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IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015

作者： Bezerra, Clauber Gomes Costa, Bruno Sielly Jales Guedes, Luiz Affonso Angelov, Plamen Parvanov Campus EaD Federal Institute of Rio Grande Do Norte-IFRN Natal Brazil Department of Computer Engineering and Automation Federal University of Rio Grande Do Norte-UFRN Brazil Lancaster University Data Science Group School of Computing and Communications LA1 4WA United Kingdom

ISBN: (纸本)9781467374286

Outlier detection is a problem that has been largely studied in the past few years due to its great applicability in real world problems (e.g. financial, social, climate, security). Fault detection in industrial processes is one of these problems. In that context, several methods have been proposed in literature to address fault detection. In this paper we propose a comparative analysis of three recently introduced outlier detection methods: RDE, RDE with Forgetting and TEDA. Such methods were applied to the data set provided in DAMADICS benchmark, a very well-known real data tool for fault detection applications. The results, however, can be extended to similar problems of the area. Therewith, in this work we compare the main features of each method as well as the results obtained with them. © 2015 IEEE.

关键词： Benchmarking

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Simulating electrical properties of interdigitated electrode designs for impedance-based biosensing applications

Simulating electrical properties of interdigitated electrode...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： Scott MacKay Peter Hermansen David Wishart Wayne Hiebert Jie Chen Electrical and Computer Engineering Department University of Alberta Canada Biological Sciences Department and Computing Science Department University of Alberta Canada National Research Council/National Institute for Nanotechnology Canada Electrical and Computer Engineering Department National Research Council/National Institute for Nanotechnology Canada

ISBN: (纸本)9781479958306

In this paper, we describe a point-of-care biosensor design. The uniqueness of our design is in its capability for detecting a wide variety of target biomolecules and the simplicity of nanoparticle enhanced electrical detection. The electrical properties of interdigitated electrodes and the mechanism for gold nanoparticle-enhanced impedance-based biosensor systems based on these electrodes were simulated using COMSOL Multiphysics software. Understanding these properties and how they can be affected by the design of the sensor, environment during detection, and target biomolecules is vital in designing effective biosensor devices. Simulations were used to show electrical screening for interdigitated electrodes in a salt solution as well as the electric field between individual digits of electrodes. Using these simulations, it was observed that gold nanoparticles bound closely to interdigitated electrodes can lower the electric field magnitude between the digits of the electrode.

关键词： Electrodes Biological system modeling Electric fields Biosensors Gold Nanoparticles Electric variables measurement

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Privacy preserving for network coding in smart grid 15th

Privacy preserving for network coding in smart grid

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： He, Shiming Zeng, Weini Xie, Kun Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China The 716th Research Institute China Shipbuilding Industry Corporation Lianyungang222061 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook New York United States

ISBN: (纸本)9783319271361

In smart grid, privacy implications to individuals and their family is an important issue, due to the fine-grained usage data collection. Wireless communications are considered by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, Network Coding introduces new challenge for privacy preserving due to the encoding of packet in forwarder nodes. We propose a distributed privacy preserving scheme for network coding in smart grid, which considers the converged flows character of smart grid and exploits a homomorphic encryption function to decrease the complex in forwarder node. The message content of packet is encrypted and the tag of packet is encrypted by homomorphic encryption function. Then the forwarder node linear random codes the encrypted message contents and directly processes the tags cryptotext based on the homomorphism feature. It offers message content confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme. © Springer International Publishing Switzerland 2015.

关键词： Smart power grids

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SAC:Exploiting Stable Set Model to Enhance CacheFiles

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Journal of computer science & Technology 2014年第2期29卷 293-302页

作者：刘建亮张永乐杨琳郭明阳刘振军许鲁 Data Storage and Management Technology Research Center Institute of Computing TechnologyChinese Academy of Sciences University of Chinese Academy of Sciences Department of Electrical and Computer Engineering University of Toronto

Client cache is an important technology for the optimization of distributed and centralized storage systems. As a representative client cache system, the performance of CacheFiles is limited by transition faults. Furthermore, CacheFiles just supports a simple LRU policy with a tightly-coupled design. To overcome these limitations, we propose to employ Stable Set Model （SSM） to improve CacheFiles and design an enhanced CacheFiles, SAC. SSM assumes that data access can be decomposed to access on some stable sets, in which elements are always repeatedly accessed or not accessed together. Using SSM methods can improve the cache management and reduce the effect of transition faults. We also adopt loosely- coupled methods to design prefetch and replacement policies. We implement our scheme on Linux 2.6.32 and measure the execution time of the scheme with various file I/O benchmarks. Experiments show that SAC can significantly improve I/O performance and reduce execution time up to 84%0, compared with the existing CacheFiles.

关键词： Stable Set Model cache management CacheFiles

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A Family of Example-Specific Density Based Matching Kernels for Classification of Varying Length Patterns of Speech Using Support Vector Machines

A Family of Example-Specific Density Based Matching Kernels ...

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International Conference on Soft computing and Machine Intelligence (ISCMI)

作者： Abhijeet Sachdev A. D. Dileep Veena Thenkanidiyoor School of Computing and Electrical Engineering Indian Institute of Technology Mandi H.P. India Department of Computer Science and Engineering National Institute of Technology Goa Ponda Goa India

ISBN: (纸本)9781467398206

In this paper, we propose example-specific density based matching kernel (ESDMK) for the classification of varying length patterns of long duration speech represented as sets of feature vectors. The proposed kernel is computed between the pair of examples, represented as sets of feature vectors, by matching the estimates of the example-specific densities computed at every feature vector in those two examples. In this work, the number of feature vectors of an example among the K nearest neighbors of a feature vector is considered as an estimate of the example-specific density. The minimum of the estimates of two example-specific densities, one for each example, at a feature vector is considered as the matching score. The ESDMK is then computed as the sum of the matching score computed at every feature vector in a pair of examples. We also propose to compute pyramid match ESDMK by considering the increasingly larger number of neighbors to form pyramid of neighbors. We study the performance of the support vector machine (SVM) based classifiers using the proposed ESDMK and pyramid match ESDMK for speech emotion recognition and speaker identification tasks and compare the same with that of the SVM-based classifiers using the state-of-the-art kernels for varying length patterns.

关键词： Kernel Speech Probabilistic logic Pattern matching Computational modeling Speech recognition Emotion recognition

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Asset tracking in critical power communications infrastructure using passive techniques

Asset tracking in critical power communications infrastructu...

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International Conference on Environment and electrical engineering (EEEIC)

作者： John O'Raw David M. Laverty D. John Morrow Department of Computing Letterkenny Institute of Technology Letterkenny Ireland School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Northern Ireland

Active network scanning injects traffic into a network and observes responses to draw conclusions about the network. Passive network analysis works by looking at network meta data or by analyzing traffic as it traverses a fixed point on the network. It may be infeasible or inappropriate to scan critical infrastructure networks. Techniques exist to uniquely map assets without resorting to active scanning. In many cases, it is possible to characterize and identify network nodes by passively analyzing traffic flows. These techniques are considered in particular with respect to their application to power industry critical infrastructure.

关键词： Protocols Standards Security IP networks Operating systems Object recognition Automation

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Risk Management Using Big Real Time data

Risk Management Using Big Real Time Data

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IEEE International Conference on Cloud computing Technology and science (CloudCom)

作者： Jie Cheng Chunming Rong Huijuan Ye Xianghan Zheng Department of Electrical Engineering and Computer Science Risk Management Using Big Real Time Data Department of Computer Science and Electronic Engineering University of Stavanger Stavanger Norway College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

Adding to societal changes today, are the miscellaneous big data produced in different fields. Coupled with these data is the appearance of risk management. Admittedly, to predict future trend by using these data is conducive to make everything more efficient and easy. Now, no matter companies or individuals, they increasingly focus on identifying risks and managing them before risks. Effective risk management will lead them to deal with potential problems. This thesis focuses on risk management of flight delay area using big real time data. It proposes two different prediction models, one is called General Long Term Departure Prediction Model and the other is named as Improved Real Time Arrival Prediction Model. By studying the main factors lead to flight delay, this thesis takes weather, carrier, National Aviation System, security and previous late aircraft as analysis factors. By utilizing our models can do not only long time but also short term flight delay predictions. The results demonstrate goodness of fit. Besides the theory part, it also presents a practical and beautiful web application for real time flight arrival prediction based on our second model.

关键词： Delays Biological system modeling Meteorology Atmospheric modeling Predictive models Airports Splines (mathematics)

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Architectures for activity recognition and context-aware computing

Architectures for activity recognition and context-aware com...

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作者： Geib, Christopher Agrawal, Vikas Sukthankar, Gita Shastri, Lokendra Bui, Hung College of Computing and Informatics Drexel University United States Infosys Limited United States Department of Electrical Engineering and Computer Science University of Central Florida United States Advanced Technology Labs Samsung Research Institute Bangalore India Laboratory for Natural Language Understanding Nuance Communications SunnyvaleCA United States

The Special issue of AI Magazine brings together extended versions of selected papers from the 2013 Plan, Activity, and Intent Recognition workshops and the Activity Context-Aware Systems workshops to highlight the state of the art in the technologies that enable these new methods of interacting with virtual and cyber physical systems. Oriel Uzan, Reuth Dekel, Or Seri, and Ya'akov Gal's article, Plan Recognition for Exploratory Learning Environments Using Interleaved Temporal Search, presents novel algorithms for inferring users' activities in a class of flexible and open-ended educational software called exploratory learning environments (ELEs) that support interaction styles including exogenous actions and trial and error, providing a rich educational environment for students but challenging teachers to keep track of students' progress and to assess their performance. Christopher W. Geib and Christopher E. Swetenham's article, Parallelizing Plan Recognition, exploits the opportunity provided by modern multicore computing devices to parallelize plan recognition algorithms to decrease run time. Mik Kersten and Gail C. Murphy show in their article, Reducing Friction for Knowledge Workers with Task Context, how this friction can be reduced, and productivity improved, by capturing and modeling the context of a knowledge worker's task based on how the knowledge worker interacts with an information space. Computational management of activities that reflect human intention through activity-based computing (ABC) is described by Jakob E. Bardram, Steven Jeuris, and Steven Houben in their article, Activity-Based computing: Computational Management of Activities Reflecting Human Intention. In their article, A General Context-Aware Framework for Improved Human System Interactions, Stacy Lovell Pfautz, Gabriel Ganberg, Adam Fouse, and Nathan Schurr describe a general framework for building context-aware interactive intelligent systems.

关键词： Friction

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Cover Image, Volume 84, Issue 7

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Proteins: Structure, Function, and Bioinformatics 2016年第7期84卷

作者： Wei Wang Juan Liu Lin Sun Department of Computer Science and Technology College of Computer and Information Engineering Henan Normal University Xinxiang 453007 China Laboratory of Computation Intelligence and Information Processing Engineering Technology Research Center for Computing Intelligence and Data Mining Henan Province China Institute of Computer Software School of Computer Wuhan University Wuhan 430072 China

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TOWARDS WMSN PERFORMANCE USING DIFFERENT PACKET SIZE

TOWARDS WMSN PERFORMANCE USING DIFFERENT PACKET SIZE

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IEEE Sensors

作者： Cesar A. da Silva Marcelo A. C. Ismael Claudio M. Zaina Linnyer B. Ruiz Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte MG Brazil Department of Computing Federal Institute of São Paulo Presidente Epitácio SP Brazil Graduate Program in Computer Science State University of Maringá Maringá PR Brazil

The task of designing WMSN real scenarios in order to evaluate the network performance is not trivial. This work sheds some light on this challenge by studying the impact of the load size when using ZigBee protocol in WMSN that transmits images. The main feature is to use real nodes for reading and dividing camera data into packages for transmission over the network. We have analyzed the number of packets transmitted by sensor node and the number of packets received by base station as a success parameter of the delivery. We have also analyzed data delay and data delivery for each load size: 64, 80 and 96 bytes. The results reveal that there is a trade-off between latency and success rate and that the packet size definition can promote the productivity of network resources and the quality of the provided services.

关键词： Protocols ZigBee Wireless sensor networks Cameras Base stations Image communication IEEE 802.15 Standard

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