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Human motion recognition using Gaussian Processes classification

Human motion recognition using Gaussian Processes classifica...

引用

作者： Zhou, Hang Wang, Liang Suter, David Department of Electrical and Computer Systems Engineering Monash University VIC 3800 Australia Department of Computer Science and Software Engineering University of Melbourne VIC 3010 Australia

ISBN: (纸本)9781424421756

This paper investigates the applicability of Gaussian Processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using Tensor Subspace Analysis (TSA), space-time human silhouettes (extracted from motion videos) are transformed to low-dimensional multivariate time series, based on which structure-based statistical features are calculated to summarize the motion properties. GP classification is then used to learn and predict motion categories. Experimental results on two real-world state-of-the-art datasets show that the proposed approach is effective, and outperforms Support Vector Machine (SVM). © 2008 IEEE.

关键词： Support vector machines

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Data mining-driven analysis and decomposition In agent supply chain management networks

Data mining-driven analysis and decomposition In agent suppl...

引用

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008

作者： Chatzidimitriou, Kyriakos C. Symeonidis, Andreas L. Mitkas, Pericles A. Department of Electrical and Computer Engineering Aristotle University of Thessaloniki GR541 24 Thessaloniki Greece Intelligent Systems and Software Engineering Laboratory Informatics and Telematics Institute CERTH 57001 Thessaloniki Greece

ISBN: (纸本)9780769534961

In complex and dynamic environments where interdependencies cannot monotonously determine causality, data mining techniques may be employed in order to analyze the problem, extract key features and identify pivotal factors. Typical cases of such complexity and dynamicity are supply chain networks, where a number of involved stakeholders struggle towards their own benefit. These stakeholders may be agents with varying degrees of autonomy and intelligence, in a constant effort to establish beneficiary contracts and maximize own revenue. In this paper, we illustrate the benefits of data mining analysis on a well-established agent supply chain management network. We apply data mining techniques, both at a macro and micro level, analyze the results and discuss them in the context of agent performance improvement. © 2008 IEEE.

关键词： Supply chain management

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Gender and diversity in hiring software professionals: What do students say? 08

Gender and diversity in hiring software professionals: What ...

引用

4th International Computing Education Research Workshop, ICER'08

作者： Chinn, Donald Vandegrift, Tammy Computing and Software Systems University of Washington Tacoma Tacoma WA 98402-3100 United States Electrical Engineering and Computer Science University of Portland Portland OR 97203-5798 United States

ISBN: (纸本)9781605582160

This paper provides an analysis of students' choices and rationale with respect to gender and diversity in hiring software professionals. The study population included students at two universities who were asked to hire a software developer and a program manager from a pool of four candidates for a fictitious software company. As part of a written assignment, students provided reasons for choosing and not choosing candidates. To understand the role gender played in selecting candidates, the study included two candidate pools. The first candidate pool included four candidates. The second candidate pool differed from the first in that the descriptions of two of the candidates, represented by opposite genders, were switched. This paper reports on the following questions: 1) Does gender matter in the rate of selection among candidates?, 2) Does gender matter in how the candidates are perceived?, and 3) What statements about gender and diversity did students make? Through analyzing students' work, our study shows that gender plays a role in the rate of selection: the female candidate is more popular. Assumptions about candidates vary with gender. Finally, some students use diversity as a hiring criterion while others openly reject using gender and diversity as criteria in hiring. Copyright 2008 ACM.

关键词： Students

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Programming support for sensor-based scientific applications

Programming support for sensor-based scientific applications

引用

International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Nanyan Jiang Manish Parashar The Applied Software Systems Laboratory Department of Electrical and Computer Engineering Rutgers University Piscataway NJ USA

Technical advances are enabling a pervasive computational ecosystem that integrates computing infrastructures with embedded sensors and actuators, and are giving rise to a new paradigm for monitoring, understanding, and managing natural and engineered systems - one that is information/data-driven. This research investigates programming systems for sensor-driven applications. It addresses abstractions and runtime mechanisms for integrating sensor systems with computational models for scientific processes, as well as for in- network data processing, e.g., aggregation, adaptive interpolation and assimilation. The current status of this research, as well as initial results are presented.

关键词： Pervasive computing Sensor systems Ecosystems Embedded computing Actuators Monitoring engineering management Data engineering systems engineering and theory Runtime

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Human motion recognition using Gaussian Processes classification

Human motion recognition using Gaussian Processes classifica...

引用

International Conference on Pattern Recognition

作者： Hang Zhou Liang Wang David Suter Department of Electrical and Computer Systems Engineering Monash University VIC Australia Department of Computer Science and Software Engineering University of Melbourne VIC Australia

ISBN: (纸本)9781424421749

This paper investigates the applicability of Gaussian processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using tensor subspace analysis (TSA), space-time human silhouettes (extracted from motion videos) are transformed to low-dimensional multivariate time series, based on which structure-based statistical features are calculated to summarize the motion properties. GP classification is then used to learn and predict motion categories. Experimental results on two real-world state-of-the-art datasets show that the proposed approach is effective, and outperforms support vector machine (SVM).

关键词： Humans Gaussian processes Motion analysis Support vector machines Support vector machine classification Image recognition Image sequences Tensile stress Image motion analysis Time series analysis

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Aircraft AC generators: Hybrid system modeling and simulation

Aircraft AC generators: Hybrid system modeling and simulatio...

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International Conference on Prognostics and Health Management, PHM

作者： Ashraf Tantawy Xenofon Koutsoukos Gautam Biswas Institute for Software Integrated Systems and the Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN USA

Integrated drive generators (IDGs) are the main source of electrical power for a number of critical systems in aircraft. Fast and accurate fault detection and isolation is a necessary component for safe and reliable operation of the IDG and the aircraft. IDGs are complex systems, and a majority of the existing fault detection and isolation techniques are based on signal analysis and heuristic methods derived from experience. Model-based fault diagnosis techniques are hypothesized to be more general and powerful in designing detection and isolation schemes, but building sufficiently accurate models of complex IDGs is a difficult task. dq0 models have been developed for design and control of generators, but these models are not suitable for fault situations, where the generator may become unbalanced. In this paper, we present a hybrid phase-domain model for the aircraft generator that accurately represents both nominal and parametric faulty behaviors. We present the details of the hybrid modeling approach and simulation results of nominal operation and fault behaviors associated with parametric faults in the aircraft generator. The simulation results show that the developed model is capable of accurately capturing the generator dynamics under a variety of normal and faulty configurations.

关键词： AC generators Power generation electrical fault detection Aircraft manufacture Power system modeling Hybrid power systems Power system reliability Signal analysis Fault diagnosis Fault detection

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Towards A Model-Based Autonomic Reliability Framework for Computing Clusters

Towards A Model-Based Autonomic Reliability Framework for Co...

引用

5th IEEE International Workshop on engineering of Autonomic & Autonomous systems (EASc 2008)

作者： Abhishek Dubey Steve Nordstrom Turker Keskinpala Sandeep Neema Ted Bapty Gabor Karsai Institute for Software Integrated Systems Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN USA

One of the primary problems with computing clusters is to ensure that they maintain a reliable working state most of the time to justify economics of operation. In this paper, we introduce a model-based hierarchical reliability framework that enables periodic monitoring of vital health parameters across the cluster and provides for autonomic fault mitigation. We also discuss some of the challenges faced by autonomic reliability frameworks in cluster environments such as non-determinism in task scheduling in standard operating systems such as Linux and need for synchronized execution of monitoring sensors across the cluster. Additionally, we present a solution to these problems in the context of our framework, which utilizes a feedback controller based approach to compensate for the scheduling jitter in non real-time operating systems. Finally, we present experimental data that illustrates the effectiveness of our approach.

关键词： Operating systems Linux Jitter Hardware Maintenance computer networks Environmental economics Sensor systems Adaptive control Quantum computing

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Autonomic Management of Hybrid Sensor Grid systems and Applications

Autonomic Management of Hybrid Sensor Grid Systems and Appli...

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International Conference on computer Communications and Networks (ICCCN)

作者： Xiaolin Li Xinxin Liu Huanyu Zhao Nanyan Jiang Manish Parashar Department of Computer Science Scalable Software Systems Laboratory Oklahoma State University Stillwater OK USA Department of Electrical & Computer Engineering Applied Software Systems Laboratory Rutgers University NJ USA

In this paper, we propose an autonomic management framework (ASGrid) to address the requirements of emerging large-scale applications in hybrid grid and sensor network systems. To the best of our knowledge, we are the first who proposed the autonomic sensor grid system concept in a holistic manner targeted at non-trivial large applications. To bridge the gap between the physical world and the digital world and facilitate information analysis and decision making, ASGrid is designed to smooth the integration of sensor networks and grid systems and efficiently use both on demand. Under the blueprint of ASGrid, we present several building blocks that fulfill the following major features: (1) Self-configuration through content-based aggregation and associative rendezvous mechanisms; (2) Self-optimization through utility-based sensor selection and model-driven hierarchical sensing task scheduling; (3) Self-protection through ActiveKey dynamic key management and S3Trust trust management mechanisms. Experimental and simulation results on these aspects are presented.

关键词： Sensor systems and applications Content management Grid computing Instruments Sensor phenomena and characterization Resource management Power system management Sensor systems Waste management Application software

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Real-Time Distributed Discrete-Event Execution with Fault Tolerance

Real-Time Distributed Discrete-Event Execution with Fault To...

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IEEE Symposium on Real-Time and Embedded Technology and Applications

作者： Thomas Huining Feng Edward A. Lee Center for Hybrid and Embedded Software Systems Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

We build on PTIDES, a programming model for distributed embedded systems that uses discrete-event (DE) models as program specifications. PTIDES improves on distributed DE execution by allowing more concurrent event processing without backtracking. This paper discusses the general execution strategy for PTIDES, and provides two feasible implementations. This execution strategy is then extended with tolerance for hardware errors. We take a program transformation approach to automatically enhance DE models with incremental checkpointing and state recovery functionality. Our fault tolerance mechanism is lightweight and has low overhead. It requires very little human intervention. We incorporate this mechanism into PTIDES for efficient execution of fault- tolerant real-time distributed DE systems.

关键词： Fault tolerance Embedded system Hardware Real time systems Embedded software Distributed computing Checkpointing Fault tolerant systems Concurrent computing Application software

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In-network data estimation for sensor-driven scientific applications 08

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Proceedings of the 15th international conference on High performance computing

作者： Nanyan Jiang Manish Parashar Center for Autonomic Computing The Applied Software Systems Laboratory Department of Electrical and Computer Engineering Rutgers University Piscataway NJ

ISBN: (纸本)9783540898931

Sensor networks employed by scientific applications oftenneed to support localized collaboration of sensor nodes to perform in-network data processing. This includes new quantitative synthesis andhypothesis testing in near real time, as data streaming from distributedinstruments, to transform raw data into high level domain-dependent information. This paper investigates in-network data processing mechanismswith dynamic data requirements in resource constrained heterogeneoussensor networks. Particularly, we explore how the temporaland spatial correlation of sensor measurements can be used to trade offbetween the complexity of coordination among sensor clusters and thesavings that result from having fewer sensors involved in in-network processing,while maintaining an acceptable error threshold. Experimentalresults show that the proposed in-network mechanisms can facilitate theefficient usage of resources and satisfy data requirement in the presenceof dynamics and uncertainty.

关键词： in-network data estimation sensor system programming sensor-driven scientific applications

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