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1212.4920
Automatic landmark annotation and dense correspondence registration for 3D human facial images
cs.CV q-bio.QM
Dense surface registration of three-dimensional (3D) human facial images holds great potential for studies of human trait diversity, disease genetics, and forensics. Non-rigid registration is particularly useful for establishing dense anatomical correspondences between faces. Here we describe a novel non-rigid registration method for fully automatic 3D facial image mapping. This method comprises two steps: first, seventeen facial landmarks are automatically annotated, mainly via PCA-based feature recognition following 3D-to-2D data transformation. Second, an efficient thin-plate spline (TPS) protocol is used to establish the dense anatomical correspondence between facial images, under the guidance of the predefined landmarks. We demonstrate that this method is robust and highly accurate, even for different ethnicities. The average face is calculated for individuals of Han Chinese and Uyghur origins. While fully automatic and computationally efficient, this method enables high-throughput analysis of human facial feature variation.
1212.4940
Fourier Domain Beamforming for Medical Ultrasound
cs.IT math.IT
Sonography techniques use multiple transducer elements for tissue visualization. Signals detected at each element are sampled prior to digital beamforming. The required sampling rates are up to 4 times the Nyquist rate of the signal and result in considerable amount of data, that needs to be stored and processed. A developed technique, based on the finite rate of innovation model, compressed sensing (CS) and Xampling ideas, allows to reduce the number of samples needed to reconstruct an image comprised of strong reflectors. A significant drawback of this method is its inability to treat speckle, which is of significant importance in medical imaging. Here we build on previous work and show explicitly how to perform beamforming in the Fourier domain. Beamforming in frequency exploits the low bandwidth of the beamformed signal and allows to bypass the oversampling dictated by digital implementation of beamforming in time. We show that this allows to obtain the same beamformed image as in standard beamforming but from far fewer samples. Finally, we present an analysis based CS-technique that allows for further reduction in sampling rate, using only a portion of the beamformed signal's bandwidth, namely, sampling the signal at sub-Nyquist rates. We demonstrate our methods on in vivo cardiac ultrasound data and show that reductions up to 1/25 over standard beamforming rates are possible.
1212.4950
Data Mapping for Unreliable Memories
cs.IT math.IT
Future digital signal processing (DSP) systems must provide robustness on algorithm and application level to the presence of reliability issues that come along with corresponding implementations in modern semiconductor process technologies. In this paper, we address this issue by investigating the impact of unreliable memories on general DSP systems. In particular, we propose a novel framework to characterize the effects of unreliable memories, which enables us to devise novel methods to mitigate the associated performance loss. We propose to deploy specifically designed data representations, which have the capability of substantially improving the system reliability compared to that realized by conventional data representations used in digital integrated circuits, such as 2s complement or sign-magnitude number formats. To demonstrate the efficacy of the proposed framework, we analyze the impact of unreliable memories on coded communication systems, and we show that the deployment of optimized data representations substantially improves the error-rate performance of such systems.
1212.4968
Dual-Polarized Ricean MIMO Channels: Modeling and Performance Assessment
cs.IT math.IT
In wireless communication systems, dual-polarized (DP) instead of single-polarized (SP) multiple-input multiple-output (MIMO) transmission is used to improve the spectral efficiency under certain conditions on the channel and the signal-to-noise ratio (SNR). In order to identify these conditions, we first propose a novel channel model for DP mobile Ricean MIMO channels for which statistical channel parameters are readily obtained from a moment-based channel decomposition. Second, we derive an approximation of the mutual information (MI), which can be expressed as a function of those statistical channel parameters. Based on this approximation, we characterize the required SNR for a DP MIMO system to outperform an SP MIMO system in terms of the MI. Finally, we apply our results to channel measurements at 2.53 GHz. We find that, using the proposed channel decomposition and the approximation of the MI, we are able to reproduce the (practically relevant) SNR values above which DP MIMO systems outperform SP MIMO systems.
1212.4989
Towards Trustworthy Mobile Social Networking Services for Disaster Response
cs.SI cs.CR
Situational awareness is crucial for effective disaster management. However, obtaining information about the actual situation is usually difficult and time-consuming. While there has been some effort in terms of incorporating the affected population as a source of information, the issue of obtaining trustworthy information has not yet received much attention. Therefore, we introduce the concept of witness-based report verification, which enables users from the affected population to evaluate reports issued by other users. We present an extensive overview of the objectives to be fulfilled by such a scheme and provide a first approach considering security and privacy. Finally, we evaluate the performance of our approach in a simulation study. Our results highlight synergetic effects of group mobility patterns that are likely in disaster situations.
1212.4991
A Physical Layer Secured Key Distribution Technique for IEEE 802.11g Wireless Networks
cs.IT cs.CR math.IT
Key distribution and renewing in wireless local area networks is a crucial issue to guarantee that unauthorized users are prevented from accessing the network. In this paper, we propose a technique for allowing an automatic bootstrap and periodic renewing of the network key by exploiting physical layer security principles, that is, the inherent differences among transmission channels. The proposed technique is based on scrambling of groups of consecutive packets and does not need the use of an initial authentication nor automatic repeat request protocols. We present a modification of the scrambling circuits included in the IEEE 802.11g standard which allows for a suitable error propagation at the unauthorized receiver, thus achieving physical layer security.
1212.4999
Hamiltonian Perspective on Compartmental Reaction-Diffusion Networks
cs.SY math.OC nlin.PS
Inspired by the recent developments in modeling and analysis of reaction networks, we provide a geometric formulation of the reversible reaction networks under the influence of diffusion. Using the graph knowledge of the underlying reaction network, the obtained reaction-diffusion system is a distributed-parameter port-Hamiltonian system on a compact spatial domain. Motivated by the need for computer based design, we offer a spatially consistent discretization of the PDE system and, in a systematic manner, recover a compartmental ODE model on a simplicial triangulation of the spatial domain. Exploring the properties of a balanced weighted Laplacian matrix of the reaction network and the Laplacian of the simplicial complex, we characterize the space of equilibrium points and provide a simple stability analysis on the state space modulo the space of equilibrium points. The paper rules out the possibility of the persistence of spatial patterns for the compartmental balanced reaction-diffusion networks.
1212.5024
On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems
cs.IT math.CO math.IT
Consider a multi-user Orthogonal Frequency Division Multiple Access (OFDMA) system where multiple users share multiple discrete subcarriers, but at most one user is allowed to transmit power on each subcarrier. To adapt fast traffic and channel fluctuations and improve the spectrum efficiency, the system should have the ability to dynamically allocate subcarriers and power resources to users. Assuming perfect channel knowledge, two formulations for the joint subcarrier and power allocation problem are considered in this paper: the first is to minimize the total transmission power subject to quality of service constraints and the OFDMA constraint, and the second is to maximize some system utility function (including the sum-rate utility, the proportional fairness utility, the harmonic mean utility, and the min-rate utility) subject to the total transmission power constraint per user and the OFDMA constraint. In spite of the existence of various heuristics approaches, little is known about the computational complexity status of the above problem. This paper aims to fill this theoretical gap, i.e., characterizing the complexity of the joint subcarrier and power allocation problem for the multi-user OFDMA system. It is shown in this paper that both formulations of the joint subcarrier and power allocation problem are strongly NP-hard. The proof is based on a polynomial time transformation from the so-called 3-dimensional matching problem. Several subclasses of the problem which can be solved to global optimality or $\epsilon$-global optimality in polynomial time are also identified. These complexity results suggest that there are not polynomial time algorithms which are able to solve the general joint subcarrier and power allocation problem to global optimality (unless P$=$NP), and determining an approximately optimal subcarrier and power allocation strategy is more realistic in practice.
1212.5032
Distributed Rate Allocation in Inter-Session Network Coding
cs.NI cs.IT math.IT
In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all the clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since the optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.
1212.5035
Online Myopic Network Covering
cs.SI physics.soc-ph
Efficient marketing or awareness-raising campaigns seek to recruit $n$ influential individuals -- where $n$ is the campaign budget -- that are able to cover a large target audience through their social connections. So far most of the related literature on maximizing this network cover assumes that the social network topology is known. Even in such a case the optimal solution is NP-hard. In practice, however, the network topology is generally unknown and needs to be discovered on-the-fly. In this work we consider an unknown topology where recruited individuals disclose their social connections (a feature known as {\em one-hop lookahead}). The goal of this work is to provide an efficient greedy online algorithm that recruits individuals as to maximize the size of target audience covered by the campaign. We propose a new greedy online algorithm, Maximum Expected $d$-Excess Degree (MEED), and provide, to the best of our knowledge, the first detailed theoretical analysis of the cover size of a variety of well known network sampling algorithms on finite networks. Our proposed algorithm greedily maximizes the expected size of the cover. For a class of random power law networks we show that MEED simplifies into a straightforward procedure, which we denote MOD (Maximum Observed Degree). We substantiate our analytical results with extensive simulations and show that MOD significantly outperforms all analyzed myopic algorithms. We note that performance may be further improved if the node degree distribution is known or can be estimated online during the campaign.
1212.5091
Maximally Informative Observables and Categorical Perception
cs.LG cs.SD
We formulate the problem of perception in the framework of information theory, and prove that categorical perception is equivalent to the existence of an observable that has the maximum possible information on the target of perception. We call such an observable maximally informative. Regardless whether categorical perception is real, maximally informative observables can form the basis of a theory of perception. We conclude with the implications of such a theory for the problem of speech perception.
1212.5095
Modelling of Optimal Design of Manufacturing Cell Layout Considering Material Flow and Closeness Rating Factors
cs.CE
Developing a group of machine cells and their corresponding part families to minimize the inter-cell and intra-cell material flow is the basic objective of the designing of a cellular manufacturing system (CMS). Afterwards achieving a competent cell layout is essential in order to minimize the total inter-cell part travels, which is principally noteworthy. There are plentiful articles of CMS literature which considered cell formation problems; however cell layout topic has rarely been addressed. Therefore this research is intended to focus on an adapted mathematical model of the layout design problem considering material handling cost and closeness ratings of manufacturing cells. Owing to the combinatorial class of the said problem, an efficient NP-hard technique based on Simulated Annealing metaheuristic is proposed henceforth. Some test problems are solved using the proposed technique. Computational results show that the proposed metaheuristic approach is extremely effective and efficient in terms of solution quality and computational complexity.
1212.5101
Hybrid Fuzzy-ART based K-Means Clustering Methodology to Cellular Manufacturing Using Operational Time
cs.LG
This paper presents a new hybrid Fuzzy-ART based K-Means Clustering technique to solve the part machine grouping problem in cellular manufacturing systems considering operational time. The performance of the proposed technique is tested with problems from open literature and the results are compared to the existing clustering models such as simple K-means algorithm and modified ART1 algorithm using an efficient modified performance measure known as modified grouping efficiency (MGE) as found in the literature. The results support the better performance of the proposed algorithm. The Novelty of this study lies in the simple and efficient methodology to produce quick solutions for shop floor managers with least computational efforts and time.
1212.5108
Rewrite Closure and CF Hedge Automata
cs.LO cs.DB cs.FL
We introduce an extension of hedge automata called bidimensional context-free hedge automata. The class of unranked ordered tree languages they recognize is shown to be preserved by rewrite closure with inverse-monadic rules. We also extend the parameterized rewriting rules used for modeling the W3C XQuery Update Facility in previous works, by the possibility to insert a new parent node above a given node. We show that the rewrite closure of hedge automata languages with these extended rewriting systems are context-free hedge languages.
1212.5156
Nonparametric ridge estimation
math.ST cs.LG stat.ML stat.TH
We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the data are noisy measurements of a manifold, we show that the ridges are close and topologically similar to the hidden manifold. To find the estimated ridges in practice, we adapt the modified mean-shift algorithm proposed by Ozertem and Erdogmus [J. Mach. Learn. Res. 12 (2011) 1249-1286]. Some numerical experiments verify that the algorithm is accurate.
1212.5182
Performance Evaluation of an Orthogonal Frequency Division Multiplexing based Wireless Communication System with implementation of Least Mean Square Equalization technique
cs.IT math.IT
Orthogonal Frequency Division Multiplexing (OFDM) has recently been applied in wireless communication systems due to its high data rate transmission capability with high bandwidth efficiency and its robustness to multi-path delay. Fading is the one of the major aspect which is considered in the receiver. To cancel the effect of fading, channel estimation and equalization procedure must be done at the receiver before data demodulation. This paper mainly deals with pilot based channel estimation techniques for OFDM communication over frequency selective fading channels. This paper proposes a specific approach to channel equalization for Orthogonal Frequency Division Multiplex (OFDM) systems. Inserting an equalizer realized as an adaptive system before the FFT processing, the influence of variable delay and multi path could be mitigated in order to remove or reduce considerably the guard interval and to gain some spectral efficiency. The adaptive algorithm is based on adaptive filtering with averaging (AFA) for parameter update. Based on the development of a model of the OFDM system, through extensive computer simulations, we investigate the performance of the channel equalized system. The results show much higher convergence and adaptation rate compared to one of the most frequently used algorithms - Least Mean Squares (LMS).
1212.5188
Combinatorial neural codes from a mathematical coding theory perspective
q-bio.NC cs.IT math.IT
Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the error correction capabilities of familiar receptive field codes (RF codes). We find, perhaps surprisingly, that the high levels of redundancy present in these codes does not support accurate error correction, although the error-correcting performance of RF codes "catches up" to that of random comparison codes when a small tolerance to error is introduced. On the other hand, RF codes are good at reflecting distances between represented stimuli, while the random comparison codes are not. We suggest that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli.
1212.5197
Seven new champion linear codes
math.CO cs.IT math.IT
We exhibit seven linear codes exceeding the current best known minimum distance d for their dimension k and block length n. Each code is defined over F_8, and their invariants [n,k,d] are given by [49,13,27], [49,14,26], [49,16,24], [49,17,23], [49,19,21], [49,25,16] and [49,26,15]. Our method includes an exhaustive search of all monomial evaluation codes generated by points in the [0,5]x[0,5] lattice square.
1212.5211
Bibliometric Networks
cs.DL cs.SI physics.soc-ph
This text is based on a translation of a chapter in a handbook about network analysis (published in German) where we tried to make beginners familiar with some basic notions and recent developments of network analysis applied to bibliometric issues (Havemann and Scharnhorst 2010). We have added some recent references.
1212.5217
A Neural Network Approach to ECG Denoising
cs.CE cs.NE
We propose an ECG denoising method based on a feed forward neural network with three hidden layers. Particulary useful for very noisy signals, this approach uses the available ECG channels to reconstruct a noisy channel. We tested the method, on all the records from Physionet MIT-BIH Arrhythmia Database, adding electrode motion artifact noise. This denoising method improved the perfomance of publicly available ECG analysis programs on noisy ECG signals. This is an offline method that can be used to remove noise from very corrupted Holter records.
1212.5238
The Twitter of Babel: Mapping World Languages through Microblogging Platforms
physics.soc-ph cs.CL cs.SI
Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the enormous amount of digital data produced by human activities. Although a characterization of several aspects of our societies is emerging from the data revolution, a number of questions concerning the reliability and the biases inherent to the big data "proxies" of social life are still open. Here, we survey worldwide linguistic indicators and trends through the analysis of a large-scale dataset of microblogging posts. We show that available data allow for the study of language geography at scales ranging from country-level aggregation to specific city neighborhoods. The high resolution and coverage of the data allows us to investigate different indicators such as the linguistic homogeneity of different countries, the touristic seasonal patterns within countries and the geographical distribution of different languages in multilingual regions. This work highlights the potential of geolocalized studies of open data sources to improve current analysis and develop indicators for major social phenomena in specific communities.
1212.5250
A genetic algorithm applied to the validation of building thermal models
cs.NE
This paper presents the coupling of a building thermal simulation code with genetic algorithms (GAs). GAs are randomized search algorithms that are based on the mechanisms of natural selection and genetics. We show that this coupling allows the location of defective sub-models of a building thermal model i.e. parts of model that are responsible for the disagreements between measurements and model predictions. The method first of all is checked and validated on the basis of a numerical model of a building taken as reference. It is then applied to a real building case. The results show that the method could constitute an efficient tool when checking the model validity.
1212.5252
Bringing simulation to implementation: Presentation of a global approach in the design of passive solar buildings under humid tropical climates
cs.CE physics.class-ph
In early 1995, a DSM pilot initiative has been launched in the French islands of Guadeloupe and Reunion through a partnership between several public and private partners (the French Public Utility EDF, the University of Reunion Island, low cost housing companies, architects, energy consultants, etc...) to set up standards to improve thermal design of new residential buildings in tropical climates. This partnership led to defining optimized bio-climatic urban planning and architectural designs featuring the use of passive cooling architectural principles (solar shading, natural ventilation) and components, as well as energy efficient systems and technologies. The design and sizing of each architectural component on internal thermal comfort in building has been assessed with a validated thermal and airflow building simulation software (CODYRUN). These technical specifications have been edited in a reference document which has been used to build over 300 new pilot dwellings through the years 1996-1998 in Reunion Island and in Guadeloupe. An experimental monitoring has been made in these first ECODOM dwellings in 1998 and 1999. It will result in experimental validation of impact of the passive cooling strategies on thermal comfort of occupants leading to modify specifications if necessary. The paper present all the methodology used for the elaboration of ECODOM, from the simulations to the experimental results. This follow up is important, as the setting up of the ECODOM standard will be the first step towards the setting up of thermal regulations in the French overseas territories, by the year 2002.
1212.5253
Development of a new model to predict indoor daylighting: Integration in CODYRUN software and validation
cs.CE
Many models exist in the scientific literature for determining indoor daylighting values. They are classified in three categories: numerical, simplified and empirical models. Nevertheless, each of these categories of models are not convenient for every application. Indeed, the numerical model requires high calculation time; conditions of use of the simplified models are limited, and experimental models need not only important financial resources but also a perfect control of experimental devices (e.g. scale model), as well as climatic characteristics of the location (e.g. in situ experiment). In this article, a new model based on a combination of multiple simplified models is established. The objective is to improve this category of model. The originality of our paper relies on the coupling of several simplified models of indoor daylighting calculations. The accuracy of the simulation code, introduced into CODYRUN software to simulate correctly indoor illuminance, is then verified. Besides, the software consists of a numerical building simulation code, developed in the Physics and Mathematical Engineering Laboratory for Energy and Environment (P.I.M.E.N.T) at the University of Reunion. Initially dedicated to the thermal, airflow and hydrous phenomena in the buildings, the software has been completed for the calculation of indoor daylighting. New models and algorithms - which rely on a semi-detailed approach - will be presented in this paper. In order to validate the accuracy of the integrated models, many test cases have been considered as analytical, inter-software comparisons and experimental comparisons. In order to prove the accuracy of the new model - which can properly simulate the illuminance - a confrontation between the results obtained from the software (developed in this research paper) and the major made at a given place is described in details. A new statistical indicator to appreciate the margins of errors - named RSD (Reliability of Software Degrees) - is also be defined.
1212.5255
A Comparison between CODYRUN and TRNSYS, simulation models for thermal buildings behaviour
cs.CE
Simulation codes of thermal behaviour could significantly improve housing construction design. Among the existing software, CODYRUN and TRNSYS are calculations codes of different conceptions. CODYRUN is exclusively dedicated to housing thermal behaviour, whereas TRNSYS is more generally used on any thermal system. The purpose of this article is to compare these two instruments in two different conditions . We will first modelize a mono-zone test cell, and analyse the results by means of signal treatment methods. Then, we will modelize a real case of multi-zone housing, representative of housing in wet tropical climates. We could so evaluate influences of meteorological and building description data on model errors.
1212.5256
Thermal Building Simulation and Computer Generation of Nodal Models
cs.CE
The designer's preoccupation to reduce the energy needs and get a better thermal quality of ambiances helped in the development of several packages simulating the dynamic behaviour of buildings. This paper shows the adaptation of a method of thermal analysis, the nodal analysis, linked to the case of building's thermal behaviour. We take successively an interest in the case of conduction into a wall, in the coupling with superficial exchanges and finally in the constitution of thermal state models of the building. Big variations existing from one building to another, it's necessary to build the thermal model from the building description. This article shows the chosen method in the case of our thermal simulation program for buildings, CODYRUN
1212.5260
Heat transfer in buildings : application to air solar heating and Trombe wall design
cs.CE
The aim of this paper is to briefly recall heat transfer modes and explain their integration within a software dedicated to building simulation (CODYRUN). Detailed elements of the validation of this software are presented and two applications are finally discussed. One concerns the modeling of a flat plate air collector and the second focuses on the modeling of Trombe solar walls. In each case, detailed modeling of heat transfer allows precise understanding of thermal and energetic behavior of the studied structures. Recent decades have seen a proliferation of tools for building thermal simulation. These applications cover a wide spectrum from very simplified steady state models to dynamic simulation ones, including computational fluid dynamics modules (Clarke, 2001). These tools are widely available in design offices and engineering firms. They are often used for the design of HVAC systems and still subject to detailed research, particularly with respect to the integration of new fields (specific insulation materials, lighting, pollutants transport, etc.). Available from: http://www.intechopen.com/books/evaporation-condensation-and-heat-transfer/heat-transfer-in-buildings-application-to-solar-air-collector-and-trombe-wall-design
1212.5262
A multimodel approach to building thermal simulation for design and research purposes
cs.CE
The designers pre-occupation to reduce energy consumption and to achieve better thermal ambience levels, has favoured the setting up of numerous building thermal dynamic simulation programs. The progress in the modelling of phenomenas and its transfer into the professional field has resulted in various numerical approaches ranging from softwares dedicated to architects for design use to tools for laboratory use by the expert thermal researcher. This analysis shows that each approach tends to fulfil the specific needs of a certain kind of manipulator only, in the building conception process. Our objective is notably different as it is a tool which can be used from the very initial stage of a construction project, to the energy audit for the existing building. In each of these cases, the objective results, the precision advocated and the time delay of the results are different parameters which call for a multiple model approach of the building system
1212.5263
Use of BESTEST procedure to improve a building thermal simulation program
cs.CE
Validation of building energy simulation programs is of major interest to both users and modellers. To achieve such a task, it is essential to apply a methodology based on a priori test and empirical validation. A priori test consists in verifying that models embedded in a program and their implementation are correct. this should be achieved before carrying out experiments. The aim of this report is to present results from the application of the BESTEST procedure to our code. We will emphasise the way it allows to find bugs in our program and also how it permits to qualify models of heat transfer by conduction
1212.5264
Statistical Traffic State Analysis in Large-scale Transportation Networks Using Locality-Preserving Non-negative Matrix Factorization
cs.CE
Statistical traffic data analysis is a hot topic in traffic management and control. In this field, current research progresses focus on analyzing traffic flows of individual links or local regions in a transportation network. Less attention are paid to the global view of traffic states over the entire network, which is important for modeling large-scale traffic scenes. Our aim is precisely to propose a new methodology for extracting spatio-temporal traffic patterns, ultimately for modeling large-scale traffic dynamics, and long-term traffic forecasting. We attack this issue by utilizing Locality-Preserving Non-negative Matrix Factorization (LPNMF) to derive low-dimensional representation of network-level traffic states. Clustering is performed on the compact LPNMF projections to unveil typical spatial patterns and temporal dynamics of network-level traffic states. We have tested the proposed method on simulated traffic data generated for a large-scale road network, and reported experimental results validate the ability of our approach for extracting meaningful large-scale space-time traffic patterns. Furthermore, the derived clustering results provide an intuitive understanding of spatial-temporal characteristics of traffic flows in the large-scale network, and a basis for potential long-term forecasting.
1212.5265
An Effective Machine-Part Grouping Algorithm to Construct Manufacturing Cells
cs.CE
The machine-part cell formation problem consists of creating machine cells and their corresponding part families with the objective of minimizing the inter-cell and intra-cell movement while maximizing the machine utilization. This article demonstrates a hybrid clustering approach for the cell formation problem in cellular manufacturing that conjoins Sorenson s similarity coefficient based method to form the production cells. Computational results are shown over the test datasets obtained from the past literature. The hybrid technique is shown to outperform the other methods proposed in literature and including powerful soft computing approaches such as genetic algorithms, genetic programming by exceeding the solution quality on the test problems.
1212.5271
Towards the Evolution of Novel Vertical-Axis Wind Turbines
cs.NE cs.AI cs.CE
Renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but still remains a long way from reaching its full potential. In this paper, we investigate the use of artificial evolution to design vertical-axis wind turbine prototypes that are physically instantiated and evaluated under approximated wind tunnel conditions. An artificial neural network is used as a surrogate model to assist learning and found to reduce the number of fabrications required to reach a higher aerodynamic efficiency, resulting in an important cost reduction. Unlike in other approaches, such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made.
1212.5275
A Picard Newton method to solve non linear airflow networks
cs.CE
In detailled buiding simulation models, airflow modelling and solving are still open and crucial problems, specially in the case of open buildings as encountered in tropical climates. As a consequence, wind speed conditioning indoor thermal comfort or energy needs in case of air conditionning are uneasy to predict. A first part of the problem is the lack of reliable and usable large opening elementary modelling and another one concerns the numerical solving of airflow network. This non linear pressure system is solved by numerous methods mainly based on Newton Raphson (NR) method. This paper is adressing this part of the difficulty, in our software CODYRUN. After model checks, we propose to use Picard method (known also as fixed point) to initialise zone pressures. A linear system (extracted from the non linear set of equations) is solved around 10 times at each time step and NR uses this result for initial values. Known to be uniformly but slowly convergent, this method appears to be really powerful for the building pressure system. The comparison of the methods in terms of number of iterations is illustrated using a real test case experiment.
1212.5276
Multi-Objective AI Planning: Evaluating DAE-YAHSP on a Tunable Benchmark
cs.AI
All standard AI planners to-date can only handle a single objective, and the only way for them to take into account multiple objectives is by aggregation of the objectives. Furthermore, and in deep contrast with the single objective case, there exists no benchmark problems on which to test the algorithms for multi-objective planning. Divide and Evolve (DAE) is an evolutionary planner that won the (single-objective) deterministic temporal satisficing track in the last International Planning Competition. Even though it uses intensively the classical (and hence single-objective) planner YAHSP, it is possible to turn DAE-YAHSP into a multi-objective evolutionary planner. A tunable benchmark suite for multi-objective planning is first proposed, and the performances of several variants of multi-objective DAE-YAHSP are compared on different instances of this benchmark, hopefully paving the road to further multi-objective competitions in AI planning.
1212.5284
Dual-Based Bounds for Resource Allocation in Zero-forcing Beamforming OFDMA-SDMA Systems
cs.IT math.IT
We consider multi-antenna base stations using orthogonal frequency division multiple access and space division multiple access techniques to serve single-antenna users. Some users, called real-time users, have minimum rate requirements and must be served in the current time slot while others, called non real-time users, do not have strict timing constraints and are served on a best-effort basis. The resource allocation problem is to find the assignment of users to subcarriers and the transmit beamforming vectors that maximize the total user rates subject to power and minimum rate constraints. In general, this is a nonlinear and non-convex program and the zero-forcing technique used here makes it integer as well, exact optimal solutions cannot be computed in reasonable time for realistic cases. For this reason, we present a technique to compute both upper and lower bounds and show that these are quite close for some realistic cases. First, we formulate the dual problem whose optimum provides an upper bound to all feasible solutions. We then use a simple method to get a primal-feasible point starting from the dual optimal solution, which is a lower bound on the primal optimal solution. Numerical results for several cases show that the two bounds are close so that the dual method can be used to benchmark any heuristic used to solve this problem. As an example, we provide numerical results showing the performance gap of the well-known weight adjustment method and show that there is considerable room for improvement.
1212.5288
Quantized Network Coding for Correlated Sources
cs.IT math.IT
Non-adaptive joint source network coding of correlated sources is discussed in this paper. By studying the information flow in the network, we propose quantized network coding as an alternative for packet forwarding. This technique has both network coding and distributed source coding advantages, simultaneously. Quantized network coding is a combination of random linear network coding in the (infinite) field of real numbers and quantization to cope with the limited capacity of links. With the aid of the results in the literature of compressed sensing, we discuss theoretical and practical feasibility of quantized network coding in lossless networks. We show that, due to the nature of the field it operates on, quantized network coding can provide good quality decoding at a sink node with the reception of a reduced number of packets. Specifically, we discuss the required conditions on local network coding coefficients, by using restricted isometry property and suggest a design, which yields in appropriate linear measurements. Finally, our simulation results show the achieved gain in terms of delivery delay, compared to conventional routing based packet forwarding.
1212.5289
Modeling and performance evaluation of computer systems security operation
cs.CR cs.SY eess.SY math.OC
A model of computer system security operation is developed based on the fork-join queueing network formalism. We introduce a security operation performance measure, and show how it may be used to performance evaluation of actual systems.
1212.5291
Products of random matrices and queueing system performance evaluation
math.OC cs.SY
We consider (max,+)-algebra products of random matrices, which arise from performance evaluation of acyclic fork-join queueing networks. A new algebraic technique to examine properties of the product and investigate its limiting behaviour is proposed based on an extension of the standard matrix (max,+)-algebra by endowing it with the ordinary matrix addition as an external operation. As an application, we derive bounds on the (max,+)-algebra maximal Lyapunov exponent which can be considered as the cycle time of the networks.
1212.5300
Distributed Full-duplex via Wireless Side Channels: Bounds and Protocols
cs.IT math.IT
In this paper, we study a three-node full-duplex network, where a base station is engaged in simultaneous up- and downlink communication in the same frequency band with two half-duplex mobile nodes. To reduce the impact of inter- node interference between the two mobile nodes on the system capacity, we study how an orthogonal side-channel between the two mobile nodes can be leveraged to achieve full-duplex-like multiplexing gains. We propose and characterize the achievable rates of four distributed full-duplex schemes, labeled bin-and- cancel, compress-and-cancel, estimate-and-cancel and decode- and-cancel. Of the four, bin-and-cancel is shown to achieve within 1 bit/s/Hz of the capacity region for all values of channel parameters. In contrast, the other three schemes achieve the near-optimal performance only in certain regimes of channel values. Asymptotic multiplexing gains of all proposed schemes are derived to show that the side-channel is extremely effective in regimes where inter-node interference has the highest impact.
1212.5303
Relational Foundations For Functorial Data Migration
cs.DB math.CT math.LO
We study the data transformation capabilities associated with schemas that are presented by directed multi-graphs and path equations. Unlike most approaches which treat graph-based schemas as abbreviations for relational schemas, we treat graph-based schemas as categories. A schema $S$ is a finitely-presented category, and the collection of all $S$-instances forms a category, $S$-inst. A functor $F$ between schemas $S$ and $T$, which can be generated from a visual mapping between graphs, induces three adjoint data migration functors, $\Sigma_F:S$-inst$\to T$-inst, $\Pi_F: S$-inst $\to T$-inst, and $\Delta_F:T$-inst $\to S$-inst. We present an algebraic query language FQL based on these functors, prove that FQL is closed under composition, prove that FQL can be implemented with the select-project-product-union relational algebra (SPCU) extended with a key-generation operation, and prove that SPCU can be implemented with FQL.
1212.5315
A hybrid FD-FV method for first-order hyperbolic conservation laws on Cartesian grids: The smooth problem case
math.NA cs.CE cs.NA
We present a class of hybrid FD-FV (finite difference and finite volume) methods for solving general hyperbolic conservation laws written in first-order form. The presentation focuses on one- and two-dimensional Cartesian grids; however, the generalization to higher dimensions is straightforward. These methods use both cell-averaged values and nodal values as dependent variables to discretize the governing partial differential equation (PDE) in space, and they are combined with method of lines for integration in time. This framework is absent of any Riemann solvers while it achieves numerical conservation naturally. This paper focuses on the accuracy and linear stability of the proposed FD-FV methods, thus we suppose in addition that the solutions are sufficiently smooth. In particular, we prove that the spatial-order of the FD-FV method is typically one-order higher than that of the discrete differential operator, which is involved in the construction of the method. In addition, the methods are linearly stable subjected to a Courant-Friedrich-Lewy condition when appropriate time-integrators are used. The numerical performance of the methods is assessed by a number of benchmark problems in one and two dimensions. These examples include the linear advection equation, nonlinear Euler equations, the solid dynamics problem for linear elastic orthotropic materials, and the Buckley-Leverett equation.
1212.5316
Quantum rate distortion coding with auxiliary resources
quant-ph cs.IT math.IT
We extend quantum rate distortion theory by considering auxiliary resources that might be available to a sender and receiver performing lossy quantum data compression. The first setting we consider is that of quantum rate distortion coding with the help of a classical side channel. Our result here is that the regularized entanglement of formation characterizes the quantum rate distortion function, extending earlier work of Devetak and Berger. We also combine this bound with the entanglement-assisted bound from our prior work to obtain the best known bounds on the quantum rate distortion function for an isotropic qubit source. The second setting we consider is that of quantum rate distortion coding with quantum side information (QSI) available to the receiver. In order to prove results in this setting, we first state and prove a quantum reverse Shannon theorem with QSI (for tensor-power states), which extends the known tensor-power quantum reverse Shannon theorem. The achievability part of this theorem relies on the quantum state redistribution protocol, while the converse relies on the fact that the protocol can cause only a negligible disturbance to the joint state of the reference and the receiver's QSI. This quantum reverse Shannon theorem with QSI naturally leads to quantum rate-distortion theorems with QSI, with or without entanglement assistance.
1212.5331
Adapting Voting Techniques for Online Forum Thread Retrieval
cs.IR
Online forums or message boards are rich knowledge-based communities. In these communities, thread retrieval is an essential tool facilitating information access. However, the issue on thread search is how to combine evidence from text units(messages) to estimate thread relevance. In this paper, we first rank a list of messages, then we score threads by aggregating their ranked messages' scores. To aggregate the message scores, we adopt several voting techniques that have been applied in ranking aggregates tasks such as blog distillation and expert finding. The experimental result shows that many voting techniques should be preferred over a baseline that treats a thread as a concatenation of its message texts.
1212.5352
On the Adaptability of Neural Network Image Super-Resolution
cs.CV
In this paper, we described and developed a framework for Multilayer Perceptron (MLP) to work on low level image processing, where MLP will be used to perform image super-resolution. Meanwhile, MLP are trained with different types of images from various categories, hence analyse the behaviour and performance of the neural network. The tests are carried out using qualitative test, in which Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The results showed that MLP trained with single image category can perform reasonably well compared to methods proposed by other researchers.
1212.5359
Fuzzy soft rough K-Means clustering approach for gene expression data
cs.LG cs.CE
Clustering is one of the widely used data mining techniques for medical diagnosis. Clustering can be considered as the most important unsupervised learning technique. Most of the clustering methods group data based on distance and few methods cluster data based on similarity. The clustering algorithms classify gene expression data into clusters and the functionally related genes are grouped together in an efficient manner. The groupings are constructed such that the degree of relationship is strong among members of the same cluster and weak among members of different clusters. In this work, we focus on a similarity relationship among genes with similar expression patterns so that a consequential and simple analytical decision can be made from the proposed Fuzzy Soft Rough K-Means algorithm. The algorithm is developed based on Fuzzy Soft sets and Rough sets. Comparative analysis of the proposed work is made with bench mark algorithms like K-Means and Rough K-Means and efficiency of the proposed algorithm is illustrated in this work by using various cluster validity measures such as DB index and Xie-Beni index.
1212.5374
A Blind Time-Reversal Detector in the Presence of Channel Correlation
cs.IT cs.PF math.IT
A blind target detector using the time reversal transmission is proposed in the presence of channel correlation. We calculate the exact moments of the test statistics involved. The derived moments are used to construct an accurate approximative Likelihood Ratio Test (LRT) based on multivariate Edgeworth expansion. Performance gain over an existing detector is observed in scenarios with channel correlation and relatively strong target signal.
1212.5389
Relationship-aware sequential pattern mining
cs.DB stat.AP
Relationship-aware sequential pattern mining is the problem of mining frequent patterns in sequences in which the events of a sequence are mutually related by one or more concepts from some respective hierarchical taxonomies, based on the type of the events. Additionally events themselves are also described with a certain number of taxonomical concepts. We present RaSP an algorithm that is able to mine relationship-aware patterns over such sequences; RaSP follows a two stage approach. In the first stage it mines for frequent type patterns and {\em all} their occurrences within the different sequences. In the second stage it performs hierarchical mining where for each frequent type pattern and its occurrences it mines for more specific frequent patterns in the lower levels of the taxonomies. We test RaSP on a real world medical application, that provided the inspiration for its development, in which we mine for frequent patterns of medical behavior in the antibiotic treatment of microbes and show that it has a very good computational performance given the complexity of the relationship-aware sequential pattern mining problem.
1212.5391
Soft Set Based Feature Selection Approach for Lung Cancer Images
cs.LG cs.CE
Lung cancer is the deadliest type of cancer for both men and women. Feature selection plays a vital role in cancer classification. This paper investigates the feature selection process in Computed Tomographic (CT) lung cancer images using soft set theory. We propose a new soft set based unsupervised feature selection algorithm. Nineteen features are extracted from the segmented lung images using gray level co-occurence matrix (GLCM) and gray level different matrix (GLDM). In this paper, an efficient Unsupervised Soft Set based Quick Reduct (SSUSQR) algorithm is presented. This method is used to select features from the data set and compared with existing rough set based unsupervised feature selection methods. Then K-Means and Self Organizing Map (SOM) clustering algorithms are used to cluster the data. The performance of the feature selection algorithms is evaluated based on performance of clustering techniques. The results show that the proposed method effectively removes redundant features.
1212.5394
Optimal Scheduling and Power Allocation for Two-Hop Energy Harvesting Communication Systems
cs.IT math.IT
Energy harvesting (EH) has recently emerged as a promising technique for green communications. To realize its potential, communication protocols need to be redesigned to combat the randomness of the harvested energy. In this paper, we investigate how to apply relaying to improve the short-term performance of EH communication systems. With an EH source and a non-EH half-duplex relay, we consider two different design objectives: 1) short-term throughput maximization; and 2) transmission completion time minimization. Both problems are joint scheduling and power allocation problems, rendered quite challenging by the half-duplex constraint at the relay. A key finding is that directional water-filling (DWF), which is the optimal power allocation algorithm for the single-hop EH system, can serve as guideline for the design of two-hop communication systems, as it not only determines the value of the optimal performance, but also forms the basis to derive optimal solutions for both design problems. Based on a relaxed energy profile along with the DWF algorithm, we derive key properties of the optimal solutions for both problems and thereafter propose efficient algorithms. Simulation results will show that both scheduling and power allocation optimizations are necessary in two-hop EH communication systems.
1212.5404
Edge Union of Networks on the Same Vertex Set
physics.soc-ph cond-mat.stat-mech cs.SI
Random networks generators like Erdoes-Renyi, Watts-Strogatz and Barabasi-Albert models are used as models to study real-world networks. Let G^1(V,E_1) and G^2(V,E_2) be two such networks on the same vertex set V. This paper studies the degree distribution and cluster coefficient of the resultant networks, G(V, E_1 U E_2).
1212.5406
Relaying Protocols for Wireless Energy Harvesting and Information Processing
cs.IT math.IT
An emerging solution for prolonging the lifetime of energy constrained relay nodes in wireless networks is to avail the ambient radio-frequency (RF) signal and to simultaneously harvest energy and process information. In this paper, an amplify-and-forward (AF) relaying network is considered, where an energy constrained relay node harvests energy from the received RF signal and uses that harvested energy to forward the source information to the destination. Based on the time switching and power splitting receiver architectures, two relaying protocols, namely, i) time switching-based relaying (TSR) protocol and ii) power splitting-based relaying (PSR) protocol are proposed to enable energy harvesting and information processing at the relay. In order to determine the throughput, analytical expressions for the outage probability and the ergodic capacity are derived for delay-limited and delay-tolerant transmission modes, respectively. The numerical analysis provides practical insights into the effect of various system parameters, such as energy harvesting time, power splitting ratio, source transmission rate, source to relay distance, noise power, and energy harvesting efficiency, on the performance of wireless energy harvesting and information processing using AF relay nodes. In particular, the TSR protocol outperforms the PSR protocol in terms of throughput at relatively low signal-to-noise-ratios and high transmission rate.
1212.5421
Design of a Smart Embedded Uninterrupted Power Supply System for Personal Computers
cs.SY
Digital equipment such as computers, telecommunication systems and instruments use microprocessors that operate at high frequencies allowing them to carry out millions or even billions of operations per second. A disturbance in the electrical supply lasting just a few milliseconds can affect thousands or millions of basic operations. The result may be malfunctioning and loss of data with dangerous or costly consequences (e.g. loss of production). That is why many loads, called sensitive or critical loads, require a supply that is protected. Many manufacturers of sensitive equipment specify very strict tolerances, much stricter than those in the distribution system for the supply of their equipment, one example being Computer Business Equipment Manufacturers Association for computer equipment against distribution system disturbances. The design of this uninterrupted power supply (UPS) for personal computer (PC) is necessitated due to a need for enhanced portability in the design of personal computer desktop workstations. Apart from its original functionality as a backup source of power, this design incorporates the unit within the system unit casing, thereby reducing the number of system components available. Also, the embedding of this unit removes the untidiness of connecting wires and makes the whole computer act like a laptop. Not to be left out is the choice of a microcontroller as an important part of the circuitry. This has eliminated the weight and space-consuming components that make up an original design. The singular use of this microcontroller places the UPS under the class of an advanced technology device.
1212.5423
Topic Extraction and Bundling of Related Scientific Articles
cs.IR cs.DL stat.ML
Automatic classification of scientific articles based on common characteristics is an interesting problem with many applications in digital library and information retrieval systems. Properly organized articles can be useful for automatic generation of taxonomies in scientific writings, textual summarization, efficient information retrieval etc. Generating article bundles from a large number of input articles, based on the associated features of the articles is tedious and computationally expensive task. In this report we propose an automatic two-step approach for topic extraction and bundling of related articles from a set of scientific articles in real-time. For topic extraction, we make use of Latent Dirichlet Allocation (LDA) topic modeling techniques and for bundling, we make use of hierarchical agglomerative clustering techniques. We run experiments to validate our bundling semantics and compare it with existing models in use. We make use of an online crowdsourcing marketplace provided by Amazon called Amazon Mechanical Turk to carry out experiments. We explain our experimental setup and empirical results in detail and show that our method is advantageous over existing ones.
1212.5440
Development of an Anti-collision Model for Vehicles
cs.SY
The Anti Collision device is a detection device meant to be incorporated into cars for the purpose of safety. As opposed to the anti collision devices present in the market today, this system is not designed to control the vehicle. Instead, it serves as an alert in the face of imminent collision. The device is intended to find a way to implement a minimum spacing for cars in traffic in an affordable way. It would also achieve safety for the passengers of a moving car. The device is made up of an infrared transmitter and receiver. Also incorporated into it is an audio visual alarm to work in with the receiver and effectively alert the driver and/or the passengers. To achieve this design, 555 timers coupled both as astable and monostable circuits were used along with a 38 KHz Square Pulse generator. The device works by sending out streams of infrared radiation and when these rays are seen by the other equipped vehicle, both are meant to take the necessary precaution to avert a collision. The device would still sound an alarm even though it is not receiving infrared beams from the oncoming vehicle. This is due to reflection of its own infrared beams. At the end of the design and testing process, overall system was implemented with a constructed work, tested working and perfectly functional.
1212.5442
\'Etude compar\'ee de quatre logiciels de gestion de r\'ef\'erences bibliographiques libres ou gratuits
cs.IR
This article is the result of the analysis of various bibliographic reference management tools, especially those that are free. The use of editorial tools by bibliographic editors has evolved rapidly since 2007. But, until recently, free software has fallen short when it comes to ergonomics or use. The functional and technical panorama offered by free software is the result of the comparison of JabRef, Mendeley Desktop, BibDesk and Zotero software undertaken in January 2012 by two research professors affiliated with the Institut national fran\c{c}ais des techniques de la documentation (INTD).
1212.5449
Characterizing Multivariate Information Flows
cs.IT math.DS math.IT stat.ME
One of the crucial steps in scientific studies is to specify dependent relationships among factors in a system of interest. Given little knowledge of a system, can we characterize the underlying dependent relationships through observation of its temporal behaviors? In multivariate systems, there are potentially many possible dependent structures confusable with each other, and it may cause false detection of illusory dependency between unrelated factors. The present study proposes a new information-theoretic measure with consideration to such potential multivariate relationships. The proposed measure, called multivariate transfer entropy, is an extension of transfer entropy, a measure of temporal predictability. In the simulations and empirical studies, we demonstrated that the proposed measure characterized the latent dependent relationships in unknown dynamical systems more accurately than its alternative measure.
1212.5454
In Vivo Quantification of Clot Formation in Extracorporeal Circuits
cs.CV physics.med-ph
Clot formation is a common complication in extracorporeal circuits. In this paper we describe a novel method for clot formation analysis using image processing. We assembled a closed extracorporeal circuit and circulated blood at varying speeds. Blood filters were placed in downstream of the flow, and clotting agents were added to the circuit. Digital images of the filter were subsequently taken, and image analysis was applied to calculate the density of the clot. Our results show a significant correlation between the cumulative size of the clots, the density measure of the clot based on image analysis, and flow duration in the system.
1212.5461
Interactive Ant Colony Optimisation (iACO) for Early Lifecycle Software Design
cs.SE cs.AI
Software design is crucial to successful software development, yet is a demanding multi-objective problem for software engineers. In an attempt to assist the software designer, interactive (i.e. human in-the-loop) meta-heuristic search techniques such as evolutionary computing have been applied and show promising results. Recent investigations have also shown that Ant Colony Optimization (ACO) can outperform evolutionary computing as a potential search engine for interactive software design. With a limited computational budget, ACO produces superior candidate design solutions in a smaller number of iterations. Building on these findings, we propose a novel interactive ACO (iACO) approach to assist the designer in early lifecycle software design, in which the search is steered jointly by subjective designer evaluation as well as machine fitness functions relating the structural integrity and surrogate elegance of software designs. Results show that iACO is speedy, responsive and highly effective in enabling interactive, dynamic multi-objective search in early lifecycle software design. Study participants rate the iACO search experience as compelling. Results of machine learning of fitness measure weightings indicate that software design elegance does indeed play a significant role in designer evaluation of candidate software design. We conclude that the evenness of the number of attributes and methods among classes (NAC) is a significant surrogate elegance measure, which in turn suggests that this evenness of distribution, when combined with structural integrity, is an implicit but crucial component of effective early lifecycle software design.
1212.5462
On the Impact of Phase Noise on Active Cancellation in Wireless Full-Duplex
cs.IT math.IT
Recent experimental results have shown that full-duplex communication is possible for short-range communications. However, extending full-duplex to long-range communication remains a challenge, primarily due to residual self-interference even with a combination of passive suppression and active cancellation methods. In this paper, we investigate the root cause of performance bottlenecks in current full-duplex systems. We first classify all known full-duplex architectures based on how they compute their cancelling signal and where the cancelling signal is injected to cancel self-interference. Based on the classification, we analytically explain several published experimental results. The key bottleneck in current systems turns out to be the phase noise in the local oscillators in the transmit and receive chain of the full-duplex node. As a key by-product of our analysis, we propose signal models for wideband and MIMO full-duplex systems, capturing all the salient design parameters, and thus allowing future analytical development of advanced coding and signal design for full-duplex systems.
1212.5473
Spin foam with topologically encoded tetrad on trivalent spin networks
cs.IT math.IT
We explore discrete approaches in LQG where all fields, the gravitational tetrad, and the matter and energy fields, are encoded implicitly in a graph instead of being additional data. Our graph should therefore be richer than a simple simplicial decomposition. It has to embed geometrical information and the standard model. We start from Lisi's model. We build a trivalent graph which is an F4 lattice of 48-valent supernodes, reduced as trivalent subgraphs, and topologically encoding data. We show it is a solution for EFE with no matter. We define bosons and half-fermions in two dual basis. They are encoded by bit exchange in supernodes, operated by Pachner 2-2 move, and rest state can be restored thanks to information redundancy. Despite its 4 dimensional nature, our graph is a trivalent spin network, and its history is a pentavalent spin foam.
1212.5524
Reinforcement learning for port-Hamiltonian systems
cs.SY cs.LG
Passivity-based control (PBC) for port-Hamiltonian systems provides an intuitive way of achieving stabilization by rendering a system passive with respect to a desired storage function. However, in most instances the control law is obtained without any performance considerations and it has to be calculated by solving a complex partial differential equation (PDE). In order to address these issues we introduce a reinforcement learning approach into the energy-balancing passivity-based control (EB-PBC) method, which is a form of PBC in which the closed-loop energy is equal to the difference between the stored and supplied energies. We propose a technique to parameterize EB-PBC that preserves the systems's PDE matching conditions, does not require the specification of a global desired Hamiltonian, includes performance criteria, and is robust to extra non-linearities such as control input saturation. The parameters of the control law are found using actor-critic reinforcement learning, enabling learning near-optimal control policies satisfying a desired closed-loop energy landscape. The advantages are that near-optimal controllers can be generated using standard energy shaping techniques and that the solutions learned can be interpreted in terms of energy shaping and damping injection, which makes it possible to numerically assess stability using passivity theory. From the reinforcement learning perspective, our proposal allows for the class of port-Hamiltonian systems to be incorporated in the actor-critic framework, speeding up the learning thanks to the resulting parameterization of the policy. The method has been successfully applied to the pendulum swing-up problem in simulations and real-life experiments.
1212.5525
Synchronization of a class of cyclic discrete-event systems describing legged locomotion
cs.SY
It has been shown that max-plus linear systems are well suited for applications in synchronization and scheduling, such as the generation of train timetables, manufacturing, or traffic. In this paper we show that the same is true for multi-legged locomotion. In this framework, the max-plus eigenvalue of the system matrix represents the total cycle time, whereas the max-plus eigenvector dictates the steady-state behavior. Uniqueness of the eigenstructure also indicates uniqueness of the resulting behavior. For the particular case of legged locomotion, the movement of each leg is abstracted to two-state circuits: swing and stance (leg in flight and on the ground, respectively). The generation of a gait (a manner of walking) for a multiple legged robot is then achieved by synchronizing the multiple discrete-event cycles via the max-plus framework. By construction, different gaits and gait parameters can be safely interleaved by using different system matrices. In this paper we address both the transient and steady-state behavior for a class of gaits by presenting closed-form expressions for the max-plus eigenvalue and max-plus eigenvector of the system matrix and the coupling time. The significance of this result is in showing guaranteed robustness to perturbations and gait switching, and also a systematic methodology for synthesizing controllers that allow for legged robots to change rhythms fast.
1212.5554
Re-encoding reformulation and application to Welch-Berlekamp algorithm
cs.IT math.IT
The main decoding algorithms for Reed-Solomon codes are based on a bivariate interpolation step, which is expensive in time complexity. Lot of interpolation methods were proposed in order to decrease the complexity of this procedure, but they stay still expensive. Then Koetter, Ma and Vardy proposed in 2010 a technique, called re-encoding, which allows to reduce the practical running time. However, this trick is only devoted for the Koetter interpolation algorithm. We propose a reformulation of the re-encoding for any interpolation methods. The assumption for this reformulation permits only to apply it to the Welch-Berlekamp algorithm.
1212.5577
A Structured Construction of Optimal Measurement Matrix for Noiseless Compressed Sensing via Analog Polarization
cs.IT math.IT
In this paper, we propose a method of structured construction of the optimal measurement matrix for noiseless compressed sensing (CS), which achieves the minimum number of measurements which only needs to be as large as the sparsity of the signal itself to be recovered to guarantee almost error-free recovery, for sufficiently large dimension. To arrive at the results, we employ a duality between noiseless CS and analog coding across sparse additive noisy channel (SANC). Extending Renyi Information Dimension to Mutual Information Dimension (MID), we show the operational meaning of MID to be the fundamental limit of asymptotically error-free analog transmission across SANC under linear analog encoding constraint. We prove that MID polarizes after analog polar transformation and obeys the same recursive relationship as BEC. We further prove that analog polar encoding can achieve the fundamental limit of achievable dimension rate with vanishing Pe across SANC. From the duality, a structured construction scheme is proposed for the linear measurement matrix which achieves the minimum measurement requirement for noiseless CS.
1212.5589
CODYRUN, outil de simulation et d'aide \`a la conception thermo-a\'eraulique de b\^atiments
cs.CE
This article presents the CODYRUN software developped by University of La R\'eunion. It is a multizone thermal software, with detailled airflow and humidity transfer calculations. One of its specific aspects is that it constitutes a research tool, a design tool used by the lab and professionnals and also a teaching tool. After a presentation of the multiple model aspect, some details of the tree modules associated to physical phenomenons are given. Elements of validation are exposed in next paraghaph, and then a few details of the front end.
1212.5590
Online Forum Thread Retrieval using Pseudo Cluster Selection and Voting Techniques
cs.IR
Online forums facilitate knowledge seeking and sharing on the Web. However, the shared knowledge is not fully utilized due to information overload. Thread retrieval is one method to overcome information overload. In this paper, we propose a model that combines two existing approaches: the Pseudo Cluster Selection and the Voting Techniques. In both, a retrieval system first scores a list of messages and then ranks threads by aggregating their scored messages. They differ on what and how to aggregate. The pseudo cluster selection focuses on input, while voting techniques focus on the aggregation method. Our combined models focus on the input and the aggregation methods. The result shows that some combined models are statistically superior to baseline methods.
1212.5592
Multiple model software for airflow and thermal building simulation. A case study under tropical humid climate, in R\'eunion Island
cs.CE
The first purpose of our work has been to allow -as far as heat transfer modes, airflow calculation and meteorological data reconstitution are concerned- the integration of diverse interchangeable physical models in a single software tool for professional use, CODYRUN. The designer's objectives, precision requested and calculation time consideration, lead us to design a structure accepting selective use of models, taking into account multizone description and airflow patterns. With a building case study in Reunion Island, we first analyse the sensibility of the thermal model to diffuse radiation reconstitution on tilted surfaces. Then, a realistic balance between precision required and calculation time leads us to select detailed models for the zone of main interest, but to choose simplified models for the other zones.
1212.5593
Time-variant Linear reduction model approximation : application to thermal and airflow building simulation
cs.CE
Considering the natural ventilation, the thermal behavior of buildings can be described by a linear time varying model. In this paper, we describe an implementation of model reduction of linear time varying systems. We show the consequences of the model reduction on computing time and accuracy. Finally, we compare experimental measures and simulation results using the initial model or the reduced model. The reduced model shows negligible difference in accuracy, and the computing time shortens.
1212.5594
Black box modelling of HVAC system : improving the performances of neural networks
cs.NE cs.CE
This paper deals with neural networks modelling of HVAC systems. In order to increase the neural networks performances, a method based on sensitivity analysis is applied. The same technique is also used to compute the relevance of each input. To avoid the prediction errors in dry coil conditions, a metamodel for each capacity is derived from the neural networks. The regression coefficients of the polynomial forms are identified through the use of spectral analysis. These methods based on sensitivity and spectral analysis lead to an optimized neural network model, as regard to its architecture and predictions.
1212.5599
Elaboration of a new tool for weather data sequences generation
cs.CE
This paper deals about the presentation of a new software RUNEOLE used to provide weather data in buildings physics. RUNEOLE associates three modules leading to the description, the modelling and the generation of weather data. The first module is dedicated to the description of each climatic variable included in the database. Graphic representation is possible (with histograms for example). Mathematical tools used to compare statistical distributions, determine daily characteristic evolutions, find typical days, and the correlations between the different climatic variables have been elaborated in the second module. Artificial weather datafiles adapted to different simulation codes are available at the issue of the third module. This tool can then be used in HVAC system evaluation, or in the study of thermal comfort. The studied buildings can then be tested under different thermal, aeraulic, and radiative solicitations, leading to a best understanding of their behaviour for example in humid climates.
1212.5620
Topological Analysis and Mitigation Strategies for Cascading Failures in Power Grid Networks
physics.soc-ph cs.SI physics.comp-ph
Recently, there has been a growing concern about the overload status of the power grid networks, and the increasing possibility of cascading failures. Many researchers have studied these networks to provide design guidelines for more robust power grids. Topological analysis is one of the components of system analysis for its robustness. This paper presents a complex systems analysis of power grid networks. First, the cascading effect has been simulated on three well known networks: the IEEE 300 bus test system, the IEEE 118 bus test system, and the WSCC 179 bus equivalent model. To extend the analysis to a larger set of networks, we develop a network generator and generate multiple graphs with characteristics similar to the IEEE test networks but with different topologies. The generated graphs are then compared to the test networks to show the effect of topology in determining their robustness with respect to cascading failures. The generated graphs turn out to be more robust than the test graphs, showing the importance of topology in the robust design of power grids. The second part of this paper concerns the discussion of two novel mitigation strategies for cascading failures: Targeted Load Reduction and Islanding using Distributed Sources. These new mitigation strategies are compared with the Homogeneous Load Reduction strategy. Even though the Homogeneous Load Reduction is simpler to implement, the Targeted Load Reduction is much more effective. Additionally, an algorithm is presented for the partitioning of the network for islanding as an effort towards fault isolation to prevent cascading failures. The results for island formation are better if the sources are well distributed, else the algorithm leads to the formation of superislands.
1212.5633
Design, implementation and experiment of a YeSQL Web Crawler
cs.IR
We describe a novel, "focusable", scalable, distributed web crawler based on GNU/Linux and PostgreSQL that we designed to be easily extendible and which we have released under a GNU public licence. We also report a first use case related to an analysis of Twitter's streams about the french 2012 presidential elections and the URL's it contains.
1212.5636
Partout: A Distributed Engine for Efficient RDF Processing
cs.DB
The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic data on the Web but also to an increasing number of backend applications with already more than a trillion triples in some cases. Confronted with such huge amounts of data and the future growth, existing state-of-the-art systems for storing RDF and processing SPARQL queries are no longer sufficient. In this paper, we introduce Partout, a distributed engine for efficient RDF processing in a cluster of machines. We propose an effective approach for fragmenting RDF data sets based on a query log, allocating the fragments to nodes in a cluster, and finding the optimal configuration. Partout can efficiently handle updates and its query optimizer produces efficient query execution plans for ad-hoc SPARQL queries. Our experiments show the superiority of our approach to state-of-the-art approaches for partitioning and distributed SPARQL query processing.
1212.5637
Random Spanning Trees and the Prediction of Weighted Graphs
cs.LG stat.ML
We investigate the problem of sequentially predicting the binary labels on the nodes of an arbitrary weighted graph. We show that, under a suitable parametrization of the problem, the optimal number of prediction mistakes can be characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the graph. The cutsize is induced by the unknown adversarial labeling of the graph nodes. In deriving our characterization, we obtain a simple randomized algorithm achieving in expectation the optimal mistake bound on any polynomially connected weighted graph. Our algorithm draws a random spanning tree of the original graph and then predicts the nodes of this tree in constant expected amortized time and linear space. Experiments on real-world datasets show that our method compares well to both global (Perceptron) and local (label propagation) methods, while being generally faster in practice.
1212.5650
Learning the Gain Values and Discount Factors of DCG
cs.IR
Evaluation metrics are an essential part of a ranking system, and in the past many evaluation metrics have been proposed in information retrieval and Web search. Discounted Cumulated Gains (DCG) has emerged as one of the evaluation metrics widely adopted for evaluating the performance of ranking functions used in Web search. However, the two sets of parameters, gain values and discount factors, used in DCG are determined in a rather ad-hoc way. In this paper we first show that DCG is generally not coherent, meaning that comparing the performance of ranking functions using DCG very much depends on the particular gain values and discount factors used. We then propose a novel methodology that can learn the gain values and discount factors from user preferences over rankings. Numerical simulations illustrate the effectiveness of our proposed methods. Please contact the authors for the full version of this work.
1212.5656
High-precision camera distortion measurements with a "calibration harp"
cs.CV
This paper addresses the high precision measurement of the distortion of a digital camera from photographs. Traditionally, this distortion is measured from photographs of a flat pattern which contains aligned elements. Nevertheless, it is nearly impossible to fabricate a very flat pattern and to validate its flatness. This fact limits the attainable measurable precisions. In contrast, it is much easier to obtain physically very precise straight lines by tightly stretching good quality strings on a frame. Taking literally "plumb-line methods", we built a "calibration harp" instead of the classic flat patterns to obtain a high precision measurement tool, demonstrably reaching 2/100 pixel precisions. The harp is complemented with the algorithms computing automatically from harp photographs two different and complementary lens distortion measurements. The precision of the method is evaluated on images corrected by state-of-the-art distortion correction algorithms, and by popular software. Three applications are shown: first an objective and reliable measurement of the result of any distortion correction. Second, the harp permits to control state-of-the art global camera calibration algorithms: It permits to select the right distortion model, thus avoiding internal compensation errors inherent to these methods. Third, the method replaces manual procedures in other distortion correction methods, makes them fully automatic, and increases their reliability and precision.
1212.5663
On the decoding of quasi-BCH codes
cs.IT math.IT
In this paper we investigate the structure of quasi-BCH codes. In the first part of this paper we show that quasi-BCH codes can be derived from Reed-Solomon codes over square matrices extending the known relation about classical BCH and Reed-Solomon codes. This allows us to adapt the Welch-Berlekamp algorithm to quasi-BCH codes. In the second part of this paper we show that quasi-BCH codes can be seen as subcodes of interleaved Reed-Solomon codes over finite fields. This provides another approach for decoding quasi-BCH codes.
1212.5664
Weather sequences for predicting HVAC system behaviour in residential units located in tropical climates
cs.CE
The purpose of our research deals with the description of a methodology for the definition of specific weather sequences and their influence on the energy needs of HVAC system. We'll apply the method on the tropical Reunion Island. The methodological approach based on a detailed analysis of weather sequences leads to a classification of climatic situations that can be applied to the site. These sequences have been used to simulate buildings and air handling systems thanks to a thermal simulation code, CODYRUN. Results bring to the light how necessary it is to have coherent meteorological data for this kind of simulation.
1212.5665
Multiple model approach and experimental validation of a residential air-to-air heat pump
cs.CE
The beginning of this work is the achievement of a design tool, which is a multiple model software called " CODYRUN ", suitable for professionnals and usable by researchers. The original aspect of this software is that the designer has at his disposal a wide panel of choices between different heat transfer models More precisely, it consists in a multizone software integrating both natural ventilation and moisture tranfers . This software is developed on PC micro computer and gets advantage of the Microsoft WINDOWS front-end. Most of time, HVAC systems and specially domestic air conditioners, are taken into account in a very simplified way, or in a elaborated one. On one side,they are just supposed to supply the demand of cooling loads with an ideal control loop (no delay between the sollicitations and the time response of the system), The available outputs are initially the hourly cooling and heating consumptions without integrating the real caracteristics of the HVAC system This paper is also following the same multiple model approach than for the building modelling by defining different modelling levels for the air conditionning systems, from a very simplified one to a detailled one. An experimental validation is achieved in order to compare the sensitivity of each defined model and to point out the interaction between the thermal behaviour of the envelop and the electrical system consumption. For validation purposes, we will describe the data acquisition system. and the used real size test cell located in the University of Reunion island, Indian Ocean.
1212.5667
Efficient Incremental Relaying
cs.IT math.IT
We propose a novel relaying scheme which improves the spectral efficiency of cooperative diversity systems by utilizing limited feedback from destination. Our scheme capitalizes on the fact that relaying is only required when direct transmission suffers deep fading. We calculate the packet error rate for the proposed efficient incremental relaying scheme with both amplify and forward and decode and forward relaying. Numerical results are also presented to verify their analytical counterparts.
1212.5679
Cumulative Distance Enumerators of Random Codes and their Thresholds
cs.IT math.IT
Cumulative weight enumerators of random linear codes are introduced, their asymptotic properties are studied, and very sharp thresholds are exhibited; as a consequence, it is shown that the asymptotic Gilbert-Varshamov bound is a very sharp threshold point for the density of the linear codes whose relative distance is greater than a given positive number. For arbitrary random codes, similar settings and results are exhibited; in particular, the very sharp threshold point for the density of the codes whose relative distance is greater than a given positive number is located at half the asymptotic Gilbert-Varshamov bound.
1212.5687
On the Construction of Nonbinary Quantum BCH Codes
quant-ph cs.IT math.IT
Four quantum code constructions generating several new families of good nonbinary quantum nonprimitive non-narrow-sense Bose-Chaudhuri-Hocquenghem (BCH) codes are presented in this paper. The first two ones are based on Calderbank-Shor-Steane (CSS) construction derived from two nonprimitive BCH codes, not necessarily self-orthogonal. The third one is based on nonbinary Steane's enlargement of CSS codes applied to suitable sub-families of nonprimitive non-narrow-sense BCH codes. The fourth construction is derived from suitable sub-families of Hermitian self-orthogonal nonprimitive non-narrow-sense BCH codes. These constructions generate new families of quantum BCH codes whose parameters are better than the ones available in the literature.
1212.5701
ADADELTA: An Adaptive Learning Rate Method
cs.LG
We present a novel per-dimension learning rate method for gradient descent called ADADELTA. The method dynamically adapts over time using only first order information and has minimal computational overhead beyond vanilla stochastic gradient descent. The method requires no manual tuning of a learning rate and appears robust to noisy gradient information, different model architecture choices, various data modalities and selection of hyperparameters. We show promising results compared to other methods on the MNIST digit classification task using a single machine and on a large scale voice dataset in a distributed cluster environment.
1212.5711
Normalized Compression Distance of Multisets with Applications
cs.CV cs.IT math.IT physics.data-an
Normalized compression distance (NCD) is a parameter-free, feature-free, alignment-free, similarity measure between a pair of finite objects based on compression. However, it is not sufficient for all applications. We propose an NCD of finite multisets (a.k.a. multiples) of finite objects that is also a metric. Previously, attempts to obtain such an NCD failed. We cover the entire trajectory from theoretical underpinning to feasible practice. The new NCD for multisets is applied to retinal progenitor cell classification questions and to related synthetically generated data that were earlier treated with the pairwise NCD. With the new method we achieved significantly better results. Similarly for questions about axonal organelle transport. We also applied the new NCD to handwritten digit recognition and improved classification accuracy significantly over that of pairwise NCD by incorporating both the pairwise and NCD for multisets. In the analysis we use the incomputable Kolmogorov complexity that for practical purposes is approximated from above by the length of the compressed version of the file involved, using a real-world compression program. Index Terms--- Normalized compression distance, multisets or multiples, pattern recognition, data mining, similarity, classification, Kolmogorov complexity, retinal progenitor cells, synthetic data, organelle transport, handwritten character recognition
1212.5720
Hierarchical Graphical Models for Multigroup Shape Analysis using Expectation Maximization with Sampling in Kendall's Shape Space
cs.CV
This paper proposes a novel framework for multi-group shape analysis relying on a hierarchical graphical statistical model on shapes within a population.The framework represents individual shapes as point setsmodulo translation, rotation, and scale, following the notion in Kendall shape space.While individual shapes are derived from their group shape model, each group shape model is derived from a single population shape model. The hierarchical model follows the natural organization of population data and the top level in the hierarchy provides a common frame of reference for multigroup shape analysis, e.g. classification and hypothesis testing. Unlike typical shape-modeling approaches, the proposed model is a generative model that defines a joint distribution of object-boundary data and the shape-model variables. Furthermore, it naturally enforces optimal correspondences during the process of model fitting and thereby subsumes the so-called correspondence problem. The proposed inference scheme employs an expectation maximization (EM) algorithm that treats the individual and group shape variables as hidden random variables and integrates them out before estimating the parameters (population mean and variance and the group variances). The underpinning of the EM algorithm is the sampling of pointsets, in Kendall shape space, from their posterior distribution, for which we exploit a highly-efficient scheme based on Hamiltonian Monte Carlo simulation. Experiments in this paper use the fitted hierarchical model to perform (1) hypothesis testing for comparison between pairs of groups using permutation testing and (2) classification for image retrieval. The paper validates the proposed framework on simulated data and demonstrates results on real data.
1212.5764
Strategy-Proof Prediction Markets
cs.GT cs.MA
Prediction markets aggregate agents' beliefs regarding a future event, where each agent is paid based on the accuracy of its reported belief when compared to the realized outcome. Agents may strategically manipulate the market (e.g., delay reporting, make false reports) aiming for higher expected payments, and hence the accuracy of the market's aggregated information will be in question. In this study, we present a general belief model that captures how agents influence each other beliefs, and show that there are three necessary and sufficient conditions for agents to behave truthfully in scoring rule based markets (SRMs). Given that these conditions are restrictive and difficult to satisfy in real-life, we present novel strategy-proof SRMs where agents are truthful while dismissing all these conditions. Although achieving such a strong form of truthfulness increases the worst-case loss in the new markets, we show that this is the minimum loss required to dismiss these conditions.
1212.5765
Stochastic Subspace Identification: Valid Model, Asymptotics and Model Error Bounds
cs.SY math.OC
This paper investigates the ability of the stochastic subspace identification technique to return a valid model from finite measurement data, its asymptotic properties as the data set becomes large, and asymptotic error bounds of the identified model (in terms of $\mathcal{H}_2$ and $\mathcal{H}_{\infty}$ norms). First, a new and straightforward LMI-based approach is proposed, which returns a valid identified model even in cases where the system poles are very close to unit circle and there is insufficient data to accurately estimate the covariance matrices. The approach, which is demonstrated by numerical examples, provides an altenative to other techniques which often fail under these circumstances. Then, an explicit expression for the variance of the asymptotically normally distributed sample output covariance matrices and block-Hankel matrix are derived. From this result, together with perturbation techniques, error bounds for the state-space matrices in the innovations model are derived, for a given confidence level. This result is in turn used to derive several error bounds for the identified transfer functions, for a given confidence level. One is an explicit $\mathcal{H}_2$ bound. Additionally, two $\mathcal{H}_{\infty}$ error bounds are derived, one via perturbation analysis, and the other via an LMI-based technique.
1212.5768
Consensus with Ternary Messages
math.OC cs.SY
We provide a protocol for real-valued average consensus by networks of agents which exchange only a single message from the ternary alphabet {-1,0,1} between neighbors at each step. Our protocol works on time-varying undirected graphs subject to a connectivity condition, has a worst-case convergence time which is polynomial in the number of agents and the initial values, and requires no global knowledge about the graph topologies on the part of each node to implement except for knowing an upper bound on the degrees of its neighbors.
1212.5776
Improving problem solving by exploiting the concept of symmetry
cs.AI
We investigate the concept of symmetry and its role in problem solving. This paper first defines precisely the elements that constitute a "problem" and its "solution," and gives several examples to illustrate these definitions. Given precise definitions of problems, it is relatively straightforward to construct a search process for finding solutions. Finally this paper attempts to exploit the concept of symmetry in improving problem solving.
1212.5777
Collaborating Robotics Using Nature-Inspired Meta-Heuristics
cs.NE cs.RO
This paper introduces collaborating robots which provide the possibility of enhanced task performance, high reliability and decreased. Collaborating-bots are a collection of mobile robots able to self-assemble and to self-organize in order to solve problems that cannot be solved by a single robot. These robots combine the power of swarm intelligence with the flexibility of self-reconfiguration as aggregate Collaborating-bots can dynamically change their structure to match environmental variations. Collaborating robots are more than just networks of independent agents, they are potentially reconfigurable networks of communicating agents capable of coordinated sensing and interaction with the environment. Robots are going to be an important part of the future. Collaborating robots are limited in individual capability, but robots deployed in large numbers can represent a strong force similar to a colony of ants or swarm of bees. We present a mechanism for collaborating robots based on swarm intelligence such as Ant colony optimization and Particle swarm Optimization
1212.5782
Random Access with Physical-layer Network Coding
cs.IT math.IT
Leveraging recent progress in physical-layer network coding we propose a new approach to random access: When packets collide, it is possible to recover a linear combination of the packets at the receiver. Over many rounds of transmission, the receiver can thus obtain many linear combinations and eventually recover all original packets. This is by contrast to slotted ALOHA where packet collisions lead to complete erasures. The throughput of the proposed strategy is derived and shown to be significantly superior to the best known strategies, including multipacket reception.
1212.5789
Self-embeddings of Hamming Steiner triple systems of small order and APN permutations
cs.IT math.IT
The classification, up to isomorphism, of all self-embedding monomial power permutations of Hamming Steiner triple systems of order n=2^m-1 for small m, m < 23, is given. As far as we know, for m in {5,7,11,13,17,19}, all given self-embeddings in closed surfaces are new. Moreover, they are cyclic for all m and nonorientable at least for all m < 21. For any non prime m, the nonexistence of such self-embeddings in a closed surface is proven.
1212.5791
Carrier Frequency Offset Estimation Approach for Multicarrier Transmission on Hexagonal Time-Frequency Lattice
cs.IT math.IT
In this paper, a novel carrier frequency offset estimation approach, including preamble structure, carrier frequency offset estimation algorithm, is proposed for hexagonal multi-carrier transmission (HMCT) system. The closed-form Cramer-Rao lower bound of the proposed carrier frequency offset estimation scheme is given. Theoretical analyses and simulation results show that the proposed preamble structure and carrier frequency offset estimation algorithm for HMCT system obtains an approximation to the Cramer-Rao lower bound mean square error (MSE) performance over the doubly dispersive (DD) propagation channel.
1212.5792
On Max-SINR Receiver for Hexagonal Multicarrier Transmission Over Doubly Dispersive Channel
cs.IT math.IT
In this paper, a novel receiver for Hexagonal Multicarrier Transmission (HMT) system based on the maximizing Signal-to-Interference-plus-Noise Ratio (Max-SINR) criterion is proposed. Theoretical analysis shows that the prototype pulse of the proposed Max-SINR receiver should adapt to the root mean square (RMS) delay spread of the doubly dispersive (DD) channel with exponential power delay profile and U-shape Doppler spectrum. Simulation results show that the proposed Max-SINR receiver outperforms traditional projection scheme and obtains an approximation to the theoretical upper bound SINR performance within the full range of channel spread factor. Meanwhile, the SINR performance of the proposed prototype pulse is robust to the estimation error between the estimated value and the real value of time delay spread.
1212.5815
Classical Model Predictive Control of a Permanent Magnet Synchronous Motor
cs.SY math.OC
A model predictive control (MPC) scheme for a permanent-magnet synchronous motor (PMSM) is presented. The torque controller optimizes a quadratic cost consisting of control error and machine losses repeatedly, accounting the voltage and current limitations. The scheme extensively relies on optimization, to meet the runtime limitation, a suboptimal algorithm based on differential flatness, continuous parameterization and linear programming is introduced. The multivariable controller exploits cross-coupling effects in the long-range constrained predictive control strategy. The optimization results in fast and smooth torque dynamics while inherently using field-weakening to improve the power efficiency and the current dynamics in high speed operation. As distinctive MPC feature, constraint handling is improved, instead of just saturating the control input, field weakening is applied dynamically to bypass the voltage limitation. The performance of the scheme is demonstrated by experimental and numerical results.
1212.5829
Modeling Non-Uniform UE Distributions in Downlink Cellular Networks
cs.IT math.IT stat.AP
A recent way to model and analyze downlink cellular networks is by using random spatial models. Assuming user equipment (UE) distribution to be uniform, the analysis is performed at a typical UE located at the origin. While this method of sampling UEs provides statistics averaged over the UE locations, it is not possible to sample cell interior and cell edge UEs separately. This complicates the problem of analyzing deployment scenarios involving non-uniform distribution of UEs, especially when the locations of the UEs and the base stations (BSs) are dependent. To facilitate this separation, we propose a new tractable method of sampling UEs by conditionally thinning the BS point process and show that the resulting framework can be used as a tractable generative model to study cellular networks with non-uniform UE distribution.
1212.5841
Data complexity measured by principal graphs
cs.LG cs.IT math.IT
How to measure the complexity of a finite set of vectors embedded in a multidimensional space? This is a non-trivial question which can be approached in many different ways. Here we suggest a set of data complexity measures using universal approximators, principal cubic complexes. Principal cubic complexes generalise the notion of principal manifolds for datasets with non-trivial topologies. The type of the principal cubic complex is determined by its dimension and a grammar of elementary graph transformations. The simplest grammar produces principal trees. We introduce three natural types of data complexity: 1) geometric (deviation of the data's approximator from some "idealized" configuration, such as deviation from harmonicity); 2) structural (how many elements of a principal graph are needed to approximate the data), and 3) construction complexity (how many applications of elementary graph transformations are needed to construct the principal object starting from the simplest one). We compute these measures for several simulated and real-life data distributions and show them in the "accuracy-complexity" plots, helping to optimize the accuracy/complexity ratio. We discuss various issues connected with measuring data complexity. Software for computing data complexity measures from principal cubic complexes is provided as well.
1212.5855
Keep Ballots Secret: On the Futility of Social Learning in Decision Making by Voting
cs.IT math.IT
We show that social learning is not useful in a model of team binary decision making by voting, where each vote carries equal weight. Specifically, we consider Bayesian binary hypothesis testing where agents have any conditionally-independent observation distribution and their local decisions are fused by any L-out-of-N fusion rule. The agents make local decisions sequentially, with each allowed to use its own private signal and all precedent local decisions. Though social learning generally occurs in that precedent local decisions affect an agent's belief, optimal team performance is obtained when all precedent local decisions are ignored. Thus, social learning is futile, and secret ballots are optimal. This contrasts with typical studies of social learning because we include a fusion center rather than concentrating on the performance of the latest-acting agents.
1212.5860
A short note on the tail bound of Wishart distribution
math.ST cs.LG stat.TH
We study the tail bound of the emperical covariance of multivariate normal distribution. Following the work of (Gittens & Tropp, 2011), we provide a tail bound with a small constant.
1212.5863
Influence Analysis in the Blogosphere
cs.SI physics.soc-ph
In this paper we analyze influence in the blogosphere. Recently, influence analysis has become an increasingly important research topic, as online communities, such as social networks and e-commerce sites, playing a more and more significant role in our daily life. However, so far few studies have succeeded in extracting influence from online communities in a satisfactory way. One of the challenges that limited previous researches is that it is difficult to capture user behaviors. Consequently, the influence among users could only be inferred in an indirect and heuristic way, which is inaccurate and noise-prone. In this study, we conduct an extensive investigation in regard to influence among bloggers at a Japanese blog web site, BIGLOBE. By processing the log files of the web servers, we are able to accurately extract the activities of BIGLOBE members in terms of writing their blog posts and reading other member's posts. Based on these activities, we propose a principled framework to detect influence among the members with high confidence level. From the extracted influence, we conduct in-depth analysis on how influence varies over different topics and how influence varies over different members. We also show the potentials of leveraging the extracted influence to make personalized recommendation in BIGLOBE. To our best knowledge, this is one of the first studies that capture and analyze influence in the blogosphere in such a large scale.