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"abstract": "The readability of text depends on many variables. In many studies, lexical and grammatical factors have been analyzed a lot. However, there are not many quantitative analyses on the impact of coherence and cohesion on text readability. Coh-Metrix is a text analysis tool based on computer technology. After continuous development and improvement, it can accurately analyze the vocabulary, phrase, sentence frequency and character length in the text, and can analyze the grammar and semantics of the text. This article uses the Coh-Metrix tool to analyze the readability of the two texts, and compares the scores of readers' understanding of the text to illustrate the impact of coherence and cohesion on the readability of the text.",
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"abstract": "Today, literature skills are necessary. Engineering and other technical professions are not an exception from this requirement. Traditionally, technical reading and writing have been framed with a limited scope, containing documentation, specifications, standards, and related text types. Nowadays, however, the scope covers also other text types, including legal, policy, and related documents. Given this motivation, this paper evaluates the readability of 201 legislations and related policy documents in the European Union (EU). The digital single market (DSM) provides the context. Five classical readability indices provide the methods; these are quantitative measures of a text’s readability. The empirical results indicate that (i) generally a Ph.D. level education is required to comprehend the DSM laws and policy documents. Although (ii) the results vary across the five indices used, (iii) readability has slightly improved over time.",
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"title": "Enhanced State History Tree (eSHT): A Stateful Data Structure for Analysis of Highly Parallel System Traces",
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"abstract": "Behaviors of distributed systems with many cores and/or many threads are difficult to understand. This is why dynamic analysis tools such as tracers are useful to collect run-time data and help programmers debug and optimize complex programs. However, manual trace analysis on very large traces with billions of events can be a difficult problem which automated trace visualizers and analyzers aim to solve. Trace analysis and visualization software needs fast access to data which it cannot achieve by searching through the entire trace for every query. A number of solutions have adopted stateful analysis which rearranges events into a more query friendly structures after a single pass through the trace. In this paper, we look into current implementations and model the behavior of previous work, the State History Tree (SHT), on traces with many thread creation and deletion. This allows us to identify which properties of the SHT are responsible for inefficient disk usage and high memory consumption. We then propose a more efficient data structure, the enhanced State History Tree (eSHT), to store and query computed states, in order to limit disk usage and reduce the query time for any state. Next, we compare the use of SHT and eSHT on traces with many attributes. We finally verify the scalability of our new data structure according to trace size. As shown by our results, the proposed solution makes near optimal use of disk space, reduces the algorithm's memory usage logarithmically for previously problematic cases, and speeds up queries on traces with many attributes by an order of magnitude. The proposed solution builds upon our previous work, enabling it to easily scale up to traces containing a million threads.",
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"title": "Pair Analytics: Capturing Reasoning Processes in Collaborative Visual Analytics",
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"abstract": "Studying how humans interact with abstract, visual representations of massive amounts of data provides knowledge about how cognition works in visual analytics. This knowledge provides guidelines for cognitive-aware design and evaluation of visual analytic tools. Different methods have been used to capture and conceptualize these processes including protocol analysis, experiments, cognitive task analysis, and field studies. In this article, we introduce Pair Analytics: a method for capturing reasoning processes in visual analytics. We claim that Pair Analytics offers two advantages with respect to other methods: (1) a more natural way of making explicit and capturing reasoning processes and (2) an approach to capture social and cognitive processes used to conduct collaborative analysis in real-life settings. We support and illustrate these claims with a pilot study of three phenomena in collaborative visual analytics: coordination of attention, cognitive workload, and navigation of analysis.",
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"abstract": "A constructive approach has been adopted to build interpolatory and B-spline like cubic spline curves with a more general continuity than /spl beta/-continuity. This method provides not only a large variety of very interesting shape controls like biased, point and interval tensions but, as a special case, also recovers a number of spline methods like /spl nu/-spline of G.M. Nielson (1974), /spl beta/-splines, /spl gamma/-splines of W. Boehm (1995) and weighted /spl nu/-splines. The curve schemes have also been generalized to produce smooth surfaces with local shape control. The local shape control has been achieved by introducing variable shape parameters.",
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"title": "2020 24th International Conference on Circuits, Systems, Communications and Computers (CSCC)",
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"title": "On Construction of Singular Splines",
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"abstract": "One of the approaches to the problem of approximating functions with a singularity is the creation of an approximating apparatus based on splines with the same feature. For spline-wavelet decomposition of spline spaces it is important that the property of the embedding of these spaces is associated with the embedding grids. In this paper the approximation relations are considered to determine coordinate splines with a predefined singularity. The concept of generalized smoothness is introduced. It allows us to consider functions with singularity as generalized smooth functions. Corresponding approximation relations are constructed. The existence and uniqueness of coordinate splines with the mentioned feature are established. The linear shells of the coordinate splines are spaces with the property of embedding on embedding grids.",
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"affiliation": "Saint Petersburg State University,Department of Parallel Algorithms,St.-Petersburg,Russia",
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"title": "Basing on the Gear Pump's Radial Deformation to the Leakage Effects of Finite Element Analysis",
"normalizedTitle": "Basing on the Gear Pump's Radial Deformation to the Leakage Effects of Finite Element Analysis",
"abstract": "To analyze the radial leakage effects of the gear pump radial deformation, this paper adopts Finite Element Method (FEM) to do static analysis between pump body and gear shaft, and then gets three deformation cases on typical temperature between them. According to the result of finite element static analysis, it discusses the effect of the pump body radial irrational deformation to the gear shaft working hours and offers references to the future structure design of gear pump.",
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"content": "We present a new approach that deals with the stability limit of explicit integration schemes in simulations of deformable objects based on the finite element method. The underlying idea consists of using a large time step of a coarse tetrahedral mesh in any volumetric mesh that can be extracted from this initial mesh. This is performed by computing the intersection between two meshes: the volumetric mesh with a large time step (a tetrahedralized cube) and a triangular mesh that is the object to simulate. The mesh intersection is observed as cutting or dissecting the coarse mesh based on a given object's surface mesh. This task can be performed by the co rotational extended Finite Element Method (XFEM) in a stable manner. The XFEM handles the dissections as discontinuities while maintaining the original mesh intact. Hence, the magnitude order of the largest time step is preserved. Elements lying outside the surface mesh are treated as fixed and thus are not considered in the simulation. The intersection method is computed only once before starting the simulation. Our approach is suitable for interactive applications with/without topological changes. Furthermore, our approach can be directly switched to implicit solvers. The proposed method is an important contribution for designing simulations of deformable objects without meshing techniques.",
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"doi": "10.1109/ICMTMA.2010.43",
"title": "Finite Element Analysis on Thermal Deformation of T-shape Groove Dry Gas Seal",
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"abstract": "In order to know thoroughly the thermal deformation characters of T-shape groove dry gas seal under stable state in synthesis gas compressor, the physical model of seal pair and the mathematical model are established on its structural and thermal analysis. Based on thermo-elastic deformation theory and finite element analysis software ANSYS, numerical analysis method and separation method are applied to resolve and analyze thermal-structural coupling deformation of seal pair, and the effective seal length is gained. The analyzed results show that the deformation of stationary ring is negative conicity, the deformation of rotating ring is positive conicity, and the later is the major reason of seal failure. The conicity and curvature of end face axial deformation are the major causes of forming end face gap shape (convergence/ parallel/ divergence), while restriction form and geometrical shape are the main reasons affecting deformation conicity and curvature. The deformation conicity and curvature of rotating ring should be decreased, so we can expect the gap between the rotating and stationary rings will keep parallel or similar parallel after deformation.",
"abstracts": [
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"content": "In order to know thoroughly the thermal deformation characters of T-shape groove dry gas seal under stable state in synthesis gas compressor, the physical model of seal pair and the mathematical model are established on its structural and thermal analysis. Based on thermo-elastic deformation theory and finite element analysis software ANSYS, numerical analysis method and separation method are applied to resolve and analyze thermal-structural coupling deformation of seal pair, and the effective seal length is gained. The analyzed results show that the deformation of stationary ring is negative conicity, the deformation of rotating ring is positive conicity, and the later is the major reason of seal failure. The conicity and curvature of end face axial deformation are the major causes of forming end face gap shape (convergence/ parallel/ divergence), while restriction form and geometrical shape are the main reasons affecting deformation conicity and curvature. The deformation conicity and curvature of rotating ring should be decreased, so we can expect the gap between the rotating and stationary rings will keep parallel or similar parallel after deformation.",
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"normalizedAbstract": "In order to know thoroughly the thermal deformation characters of T-shape groove dry gas seal under stable state in synthesis gas compressor, the physical model of seal pair and the mathematical model are established on its structural and thermal analysis. Based on thermo-elastic deformation theory and finite element analysis software ANSYS, numerical analysis method and separation method are applied to resolve and analyze thermal-structural coupling deformation of seal pair, and the effective seal length is gained. The analyzed results show that the deformation of stationary ring is negative conicity, the deformation of rotating ring is positive conicity, and the later is the major reason of seal failure. The conicity and curvature of end face axial deformation are the major causes of forming end face gap shape (convergence/ parallel/ divergence), while restriction form and geometrical shape are the main reasons affecting deformation conicity and curvature. The deformation conicity and curvature of rotating ring should be decreased, so we can expect the gap between the rotating and stationary rings will keep parallel or similar parallel after deformation.",
"fno": "3962c284",
"keywords": [
"T Shape Groove Dry Gas Seal",
"Thermal Deformation",
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"fullName": "Weibing Zhu",
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"fullName": "Na Li",
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"abstract": "Aiming at the problem of deformation of heavy hydrostatic thrust bearing, finite element method (FEM) is used to conduct its numerical simulation, and the law of the influence of temperature and load on bearing deformation is revealed. Experiment of oil film thickness in different velocity is also made. The results demonstrate that: the free thermal deformation of workbench and base is significant. The thermal deformation can be counteracted by the pressure deformation partly in radial, which could improve deformation situation of workbench, the edge of deformed workbench becomes upper convex, the base becomes lower convex, and their whole deformation is a bugle-like from inside to outside., There is a nice coincidence between numerical simulation and experiment. Development cost can be economized significantly and the performance forecast of bearing can be realized. Furthermore, the theoretical basis and optimization direction for bearing design and calculation of its lubrication performance can be provided from this.",
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"title": "2013 Fifth International Conference on Measuring Technology and Mechatronics Automation",
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"title": "Energy Absorption Study on Drive Cab of an Intercity Coach in Frontal Impact Analysis",
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"abstract": "Investigation of major safety accidents occurred from April to June in 2010 in China shows that occupants of coach & bus have been injured more seriously. In order to analyze the passenger safety of front body structure for coach & bus, a finite element model of a body-over-frame coach was built. Front crash analysis of the structure of a bus front body was performed according to the ECE R29-2005 protection of the occupants of the cab of commercial vehicles of European regulation requirements, GB11551-2003 the protection of the occupant in the event of a frontal collision for passenger car of china regulation requirements, and the strength of the bus structure was checked whether the safety requirements are satisfied. The nonlinear explicit finite element code LS-DYNA was used to improve the frontal crash safety as impact velocity was 30km/h. The crashworthiness and perfection of drive cab in front impact was studied and compared by taking into account crush variables, which include guide-side-door deformation, drive-side-door deformation and the frame deformation of drive cab floor. The results indicated that it is necessary to optimize the front absorbing components of bus to improve the protection level of passenger and the crashworthiness of drive cab, and front dynamic crash analysis simulated clearly in the real world accidents.",
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{
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"content": "Investigation of major safety accidents occurred from April to June in 2010 in China shows that occupants of coach & bus have been injured more seriously. In order to analyze the passenger safety of front body structure for coach & bus, a finite element model of a body-over-frame coach was built. Front crash analysis of the structure of a bus front body was performed according to the ECE R29-2005 protection of the occupants of the cab of commercial vehicles of European regulation requirements, GB11551-2003 the protection of the occupant in the event of a frontal collision for passenger car of china regulation requirements, and the strength of the bus structure was checked whether the safety requirements are satisfied. The nonlinear explicit finite element code LS-DYNA was used to improve the frontal crash safety as impact velocity was 30km/h. The crashworthiness and perfection of drive cab in front impact was studied and compared by taking into account crush variables, which include guide-side-door deformation, drive-side-door deformation and the frame deformation of drive cab floor. The results indicated that it is necessary to optimize the front absorbing components of bus to improve the protection level of passenger and the crashworthiness of drive cab, and front dynamic crash analysis simulated clearly in the real world accidents.",
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"normalizedAbstract": "Investigation of major safety accidents occurred from April to June in 2010 in China shows that occupants of coach & bus have been injured more seriously. In order to analyze the passenger safety of front body structure for coach & bus, a finite element model of a body-over-frame coach was built. Front crash analysis of the structure of a bus front body was performed according to the ECE R29-2005 protection of the occupants of the cab of commercial vehicles of European regulation requirements, GB11551-2003 the protection of the occupant in the event of a frontal collision for passenger car of china regulation requirements, and the strength of the bus structure was checked whether the safety requirements are satisfied. The nonlinear explicit finite element code LS-DYNA was used to improve the frontal crash safety as impact velocity was 30km/h. The crashworthiness and perfection of drive cab in front impact was studied and compared by taking into account crush variables, which include guide-side-door deformation, drive-side-door deformation and the frame deformation of drive cab floor. The results indicated that it is necessary to optimize the front absorbing components of bus to improve the protection level of passenger and the crashworthiness of drive cab, and front dynamic crash analysis simulated clearly in the real world accidents.",
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"fullName": "Tang Youming",
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"fullName": "Yan Yongpan",
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"title": "Soft Tissue Deformation and Optimized Data Structures for Mass Spring Methods",
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"abstract": "One of the essential components of a virtual reality surgical simulation is deformation. Deformations in computer graphics and surgical simulations are commonly modeled with three different approaches e.g. geometry based methods, Finite Element method(FEM), and Mass-spring Method (MSM). The geometry based methods are quite fast and visually appealing. Late two methods take the physics of deformation into consideration. Even though the FEM results in more physically realistic deformations, a significant drawback of this method is its expensive computation cost and vulnerability to surgical procedures such as incision. However,MSM is relatively computationally inexpensive.Because of the real-time physics based behavior of MSM, it is widely accepted by surgical simulation community. This study summarizes deformation simulation methods and their pros and cons for surgical simulations. Moreover, because of wide usage of the MSM, optimized data structures for MSM are provided and analyzed under different deformation settings.",
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"content": "One of the essential components of a virtual reality surgical simulation is deformation. Deformations in computer graphics and surgical simulations are commonly modeled with three different approaches e.g. geometry based methods, Finite Element method(FEM), and Mass-spring Method (MSM). The geometry based methods are quite fast and visually appealing. Late two methods take the physics of deformation into consideration. Even though the FEM results in more physically realistic deformations, a significant drawback of this method is its expensive computation cost and vulnerability to surgical procedures such as incision. However,MSM is relatively computationally inexpensive.Because of the real-time physics based behavior of MSM, it is widely accepted by surgical simulation community. This study summarizes deformation simulation methods and their pros and cons for surgical simulations. Moreover, because of wide usage of the MSM, optimized data structures for MSM are provided and analyzed under different deformation settings.",
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"fno": "3656a045",
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"fullName": "Coskun Bayrak",
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"fullName": "Richard Rowe",
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{
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"fullName": "Bernard Chen",
"givenName": "Bernard",
"surname": "Chen",
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"abstract": "Deformational control is a critical problem for composite structures, especially for complex geometry composites. This paper presents a new anti-deformation compensation method to decrease the deformation for the polymer matrix fiber reinforced composite parts. The new method uses a mathematical model way, and includes a dimension predication model and an anti-deformation compensation model. The dimension predication model is developed to calculate the residual stresses of the composite part during the curing process, and aims to get the deformation of the composite part after demould. The anti-deformation compensation model uses the predicated deformation as input to calculate the reverse deformation, and provides the basis for redesigning the composite part surface to reduce the ultimate deformation.",
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"abstract": "The reuse of motion capture data has become an important way to generate realistic motions. Retrieval of similar motion segments from large motion datasets accordingly serves as a fundamental problem for data-based motion processing methods. The retrieval task is difficult due to the spatio-temporal variances existing in human motion. With the increasing amount of data, the retrieval task has become even more time consuming. In this paper, we present a motion retrieval approach that is capable of extracting similar motion subsequences from very large motion databases given a query motion input. Our method employs BIRCH-based(Balanced Iterative Reducing and Clustering using Hierarchies) clustering method to incrementally cluster poses so as to effectively deal with very large datasets. An elastic LCS(longest common subsequence) algorithm is then proposed to discover the similar motion subsequences based on the posture clustering result. Finally, the motion patterns are extracted and stored, with each pattern containing a set of similar motions. In the runtime retrieval stage, as each stored pattern effectively compared with the query motion, the group of the similar motions is acquired. Experimental results show that our method successfully retrieves similar motions and outperforms the existing methods in time and space costs when applying to very large motion datasets.",
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"content": "The reuse of motion capture data has become an important way to generate realistic motions. Retrieval of similar motion segments from large motion datasets accordingly serves as a fundamental problem for data-based motion processing methods. The retrieval task is difficult due to the spatio-temporal variances existing in human motion. With the increasing amount of data, the retrieval task has become even more time consuming. In this paper, we present a motion retrieval approach that is capable of extracting similar motion subsequences from very large motion databases given a query motion input. Our method employs BIRCH-based(Balanced Iterative Reducing and Clustering using Hierarchies) clustering method to incrementally cluster poses so as to effectively deal with very large datasets. An elastic LCS(longest common subsequence) algorithm is then proposed to discover the similar motion subsequences based on the posture clustering result. Finally, the motion patterns are extracted and stored, with each pattern containing a set of similar motions. In the runtime retrieval stage, as each stored pattern effectively compared with the query motion, the group of the similar motions is acquired. Experimental results show that our method successfully retrieves similar motions and outperforms the existing methods in time and space costs when applying to very large motion datasets.",
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"fullName": "Cheng Ren",
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"abstract": "Thai boxing is a heritage of Thailand. We were interested in doing a research on the development of edutainment concerning Thai martial arts and self-defense in order to give both knowledge and entertainment at the same time. There were 30 postures (double posture) of Thai boxing exercises. The edutainment was designed to gain attention from the learners by using 3-dimension characters, scenes, sounds, animations, emotions, interactions, movements, virtual reality, and simulated situations. The motion picture was captured using 9 optical motion captures to record the data about the right movements performed by 2 experts in the art of self-defense and Thai boxing. This was done at the same time and there was no obstacle to perform dangerous postures. The results revealed that the edutainment helped the learners gain interest in Thai culture, the right exercise postures, physical activities, self-defense techniques, and entertainment for the learners who majored in physical education at the good level.",
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"abstract": "In this work we propose an effective method for frequency-controlled dense flow visualization derived from a generalization of the Line Integral Convolution (LIC) technique. Our approach consists in considering the spectral properties of the dense flow visualization process as an integral operator defined in a local curvilinear coordinate system aligned with the flow. Exploring LIC from this point of view, we suggest a systematic way to design a flow visualization process with particular local spatial frequency properties of the resulting image. Our method is efficient, intuitive, and based on a long-standing model developed as a result of numerous perception studies. The method can be described as an iterative application of line integral convolution, followed by a one-dimensional Gabor filtering orthogonal to the flow. To demonstrate the utility of the technique, we generated novel adaptive multi-frequency flow visualizations, that according to our evaluation, feature a higher level of frequency control and higher quality scores than traditional approaches in texture-based flow visualization.",
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"content": "In this work we propose an effective method for frequency-controlled dense flow visualization derived from a generalization of the Line Integral Convolution (LIC) technique. Our approach consists in considering the spectral properties of the dense flow visualization process as an integral operator defined in a local curvilinear coordinate system aligned with the flow. Exploring LIC from this point of view, we suggest a systematic way to design a flow visualization process with particular local spatial frequency properties of the resulting image. Our method is efficient, intuitive, and based on a long-standing model developed as a result of numerous perception studies. The method can be described as an iterative application of line integral convolution, followed by a one-dimensional Gabor filtering orthogonal to the flow. To demonstrate the utility of the technique, we generated novel adaptive multi-frequency flow visualizations, that according to our evaluation, feature a higher level of frequency control and higher quality scores than traditional approaches in texture-based flow visualization.",
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"abstract": "The distributed alternating direction method of mul-tipliers (ADMM) is an effective algorithm to solve large-scale op-timization problems. However, there are still massive computation and communication cost in distributed ADMM when processing high-dimensional data. To solve this problem, we propose a distributed ADMM with sparse computation and Allreduce communication (SCAC-ADMM) which can process high-dimensional data effectively. In the algorithm, each node optimizes a sub-model of the target model in parallel. Then, the target model is obtained by aggregating all sub-models. The features in the sub-model are named associated features. In SCAC-ADMM, we first design a selecting method of associated features to determine the composition of each sub-model. This method can limit the dimension of the sub-model by setting appropriate parameters, so as to limit the computation cost. Secondly, to reduce the communication traffic caused by transmitting high-dimensional parameters, we propose a novel Allreduce communication model which can only aggregate associated parameters in sub-models. Experiments on high-dimensional datasets show that SCAC-ADMM has less computation cost and higher communication efficiency than traditional distributed ADMM. When solving large-scale logistic regression problem, SCAC-ADMM can reduce the system time by 73% compared with traditional distributed ADMM.",
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"content": "The distributed alternating direction method of mul-tipliers (ADMM) is an effective algorithm to solve large-scale op-timization problems. However, there are still massive computation and communication cost in distributed ADMM when processing high-dimensional data. To solve this problem, we propose a distributed ADMM with sparse computation and Allreduce communication (SCAC-ADMM) which can process high-dimensional data effectively. In the algorithm, each node optimizes a sub-model of the target model in parallel. Then, the target model is obtained by aggregating all sub-models. The features in the sub-model are named associated features. In SCAC-ADMM, we first design a selecting method of associated features to determine the composition of each sub-model. This method can limit the dimension of the sub-model by setting appropriate parameters, so as to limit the computation cost. Secondly, to reduce the communication traffic caused by transmitting high-dimensional parameters, we propose a novel Allreduce communication model which can only aggregate associated parameters in sub-models. Experiments on high-dimensional datasets show that SCAC-ADMM has less computation cost and higher communication efficiency than traditional distributed ADMM. When solving large-scale logistic regression problem, SCAC-ADMM can reduce the system time by 73% compared with traditional distributed ADMM.",
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"content": "Decentralized consensus optimization algorithms are often applied in peer-to-peer network where the agents communicate with their neighbors and perform local computation. However, in many cases, the synchronous decentralized algorithms suffer from the straggler problem and the consequent communication latency. This paper proposes an asynchronous decentralized consensus alternating direction method of multipliers (ADMM) algorithm that can effectively reduce the communication latency. In the algorithm, each agent can compute and communicate independently under two control conditions (partial barrier, bounded delay), non-blocking communication is adopted to make the communication and computation perform simultaneously, and the step-size of the algorithm is adjusted to accelerate convergence. We test the algorithm on a high-performance computing cluster, experiments on distributed sparse logistic regression show that the asynchronous algorithm achieves faster convergence meanwhile the network waiting time is significantly reduced.",
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"normalizedAbstract": "Decentralized consensus optimization algorithms are often applied in peer-to-peer network where the agents communicate with their neighbors and perform local computation. However, in many cases, the synchronous decentralized algorithms suffer from the straggler problem and the consequent communication latency. This paper proposes an asynchronous decentralized consensus alternating direction method of multipliers (ADMM) algorithm that can effectively reduce the communication latency. In the algorithm, each agent can compute and communicate independently under two control conditions (partial barrier, bounded delay), non-blocking communication is adopted to make the communication and computation perform simultaneously, and the step-size of the algorithm is adjusted to accelerate convergence. We test the algorithm on a high-performance computing cluster, experiments on distributed sparse logistic regression show that the asynchronous algorithm achieves faster convergence meanwhile the network waiting time is significantly reduced.",
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"abstract": "The Alternating Direction Multiplier Method (ADMM) is an algorithm for solving large-scale machine learning optimization problems. In order to reduce the communication delay in a distributed environment, asynchronous distributed ADMM (AD-ADMM) was proposed. However, low convergence speed and the master-slave communication structure greatly reduce the performance of AD-ADMM in multi-core cluster. In this paper, we propose a new method to speed up the convergence of ADMM. The proposed method accelerates the convergence speed by automatically deciding the optimization algorithms needed for the solution of ADMM subproblem in each iteration. The dynamic scheduling strategy chooses the optimization algorithm mainly based on the primal residual and the dual residual. In addition, we also combine the hierarchical communication structure with the strategy to guarantee the efficiency. Experiments in the ZiQiang 4000 cluster experimental environment show that the dynamic scheduling strategy based on hierarchical communication structure for solving ADMM subproblem improves the convergence speed and the communication efficiency of the algorithm efficiently.",
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"content": "The Alternating Direction Multiplier Method (ADMM) is an algorithm for solving large-scale machine learning optimization problems. In order to reduce the communication delay in a distributed environment, asynchronous distributed ADMM (AD-ADMM) was proposed. However, low convergence speed and the master-slave communication structure greatly reduce the performance of AD-ADMM in multi-core cluster. In this paper, we propose a new method to speed up the convergence of ADMM. The proposed method accelerates the convergence speed by automatically deciding the optimization algorithms needed for the solution of ADMM subproblem in each iteration. The dynamic scheduling strategy chooses the optimization algorithm mainly based on the primal residual and the dual residual. In addition, we also combine the hierarchical communication structure with the strategy to guarantee the efficiency. Experiments in the ZiQiang 4000 cluster experimental environment show that the dynamic scheduling strategy based on hierarchical communication structure for solving ADMM subproblem improves the convergence speed and the communication efficiency of the algorithm efficiently.",
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"normalizedAbstract": "The Alternating Direction Multiplier Method (ADMM) is an algorithm for solving large-scale machine learning optimization problems. In order to reduce the communication delay in a distributed environment, asynchronous distributed ADMM (AD-ADMM) was proposed. However, low convergence speed and the master-slave communication structure greatly reduce the performance of AD-ADMM in multi-core cluster. In this paper, we propose a new method to speed up the convergence of ADMM. The proposed method accelerates the convergence speed by automatically deciding the optimization algorithms needed for the solution of ADMM subproblem in each iteration. The dynamic scheduling strategy chooses the optimization algorithm mainly based on the primal residual and the dual residual. In addition, we also combine the hierarchical communication structure with the strategy to guarantee the efficiency. Experiments in the ZiQiang 4000 cluster experimental environment show that the dynamic scheduling strategy based on hierarchical communication structure for solving ADMM subproblem improves the convergence speed and the communication efficiency of the algorithm efficiently.",
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"title": "Differentially Private Robust ADMM for Distributed Machine Learning",
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"abstract": "To embrace the era of big data, there has been growing interest in designing distributed machine learning to exploit the collective computing power of the local computing nodes. Alternating Direction Method of Multipliers (ADMM) is one of the most popular methods. This method applies iterative local computations over local datasets at each agent and computation results exchange between the neighbors. During this iterative process, data privacy leakage arises when performing local computation over sensitive data. Although many differentially private ADMM algorithms have been proposed to deal with such privacy leakage, they still have to face many challenging issues such as low model accuracy over strict privacy constraints and requiring strong assumptions of convexity of the objective function. To address those issues, in this paper, we propose a differentially private robust ADMM algorithm (PR-ADMM) with Gaussian mechanism. We employ two kinds of noise variance decay schemes to carefully adjust the noise addition in the iterative process and utilize a threshold to eliminate the too noisy results from neighbors. We also prove that PR-ADMM satisfies dynamic zero-concentrated differential privacy (dynamic zCDP) and a total privacy loss is given by (∈, δ)-differential privacy. From a theoretical point of view, we analyze the convergence rate of PR-ADMM for general convex objectives, which is O(1/K) with K being the number of iterations. The performance of the proposed algorithm is evaluated on real-world datasets. The experimental results show that the proposed algorithm outperforms other differentially private ADMM based algorithms under the same total privacy loss.",
"abstracts": [
{
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"content": "To embrace the era of big data, there has been growing interest in designing distributed machine learning to exploit the collective computing power of the local computing nodes. Alternating Direction Method of Multipliers (ADMM) is one of the most popular methods. This method applies iterative local computations over local datasets at each agent and computation results exchange between the neighbors. During this iterative process, data privacy leakage arises when performing local computation over sensitive data. Although many differentially private ADMM algorithms have been proposed to deal with such privacy leakage, they still have to face many challenging issues such as low model accuracy over strict privacy constraints and requiring strong assumptions of convexity of the objective function. To address those issues, in this paper, we propose a differentially private robust ADMM algorithm (PR-ADMM) with Gaussian mechanism. We employ two kinds of noise variance decay schemes to carefully adjust the noise addition in the iterative process and utilize a threshold to eliminate the too noisy results from neighbors. We also prove that PR-ADMM satisfies dynamic zero-concentrated differential privacy (dynamic zCDP) and a total privacy loss is given by (∈, δ)-differential privacy. From a theoretical point of view, we analyze the convergence rate of PR-ADMM for general convex objectives, which is O(1/K) with K being the number of iterations. The performance of the proposed algorithm is evaluated on real-world datasets. The experimental results show that the proposed algorithm outperforms other differentially private ADMM based algorithms under the same total privacy loss.",
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"fullName": "Jiahao Ding",
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"affiliation": "University of Houston,Department of Electrical and Computer Engineering,Houston,TX,77204",
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"affiliation": "East China Normal University,Shanghai Key Lab of Trustworthy Computing,Shanghai,China,200062",
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"affiliation": "University of Houston,Department of Electrical and Computer Engineering,Houston,TX,77204",
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"abstract": "Nested microgrids is an emerging configuration of microgrids where one microgrid can operate as part of a bigger microgrid to ensure supply and increase reliability. Each microgrid contains dispatchable and non-dispatchable distributed generators (DGs) from renewable energy sources (RES), and loads so it can be optimized to be self-sufficient. Yet, it is given the option to buy power from the upper level to meet its deficit or sell its surplus of power to the lower level. This paper proposed a method to optimize DGs output power and the power trading between upper and lower microgrids with the distributed optimization technique. Using the alternating direction method of multipliers (ADMM) algorithm, each level is optimized in parallel for a day-ahead energy management system (EMS). Then the boundary variables are checked until convergence criteria are met. A case study was executed on IEEE 33-bus system to evaluate the performance of the proposed technique.",
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"content": "Nested microgrids is an emerging configuration of microgrids where one microgrid can operate as part of a bigger microgrid to ensure supply and increase reliability. Each microgrid contains dispatchable and non-dispatchable distributed generators (DGs) from renewable energy sources (RES), and loads so it can be optimized to be self-sufficient. Yet, it is given the option to buy power from the upper level to meet its deficit or sell its surplus of power to the lower level. This paper proposed a method to optimize DGs output power and the power trading between upper and lower microgrids with the distributed optimization technique. Using the alternating direction method of multipliers (ADMM) algorithm, each level is optimized in parallel for a day-ahead energy management system (EMS). Then the boundary variables are checked until convergence criteria are met. A case study was executed on IEEE 33-bus system to evaluate the performance of the proposed technique.",
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"abstract": "Micro-expressions are difficult to spot but are utterly important for engaging in a conversation or negotiation. Through motion magnification, these expressions become much more distinguishable and easily recognized. This work proposes Global Lagrangian Motion Magnification (GLMM) for consistent exaggeration of facial expressions and dynamics across a whole video. As the proposal takes an opposite approach to a previous pivotal work, i.e. local Amplitude-based Eulerian Motion Magnification (AEMM). GLMM and AEMM are theoretically analyzed for potential advantages and disadvantages, especially with respect to how magnified noise and distortions are dealt with. Then, both GLMM and AEMM are empirically evaluated and compared using the CASME II micro-expression corpus.",
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"abstract": "Fluid mechanics considers two frames of reference for an observer watching a flow field: Eulerian and Lagrangian. The former is the frame of reference traditionally used for flow analysis, and involves extracting particle trajectories based on a vector field. With this work, we explore the opportunities that arise when considering these trajectories from the Lagrangian frame of reference. Specifically, we consider a form where flows are extracted in situ and then used for subsequent post hoc analysis. We believe this alternate, Lagrangian-based form will be increasingly useful, because the Eulerian frame of reference is sensitive to temporal frequency, and architectural trends are causing temporal frequency to drop rapidly on modern supercomputers. We support our viewpoint by running a series of experiments, which demonstrate the Lagrangian form can be more accurate, require less I/O, and be faster when compared to traditional advection.",
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"abstract": "EDDY (Evaluation of Differential DependencY) interrogates transcriptomic data to identify differential genetic dependencies within a biological pathway. Through its probabilistic framework with resampling and permutation, aided by the incorporation of annotated gene sets, EDDY demonstrated superior sensitivity to other methods. However, this statistical rigor incurs considerable computational cost, limiting its application to larger datasets. The ample and independent computation coupled with manageable memory footprint positioned EDDY as a strong candidate for graphical processing unit (GPU) implementation. Custom kernels decompose the independence test loop, network construction, network enumeration, and Bayesian network scoring to accelerate the computation. GPU-accelerated EDDY consistently exhibits two orders of magnitude in performance enhancement, allowing the statistical rigor of the EDDY algorithm to be applied to larger datasets.",
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