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IEEE International Conference on systems, Man and Cybernetics

作者： Anastasios Koutlas Dimitrios I. Fotiadis Department of Medical Physics Medical School Unit of Medical Technology and Intelligent Information Systems University of Ioannina (UoI) Ioannina Greece Department of Computer Science Medical School Unit of Medical Technology and Intelligent Information Systems University of Ioannina (UoI) Ioannina Greece

This work investigates the use of a point distribution model to detect prominent features in a face (eyes, brows, mouth, etc) and the subsequent facial feature extraction and facial expression classification into seven categories (anger, fear, surprise, happiness, disgust, neutral and sadness). A multi-scale and multi-orientation Gabor filter bank, designed in such a way so as to avoid redundant information, is used to extract facial features at selected locations of the prominent features of a face (fiducial points). A region based approach is employed at the location of the fiducial points using different region sizes to allow some degree of flexibility and avoid artefacts due to incorrect automatic discovery of these points. A feed forward back propagation Artificial Neural Network is employed to classify the extracted feature vectors. The methodology is evaluated by forming 7 different regions and the feature vector is extracted at the location of 20 fiducial points.

关键词： Face recognition Face detection Facial features data mining Feature extraction computer vision Eyes Mouth Gabor filters Feeds

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Perspectives on Requirements Understandability -- For Whom Does the Teacher's Bell Toll?

Perspectives on Requirements Understandability -- For Whom D...

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Requirements Engineering Education and Training, REET

作者： Mikael Svahnberg Tony Gorschek Magnus Eriksson Andreas Borg Kristian Sandahl Jürgen Börster Annabella Loconsole School of Engineering Blekinge Institute of Technology Sweden Land Systems Hägglunds AB Ornskoldsvik Sweden Department of Computer and Information Science Linköping University Sweden Department of Computing Science Umeå University Sweden

Software development decision makers use many different information sources as a basis for their decisions. One of these sources is the requirements specification, which is used in a large number of processes throughout the software development cycle. In order to make good decisions, the quality and completeness of the available information is important. Hence, requirements must be written in a way that is understandable for the different decision makers. However, requirements are rarely written with an explicit perception of how to make them understandable for different target usages. In this study we investigate the implicit assumptions of current and future requirements engineers and their teachers regarding which usages they perceive as most important when creating requirements. This is contrasted with industrial viewpoints of the relative importance of different requirements usages. The results indicate that the teachers and future requirements engineers have a strong focus towards in-project perspectives, and very little in common with the perspectives of industry managers. Thus, we are training students to serve as software developers, and not software engineering managers.

关键词： Management training Programming Engineering management Software quality Engineering education Books information science Industrial training Software engineering Software development management

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Neuromuscular Discrimination by Aggregating information in Motor unit Potentials

Neuromuscular Discrimination by Aggregating Information in M...

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Conference of the North American Fuzzy information Processing Society - NAFIPS

作者： Andrew Hamilton-Wright Linda McLean Daniel W. Stashuk Kristina Calder The Mathematics and Computer Science Department Mount Allison University Canada Computing and Information Science University of Guelph Canada The School of Rehabilitation Therapy Queen's University Canada Systems Design Engineering University of Waterloo Canada

When classifying data obtained by multiply sampling the same underlying entity, it is expected that characterizations based on aggregation of the information provided by all of the samples will be more accurate. Electromyographic (EMG) data presents such a scenario when individual motor unit potential trains (MUPTs) detected in a muscle during voluntary contraction are examined. We present a MUPT characterization technique based on quantitative analysis of EMG data, and further examine the value of various systems of aggregating MUPT information in order to achieve an overall electrophysiological assessment of the muscle. The data underlying this study was drawn from a population of patients who exhibit forearm pain associated with repetitive strain injury, and it is expected that these results will assist in electrophysiologically characterizing muscles of individuals having this condition and distinguishing these muscles from those of normative individuals and, in future, those suffering from other related conditions.

关键词： Neuromuscular Muscles Electromyography Electrophysiology Sampling methods data analysis information analysis Pain Capacitive sensors Injuries

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Reports of the AAAI 2008 Spring Symposia

Reports of the AAAI 2008 Spring Symposia

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作者： Balduccini, Marcello Baral, Chitta Brodaric, Boyan Colton, Simon Fox, Peter Gutelius, David Hinkelman, Knut Horswill, Ian Huberman, Bernardo Hudlicka, Eva Lerman, Kristina Lisetti, Christine McGuinness, Deborah Maher, Mary Lou Musen, Mark A. Sahami, Mehran Sleeman, Derek Thönssen, Barbara Velasquez, Juan Ventura, Dan Eastman Kodak Company Arizona State University Tempe AZ United States Geological Survey of Canada Department of Computing Imperial College London United Kingdom National Center for Atmospheric Research Artificial Intelligence Center SRI International Menlo Park CA United States University of Applied Sciences Zurich Switzerland Department of Computer Science Northwestern University Evanston IL United States Social Computing Lab. Hewlett-Packard Laboratories Psychometric Associates USC Information Sciences Institute University of Southern California Los Angeles CA United States Computer Science Department University of Southern California Los Angeles CA United States School of Computing and Information Sciences Florida International University Miami FL United States Rensselaer Polytechnic Institute Information and Intelligent Systems Division National Science Foundation University of Sydney Sydney NSW Australia Faculty of Architecture Design and Planning University of Sydney Sydney NSW Australia Department of Medicine Biomedica Informatics Research Department Stanford University Stanford CA United States Computer Science Department Stanford University Stanford CA United States Department of Computing Science University of Aberdeen Aberdeen United Kingdom MIT CSAIL Department of Computer Science Brigham Young University Provo UT United States

The Association for the Advancement of Artificial Intelligence (AAAI) was pleased to present the AAAI 2008 Spring Symposium Series, held Wednesday through Friday, March 26-28, 2008, at Stanford University, California. The eight symposia were titled (1) AI Meets Business Rules and Process Management, (2) Architectures for Intelligent Theory-Based Agents, (3) Creative Intelligent systems, (4) Emotion, Personality, and Social Behavior, (5) Semantic Scientific Knowledge Integration, (6) Social information Processing, (7) Symbiotic Relationships between Semantic Web and Knowledge Engineering, (8) Using Al to Motivate Greater Participation in computer science. The goal of the AI Meets Business Rules and Process Management AAAI symposium was to investigate the various approaches and standards to represent business rules, business process management, and the semantic web with respect to expressiveness and reasoning capabilities. The focus of the Architectures ror Intelligent Theory-Based Agents AAAI symposium was the definition or architectures for intelligent theory-based agents, comprising languages, knowledge representation methodologies, reasoning algorithms, and control loops. The Creative Intelligent systems symposium included five major discussion sessions and a general poster session (in which all contributing papers were presented). The purpose of this symposium was to explore the synergies between creative cognition and intelligent systems. The goal of the Emotion, Personality, and Social Behavior symposium was to examine fundamental issues in affect and personality in both biological and artificial agents, focusing on the roles of these factors in mediating social behavior. The Semantic Scientific Knowledge Integration symposium brought together the semantic technologies community with the scientific information technology community in an effort to build the general semantic science information community. The Social information Processing symposium's goal was to

关键词： Knowledge representation

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An image quality assessment metric based contourlet

An image quality assessment metric based contourlet

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IEEE International Conference on Image Processing

作者： Wen Lu Xinbo Gao Xuelong Li Dacheng Tao School of Electronic Engineering Xidian University Xi'an China School of Computer Science and Information Systems University of London London UK Department of computing Hong Kong Polytechnic University Hung Hom Hong Kong China

In reduced-reference (RR) image quality assessment (IQA), the visual quality of distorted images is evaluated with only partial information extracted from original images. In this paper, by considering the information of textures and directions during image distortion, we propose a new reduced- reference IQA metric to calculate the diversifications based on contourlet transform Experimental results illustrate that even with low data rate, the presented metric has still good consistency with the subjective perception.

关键词： Image quality Feature extraction data mining PSNR Statistical distributions Wavelet coefficients Image resolution Filter bank computer science information systems

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DLM: A distributed Large Memory System using remote memory swapping over cluster nodes

DLM: A distributed Large Memory System using remote memory s...

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IEEE International Conference on Cluster computing

作者： Hiroko Midorikawa Motoyoshi Kurokawa Ryutaro Himeno Mitsuhisa Sato Department of Computer and Information Science Seikei University Musashino Tokyo Japan Graduate School of Systems and Information Engineering University of Tsukuba Tennodai Tsukuba Ibaraki Japan Advanced Center of Computing and Communication Wako Saitama Japan Research Program for Computational Science RIKEN Wako Saitama Japan

Emerging 64 bitOSpsilas supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages efficiently, especially in a dedicated cluster which has a high-speed network such as 10 GbE and Infiniband. In this paper, we propose the distributed large memory system (DLM), which provides very large virtual memory by using remote memory distributed over the nodes in a cluster. The performance of DLM programs using remote memory is compared to ordinary programs using local memory. The results of STREAM, NPB and Himeno benchmarks show that the DLM achieves better performance than other remote paging schemes using a block swap device to access remote memory. In addition to performance, DLM offers the advantages of easy availability and high portability, because it is a user-level software without the need for special hardware. To obtain high performance, the DLM can tune its parameters independently from kernel swap parameters. We also found that DLMpsilas independence of kernel swapping provides more stable behavior.

关键词： Kernel Arrays Memory management Servers Bandwidth Performance evaluation Benchmark testing

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Web caching and prefetching: What, why, and how?

Web caching and prefetching: What, why, and how?

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International Symposium on information Technology, ITSim

作者： Sarina Sulaiman Siti Mariyam Shamsuddin Ajith Abraham Shahida Sulaiman Soft Computing Research Group Faculty of Computer Science and Information System Universiti Teknologi Malaysia Johor Malaysia Centre for Quantifiable Quality of Service in Communication Systems Norwegian University of Science and Technology Trondheim Norway School of Computer Sciences Universiti Sains Islam Malaysia Penang Malaysia

The demand for Internet content rose dramatically in recent years. Servers became more and more powerful and the bandwidth of end user connections and backbones grew constantly during the last decade. Nevertheless users often experience poor performance when they access web sites or download files. Reasons for such problems are often performance problems which occur directly on the servers (e.g. poor performance of server-side applications or during flash crowds) and problems concerning the network infrastructure (e.g. long geographical distances, network overloads, etc.). Web caching and prefetching have been recognized as the effective schemes to alleviate the service bottleneck, minimize the user access latency and reduce the network traffic. In this paper, we express the discussion on what is the Web caching and prefetching, why we have to opt its and how to pertain of these two technologies.

关键词： Prefetching Servers Internet Mobile communication World Wide Web Web server Algorithm design and analysis

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An automated supervised method for the diagnosis of Alzheimer’s disease based on fMRI data using weighted voting schemes

An automated supervised method for the diagnosis of Alzheime...

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IEEE International Workshop on Imaging systems and Techniques (IST)

作者： Evathia E. Tripoliti Dimitrios I. Fotiadis Maria Argyropoulou Department of Computer Science Unit of Medical Technology & Intelligent Information Systems University of Ioannina (UoI) Ioannina Greece Department of Radiology Medical School University of Ioannina (UoI) Ioannina Greece

We present an automated supervised method which assists in the diagnosis of Alzheimerpsilas disease (AD) using fMRI data. The method consists of five stages: a) preprocessing of fMRI data to remove motion and spatial noise artifacts, b) modeling of the data using generalized linear models (GLM), c) feature extraction, d) feature selection and e) classification using majority and weighted voting schemes.

关键词： Radio frequency Classification algorithms Feature extraction Distance measurement data mining data models Imaging

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A classification-based segmentation of cDNA microarray images using Support Vector machines

A classification-based segmentation of cDNA microarray image...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Nikolaos Giannakeas Petros S. Karvelis Dimitrios I. Fotiadis Laboratory of Biological Chemistry Medical School University of Ioannina (UoI) Ioannina Greece Unit of Medical Technology and Intelligent Information Systems Department of Computer Science University of Ioannina (UoI) Ioannina Greece

Microarray technology provides a tool for the simultaneous analysis of the expression level for an amount of genes. Microarray studies have been shown that image processing techniques can significantly influence microarray data precision. In this paper we propose a supervised method for the segmentation of microarray images based on classification techniques. Support Vector machine is employed to classify each pixel of the image into signal, background or artefacts. In addition, a preprocessing step is applied in order to filter the initial image. The proposed method is applied both to real and simulated images. The pixels of the image are classified in two classes for the real images and three classes for the simulated one. For this task, an informative set of features is used from both green and red channels. The results obtained indicate high accuracy (∼99%).

关键词： Image segmentation Support vector machines Feature extraction Probes Shape RNA Fluorescence

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Stabilizing controllers, Lyapunov functions, and the inverse problem of optimal control

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IFAC Proceedings Volumes 2008年第2期41卷 5885-5890页

作者： P. Rapisarda C. Kojima Information: Signal Images Systems (ISIS) Research Group School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom tel.: +44 (0)23 8059 3367 fax: +44 (0)23 80594498 Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo Hongo Bunkyo-Ku Tokyo 113-0033 Japan tel/fax: +81-3-5841-6890

We explore the connections of Margreta Kuijper's parametrization of stabilizing controllers, with some issues arising in inverse optimal control and in Lyapunov stability theory for higher-order linear time-invari... 详细信息

关键词： Lyapunov functions stationarity quadratic differential forms inverse problems dissipative systems

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