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作者： Machida, Fumio Nicola, Victor F. Trivedi, Kishor S. Knowledge Discovery Research Laboratories NEC Corporation Japan Mathematics and Computer Science University of Twente Netherlands Department of Electrical and Computer Engineering Duke University United States

This article analyzes the completion time of a job running on a virtualized server subject to software aging and rejuvenation in a virtual machine monitor (VMM). A job running on the server may be interrupted by virtual machine (VM) failure, VMM failure or VMM rejuvenation. The job interruption is categorized as either preemptive-repeat (prt), in which case the interrupted job needs to restart from the beginning, or preemptive-resume (prs), in which case the job resumes execution from the point of interruption. Using a semi-Markov process (SMP) to model the server behavior, the steady-state server availability is computed and the theory developed in Kulkarni et al. [1987] is used to obtain the Laplace-Stieltjes transform (LST) of the job completion time. In the numerical experiments, we introduce four types of aging behavior of VMM. The effectiveness of VMM rejuvenation on job completion time is discussed in association with the type of interruption it causes and the VMM aging type. With our parameter settings, VMM rejuvenation with prs job interruption improves the performance of job execution regardless of the aging type, with performance degradation is taken into account. © 2014 ACM 1550-4832/2014/01-ART10 $15.00.

关键词： Virtual machine

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Proceedings of the 23rd Paediatric Rheumatology European Society Congress: part three Abstracts

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PEDIATRIC RHEUMATOLOGY 2017年第1期15卷 203-259页

作者： [Anonymous] Pediatria II Reumatologia Istituto Giannina Gaslini Genoa Italy Radiologia Istituto Giannina Gaslini Genoa Italy University of Trieste Trieste Italy Division of Rheumatology Ospedale Pediatrico Bambino Gesù IRCCS Roma Italy Institute for Maternal and Child Health - IRCCS “Burlo Garofolo” Trieste Italy Pediatric Rheumatology Uludag University Medical Faculty Bursa Turkey Department of Pediatrics Nippon Medical School Tokyo Japan Division of Physiotherapy and Rehabilitaiton Faculty of Health Sciences Istanbul University Istanbul Turkey Department of Computer Engineering Gebze Institute of Technology Kocaeli Turkey Department of Pediatric Rheumatology Medical Faculty of Cerrahpasa Istanbul University Istanbul Turkey Department of Paediatric Rheumatology and Psychology Alder Hey Children’s NHS Foundation Trust Liverpool UK Department of Women’s and Children’s Health Institute of Translational Medicine Liverpool UK UK Experimental Arthritis Treatment Centre for Children University of Liverpool Liverpool UK Rheumatology Hospital for Sick Children Toronto Canada Pediatrics University of Toronto Toronto Canada Child Evaluative Health Sciences The Hospital for Sick Children Toronto Canada Lawrence S. Bloomberg Faculty of Medicine University of Toronto Toronto Canada Psychology University of Kansas Medical Center Lawrence USA Rheumatology IWK Health Center Halifax Canada Rheumatology Alberta children’s Hospital Calgary Canada Ingram School of Nursing Mcgill University Montreal Canada Child Health Evaluative Sciences Hospital for Sick Children Toronto Canada Rheumatology Children’s Hospital of Western Ontario London Canada Rheumatology CHU Ste-Justine Montreal Canada Rheumatology Montreal Children’s Hospital Montreal Canada Pediatrics Memorial University of Newfoundland St John’s Canada Pediatrics Children’s Hospital of Eastern Ontario Ottawa Canada Research Innovation and Knowledge Translation IWK Health Center Halifax Canada Pediatrics

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Introduction to the soft computing and intelligent data analysis minitrack

Introduction to the soft computing and intelligent data anal...

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Annual Hawaii International Conference on System sciences (HICSS)

作者： Rudolf Kruse Gabriella Pasi José María Alonso Magdeburg Germany Faculty of Computer Science Department of Knowledge Processing and Language Engineering Otto von Guericke University Università degli Studi di Milano Bicocca Italia Dipartimento di Informatica Laboratorio di Information Retrieval European Centre for Soft Computing Mieres Spain

Briefly summarizes the four papers presented in this minitrack.

关键词： Computational modeling Artificial intelligence Time series analysis Assembly Data analysis computer science Biological system modeling

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Introduction to the soft computing and intelligent data analysis minitrack

Proceedings of the Annual Hawaii International Conference on...

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Proceedings of the Annual Hawaii International Conference on System sciences 2015年 2015-March卷 1472-1473页

作者： Kruse, Rudolf Pasi, Gabriella Alonso, Jose Maria Otto von Guericke University Magdeburg Germany Faculty of Computer Science Department of Knowledge Processing and Language Engineering Germany Universit degli Studi di Milano Bicocca Italy Dipartimento di Informatica Laboratorio di Information Retrieval Italy European Centre for Soft Computing Mieres Spain Cognitive Computing with Perceptions Spain

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A fast noise resilient anomaly detection using GMM-based collective labelling

A fast noise resilient anomaly detection using GMM-based col...

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science and Information Conference (SAI)

作者： Elnaz Bigdeli Bijan Raahemi Mahdi Mohammadi Stan Matwin School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada Telfer School of Management Knowledge Discovery and Data Mining lab University of Ottawa E. Ottawa ON Canada Department of Computing Dalhousie University Halifax NB Canada Polish Academy of Sciences Warsaw Poland

Anomaly detection algorithms face several challenges including computational complexity and resiliency to noise in input data. In this paper, we propose a fast and noise-resilient cluster-based anomaly detection method using collective labelling approach. In the proposed Collective Probabilistic Anomaly Detection method, first instead of labelling each new sample (as normal or anomaly) individually, the new samples are clustered, then labelled. This collective labelling mitigates the negative impact of noise by relying on group behaviour rather than individual characteristics of incoming samples. Second, since grouping and labelling new samples may be time-consuming, we summarize clusters using Gaussian Mixture Model (GMM). Not only does GMM offer faster processing speed; it also facilitates summarizing clusters with arbitrary shape, and consequently, reducing the memory space requirement. Finally, a modified distance measure, based on Kullback-Liebner method, is proposed to calculate the similarity among clusters represented by GMMs. We evaluate the proposed method on various datasets by measuring its false alarm rate, detection rate and memory requirement. We also add different levels of noise to the input datasets to demonstrate the performance of the proposed collective anomaly detection method in the presence of noise. The experimental results confirm superior performance of the proposed method compared to individually-based labelling techniques in terms of memory usage, detection rate and false alarm rate.

关键词： Noise Shape Training Gaussian mixture model Clustering algorithms Support vector machines

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Footprint Recognition with Principal Component Analysis and Independent Component Analysis

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Macromolecular Symposia 2015年第1期347卷

作者： Rohit Khokher Ram Chandra Singh Rahul Kumar Department of Computer Science and Engineering Vidya College of Engineering Vidya Knowledge Park Meerut 250005 India Department of Physics Vidya College of Engineering Vidya Knowledge Park Meerut 250005 India Department of Computer Science and Engineering School of Engineering and Technology Sharda University Knowledge Park III Greater Noida 201306 India

The finger print recognition, face recognition, hand geometry, iris recognition, voice scan, signature, retina scan and several other biometric patterns are being used for recognition of an individual. Human footprint is one of the relatively new physiological biometrics due to its stable and unique characteristics. The texture and foot shape information of footprint offers one of the powerful means in personal recognition. This work proposes a footprint based biometric identification of an individual by extracting texture and shape based features using Principal Component Analysis (PCA) and Independent Component Analysis (ICA) linear projection techniques. PCA is a commonly used technique for data classification and dimensionality reduction and ICA is one of the most widely used blind source separation technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. In this study PCA and ICA have been compared for footprint recognition using distance classification techniques such as Euclidean distance, city block, cosine and correlation. Experimental results show that ICA performs better than PCA for footprint recognition.

关键词： biometrics distance algorithms footprint recognition independent component analysis principal component analysis

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Geometric intuition and algorithms for Ev-SVM

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2015年第1期16卷

作者： Àlvaro Barbero Akiko Takeda Jorge López Department of Computer Science and Knowledge-Engineering Institute Autonomous University of Madrid Madrid Spain Department of Mathematical Informatics The University of Tokyo Tokyo Japan Department of Computer Science and Knowledge-Engineering Institute Autonomous University of Madrid Madrid Spain

In this work we address the Ev-SVM model proposed by Pérez-Cruz et al. as an extension of the traditional v support vector classification model (v-SVM). Through an enhancement of the range of admissible values for the regularization parameter v, the Ev-SVM has been shown to be able to produce a wider variety of decision functions, giving rise to a better adaptability to the data. However, while a clear and intuitive geometric interpretation can be given for the v-SVM model as a nearest-point problem in reduced convex hulls (RCH-NPP), no previous work has been made in developing such intuition for the Ev-SVM model. In this paper we show how Ev-SVM can be reformulated as a geometrical problem that generalizes RCH-NPP, providing new insights into this model. Under this novel point of view, we propose the RapMinos algorithm, able to solve Ev-SVM more efficiently than the current methods. Furthermore, we show how RapMinos is able to address the Ev-SVM model for any choice of regularization norm lp ≥1 seamlessly, which further extends the SVM model flexibility beyond the usual Ev-SVM models.

关键词： Ev-SVM SVM classification nearest point problem reduced convex hulls

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Airport context analytics

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8741卷 179-184页

作者： Katsiri, Eli Papastefanatos, George Terrovitis, Manolis Sellis, Timos Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi67100 Greece Institute for the Management of Information Systems Research and Innovation Centre in Information Communication and Knowledge Technologies - "Athena" Artemidos 6 & Epidaurou Marousi Athens15125 Greece School of Computer Science and Information Technology RMIT University Australia

Underpinning the above vision is the ability to target service content to users’ current context, e.g., their location, intent, environment, in real time. The contribution of this work is that it uses a pervasive computing system with three key ingredients: (a) a data model, comprising user and service content entities, (b) a user context model and (c) rules for simple pattern matching on service content and user context event streams. This modus operandi is encapsulated inside a SOA architecture, the Common Airport Portal - CAP and it is illustrated through the description of a real application, Offers and Coupons Services that was deployed recently at Athens International Airport (AIA) (http://***).Airports today can constitute a perfect environment for developing novel digital marketplaces offering location-specific and semantically rich context-aware services, such as personalized marketing campaigns, last minute, discounted airline tickets while helping users access the airport and speed through the airport process. © Springer International Publishing Switzerland 2014.

关键词： Information services

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Attenuation of signal at a tropical location with radiosonde data due to cloud

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International Journal of Smart Home 2014年第1期8卷 15-22页

作者： Mandal, Bijoy Kumar Bhattacharyya, Debnath Kang, Sungmin Computer Science and Engineering Department FET NSHM Knowledge Campus - Durgapur Durgapur-713212 India School of Business Administration College of Business and Economics Chung-Ang University 84 Heukseok-ro Dongjak-gu Seoul 156-861 Korea Republic of

Cloud attenuation is calculated from cloud liquid water content (LWC). Cloud liquid water content (LWC) is derived from the radiosonde data using the Salonen model, show a prominent linear variation with the attenuation contribution due to cloud at a tropical location. In this paper, the attenuation contribution due to cloud liquid water content (LWC) and attenuation contribution due to cloud ice water content is studied at different frequencies in the tropical region. Cloud liquid water content shows a greater contribution compared to Cloud ice water content in causing attenuation of signal due to cloud in troposphere. ©2014 SERSC.

关键词： Liquids

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Monte Carlo Tree Search with heuristic evaluations using implicit minimax backups

Monte Carlo Tree Search with heuristic evaluations using imp...

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Marc Lanctot Mark H. M. Winands Tom Pepels Nathan R. Sturtevant Department of Knowledge Engineering Maastricht University Computer Science Department University of Denver

Monte Carlo Tree Search (MCTS) has improved the performance of game engines in domains such as Go, Hex, and general game playing. MCTS has been shown to outperform classic αβ search in games where good heuristic evaluations are difficult to obtain. In recent years, combining ideas from traditional minimax search in MCTS has been shown to be advantageous in some domains, such as Lines of Action, Amazons, and Breakthrough. In this paper, we propose a new way to use heuristic evaluations to guide the MCTS search by storing the two sources of information, estimated win rates and heuristic evaluations, separately. Rather than using the heuristic evaluations to replace the playouts, our technique backs them up implicitly during the MCTS simulations. These minimax values are then used to guide future simulations. We show that using implicit minimax backups leads to stronger play performance in Kalah, Breakthrough, and Lines of Action.

关键词： Games Silicon

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