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INTREPID, a biosignal-based system for the monitoring of patients with anxiety disorders

INTREPID, a biosignal-based system for the monitoring of pat...

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IEEE EMBS International Conference on Information technology Applications in Biomedicine (ITAB)

作者： Nikolaos S. Katertsidis Christos D. Katsis Dimitrios I. Fotiadis Unit of Medical Technology and Intelligent Information Systems Department of Computer Science University of Ioannina (UoI) Ioannina Greece Department of Medical Physics Medical School and the Unit of Medical Technology and Intelligent Information Systems Dept of Computer Science University of Ioannina (UoI) Ioannina Greece Department of Materials Science and Engineering University of Ioannina (UoI) Ioannina Greece

In this work, we present the concept, the architecture and the evaluation of the INTREPID system. INTREPID is an advanced monitoring system which optimally classifies an individual's emotional state based on 5 pre-defined emotional classes, (relaxed, neutral, startled, apprehensive and very apprehensive), through association of the information arising from specific biological signals (Blood Volume Pulse, Heart Rate, Galvanic Skin Response and Respiration). The system is utilized for the monitoring of patients with anxiety disorder during therapeutic sessions. It is validated using data obtained through an emotion elicitation experiment based on the International Affective Picture System. An overall classification ratio of 85% is obtained.

关键词： Patient monitoring Emotion recognition Humans Biomedical monitoring Skin Blood Feature extraction Heart rate Data mining Galvanizing

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An optimized sequential pattern matching methodology for sequence classification

An optimized sequential pattern matching methodology for seq...

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作者： Exarchos, Themis P. Tsipouras, Markos G. Papaloukas, Costas Fotiadis, Dimitrios I. Department of Medical Physics Medical School University of Ioannina PO Box 1186 45110 Ioannina Greece Department of Computer Science Unit of Medical Technology and Intelligent Information Systems University of Ioannina PO Box 1186 45110 Ioannina Greece Department of Biological Applications and Technology University of Ioannina PO Box 1186 45110 Ioannina Greece

In this paper we present a novel methodology for sequence classification, based on sequential pattern mining and optimization algorithms. The proposed methodology automatically generates a sequence classification model, based on a two stage process. In the first stage, a sequential pattern mining algorithm is applied to a set of sequences and the sequential patterns are extracted. Then, the score of every pattern with respect to each sequence is calculated using a scoring function and the score of each class under consideration is estimated by summing the specific pattern scores. Each score is updated, multiplied by a weight and the output of the first stage is the classification confusion matrix of the sequences. In the second stage an optimization technique, aims to finding a set of weights which minimize an objective function, defined using the classification confusion matrix. The set of the extracted sequential patterns and the optimal weights of the classes comprise the sequence classification model. Extensive evaluation of the methodology was carried out in the protein classification domain, by varying the number of training and test sequences, the number of patterns and the number of classes. The methodology is compared with other similar sequence classification approaches. The proposed methodology exhibits several advantages, such as automated weight assignment to classes using optimization techniques and knowledge discovery in the domain of application. © Springer-Verlag London Limited 2008.

关键词： Classification (of information)

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Two-stage Approach for Word-wise Script Identification

Two-stage Approach for Word-wise Script Identification

引用

International Conference on Document Analysis and Recognition

作者： Sukalpa Chanda Srikanta Pal Katrin Franke Umapada Pal Department of Computer Science and Media Technology Gjovik University College GjOvik Norway CVPR Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781424445004

A two-stage approach for word-wise identification of English (Roman), Devnagari and Bengali (Bangla) scripts is proposed. This approach balances the tradeoff between recognition accuracy and processing speed. The 1st stage allows identifying scripts with high speed, yet less accuracy when dealing with noisy data. The advanced 2nd stage processes only those samples that yield low recognition confidence in the first stage. For both stages a rough character segmentation is performed and features are computed on segmented character components. Features used in the 1st stage are a 64-dimensional chain-code-histogram feature, while 400-dimensional gradient features are used in the 2nd stage. Final classification of a word to a particular script is done via majority voting of each recognized character component of the word. Extensive experiments with various confidence scores were conducted and reported here. The overall recognition accuracy and speed is remarkable. Correct classification of 98.51% on 11,123 test words is achieved, even when the recognition-confidence is as high as 95% at both stages.

关键词： Optical character recognition software Character recognition Natural languages Voting Text analysis Information analysis Information security computer science Educational institutions Automatic testing

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Piecewise planar city 3D modeling from street view panoramic sequences

Piecewise planar city 3D modeling from street view panoramic...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Branislav Micusik Jana Kosecka Austrian Research Centers Video and Security Technology Unit Vienna Austria Computer Science Department George Mason University Fairfax USA

City environments often lack textured areas, contain repetitive structures, strong lighting changes and therefore are very difficult for standard 3D modeling pipelines. We present a novel unified framework for creating 3D city models which overcomes these difficulties by exploiting image segmentation cues as well as presence of dominant scene orientations and piecewise planar structures. Given panoramic street view sequences, we first demonstrate how to robustly estimate camera poses without a need for bundle adjustment and propose a multi-view stereo method which operates directly on panoramas, while enforcing the piecewise planarity constraints in the sweeping stage. At last, we propose a new depth fusion method which exploits the constraints of urban environments and combines advantages of volumetric and viewpoint based fusion methods. Our technique avoids expensive voxelization of space, operates directly on 3D reconstructed points through effective kd-tree representation, and obtains a final surface by tessellation of backprojections of those points into the reference image.

关键词： Cities and towns Image reconstruction Surface reconstruction Pipelines Layout Cameras Surface texture Image segmentation Earth Laser modes

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Key Predistribution Schemes Using Block Designs in Wireless Sensor Networks

Key Predistribution Schemes Using Block Designs in Wireless ...

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IEEE International Conference on Computational science and Engineering, CSE

作者： Sushmita Ruj Jennifer Seberry Bimal Roy Applied Statistics Unit Indian Statistical Institute Kolkata India School of Information Technology and Computer Science University of Wollongong Wollongong NSW Australia

We present a deterministic key predistribution scheme in wireless sensor networks (WSN) using combinatorial designs. The design finds application where a large number sensor nodes are to be deployed. This scheme has the advantage that each sensor node contains very few keys, however every pair of sensor nodes within communication range can directly communicate with each other. We calculate the resiliency of the network with respect to two parameters of resiliency. Our scheme is resilient to selective node capture attack and node fabrication attack.

关键词： Wireless sensor networks Statistics Fabrication Radio frequency computer networks Design engineering Information technology computer science Australia Application software

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Algorithms for biological cell sorting with a Lab-on-a-chip

Algorithms for biological cell sorting with a Lab-on-a-chip

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： Arijit Ghosh Rushin Shah Arijit Bishnu Bhargab B. Bhattacharya Computer Science and Engineering Department Indian Institute of Technology Kharagpur India Advanced Computing and Microelectronics Unit Indian Statistical Institute Kolkata India

Automatic cell sorting and isolation for recovery of such live cells, mostly microorganisms, is a challenging task. Lab-on-a-chip devices implemented as cell arrays are used for this purpose. For an abstract model of the problem, we can assume the cell array to be represented by a matrix where each cell can be any of the three types: empty, good (or desired) and bad (or undesired). The problem is to separate the good and the bad cells by pushing them under electric field to their respective receptors at the corners of the cell array. We address some combinatorial optimization problems related to this biological phenomenon.

关键词： Biological cells Sorting Lab-on-a-chip Microorganisms Stem cells Cells (biology) Voltage Niobium computer science Isolation technology

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Cardiac electrophysiology numerical models using symmetric multiprocessing (SMP)

Cardiac electrophysiology numerical models using symmetric m...

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

作者： Stefanos Konstantinos D. Petsios Dimitrios I. Fotiadis Department of Computer Science University of Ioannina (UoI) Ioannina Greece Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina (UoI) Ioannina Greece

Multi-dimensional electrophysiological models have been introduced to investigate electrical propagation in tissue level, based on cell-dynamics models. The models include a set of non-linear differential equations which describe the dynamics of cell and tissue excitation. However, as models evolve, it is inevitable that proper and powerful tools need to be introduced in order to reproduce the detailed and thus computationally intensive simulations. To build such tools, several computational methodologies need to be adopted regarding efficiency and reliability. On the other hand improvements apply to the hardware too. State of the art computers, even personal computers, tend to make use of multiple core Central Processing units. Unfortunately the aforementioned methodologies follow sequential logic, resulting to low efficiency of the working platform. In this work we present the performance bottleneck in symmetric multiprocessing (SMP) for simulations of propagation phenomena in cardiac tissue electrophysiological models. We demonstrate the scalability and efficacy of the different methodologies used in the discretisation scheme and message passing in SMP.

关键词： Numerical models Computational modeling Differential equations Hardware Microcomputers Central Processing unit Logic Cardiac tissue Scalability Message passing

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Reports of the AAAI 2009 spring symposia

Reports of the AAAI 2009 spring symposia

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作者： Bao, Jie Bojars, Uldis Choudhury, Tanzeem Ding, Li Greaves, Mark Kapoor, Ashish Louchart, Sandy Mehta, Manish Nebel, Bernhard Nirenburg, Sergei Oates, Tim Roberts, David L. Sanfilippo, Antonio Stojanovic, Nenad Stubbs, Kristen Thomaz, Andrea L. Tsui, Katherine Woelfl, Stefan Tetherless World Constellation Rensselaer Polytechnic Institute United States Social Software Unit of DERI Galway Ireland Computer Science Department Dartmouth College United States Knowledge Systems at Vulcan Inc United States Adaptive Systems and Interaction Group Microsoft Research Redmond United States School for Mathematics and Computer Sciences Heriot-Watt University United Kingdom School ot Interactive Computing Georgia Institute of Technology United States Department of Computer Science University of Freiburg Germany Computer Science and Electrical Engineering Department University of Maryland Baltimore County United States Pacific Northwest National Laboratory Richland WA United States University of Karlsruhe Germany IRobot Corporation United States University of Massachusetts Lowell United States

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of computer science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real- World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to leam from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more Al-based approaches in event pro-cessing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies IIAAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

关键词： Benchmarking

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Governance of Information Security Elements in Service-Oriented Enterprise Architecture

Governance of Information Security Elements in Service-Orien...

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International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN)

作者： Janne J. Korhonen Mehmet Yildiz Juha Mykkänen Department of Computer Science and Engineering Helsinki University of Technology Helsinki Finland Global Technology Services IBM Australia and New Zealand Melbourne Australia HIS Research and Development Unit University of Kuopio Kuopio Finland

This paper identifies and analyzes governance roles and tasks in SOA security governance at macro level. Drawing from Information security management standards and frameworks on one hand and SOA considerations on the other hand, the identified governance elements are mapped to a governance structure that specifies planning and execution aspects at four organizational decision-making levels, resulting in a prescriptive model with practical relevance. This constructive study combines theoretical models and standards with industry experience of the authors.

关键词： Information security Service oriented architecture Information management Standards organizations Resource management Risk management IEC standards ISO standards Web services Semiconductor optical amplifiers

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Automatic feature definition and selection in fault diagnosis of oil rig motor pumps

Automatic feature definition and selection in fault diagnosi...

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2009 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2009

作者： Wandekokem, E.D. Rauber, T.W. Varej˜ao, F.M. Batista, R.J. Department of Computer Science Technology Center Federal University of Espírito Santo Av. Fernando Ferrari S/n 29060-970 Vitória ES Brazil Espírito Santo Exploration and Production Business Unit Department of Automation Inspection and Maintenance Engineering Petróleo Brasileiro S.A. PETROBRAS Vitória ES Brazil

ISBN: (纸本)9781424446827

We present a collection of pattern recognition techniques applied to fault detection and diagnosis of motor pumps. Vibrational patterns are the basis for describing the condition of the process. We rely on the data-driven approach to the learning of the fault classes, i.e. supervised learning in pattern recognition. Our work is motivated by the diversity of the studied defects, the availability of real data from operational oil rigs, and the use of statistical pattern recognition techniques usually not explored sufficiently in similar works. We show the results of automatic methods to define, select and combine features that describe the process and to classify the faults on the provided examples. The support vector machine is chosen as the classification architecture. © 2009 IEEE.

关键词： Fault detection

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