic analysis of ultra-thin magnetic films
Ultra-thin magnetic dielectric films are of prime importance due to their applications for nanophotonics and spintronics. Here, we propose an efficient method for the magneto-optical investigation of ultra-thin magnetic films which allows one to access their state of magnetization and magneto-optical properties. It is based on the surface-plasmon-polariton-assisted transverse magneto-optical Kerr effect (TMOKE). In our experiments, sub-100 nm-thick bismuth-substituted lutetium iron-garnet films covered with a plasmonic gold grating have been analyzed. The excitation of surface plasmon-polaritons provides resonance enhancement of TMOKE up to 0.04 and makes it easily detectable in the experiment. For films thicker than 40 nm, the TMOKE marginally depends on the film thickness. A further decrease in the film thickness diminishes TMOKE since for such thicknesses the surface plasmon-polariton field partly penetrates inside the non-magnetic substrate. Nevertheless, the TMOKE remains measurable even for few-nm-thick films, which makes this technique unique for the magneto-optical study of ultra-thin films. Particularly, the proposed method reveals that the off-diagonal components of the magnetic film permittivity tensor grow slightly with the reduction of the film thickness.
physics.ins-det physics.optics
ultrathin magnetic dielectric films are of prime importance due to their applications for nanophotonics and spintronics here we propose an efficient method for the magnetooptical investigation of ultrathin magnetic films which allows one to access their state of magnetization and magnetooptical properties it is based on the surfaceplasmonpolaritonassisted transverse magnetooptical kerr effect tmoke in our experiments sub100 nmthick bismuthsubstituted lutetium irongarnet films covered with a plasmonic gold grating have been analyzed the excitation of surface plasmonpolaritons provides resonance enhancement of tmoke up to 004 and makes it easily detectable in the experiment for films thicker than 40 nm the tmoke marginally depends on the film thickness a further decrease in the film thickness diminishes tmoke since for such thicknesses the surface plasmonpolariton field partly penetrates inside the nonmagnetic substrate nevertheless the tmoke remains measurable even for fewnmthick films which makes this technique unique for the magnetooptical study of ultrathin films particularly the proposed method reveals that the offdiagonal components of the magnetic film permittivity tensor grow slightly with the reduction of the film thickness
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1,802.04112
Infrastructure Enabled Autonomy: A Distributed Intelligence Architecture for Autonomous Vehicles
Multiple studies have illustrated the potential for dramatic societal, environmental and economic benefits from significant penetration of autonomous driving. However, all the current approaches to autonomous driving require the automotive manufacturers to shoulder the primary responsibility and liability associated with replacing human perception and decision making with automation, potentially slowing the penetration of autonomous vehicles, and consequently slowing the realization of the societal benefits of autonomous vehicles. We propose here a new approach to autonomous driving that will re-balance the responsibility and liabilities associated with autonomous driving between traditional automotive manufacturers, infrastructure players, and third-party players. Our proposed distributed intelligence architecture leverages the significant advancements in connectivity and edge computing in the recent decades to partition the driving functions between the vehicle, edge computers on the road side, and specialized third-party computers that reside in the vehicle. Infrastructure becomes a critical enabler for autonomy. With this Infrastructure Enabled Autonomy (IEA) concept, the traditional automotive manufacturers will only need to shoulder responsibility and liability comparable to what they already do today, and the infrastructure and third-party players will share the added responsibility and liabilities associated with autonomous functionalities. We propose a Bayesian Network Model based framework for assessing the risk benefits of such a distributed intelligence architecture. An additional benefit of the proposed architecture is that it enables "autonomy as a service" while still allowing for private ownership of automobiles.
cs.CY cs.DC cs.MA cs.RO
multiple studies have illustrated the potential for dramatic societal environmental and economic benefits from significant penetration of autonomous driving however all the current approaches to autonomous driving require the automotive manufacturers to shoulder the primary responsibility and liability associated with replacing human perception and decision making with automation potentially slowing the penetration of autonomous vehicles and consequently slowing the realization of the societal benefits of autonomous vehicles we propose here a new approach to autonomous driving that will rebalance the responsibility and liabilities associated with autonomous driving between traditional automotive manufacturers infrastructure players and thirdparty players our proposed distributed intelligence architecture leverages the significant advancements in connectivity and edge computing in the recent decades to partition the driving functions between the vehicle edge computers on the road side and specialized thirdparty computers that reside in the vehicle infrastructure becomes a critical enabler for autonomy with this infrastructure enabled autonomy iea concept the traditional automotive manufacturers will only need to shoulder responsibility and liability comparable to what they already do today and the infrastructure and thirdparty players will share the added responsibility and liabilities associated with autonomous functionalities we propose a bayesian network model based framework for assessing the risk benefits of such a distributed intelligence architecture an additional benefit of the proposed architecture is that it enables autonomy as a service while still allowing for private ownership of automobiles
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1,802.04113
Linear Regression for Speaker Verification
This paper presents a linear regression based back-end for speaker verification. Linear regression is a simple linear model that minimizes the mean squared estimation error between the target and its estimate with a closed form solution, where the target is defined as the ground-truth indicator vectors of utterances. We use the linear regression model to learn speaker models from a front-end, and verify the similarity of two speaker models by a cosine similarity scoring classifier. To evaluate the effectiveness of the linear regression model, we construct three speaker verification systems that use the Gaussian mixture model and identity-vector (GMM/i-vector) front-end, deep neural network and i-vector (DNN/i-vector) front-end, and deep vector (d-vector) front-end as their front-ends, respectively. Our empirical comparison results on the NIST speaker recognition evaluation data sets show that the proposed method outperforms within-class covariance normalization, linear discriminant analysis, and probabilistic linear discriminant analysis, given any of the three front-ends.
cs.SD eess.AS
this paper presents a linear regression based backend for speaker verification linear regression is a simple linear model that minimizes the mean squared estimation error between the target and its estimate with a closed form solution where the target is defined as the groundtruth indicator vectors of utterances we use the linear regression model to learn speaker models from a frontend and verify the similarity of two speaker models by a cosine similarity scoring classifier to evaluate the effectiveness of the linear regression model we construct three speaker verification systems that use the gaussian mixture model and identityvector gmmivector frontend deep neural network and ivector dnnivector frontend and deep vector dvector frontend as their frontends respectively our empirical comparison results on the nist speaker recognition evaluation data sets show that the proposed method outperforms withinclass covariance normalization linear discriminant analysis and probabilistic linear discriminant analysis given any of the three frontends
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1,802.04114
A sharpened Strichartz inequality for the wave equation
We disprove a conjecture of Foschi, regarding extremizers for the Strichartz inequality with data in the Sobolev space $\dot{H}^{1/2}\times\dot{H}^{-1/2}(\mathbb R^d)$, for even $d\ge 2$. On the other hand, we provide evidence to support the conjecture in odd dimensions, and refine his sharp inequality in $\mathbb R^{1+3}$, adding a term proportional to the distance of the initial data from the set of extremizers. The proofs use the conformal compactification of the Minkowski space-time given by the Penrose transform.
math.CA math.AP
we disprove a conjecture of foschi regarding extremizers for the strichartz inequality with data in the sobolev space doth12timesdoth12mathbb rd for even dge 2 on the other hand we provide evidence to support the conjecture in odd dimensions and refine his sharp inequality in mathbb r13 adding a term proportional to the distance of the initial data from the set of extremizers the proofs use the conformal compactification of the minkowski spacetime given by the penrose transform
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1,802.04115
Socle deformed preprojective algebras of generalized Dynkin type
We provide a complete classification of finite-dimensional self-injective algebras which are socle equivalent to preprojective algebras of generalized Dynkin type. In particular, we conclude that these algebras are deformed preprojective algebras of generalized Dynkin type (in the sense of [5, 12]), and hence are periodic algebras.
math.RT
we provide a complete classification of finitedimensional selfinjective algebras which are socle equivalent to preprojective algebras of generalized dynkin type in particular we conclude that these algebras are deformed preprojective algebras of generalized dynkin type in the sense of 5 12 and hence are periodic algebras
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1,802.04116
A Split Random Time Stepping Method for Stiff and Non-stiff Chemically Reacting Flows
In this paper, a new fractional step method is proposed for simulating stiff and nonstiff chemically reacting flows. In stiff cases, a well-known spurious numerical phenomenon, i.e. the incorrect propagation speed of discontinuities, may be produced by general fractional step methods due to the under-resolved discretization in both space and time. The previous random projection method has been successfully applied for stiff detonation capturing in under-resolved conditions. Not to randomly project the intermediate state into two presumed equilibrium states (completely burnt or unburnt) as in the random projection method, the present study is to randomly choose the time-dependent advance or stop of a reaction process. Each one-way reaction has been decoupled from the multi-reaction kinetics using operator splitting and the local smeared temperature due to numerical dissipation of shock-capturing schemes is compared with a random one within two limited temperatures corresponding to the advance and its inverse states, respectively, to control the random reaction. The random activation or deactivation in the reaction step is thus promising to correct the deterministic accumulative error of the propagation of discontinuities. Extensive numerical experiments, including model problems and realistic reacting flows in one and two dimensions, demonstrate this expectation as well as the effectiveness and robustness of the method. Meanwhile, for nonstiff problems when spatial and temporal resolutions are fine, the proposed random method recovers the results as general fractional step methods, owing to the increasing possibility of activation with diminishing randomness by adding a shift term.
physics.comp-ph physics.chem-ph
in this paper a new fractional step method is proposed for simulating stiff and nonstiff chemically reacting flows in stiff cases a wellknown spurious numerical phenomenon ie the incorrect propagation speed of discontinuities may be produced by general fractional step methods due to the underresolved discretization in both space and time the previous random projection method has been successfully applied for stiff detonation capturing in underresolved conditions not to randomly project the intermediate state into two presumed equilibrium states completely burnt or unburnt as in the random projection method the present study is to randomly choose the timedependent advance or stop of a reaction process each oneway reaction has been decoupled from the multireaction kinetics using operator splitting and the local smeared temperature due to numerical dissipation of shockcapturing schemes is compared with a random one within two limited temperatures corresponding to the advance and its inverse states respectively to control the random reaction the random activation or deactivation in the reaction step is thus promising to correct the deterministic accumulative error of the propagation of discontinuities extensive numerical experiments including model problems and realistic reacting flows in one and two dimensions demonstrate this expectation as well as the effectiveness and robustness of the method meanwhile for nonstiff problems when spatial and temporal resolutions are fine the proposed random method recovers the results as general fractional step methods owing to the increasing possibility of activation with diminishing randomness by adding a shift term
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1,802.04117
Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges
The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected. Meanwhile, the deregulation of the power industry, particularly on the delivery side, has continuously been moving forward worldwide. How to employ massive smart meter data to promote and enhance the efficiency and sustainability of the power grid is a pressing issue. To date, substantial works have been conducted on smart meter data analytics. To provide a comprehensive overview of the current research and to identify challenges for future research, this paper conducts an application-oriented review of smart meter data analytics. Following the three stages of analytics, namely, descriptive, predictive and prescriptive analytics, we identify the key application areas as load analysis, load forecasting, and load management. We also review the techniques and methodologies adopted or developed to address each application. In addition, we also discuss some research trends, such as big data issues, novel machine learning technologies, new business models, the transition of energy systems, and data privacy and security.
cs.CY
the widespread popularity of smart meters enables an immense amount of finegrained electricity consumption data to be collected meanwhile the deregulation of the power industry particularly on the delivery side has continuously been moving forward worldwide how to employ massive smart meter data to promote and enhance the efficiency and sustainability of the power grid is a pressing issue to date substantial works have been conducted on smart meter data analytics to provide a comprehensive overview of the current research and to identify challenges for future research this paper conducts an applicationoriented review of smart meter data analytics following the three stages of analytics namely descriptive predictive and prescriptive analytics we identify the key application areas as load analysis load forecasting and load management we also review the techniques and methodologies adopted or developed to address each application in addition we also discuss some research trends such as big data issues novel machine learning technologies new business models the transition of energy systems and data privacy and security
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1,802.04118
On a toy network of neurons interacting through their dendrites
Consider a large number $n$ of neurons, each being connected to approximately $N$ other ones, chosen at random. When a neuron spikes, which occurs randomly at some rate depending on its electric potential, its potential is set to a minimum value $v_{min}$, and this initiates, after a small delay, two fronts on the (linear) dendrites of all the neurons to which it is connected. Fronts move at constant speed. When two fronts (on the dendrite of the same neuron) collide, they annihilate. When a front hits the soma of a neuron, its potential is increased by a small value $w_n$. Between jumps, the potentials of the neurons are assumed to drift in $[v_{min},\infty)$, according to some well-posed ODE. We prove the existence and uniqueness of a heuristically derived mean-field limit of the system when $n,N \to \infty$ with $w_n \simeq N^{-1/2}$. We make use of some recent versions of the results of Deuschel and Zeitouni \cite{dz} concerning the size of the longest increasing subsequence of an i.i.d. collection of points in the plan. We also study, in a very particular case, a slightly different model where the neurons spike when their potential reach some maximum value $v_{max}$, and find an explicit formula for the (heuristic) mean-field limit.
math.PR q-bio.NC
consider a large number n of neurons each being connected to approximately n other ones chosen at random when a neuron spikes which occurs randomly at some rate depending on its electric potential its potential is set to a minimum value v_min and this initiates after a small delay two fronts on the linear dendrites of all the neurons to which it is connected fronts move at constant speed when two fronts on the dendrite of the same neuron collide they annihilate when a front hits the soma of a neuron its potential is increased by a small value w_n between jumps the potentials of the neurons are assumed to drift in v_mininfty according to some wellposed ode we prove the existence and uniqueness of a heuristically derived meanfield limit of the system when nn to infty with w_n simeq n12 we make use of some recent versions of the results of deuschel and zeitouni citedz concerning the size of the longest increasing subsequence of an iid collection of points in the plan we also study in a very particular case a slightly different model where the neurons spike when their potential reach some maximum value v_max and find an explicit formula for the heuristic meanfield limit
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1,802.04119
Fully self-referenced frequency comb consuming 5 Watts of electrical power
We present a hybrid fiber/waveguide design for a 100-MHz frequency comb that is fully self-referenced and temperature controlled with less than 5 W of electrical power. Self-referencing is achieved by supercontinuum generation in a silicon nitride waveguide, which requires much lower pulse energies (~200 pJ) than with highly nonlinear fiber. These low-energy pulses are achieved with an erbium fiber oscillator/amplifier pumped by two 250-mW passively-cooled pump diodes that consume less than 5 W of electrical power. The temperature tuning of the oscillator, necessary to stabilize the repetition rate in the presence of environmental temperature changes, is achieved by resistive heating of a section of gold-palladium-coated fiber within the laser cavity. By heating only the small thermal mass of the fiber, the repetition rate is tuned over 4.2 kHz (corresponding to an effective temperature change of 4.2 {\deg}C) with a fast time constant of 0.5 s, at a low power consumption of 0.077 W/{\deg}C, compared to 2.5 W/{\deg}C in the conventional 200-MHz comb design.
physics.ins-det physics.optics
we present a hybrid fiberwaveguide design for a 100mhz frequency comb that is fully selfreferenced and temperature controlled with less than 5 w of electrical power selfreferencing is achieved by supercontinuum generation in a silicon nitride waveguide which requires much lower pulse energies 200 pj than with highly nonlinear fiber these lowenergy pulses are achieved with an erbium fiber oscillatoramplifier pumped by two 250mw passivelycooled pump diodes that consume less than 5 w of electrical power the temperature tuning of the oscillator necessary to stabilize the repetition rate in the presence of environmental temperature changes is achieved by resistive heating of a section of goldpalladiumcoated fiber within the laser cavity by heating only the small thermal mass of the fiber the repetition rate is tuned over 42 khz corresponding to an effective temperature change of 42 degc with a fast time constant of 05 s at a low power consumption of 0077 wdegc compared to 25 wdegc in the conventional 200mhz comb design
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1,802.0412
Exact solution for Schwarzschild black hole in radiation gauge
Recently Chen and Zhu propose a true radiation gauge for gravity [Phys. Rev. D 83, 061501(R) (2011)]. This work presents a general solution for the metric of Schwarzschild black hole in this radiation gauge.
physics.gen-ph
recently chen and zhu propose a true radiation gauge for gravity phys rev d 83 061501r 2011 this work presents a general solution for the metric of schwarzschild black hole in this radiation gauge
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1,802.04121
Comparison Criteria for Discrete Fractional Sturm-Liouville Equations
In this study, we give the Sturm comparison theorems for discrete fractional Sturm-Liouville (DFSL) equations within Riemann-Liouville and Gr\"unwald-Letnikov sense. The emergence of Sturm-Liouville equations began as one dimensional Schr\"odinger equation in quantum mechanics and one of the most important results is Sturm comparison theorems [27]. These theorems give information about the properties of zeros of two equations having different potentials.
math.CA math.SP
in this study we give the sturm comparison theorems for discrete fractional sturmliouville dfsl equations within riemannliouville and grunwaldletnikov sense the emergence of sturmliouville equations began as one dimensional schrodinger equation in quantum mechanics and one of the most important results is sturm comparison theorems 27 these theorems give information about the properties of zeros of two equations having different potentials
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1,802.04122
Tagvisor: A Privacy Advisor for Sharing Hashtags
Hashtag has emerged as a widely used concept of popular culture and campaigns, but its implications on people's privacy have not been investigated so far. In this paper, we present the first systematic analysis of privacy issues induced by hashtags. We concentrate in particular on location, which is recognized as one of the key privacy concerns in the Internet era. By relying on a random forest model, we show that we can infer a user's precise location from hashtags with accuracy of 70\% to 76\%, depending on the city. To remedy this situation, we introduce a system called Tagvisor that systematically suggests alternative hashtags if the user-selected ones constitute a threat to location privacy. Tagvisor realizes this by means of three conceptually different obfuscation techniques and a semantics-based metric for measuring the consequent utility loss. Our findings show that obfuscating as little as two hashtags already provides a near-optimal trade-off between privacy and utility in our dataset. This in particular renders Tagvisor highly time-efficient, and thus, practical in real-world settings.
cs.CR cs.SI
hashtag has emerged as a widely used concept of popular culture and campaigns but its implications on peoples privacy have not been investigated so far in this paper we present the first systematic analysis of privacy issues induced by hashtags we concentrate in particular on location which is recognized as one of the key privacy concerns in the internet era by relying on a random forest model we show that we can infer a users precise location from hashtags with accuracy of 70 to 76 depending on the city to remedy this situation we introduce a system called tagvisor that systematically suggests alternative hashtags if the userselected ones constitute a threat to location privacy tagvisor realizes this by means of three conceptually different obfuscation techniques and a semanticsbased metric for measuring the consequent utility loss our findings show that obfuscating as little as two hashtags already provides a nearoptimal tradeoff between privacy and utility in our dataset this in particular renders tagvisor highly timeefficient and thus practical in realworld settings
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1,802.04123
Iterated logarithms and gradient flows
We consider applications of the theory of balanced weight filtrations and iterated logarithms, initiated in arXiv:1706.01073, to PDEs. The main result is a complete description of the asymptotics of the Yang--Mills flow on the space of metrics on a holomorphic bundle over a Riemann surface. A key ingredient in the argument is a monotonicity property of the flow which holds in arbitrary dimension. The A-side analog is a modified curve shortening flow for which we provide a heuristic calculation in support of a detailed conjectural picture.
math.RT math.AP math.DG
we consider applications of the theory of balanced weight filtrations and iterated logarithms initiated in arxiv170601073 to pdes the main result is a complete description of the asymptotics of the yangmills flow on the space of metrics on a holomorphic bundle over a riemann surface a key ingredient in the argument is a monotonicity property of the flow which holds in arbitrary dimension the aside analog is a modified curve shortening flow for which we provide a heuristic calculation in support of a detailed conjectural picture
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1,802.04124
Impact of Oxygen Diffusion on Superconductivity in YBa$_2$Cu$_3$O$_{7-\delta}$ Thin Films Studied by Positron Annihilation Spectroscopy
The oxygen deficiency $\delta$ in YBa$_2$Cu$_3$O$_{7-\delta}$ (YBCO) plays a crucial role for affecting high-temperature superconductivity. We applied (coincident) Doppler broadening spectroscopy of the electron-positron annihilation line to study in situ the temperature dependence of the oxygen concentration and its depth profile in single crystalline YBCO film grown on SrTiO$_3$ (STO) substrates. The oxygen diffusion during tempering was found to lead to a distinct depth dependence of $\delta$, which is not accessible using X-ray diffraction. A steady-state reached within a few minutes is defined by both, the oxygen exchange at the surface and at the interface to the STO substrate. Moreover, we revealed the depth dependent critical temperature $T_{\mathrm{c}}$ in the as prepared and tempered YBCO film.
cond-mat.supr-con
the oxygen deficiency delta in yba_2cu_3o_7delta ybco plays a crucial role for affecting hightemperature superconductivity we applied coincident doppler broadening spectroscopy of the electronpositron annihilation line to study in situ the temperature dependence of the oxygen concentration and its depth profile in single crystalline ybco film grown on srtio_3 sto substrates the oxygen diffusion during tempering was found to lead to a distinct depth dependence of delta which is not accessible using xray diffraction a steadystate reached within a few minutes is defined by both the oxygen exchange at the surface and at the interface to the sto substrate moreover we revealed the depth dependent critical temperature t_mathrmc in the as prepared and tempered ybco film
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1,802.04125
On a nonstatic Painleve-Gullstrand spacetime
A time dependent geometry outside a spherically symmetric mass is proposed. The source has zero energy density but nonzero radial and tangential pressures. The time variable is interpreted as the duration of measurement performed upon the physical system. For very short time intervals, the effect of the mass source is much reduced, going to zero when $t \rightarrow 0$. All physical quantities are finite when $t \rightarrow 0$ and $r \rightarrow 0$ and also at infinity. The total energy flux measured on a hypersurface of constant $r$ is vanishing.
physics.gen-ph
a time dependent geometry outside a spherically symmetric mass is proposed the source has zero energy density but nonzero radial and tangential pressures the time variable is interpreted as the duration of measurement performed upon the physical system for very short time intervals the effect of the mass source is much reduced going to zero when t rightarrow 0 all physical quantities are finite when t rightarrow 0 and r rightarrow 0 and also at infinity the total energy flux measured on a hypersurface of constant r is vanishing
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1,802.04126
Classification of proper holomorphic mappings between certain unbounded non-hyperbolic domains
The Fock-Bargmann-Hartogs domain $D_{n,m}(\mu)$ ($\mu>0$) in $\mathbb{C}^{n+m}$ is defined by the inequality $\|w\|^2<e^{-\mu\|z\|^2},$ where $(z,w)\in \mathbb{C}^n\times \mathbb{C}^m$, which is an unbounded non-hyperbolic domain in $\mathbb{C}^{n+m}$. Recently, Tu-Wang obtained the rigidity result that proper holomorphic self-mappings of $D_{n,m}(\mu)$ are automorphisms for $m\geq 2$, and found a counter-example to show that the rigidity result isn't true for $D_{n,1}(\mu)$. In this article, we obtain a classification of proper holomorphic mappings between $D_{n,1}(\mu)$ and $D_{N,1}(\mu)$ with $N<2n$.
math.CV
the fockbargmannhartogs domain d_nmmu mu0 in mathbbcnm is defined by the inequality w2emuz2 where zwin mathbbcntimes mathbbcm which is an unbounded nonhyperbolic domain in mathbbcnm recently tuwang obtained the rigidity result that proper holomorphic selfmappings of d_nmmu are automorphisms for mgeq 2 and found a counterexample to show that the rigidity result isnt true for d_n1mu in this article we obtain a classification of proper holomorphic mappings between d_n1mu and d_n1mu with n2n
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1,802.04127
A New Algorithmic Decision for Categorical Syllogisms via Caroll's Diagrams
In this paper, we deal with a calculus system SLCD (Syllogistic Logic with Carroll Diagrams), which gives a formal approach to logical reasoning with diagrams, for representations of the fundamental Aristotelian categorical propositions and show that they are closed under the syllogistic criterion of inference which is the deletion of middle term. Therefore, it is implemented to let the formalism comprise synchronically bilateral and trilateral diagrammatical appearance and a naive algorithmic nature. And also, there is no need specific knowledge or exclusive ability to understand as well as to use it. Consequently, we give an effective algorithm used to determine whether a syllogistic reasoning valid or not by using SLCD.
cs.AI cs.LO
in this paper we deal with a calculus system slcd syllogistic logic with carroll diagrams which gives a formal approach to logical reasoning with diagrams for representations of the fundamental aristotelian categorical propositions and show that they are closed under the syllogistic criterion of inference which is the deletion of middle term therefore it is implemented to let the formalism comprise synchronically bilateral and trilateral diagrammatical appearance and a naive algorithmic nature and also there is no need specific knowledge or exclusive ability to understand as well as to use it consequently we give an effective algorithm used to determine whether a syllogistic reasoning valid or not by using slcd
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1,802.04128
Smart energy management as a means towards improved energy efficiency
The costs associated with refrigerator equipment often represent more than half of the total energy costs in supermarkets. This presents a good motivation for running these systems efficiently. In this study, we investigate different ways to construct a reference behavior, which can serve as a baseline for judging the performance of energy consumption. We used 3 distinct learning models: Multiple Linear Regression, Random Forests, and Artificial Neural Networks. During our experiments we used a variation of the sliding window method in combination with learning curves. We applied this approach on five different supermarkets, across Portugal. We are able to create baselines using off-the-shelf data mining techniques. Moreover, we found a way to create them based on short term historical data. We believe that our research will serve as a base for future studies, for which we provide interesting directions.
cs.CY cs.LG
the costs associated with refrigerator equipment often represent more than half of the total energy costs in supermarkets this presents a good motivation for running these systems efficiently in this study we investigate different ways to construct a reference behavior which can serve as a baseline for judging the performance of energy consumption we used 3 distinct learning models multiple linear regression random forests and artificial neural networks during our experiments we used a variation of the sliding window method in combination with learning curves we applied this approach on five different supermarkets across portugal we are able to create baselines using offtheshelf data mining techniques moreover we found a way to create them based on short term historical data we believe that our research will serve as a base for future studies for which we provide interesting directions
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1,802.04129
Integer completely positive matrices of order two
We show that every integer doubly nonnegative $2 \times 2$ matrix has an integer cp-factorization.
math.OC
we show that every integer doubly nonnegative 2 times 2 matrix has an integer cpfactorization
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1,802.0413
Exploring the decay probability of neutron-rich superheavy nuclei
The modes of decay for the even-even isotopes of superheavy nuclei of Z = 118 and 120 with neutron number $160 \leq N \leq 204$ are investigated in the framework of the axially deformed relativistic mean field model. The asymmetry parameter $\eta$ and the relative neutron-proton asymmetry of the surface to the center ($R_{\eta}$) are estimated for the ground state density distributions of the nuclei. We suggest that the resulting asymmetry parameter $\eta$ and the relative neutron-proton asymmetry $R_{\eta}$ of the density play a crucial role in the preformation factor of the decay half life.
nucl-th
the modes of decay for the eveneven isotopes of superheavy nuclei of z 118 and 120 with neutron number 160 leq n leq 204 are investigated in the framework of the axially deformed relativistic mean field model the asymmetry parameter eta and the relative neutronproton asymmetry of the surface to the center r_eta are estimated for the ground state density distributions of the nuclei we suggest that the resulting asymmetry parameter eta and the relative neutronproton asymmetry r_eta of the density play a crucial role in the preformation factor of the decay half life
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1,802.04131
Annular Evaluation and Link Homology
We use categorical annular evaluation to give a uniform construction of both $\mathfrak{sl}_n$ and HOMFLYPT Khovanov-Rozansky link homology, as well as annular versions of these theories. Variations on our construction yield $\mathfrak{gl}_{-n}$ link homology, i.e. a link homology theory associated to the Lie superalgebra $\mathfrak{gl}_{0|n}$, both for links in $S^3$ and in the thickened annulus. In the $n=2$ case, this produces a categorification of the Jones polynomial that we show is distinct from Khovanov homology, and gives a finite-dimensional categorification of the colored Jones polynomial. This behavior persists for general $n$. Our approach yields simple constructions of spectral sequences relating these theories, and emphasizes the roles of super vector spaces, categorical traces, and current algebras in link homology.
math.GT math.QA math.RT
we use categorical annular evaluation to give a uniform construction of both mathfraksl_n and homflypt khovanovrozansky link homology as well as annular versions of these theories variations on our construction yield mathfrakgl_n link homology ie a link homology theory associated to the lie superalgebra mathfrakgl_0n both for links in s3 and in the thickened annulus in the n2 case this produces a categorification of the jones polynomial that we show is distinct from khovanov homology and gives a finitedimensional categorification of the colored jones polynomial this behavior persists for general n our approach yields simple constructions of spectral sequences relating these theories and emphasizes the roles of super vector spaces categorical traces and current algebras in link homology
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1,802.04132
Hierarchical Learning for Modular Robots
We argue that hierarchical methods can become the key for modular robots achieving reconfigurability. We present a hierarchical approach for modular robots that allows a robot to simultaneously learn multiple tasks. Our evaluation results present an environment composed of two different modular robot configurations, namely 3 degrees-of-freedom (DoF) and 4DoF with two corresponding targets. During the training, we switch between configurations and targets aiming to evaluate the possibility of training a neural network that is able to select appropriate motor primitives and robot configuration to achieve the target. The trained neural network is then transferred and executed on a real robot with 3DoF and 4DoF configurations. We demonstrate how this technique generalizes to robots with different configurations and tasks.
cs.RO
we argue that hierarchical methods can become the key for modular robots achieving reconfigurability we present a hierarchical approach for modular robots that allows a robot to simultaneously learn multiple tasks our evaluation results present an environment composed of two different modular robot configurations namely 3 degreesoffreedom dof and 4dof with two corresponding targets during the training we switch between configurations and targets aiming to evaluate the possibility of training a neural network that is able to select appropriate motor primitives and robot configuration to achieve the target the trained neural network is then transferred and executed on a real robot with 3dof and 4dof configurations we demonstrate how this technique generalizes to robots with different configurations and tasks
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1,802.04133
A semi-analytical approach to black body radiation
We describe a semi-analytical method to calculate the total radiance received form a black body, between two frequencies. As has been done before, the method takes advantage of the fact that the solution simplifies with the use of polylogarithm functions. We then use it to study the amount of radiation from the sun received by bodies at Earths surface.
physics.gen-ph
we describe a semianalytical method to calculate the total radiance received form a black body between two frequencies as has been done before the method takes advantage of the fact that the solution simplifies with the use of polylogarithm functions we then use it to study the amount of radiation from the sun received by bodies at earths surface
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1,802.04134
Power System Simulation Using the Differential Transformation Method
This paper proposes a new semi-analytical approach for online time-domain power system simulation. The approach applies the differential transformation method (DTM) to the power system differential equation model to offline derive a semi-analytical solution (SAS) having symbolic variables about time, the initial state and system conditions. When simulation is online needed for a contingency under the current system condition, the SAS can be evaluated in real time to generate simulation results. Compared to the Adomian decomposition method in obtaining a power system SAS, an SAS derived by the DTM adopts a recursive form to avoid generating and storing its complete symbolic expression, which makes both derivation and evaluation of the SAS more efficient especially for multi-machine power systems. The optimal order of a DTM-based SAS is studied for the best time performance of simulation. The paper also designs a parallel computing strategy for power system simulation using the DTM-based SAS. Tests on the IEEE 10-machine 39-bus system demonstrate significant speedup of simulation using the proposed approach compared with the Runge-Kutta method.
math.DS cs.SY math.NA
this paper proposes a new semianalytical approach for online timedomain power system simulation the approach applies the differential transformation method dtm to the power system differential equation model to offline derive a semianalytical solution sas having symbolic variables about time the initial state and system conditions when simulation is online needed for a contingency under the current system condition the sas can be evaluated in real time to generate simulation results compared to the adomian decomposition method in obtaining a power system sas an sas derived by the dtm adopts a recursive form to avoid generating and storing its complete symbolic expression which makes both derivation and evaluation of the sas more efficient especially for multimachine power systems the optimal order of a dtmbased sas is studied for the best time performance of simulation the paper also designs a parallel computing strategy for power system simulation using the dtmbased sas tests on the ieee 10machine 39bus system demonstrate significant speedup of simulation using the proposed approach compared with the rungekutta method
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1,802.04135
A New Uzawa-exact Type Algorithm for Nonsymmetric Saddle Point Problems
Saddle point problems have been attracting people's attention in recent years. To solve large and sparse saddle point problems, Uzawa type algorithms were proposed. The main contribution of this paper is to present a new Uzawa-exact type algorithm from the aspect of optimization method to solve nonsymmetric saddle point problems, which often arise from linear variational inequalities and finite element discretization of Navier-Stokes equations. In the paper, convergence of the new algorithm is analysed and numerical experiments are presented.
math.OC
saddle point problems have been attracting peoples attention in recent years to solve large and sparse saddle point problems uzawa type algorithms were proposed the main contribution of this paper is to present a new uzawaexact type algorithm from the aspect of optimization method to solve nonsymmetric saddle point problems which often arise from linear variational inequalities and finite element discretization of navierstokes equations in the paper convergence of the new algorithm is analysed and numerical experiments are presented
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1,802.04136
Cryptographically Secure Multi-Tenant Provisioning of FPGAs
FPGAs (Field Programmable Gate arrays) have gained massive popularity today as accelerators for a variety of workloads, including big data analytics, and parallel and distributed computing. This has fueled the study of mechanisms to provision FPGAs among multiple tenants as general purpose computing resources on the cloud. Such mechanisms offer new challenges, such as ensuring IP protection and bitstream confidentiality for mutually distrusting clients sharing the same FPGA. A direct adoption of existing IP protection techniques from the single tenancy setting do not completely address these challenges, and are also not scalable enough for practical deployment. In this paper, we propose a dedicated and scalable framework for secure multi-tenant FPGA provisioning that can be easily integrated into existing cloud-based infrastructures such as OpenStack. Our technique has constant resource/memory overhead irrespective of the number of tenants sharing a given FPGA, and is provably secure under well-studied cryptographic assumptions. A prototype implementation of our proposition on Xilinx Virtex-7 UltraScale FPGAs is presented to validate its overheads and scalability when supporting multiple tenants and workloads. To the best of our knowledge, this is the first FPGA provisioning framework to be prototyped that achieves a desirable balance between security and scalability in the multi-tenancy setting.
cs.CR
fpgas field programmable gate arrays have gained massive popularity today as accelerators for a variety of workloads including big data analytics and parallel and distributed computing this has fueled the study of mechanisms to provision fpgas among multiple tenants as general purpose computing resources on the cloud such mechanisms offer new challenges such as ensuring ip protection and bitstream confidentiality for mutually distrusting clients sharing the same fpga a direct adoption of existing ip protection techniques from the single tenancy setting do not completely address these challenges and are also not scalable enough for practical deployment in this paper we propose a dedicated and scalable framework for secure multitenant fpga provisioning that can be easily integrated into existing cloudbased infrastructures such as openstack our technique has constant resourcememory overhead irrespective of the number of tenants sharing a given fpga and is provably secure under wellstudied cryptographic assumptions a prototype implementation of our proposition on xilinx virtex7 ultrascale fpgas is presented to validate its overheads and scalability when supporting multiple tenants and workloads to the best of our knowledge this is the first fpga provisioning framework to be prototyped that achieves a desirable balance between security and scalability in the multitenancy setting
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1,802.04137
Erd\H{o}s Semi-groups, arithmetic progressions and Szemer\'edi's theorem
In this paper we introduce and study a certain type of sub semi-group of $\mathbb{R}/\mathbb{Z}$ which turns out to be closely related to \sz's theorem on arithmetic progressions.
math.MG
in this paper we introduce and study a certain type of sub semigroup of mathbbrmathbbz which turns out to be closely related to szs theorem on arithmetic progressions
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1,802.04138
Growth of Sobolev norms for time dependent periodic Schr\"odinger equations with sublinear dispersion
In this paper we consider Schr\"odinger equations with sublinear dispersion relation on the one-dimensional torus $\T := \R /(2 \pi \Z)$. More precisely, we deal with equations of the form $\partial_t u = \ii {\cal V}(\omega t)[u]$ where ${\cal V}(\omega t)$ is a quasi-periodic in time, self-adjoint pseudo-differential operator of the form ${\cal V}(\omega t) = V(\omega t, x) |D|^M + {\cal W}(\omega t)$, $0 < M \leq 1$, $|D| := \sqrt{- \partial_{xx}}$, $V$ is a smooth, quasi-periodic in time function and ${\cal W}$ is a quasi-periodic time-dependent pseudo-differential operator of order strictly smaller than $M$. Under suitable assumptions on $V$ and ${\cal W}$, we prove that if $\omega$ satisfies some non-resonance conditions, the solutions of the Schr\"odinger equation $\partial_t u = \ii {\cal V}(\omega t)[u]$ grow at most as $t^\eta$, $t \to + \infty$ for any $\eta > 0$. The proof is based on a reduction to constant coefficients up to smoothing remainders of the vector field $\ii {\cal V}(\omega t)$ which uses Egorov type theorems and pseudo-differential calculus. The {\it homological equations} arising in the reduction procedure involve both time and space derivatives, since the dispersion relation is sublinear. Such equations can be solved by imposing some Melnikov non-resonance conditions on the frequency vector $\omega$.
math.AP
in this paper we consider schrodinger equations with sublinear dispersion relation on the onedimensional torus t r 2 pi z more precisely we deal with equations of the form partial_t u ii cal vomega tu where cal vomega t is a quasiperiodic in time selfadjoint pseudodifferential operator of the form cal vomega t vomega t x dm cal womega t 0 m leq 1 d sqrt partial_xx v is a smooth quasiperiodic in time function and cal w is a quasiperiodic timedependent pseudodifferential operator of order strictly smaller than m under suitable assumptions on v and cal w we prove that if omega satisfies some nonresonance conditions the solutions of the schrodinger equation partial_t u ii cal vomega tu grow at most as teta t to infty for any eta 0 the proof is based on a reduction to constant coefficients up to smoothing remainders of the vector field ii cal vomega t which uses egorov type theorems and pseudodifferential calculus the it homological equations arising in the reduction procedure involve both time and space derivatives since the dispersion relation is sublinear such equations can be solved by imposing some melnikov nonresonance conditions on the frequency vector omega
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1,802.04139
Quasi-periodic solutions for the forced Kirchhoff equation on $\mathbb{T}^d$
In this paper we prove the existence of small-amplitude quasi-periodic solutions with Sobolev regularity, for the $d$-dimensional forced Kirchhoff equation with periodic boundary conditions. This is the first result of this type for a quasi-linear equations in high dimension. The proof is based on a Nash-Moser scheme in Sobolev class and a regularization procedure combined with a multiscale analysis in order to solve the linearized problem at any approximate solution.
math.AP
in this paper we prove the existence of smallamplitude quasiperiodic solutions with sobolev regularity for the ddimensional forced kirchhoff equation with periodic boundary conditions this is the first result of this type for a quasilinear equations in high dimension the proof is based on a nashmoser scheme in sobolev class and a regularization procedure combined with a multiscale analysis in order to solve the linearized problem at any approximate solution
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1,802.0414
Making "fetch" happen: The influence of social and linguistic context on nonstandard word growth and decline
In an online community, new words come and go: today's "haha" may be replaced by tomorrow's "lol." Changes in online writing are usually studied as a social process, with innovations diffusing through a network of individuals in a speech community. But unlike other types of innovation, language change is shaped and constrained by the system in which it takes part. To investigate the links between social and structural factors in language change, we undertake a large-scale analysis of nonstandard word growth in the online community Reddit. We find that dissemination across many linguistic contexts is a sign of growth: words that appear in more linguistic contexts grow faster and survive longer. We also find that social dissemination likely plays a less important role in explaining word growth and decline than previously hypothesized.
cs.CL
in an online community new words come and go todays haha may be replaced by tomorrows lol changes in online writing are usually studied as a social process with innovations diffusing through a network of individuals in a speech community but unlike other types of innovation language change is shaped and constrained by the system in which it takes part to investigate the links between social and structural factors in language change we undertake a largescale analysis of nonstandard word growth in the online community reddit we find that dissemination across many linguistic contexts is a sign of growth words that appear in more linguistic contexts grow faster and survive longer we also find that social dissemination likely plays a less important role in explaining word growth and decline than previously hypothesized
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1,802.04141
Conservative stochastic 2-dimensional Cahn-Hilliard equation
We consider the stochastic 2-dimensional Cahn-Hilliard equation which is driven by the derivative in space of a space-time white noise. We use two different approaches to study this equation. First we prove that there exists a unique solution $Y$ to the shifted equation (see (1.4) below), then $X:=Y+{Z}$ is the unique solution to stochastic Cahn-Hilliard equaiton, where ${Z}$ is the corresponding O-U process. Moreover, we use Dirichlet form approach in \cite{Albeverio:1991hk} to construct the probabilistically weak solution the the original equation (1.1) below. By clarifying the precise relation between the solutions obtained by the Dirichlet forms aprroach and $X$, we can also get the restricted Markov uniquness of the generator and the uniqueness of martingale solutions to the equation (1.1).
math.PR math.AP math.FA
we consider the stochastic 2dimensional cahnhilliard equation which is driven by the derivative in space of a spacetime white noise we use two different approaches to study this equation first we prove that there exists a unique solution y to the shifted equation see 14 below then xyz is the unique solution to stochastic cahnhilliard equaiton where z is the corresponding ou process moreover we use dirichlet form approach in citealbeverio1991hk to construct the probabilistically weak solution the the original equation 11 below by clarifying the precise relation between the solutions obtained by the dirichlet forms aprroach and x we can also get the restricted markov uniquness of the generator and the uniqueness of martingale solutions to the equation 11
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1,802.04142
An ADMM Based Method for Computation Rate Maximization in Wireless Powered Mobile-Edge Computing Networks
In this paper, we consider a wireless powered mobile edge computing (MEC) network, where the distributed energy-harvesting wireless devices (WDs) are powered by means of radio frequency (RF) wireless power transfer (WPT). In particular, the WDs follow a binary computation offloading policy, i.e., data set of a computing task has to be executed as a whole either locally or remotely at the MEC server via task offloading. We are interested in maximizing the (weighted) sum computation rate of all the WDs in the network by jointly optimizing the individual computing mode selection (i.e., local computing or offloading) and the system transmission time allocation (on WPT and task offloading). The major difficulty lies in the combinatorial nature of multi-user computing mode selection and its strong coupling with transmission time allocation. To tackle this problem, we propose a joint optimization method based on the ADMM (alternating direction method of multipliers) decomposition technique. Simulation results show that the proposed method can efficiently achieve near-optimal performance under various network setups, and significantly outperform the other representative benchmark methods considered. Besides, using both theoretical analysis and numerical study, we show that the proposed method enjoys low computational complexity against the increase of networks size.
cs.IT math.IT
in this paper we consider a wireless powered mobile edge computing mec network where the distributed energyharvesting wireless devices wds are powered by means of radio frequency rf wireless power transfer wpt in particular the wds follow a binary computation offloading policy ie data set of a computing task has to be executed as a whole either locally or remotely at the mec server via task offloading we are interested in maximizing the weighted sum computation rate of all the wds in the network by jointly optimizing the individual computing mode selection ie local computing or offloading and the system transmission time allocation on wpt and task offloading the major difficulty lies in the combinatorial nature of multiuser computing mode selection and its strong coupling with transmission time allocation to tackle this problem we propose a joint optimization method based on the admm alternating direction method of multipliers decomposition technique simulation results show that the proposed method can efficiently achieve nearoptimal performance under various network setups and significantly outperform the other representative benchmark methods considered besides using both theoretical analysis and numerical study we show that the proposed method enjoys low computational complexity against the increase of networks size
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1,802.04143
The Fundamentals of Policy Crowdsourcing
What is the state of the research on crowdsourcing for policy making? This article begins to answer this question by collecting, categorizing, and situating an extensive body of the extant research investigating policy crowdsourcing, within a new framework built on fundamental typologies from each field. We first define seven universal characteristics of the three general crowdsourcing techniques (virtual labor markets, tournament crowdsourcing, open collaboration), to examine the relative trade-offs of each modality. We then compare these three types of crowdsourcing to the different stages of the policy cycle, in order to situate the literature spanning both domains. We finally discuss research trends in crowdsourcing for public policy, and highlight the research gaps and overlaps in the literature. KEYWORDS: crowdsourcing, policy cycle, crowdsourcing trade-offs, policy processes, policy stages, virtual labor markets, tournament crowdsourcing, open collaboration
cs.CY cs.HC cs.SI
what is the state of the research on crowdsourcing for policy making this article begins to answer this question by collecting categorizing and situating an extensive body of the extant research investigating policy crowdsourcing within a new framework built on fundamental typologies from each field we first define seven universal characteristics of the three general crowdsourcing techniques virtual labor markets tournament crowdsourcing open collaboration to examine the relative tradeoffs of each modality we then compare these three types of crowdsourcing to the different stages of the policy cycle in order to situate the literature spanning both domains we finally discuss research trends in crowdsourcing for public policy and highlight the research gaps and overlaps in the literature keywords crowdsourcing policy cycle crowdsourcing tradeoffs policy processes policy stages virtual labor markets tournament crowdsourcing open collaboration
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1,802.04144
Arithmetic summable sequence space over non-Newtonian field
Recently Ruckle \cite{RuckleArithmeticalSummability} introduced the theory of arithmetical summability suggested by the sum $ \sum_{k|m}f(k) $ as $ k $ ranges over the divisors of $m$ including $ 1 $ and $ m .$ Following Ruckle \cite{RuckleArithmeticalSummability} we construct the sequence space $ AS(G) $ and $ AC(G) $ of arithmetic summable and arithmetic convergent sequences in the sense of geometric calculus and derive interesting results in the geometric field.
math.GM
recently ruckle citerucklearithmeticalsummability introduced the theory of arithmetical summability suggested by the sum sum_kmfk as k ranges over the divisors of m including 1 and m following ruckle citerucklearithmeticalsummability we construct the sequence space asg and acg of arithmetic summable and arithmetic convergent sequences in the sense of geometric calculus and derive interesting results in the geometric field
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1,802.04145
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
Filters in a Convolutional Neural Network (CNN) contain model parameters learned from enormous amounts of data. In this paper, we suggest to decompose convolutional filters in CNN as a truncated expansion with pre-fixed bases, namely the Decomposed Convolutional Filters network (DCFNet), where the expansion coefficients remain learned from data. Such a structure not only reduces the number of trainable parameters and computation, but also imposes filter regularity by bases truncation. Through extensive experiments, we consistently observe that DCFNet maintains accuracy for image classification tasks with a significant reduction of model parameters, particularly with Fourier-Bessel (FB) bases, and even with random bases. Theoretically, we analyze the representation stability of DCFNet with respect to input variations, and prove representation stability under generic assumptions on the expansion coefficients. The analysis is consistent with the empirical observations.
stat.ML cs.CV cs.LG
filters in a convolutional neural network cnn contain model parameters learned from enormous amounts of data in this paper we suggest to decompose convolutional filters in cnn as a truncated expansion with prefixed bases namely the decomposed convolutional filters network dcfnet where the expansion coefficients remain learned from data such a structure not only reduces the number of trainable parameters and computation but also imposes filter regularity by bases truncation through extensive experiments we consistently observe that dcfnet maintains accuracy for image classification tasks with a significant reduction of model parameters particularly with fourierbessel fb bases and even with random bases theoretically we analyze the representation stability of dcfnet with respect to input variations and prove representation stability under generic assumptions on the expansion coefficients the analysis is consistent with the empirical observations
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1,802.04146
Measurements of Higgs boson properties in the diphoton decay channel with 36 fb$^{-1}$ of $pp$ collision data at $\sqrt{s} = 13$ TeV with the ATLAS detector
Properties of the Higgs boson are measured in the two-photon final state using 36.1 fb$^{-1}$ of proton-proton collision data recorded at $\sqrt{s} = 13$ TeV by the ATLAS experiment at the Large Hadron Collider. Cross-section measurements for the production of a Higgs boson through gluon-gluon fusion, vector-boson fusion, and in association with a vector bosonor a top-quark pair are reported. The signal strength, defined as the ratio of the observed to the expected signal yield, is measured for each of these production processes as well as inclusively. The global signal strength measurement of $0.99 \pm 0.14$ improves on the precision of the ATLAS measurement at $\sqrt{s} = 7$ and 8 TeV by a factor of two. Measurements of gluon-gluon fusion and vector-boson fusion productions yield signal strengths compatible with the Standard Model prediction. Measurements of simplified template cross sections, designed to quantify the different Higgs boson production processes in specific regions of phase space, are reported. The cross section for the production of the Higgs boson decaying to two isolated photons in a fiducial region closely matching the experimental selection of the photons is measured to be $55 \pm 10$ fb, which is in good agreement with the Standard Model prediction of $64 \pm 2$ fb. Furthermore, cross sections in fiducial regions enriched in Higgs boson production in vector-boson fusion or in association with large missing transverse momentum, leptons or top-quark pairs are reported. Differential and double-differential measurements are performed for several variables related to the diphoton kinematics as well as the kinematics and multiplicity of the jets produced in association with a Higgs boson. No significant deviations from a wide array of Standard Model predictions are observed.
hep-ex
properties of the higgs boson are measured in the twophoton final state using 361 fb1 of protonproton collision data recorded at sqrts 13 tev by the atlas experiment at the large hadron collider crosssection measurements for the production of a higgs boson through gluongluon fusion vectorboson fusion and in association with a vector bosonor a topquark pair are reported the signal strength defined as the ratio of the observed to the expected signal yield is measured for each of these production processes as well as inclusively the global signal strength measurement of 099 pm 014 improves on the precision of the atlas measurement at sqrts 7 and 8 tev by a factor of two measurements of gluongluon fusion and vectorboson fusion productions yield signal strengths compatible with the standard model prediction measurements of simplified template cross sections designed to quantify the different higgs boson production processes in specific regions of phase space are reported the cross section for the production of the higgs boson decaying to two isolated photons in a fiducial region closely matching the experimental selection of the photons is measured to be 55 pm 10 fb which is in good agreement with the standard model prediction of 64 pm 2 fb furthermore cross sections in fiducial regions enriched in higgs boson production in vectorboson fusion or in association with large missing transverse momentum leptons or topquark pairs are reported differential and doubledifferential measurements are performed for several variables related to the diphoton kinematics as well as the kinematics and multiplicity of the jets produced in association with a higgs boson no significant deviations from a wide array of standard model predictions are observed
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1,802.04147
Vanishing Shear Viscosity Limit and Boundary Layer Study on the Planar MHD system
We consider an initial boundary problem for the planar MHD system under the general condition on the heat conductivity $\kappa$ that may depend on both the density $\rho$ and the temperature $\theta$ satisfying $\kappa(\rho,\theta)\geq\kappa_1 \theta^{q}$ for some constants $\kappa_1>0$ and $q>0.$ Firstly, the global existence of strong solution for large initial data is obtained, and then the limit of the vanishing shear viscosity is justified. In addition, the $L^2$ convergence rate is obtained together with the estimation on the thickness of the boundary layer.
math.AP
we consider an initial boundary problem for the planar mhd system under the general condition on the heat conductivity kappa that may depend on both the density rho and the temperature theta satisfying kapparhothetageqkappa_1 thetaq for some constants kappa_10 and q0 firstly the global existence of strong solution for large initial data is obtained and then the limit of the vanishing shear viscosity is justified in addition the l2 convergence rate is obtained together with the estimation on the thickness of the boundary layer
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1,802.04148
On Dendrites Generated By Symmetric Polygonal Systems: The Case of Regular Polygons
We define $G$-symmetric polygonal systems of similarities and study the properties of symmetric dendrites, which appear as their attractors. This allows us to find the conditions under which the attractor of a zipper becomes a dendrite.
math.MG math.DS
we define gsymmetric polygonal systems of similarities and study the properties of symmetric dendrites which appear as their attractors this allows us to find the conditions under which the attractor of a zipper becomes a dendrite
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1,802.04149
Algorithms and Uncertainty Sets for Data-Driven Robust Shortest Path Problems
We consider robust shortest path problems, where the aim is to find a path that optimizes the worst-case performance over an uncertainty set containing all relevant scenarios for arc costs. The usual approach for such problems is to assume this uncertainty set given by an expert who can advise on the shape and size of the set. Following the idea of data-driven robust optimization, we instead construct a range of uncertainty sets from the current literature based on real-world traffic measurements provided by the City of Chicago. We then compare the performance of the resulting robust paths within and outside the sample, which allows us to draw conclusions what the most suited uncertainty set is. Based on our experiments, we then focus on ellipsoidal uncertainty sets, and develop a new solution algorithm that significantly outperforms a state-of-the-art solver.
math.OC
we consider robust shortest path problems where the aim is to find a path that optimizes the worstcase performance over an uncertainty set containing all relevant scenarios for arc costs the usual approach for such problems is to assume this uncertainty set given by an expert who can advise on the shape and size of the set following the idea of datadriven robust optimization we instead construct a range of uncertainty sets from the current literature based on realworld traffic measurements provided by the city of chicago we then compare the performance of the resulting robust paths within and outside the sample which allows us to draw conclusions what the most suited uncertainty set is based on our experiments we then focus on ellipsoidal uncertainty sets and develop a new solution algorithm that significantly outperforms a stateoftheart solver
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1,802.0415
Late-time acceleration driven by shift-symmetric Galileon in the presence of Torsion
A shift-symmetric Galileon model in presence of spacetime torsion has been constructed for the first time. This has been realized by localizing (or, gauging) the Galileon symmetry in flat spacetime in an appropriate manner. We have applied the above model to study the evolution of the universe at a cosmological scale. Interestingly, for a wide class of torsional structures we have shown that the model leads to late time cosmic acceleration. Furthermore, as torsion vanishes, our model reproduces the standard results.
gr-qc hep-th
a shiftsymmetric galileon model in presence of spacetime torsion has been constructed for the first time this has been realized by localizing or gauging the galileon symmetry in flat spacetime in an appropriate manner we have applied the above model to study the evolution of the universe at a cosmological scale interestingly for a wide class of torsional structures we have shown that the model leads to late time cosmic acceleration furthermore as torsion vanishes our model reproduces the standard results
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1,802.04151
The HERA-19 Commissioning Array: Direction Dependent Effects
Foreground power dominates the measurements of interferometers that seek a statistical detection of highly-redshifted HI emission from the Epoch of Reionization (EoR). The chromaticity of the instrument creates a boundary in the Fourier transform of frequency (proportional to $k_\parallel$) between spectrally smooth emission, characteristic of the strong synchrotron foreground (the "wedge"), and the spectrally structured emission from HI in the EoR (the "EoR window"). Faraday rotation can inject spectral structure into otherwise smooth polarized foreground emission, which through instrument effects or miscalibration could possibly pollute the EoR window. Using data from the HERA 19-element commissioning array, we investigate the polarization response of this new instrument in the power spectrum domain. We perform a simple image-based calibration based on the unpolarized diffuse emission of the Global Sky Model, and show that it achieves qualitative redundancy between the nominally-redundant baselines of the array and reasonable amplitude accuracy. We construct power spectra of all fully polarized coherencies in all pseudo-Stokes parameters. We compare to simulations based on an unpolarized diffuse sky model and detailed electromagnetic simulations of the dish and feed, confirming that in Stokes I, the calibration does not add significant spectral structure beyond the expected level. Further, this calibration is stable over the 8 days of observations considered. Excess power is seen in the power spectra of the linear polarization Stokes parameters which is not easily attributable to leakage via the primary beam, and results from some combination of residual calibration errors and actual polarized emission. Stokes V is found to be highly discrepant from the expectation of zero power, strongly pointing to the need for more accurate polarized calibration.
astro-ph.IM
foreground power dominates the measurements of interferometers that seek a statistical detection of highlyredshifted hi emission from the epoch of reionization eor the chromaticity of the instrument creates a boundary in the fourier transform of frequency proportional to k_parallel between spectrally smooth emission characteristic of the strong synchrotron foreground the wedge and the spectrally structured emission from hi in the eor the eor window faraday rotation can inject spectral structure into otherwise smooth polarized foreground emission which through instrument effects or miscalibration could possibly pollute the eor window using data from the hera 19element commissioning array we investigate the polarization response of this new instrument in the power spectrum domain we perform a simple imagebased calibration based on the unpolarized diffuse emission of the global sky model and show that it achieves qualitative redundancy between the nominallyredundant baselines of the array and reasonable amplitude accuracy we construct power spectra of all fully polarized coherencies in all pseudostokes parameters we compare to simulations based on an unpolarized diffuse sky model and detailed electromagnetic simulations of the dish and feed confirming that in stokes i the calibration does not add significant spectral structure beyond the expected level further this calibration is stable over the 8 days of observations considered excess power is seen in the power spectra of the linear polarization stokes parameters which is not easily attributable to leakage via the primary beam and results from some combination of residual calibration errors and actual polarized emission stokes v is found to be highly discrepant from the expectation of zero power strongly pointing to the need for more accurate polarized calibration
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1,802.04152
Mid Infrared Nonlinear Plasmonics using Germanium Nanoantennas on Silicon Substrates
We demonstrate third harmonic generation in plasmonic antennas made of highly doped germanium and designed to be resonant in the mid infrared. Owing to the near-field enhancement, the result is an ultrafast, sub-diffraction, coherent light source tunable between 3 and 5 micrometer wavelength on a silicon substrate. To observe nonlinearity in this challenging spectral region, a high-power femtosecond laser system equipped with parametric frequency conversion in combination with an all-reflective confocal microscope setup is employed. We show spatially resolved maps of the linear scattering cross section and the nonlinear emission of single isolated antenna structures. A clear third order power dependence as well as the mid-infrared emission spectra prove the nonlinear nature of the light emission. Simulations support the observed resonance length of the double rod antenna and demonstrate that the field enhancement inside the antenna material is responsible for the nonlinear frequency mixing.
physics.app-ph cond-mat.mes-hall
we demonstrate third harmonic generation in plasmonic antennas made of highly doped germanium and designed to be resonant in the mid infrared owing to the nearfield enhancement the result is an ultrafast subdiffraction coherent light source tunable between 3 and 5 micrometer wavelength on a silicon substrate to observe nonlinearity in this challenging spectral region a highpower femtosecond laser system equipped with parametric frequency conversion in combination with an allreflective confocal microscope setup is employed we show spatially resolved maps of the linear scattering cross section and the nonlinear emission of single isolated antenna structures a clear third order power dependence as well as the midinfrared emission spectra prove the nonlinear nature of the light emission simulations support the observed resonance length of the double rod antenna and demonstrate that the field enhancement inside the antenna material is responsible for the nonlinear frequency mixing
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1,802.04153
Influence of a chemical reaction on viscous fingering: Effect of the injection flow rate
The hydrodynamic viscous fingering instability can be influenced by a simple viscosity changing chemical reaction of type A+B --> C, when a solution of reactant A is injected into a solution of B and a product C of different viscosity is formed. We investigate here numerically such reactive viscous fingering in the case of a reaction decreasing the viscosity to define the optimal conditions on the chemical and hydrodynamic parameters for controlling fingering. In particular, we analyze the influence of the injection flow rate or equivalently of the Peclet number (Pe) of the problem on the efficiency of the chemical control of fingering. We show that the viscosity decreasing reaction has an increased stabilizing effect when Pe is decreased. On the contrary, fingering is more intense and the system more unstable when Pe is increased. The related reactive fingering patterns cover then respectively a smaller (larger) area than in the non-reactive equivalent. Depending on the value of the flow rate, a given chemical reaction may thus either enhance or suppress a fingering instability. This stabilization and destabilization at low and high Pe are shown to be related to the Pe-dependent characteristics of a minimum in the viscosity profile that develops around the miscible interface thanks to the effect of the chemical reaction.
physics.flu-dyn
the hydrodynamic viscous fingering instability can be influenced by a simple viscosity changing chemical reaction of type ab c when a solution of reactant a is injected into a solution of b and a product c of different viscosity is formed we investigate here numerically such reactive viscous fingering in the case of a reaction decreasing the viscosity to define the optimal conditions on the chemical and hydrodynamic parameters for controlling fingering in particular we analyze the influence of the injection flow rate or equivalently of the peclet number pe of the problem on the efficiency of the chemical control of fingering we show that the viscosity decreasing reaction has an increased stabilizing effect when pe is decreased on the contrary fingering is more intense and the system more unstable when pe is increased the related reactive fingering patterns cover then respectively a smaller larger area than in the nonreactive equivalent depending on the value of the flow rate a given chemical reaction may thus either enhance or suppress a fingering instability this stabilization and destabilization at low and high pe are shown to be related to the pedependent characteristics of a minimum in the viscosity profile that develops around the miscible interface thanks to the effect of the chemical reaction
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1,802.04154
Laboratory Space Physics: Investigating the Physics of Space Plasmas in the Laboratory
Laboratory experiments provide a valuable complement to explore the fundamental physics of space plasmas without the limitations inherent to spacecraft measurements. Specifically, experiments overcome the restriction that spacecraft measurements are made at only one (or a few) points in space, enable greater control of the plasma conditions and applied perturbations, can be reproducible, and are orders of magnitude less expensive than launching spacecraft. Here I highlight key open questions about the physics of space plasmas and identify the aspects of these problems that can potentially be tackled in laboratory experiments. Several past successes in laboratory space physics provide concrete examples of how complementary experiments can contribute to our understanding of physical processes at play in the solar corona, solar wind, planetary magnetospheres, and outer boundary of the heliosphere. I present developments on the horizon of laboratory space physics, identifying velocity space as a key new frontier, highlighting new and enhanced experimental facilities, and showcasing anticipated developments to produce improved diagnostics and innovative analysis methods. A strategy for future laboratory space physics investigations will be outlined, with explicit connections to specific fundamental plasma phenomena of interest.
physics.space-ph astro-ph.EP astro-ph.SR physics.plasm-ph
laboratory experiments provide a valuable complement to explore the fundamental physics of space plasmas without the limitations inherent to spacecraft measurements specifically experiments overcome the restriction that spacecraft measurements are made at only one or a few points in space enable greater control of the plasma conditions and applied perturbations can be reproducible and are orders of magnitude less expensive than launching spacecraft here i highlight key open questions about the physics of space plasmas and identify the aspects of these problems that can potentially be tackled in laboratory experiments several past successes in laboratory space physics provide concrete examples of how complementary experiments can contribute to our understanding of physical processes at play in the solar corona solar wind planetary magnetospheres and outer boundary of the heliosphere i present developments on the horizon of laboratory space physics identifying velocity space as a key new frontier highlighting new and enhanced experimental facilities and showcasing anticipated developments to produce improved diagnostics and innovative analysis methods a strategy for future laboratory space physics investigations will be outlined with explicit connections to specific fundamental plasma phenomena of interest
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1,802.04155
Long-distance near-field energy transport via propagating surface waves
Near-field radiative heat transfer (RHT) between two bodies can significantly exceed the far-field limit set by Planck's law due to the evanescent wave tunneling, which typically can only occur when the two bodies are separated at subwavelength distances. We show that the RHT between two SiC nanoparticles with separation distances much larger than the thermal wavelength can still exceed the far-field limit when the particles are located within a subwavelength distance away from a SiC substrate. In this configuration, the localized surface phonon polariton (SPhP) of the particles couples to the propagating SPhP of the substrate which then provides a new channel for the near-field energy transport and enhances the RHT by orders of magnitude at large distances. The enhancement is also demonstrated to appear in a chain of closely spaced SiC nanoparticles located in the near field of a SiC substrate. The findings provide a new way for the long-distance transport of near-field energy.
physics.app-ph
nearfield radiative heat transfer rht between two bodies can significantly exceed the farfield limit set by plancks law due to the evanescent wave tunneling which typically can only occur when the two bodies are separated at subwavelength distances we show that the rht between two sic nanoparticles with separation distances much larger than the thermal wavelength can still exceed the farfield limit when the particles are located within a subwavelength distance away from a sic substrate in this configuration the localized surface phonon polariton sphp of the particles couples to the propagating sphp of the substrate which then provides a new channel for the nearfield energy transport and enhances the rht by orders of magnitude at large distances the enhancement is also demonstrated to appear in a chain of closely spaced sic nanoparticles located in the near field of a sic substrate the findings provide a new way for the longdistance transport of nearfield energy
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1,802.04156
The Coupled TuFF-BFF Algorithm for Automatic 3D Segmentation of Microglia
We propose an automatic 3D segmentation algorithm for multiphoton microscopy images of microglia. Our method is capable of segmenting tubular and blob-like structures from noisy images. Current segmentation techniques and software fail to capture the fine processes and soma of the microglia cells, useful for the study of the microglia role in the brain during healthy and diseased states. Our coupled tubularity flow field (TuFF)-blob flow field (BFF) method evolves a level set toward the object boundary using the directional tubularity and blobness measure of 3D images. Our method found a 20% performance increase against state of the art segmentation methods on a dataset of 3D images of microglia even in images with intensity heterogeneity throughout the object. The coupled TuFF-BFF segmentation results also yielded 40% improvement in accuracy for the ramification index of the processes, which displays the efficacy of our method.
eess.IV
we propose an automatic 3d segmentation algorithm for multiphoton microscopy images of microglia our method is capable of segmenting tubular and bloblike structures from noisy images current segmentation techniques and software fail to capture the fine processes and soma of the microglia cells useful for the study of the microglia role in the brain during healthy and diseased states our coupled tubularity flow field tuffblob flow field bff method evolves a level set toward the object boundary using the directional tubularity and blobness measure of 3d images our method found a 20 performance increase against state of the art segmentation methods on a dataset of 3d images of microglia even in images with intensity heterogeneity throughout the object the coupled tuffbff segmentation results also yielded 40 improvement in accuracy for the ramification index of the processes which displays the efficacy of our method
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1,802.04157
Elliptic boundary value problems for the stationary vacuum spacetimes
We develop a general method of proving the ellipticity of boundary value problems for the stationary vacuum space time, by showing that the stationary vacuum field equations are elliptic subjected to a geometrically natural collection of boundary conditions in the projection formalism. Using this we prove the manifold theorem for the moduli space of stationary vacuum spacetimes.
math.DG gr-qc math.AP
we develop a general method of proving the ellipticity of boundary value problems for the stationary vacuum space time by showing that the stationary vacuum field equations are elliptic subjected to a geometrically natural collection of boundary conditions in the projection formalism using this we prove the manifold theorem for the moduli space of stationary vacuum spacetimes
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1,802.04158
Influence of multiplet structure on photoemission spectra of spin-orbit driven Mott insulators: application to $\bf{Sr_2IrO_4}$
Most of the low-energy effective descriptions of spin-orbit driven Mott insulators consider spin orbit coupling (SOC) as a second order perturbation to electron-electron interactions. However, when SOC is comparable to anisotropic Hund's coupling, such as in Ir, validity of this formally weak-SOC approach is not a priori known. Depending on the relative strength of SOC and anisotropic Hund's coupling, different descriptions of the multiplet structure should be employed in the weak and strong SOC limits, \textit{viz.} \textit{LS} and \textit{jj} coupling schemes, respectively. We investigate the implications of both the coupling schemes on the low-energy effective $t-J$ model and calculate the angle resolved photoemission (ARPES) spectra using self-consistent Born approximation. In particular, we obtain the ARPES spectra of quasi-two-dimensional square-lattice iridate ${\rm Sr_2IrO_4}$ in both weak and strong SOC limits. The differences in the limiting cases are understood in terms of the composition and relative energy splittings of the multiplet structure. Our results indicate that the LS coupling scheme yields better agreement with the experiment, thus providing an indirect evidence for the validity of LS coupling scheme for iridates. We also discuss the implications for other metal ions with strong SOC.
cond-mat.str-el
most of the lowenergy effective descriptions of spinorbit driven mott insulators consider spin orbit coupling soc as a second order perturbation to electronelectron interactions however when soc is comparable to anisotropic hunds coupling such as in ir validity of this formally weaksoc approach is not a priori known depending on the relative strength of soc and anisotropic hunds coupling different descriptions of the multiplet structure should be employed in the weak and strong soc limits textitviz textitls and textitjj coupling schemes respectively we investigate the implications of both the coupling schemes on the lowenergy effective tj model and calculate the angle resolved photoemission arpes spectra using selfconsistent born approximation in particular we obtain the arpes spectra of quasitwodimensional squarelattice iridate rm sr_2iro_4 in both weak and strong soc limits the differences in the limiting cases are understood in terms of the composition and relative energy splittings of the multiplet structure our results indicate that the ls coupling scheme yields better agreement with the experiment thus providing an indirect evidence for the validity of ls coupling scheme for iridates we also discuss the implications for other metal ions with strong soc
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1,802.04159
Urban vs. rural divide in HTTPS implementation for hospital websites in Illinois
The Hypertext Transfer Protocol Secure (HTTPS) communications protocol is used to secure traffic between a web browser and server. This technology can significantly reduce the risk of interception and manipulation of web information for nefarious purposes such as identity theft. Deployment of HTTPS has reached about 50% of all webs sites. Little is known about HTTPS implantation for hospital websites. To investigate the prevalence of HTTPS implementation, we analyzed the websites of the 210 public hospitals in the state of Illinois, USA. HTTPS was implemented to industry standards for 54% of all hospital websites in Illinois. Geographical analysis showed an urban vs. rural digital divide with 60% of urban hospitals and 40% of rural hospitals implementing HTTPS.
cs.CY
the hypertext transfer protocol secure https communications protocol is used to secure traffic between a web browser and server this technology can significantly reduce the risk of interception and manipulation of web information for nefarious purposes such as identity theft deployment of https has reached about 50 of all webs sites little is known about https implantation for hospital websites to investigate the prevalence of https implementation we analyzed the websites of the 210 public hospitals in the state of illinois usa https was implemented to industry standards for 54 of all hospital websites in illinois geographical analysis showed an urban vs rural digital divide with 60 of urban hospitals and 40 of rural hospitals implementing https
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