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33rd Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBS 2011

作者： Astolfi, L. Toppi, J. Borghini, G. Vecchiato, G. Isabella, R. De Vico Fallani, F. Cincotti, F. Salinari, S. Mattia, D. He, B. Caltagirone, C. Babiloni, F. Dept. of Computer Science and Systems Univ. of Rome Sapienza IRCCS Fondazione Santa Lucia Rome Italy Direzione Generale della Sanit Militare Rome Italy Department of Biomedical Engineering University of Minnesota Minneapolis MN United States Fondazione S.Lucia University of Rome Tor Vergata Rome Italy Dept. of Physiology and Pharmacology University of Rome Sapienza IRCCS Fondazione Santa Lucia Rome Italy

ISBN: (纸本)9781424441211

Brain Hyperscanning, i.e. the simultaneous recording of the cerebral activity of different human subjects involved in interaction tasks, is a very recent field of Neuroscience aiming at understanding the cerebral processes generating and generated by social interactions. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects, and, even more interestingly, of the functional links existing between the activities in the brains of the subjects interacting together. In this EEG hyperscanning study we explored the functional hyperconnectivity between the activity in different scalp sites of couples of Civil Aviation Pilots during different phases of a flight reproduced in a flight simulator. Results shown a dense network of connections between the two brains in the takeoff and landing phases, when the cooperation between them is maximal, in contrast with phases during which the activity of the two pilots was independent, when no or quite few links were shown. These results confirms that the study of the brain connectivity between the activity simultaneously acquired in human brains during interaction tasks can provide important information about the neural basis of the spirit of the group. © 2011 IEEE.

关键词： Brain

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Study of the Functional Hyperconnectivity between Couples of Pilots during Flight Simulation: an EEG Hyperscanning Study

Study of the Functional Hyperconnectivity between Couples of...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： L. Astolfi J. Toppi G. Borghini G. Vecchiato R. Isabella F. De Vico Fallani F. Cincotti S. Salinari D. Mattia B. He C. Caltagirone F. Babiloni Dept. of Computer Science and Systems Univ. of Rome "Sapienza" Dept. of Computer Science and Systems of the Univ. of Rome "Sapienza" and IRCCS "Fondazione Santa Lucia" Fondazione Santa Lucia Dept. of Physiology and Pharmacology of the University of Rome "Sapienza" and IRCCS "Fondazione Santa Lucia" Direzione Generale della Sanita Militare Department of Biomedical Engineering University of Minnesota Fondazione S.Lucia and University of Rome "Tor Vergata"

ISBN: (纸本)9781424441211

关键词： Pilots Flight simulation Spouses Cerebrum brain activity Brain Connectivity flight coupling Electroencephalography human subject

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Mobile nursing cart with software defined radio for healthcare enterprises

Mobile nursing cart with software defined radio for healthca...

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IEEE Region 10 International Conference TENCON

作者： Chi-Hang Hsu Sung-Huai Hsieh Jun-Teng Hsu Po-Hsun Cheng Sao-Jie Chen Fei-pei Lai Dept. of Computer Science and Information Engineering Providence University Taichung Taiwan Department of Software Engineering National Kaohsiung Normal University Kaohsiung Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan

ISBN: (纸本)9781457702563

Ubiquitous tele-care (u-Telecare) is a migration from tele-health and mobile health (m-Health) for continuous care. The u-Telecare is quite adaptable in the user environment which owns specific attributes, such as telecommunication, highly mobility, and medical care. Based on the preliminary survey and evaluation, some innovative software applications can support mobile nursing carts (MNC) for nurses, handheld devices for physicians, hospice care for terminal cancer patients, and home care devices for chronic diabetic patients. The research findings discovered that software defined radio (SDR) is a feasible solution and can be implemented for handling the physical layer of the multi-wireless communication standards. In this paper, we propose an ubiquitous seamless MNC (u-SMNC), which provides agile and high quality software focusing on the design and application implementation in order to supply an experimental software platform that allows MNCs and physician's handheld devices.

关键词： Mobile communication Software Hospitals Educational institutions Personal digital assistants

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Nonlinear Control of Large Scale Complex Systems Using Convex Optimization Tools and Self-Adaptation

Nonlinear Control of Large Scale Complex Systems Using Conve...

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IEEE Conference on Decision and Control

作者： S. Baldi E. B. Kosmatopoulos K. Aboudolas D. Rovas A. Papachristodoulou P. A. Ioannou Department of Computer Science University of Cyprus Nicosia CY 1678 Cyprus Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi 67100 Greece Informatics & Telematics Institute Center for Research and Technology-Hellas (ITI-CERTH) 6th km Xarilaou - Thermi 57001 Thessaloniki Greece Dept. of Production & Management Engineering Technical University of Crete Chania 73100 Greece Department of Engineering Science University of Oxford Parks Road Oxford OX1 3PJ U.K.

ISBN: (纸本)9781612848006

Based on recent advances on convex design for Large-Scale Control Systems (LSCSs) and robust and efficient LSCS self-tuning/adaptation, a methodology is proposed in this paper which aims at providing an integrated LSCS-design, applicable to large-scale systems of arbitrary scale, heterogeneity and complexity and capable of: 1) Providing stable, efficient and arbitrarily-close-to-optimal LSCS performance;2) Being able to incorporate a variety of constraints, including limited control constraints as well as constraints that are nonlinear functions of the system controls and states;3) Being intrinsically self-tunable, able to rapidly and efficiently optimize LSCS performance when short-, medium- or long-time variations affect the large-scale system;4) Achieving the above, while being scalable and modular. The purpose of the present paper is to provide the main features of the proposed control design methodology.

关键词： Approximation methods Optimization Vectors Symmetric matrices Optimal control Equations

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Bayesian mixed-effects inference on classification performance in hierarchical data sets

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2012年第1期13卷

作者： Kay H. Brodersen Christoph Mathys Justin R. Chumbley Jean Daunizeau Cheng Soon Ong Joachim M. Buhmann Klaas E. Stephan Machine Learning Lab. Dept. of Comp. Sci. ETH Zurich Switzerland and Lab. for Social and Neural Systems Res. Dept. of Economics Univ. of Zurich Zurich Switzerland and Translational Neuromodeling Unit Inst. for Biomed. Eng. ETH Zurich and Univ. of Zurich Zurich Switzerland Laboratory for Social and Neural Systems Research Department of Economics University of Zurich Zurich Switzerland and Translational Neuromodeling Unit Institute for Biomedical Engineering ETH Zurich & University of Zurich Zurich Switzerland Laboratory for Social and Neural Systems Research Department of Economics University of Zurich Zurich Switzerland Machine Learning Laboratory Department of Computer Science ETH Zurich Zurich Switzerland Lab. for Social and Neural Sys. Res. Dept. of Economics Univ. of Zurich Switzerland Wellcome Trust Centre for Neuroimaging Univ. College London London United Kingdom and Translational Neuromodeling Unit Inst. for Biomedical Eng. ETH Zurich and Univ. of Zurich Zurich Switzerland

Classification algorithms are frequently used on data with a natural hierarchical structure. For instance, classifiers are often trained and tested on trial-wise measurements, separately for each subject within a group. One important question is how classification outcomes observed in individual subjects can be generalized to the population from which the group was sampled. To address this question, this paper introduces novel statistical models that are guided by three desiderata. First, all models explicitly respect the hierarchical nature of the data, that is, they are mixed-effects models that simultaneously account for within-subjects (fixed-effects) and across-subjects (random-effects) variance components. Second, maximum-likelihood estimation is replaced by full Bayesian inference in order to enable natural regularization of the estimation problem and to afford conclusions in terms of posterior probability statements. Third, inference on classification accuracy is complemented by inference on the balanced accuracy, which avoids inflated accuracy estimates for imbalanced data sets. We introduce hierarchical models that satisfy these criteria and demonstrate their advantages over conventional methods usingMCMC implementations for model inversion and model selection on both synthetic and empirical data. We envisage that our approach will improve the sensitivity and validity of statistical inference in future hierarchical classification studies.

关键词： Bayesian inference balanced accuracy beta-binomial group studies normal-binomial

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Intelligent operating conditions design by means of bio-inspired models

Intelligent operating conditions design by means of bio-insp...

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： José R. Villar Javier Sedano Emilio Corchado Vicente Vera Beatriz Hernando Raquel Redondo Computer Science Department University of Oviedo Gijón Spain Informatics and Automatica Department University of Salamanca Salamanca Spain Odontology Faculty Universidad Complutense of Madrid Madrid Spain Dept. of A.I. & Applied Electronics Castilla y León Technological Institute (ITCL) Burgos Spain Department of Civil Engineering University of Burgos Burgos Spain

This study presents a novel hybrid intelligent system, which focuses on the optimisation of machine parameters for dental milling purposes. The basis of this approach is hybridizing two bio-inspired algorithms, as Neural Networks with Genetic Algorithms for choosing and modelling the feature subset that best descript the operation conditions. These operating conditions are given as parameters for a dental drill machine. The aim of this approach is twofold: a feature selection process is carried out while the modelling of the operating conditions is achieved. The reliability of the proposed novel hybrid system is validated with a real industrial use case, based on the optimisation of a high-precision machining centre with five axes for dental milling purposes.

关键词： Artificial neural networks Genetic algorithms Computational modeling Data models Biological system modeling Manufacturing Dentistry

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Run-time optimizations for replicated dataflows on heterogeneous environments 10

Run-time optimizations for replicated dataflows on heterogen...

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Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

作者： Teodoro, George Hartley, Timothy D.R. Catalyurek, Umit Ferreira, Renato Dept. of Computer Science Universidade Federal de Minas Gerais Brazil Dept. of Biomedical Informatics Ohio State University United States Dept. of Electrical and Computer Engineering Ohio State University United States

ISBN: (纸本)9781605589428

The increases in multi-core processor parallelism and in the flexibility of many-core accelerator processors, such as GPUs, have turned traditional SMP systems into hierarchical, heterogeneous computing environments. Fully exploiting these improvements in parallel system design remains an open problem. Moreover, most of the current tools for the development of parallel applications for hierarchical systems concentrate on the use of only a single processor type (e.g., accelerators) and do not coordinate several heterogeneous processors. Here, we show that making use of all of the heterogeneous computing resources can significantly improve application performance. Our approach, which consists of optimizing applications at run-time by efficiently coordinating application task execution on all available processing units is evaluated in the context of replicated dataflow applications. The proposed techniques were developed and implemented in an integrated run-time system targeting both intra- and inter-node parallelism. The experimental results with a real-world complex biomedical application show that our approach nearly doubles the performance of the GPU-only implementation on a distributed heterogeneous accelerator cluster. Copyright 2010 ACM.

关键词： Hierarchical systems

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Corrigendum to “Text-independent speaker verification using ant colony optimization-based selected features” [Expert Systems with Applications 38 (1) (2011) 620–630]

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Expert Systems with Applications 2011年第4期38卷 4658-4658页

作者： Shahla Nemati Reza Boostani Mohammad Davarpanah Jazi Mehdi Hosseinzadeh Aghdam Ehsan Basiri Computer Department Faculty of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Biomedical Engineering Group CSE & IT Department Faculty of Electrical and Computer Engineering Shiraz University Shiraz Iran Computer Dept. Faculty of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Computer Engineering Faculty Iran University of Science and Technology Tehran Iran Computer Engineering Dept. University of Isfahan Isfahan Iran

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Markov Clustering of protein interaction networks with improved balance and scalability 10

Markov Clustering of protein interaction networks with impro...

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Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology

作者： Satuluri, Venu Parthasarathy, Srinivasan Ucar, Duygu Dept. of Computer Science and Engineering Ohio State University United States Department of Internal Medicine and Biomedical Engineering University of Iowa United States

ISBN: (纸本)9781450304382

Markov Clustering (MCL) is a popular algorithm for clustering networks in bioinformatics such as protein-protein interaction networks and protein similarity networks. An important requirement when clustering protein networks is minimizing the number of big clusters, since it is generally understood that protein complexes tend not to have more than 15-30 nodes. Similarly, it is important to not output too many singleton clusters, since they do not provide much useful information. In this paper, we show how MCL may be modified so as to better respect these two requirements, while also taking the link structure in the graph into account. We design our algorithm on top of Regularized MCL (R-MCL) [16], a previously proposed modification of MCL. Our proposed variation computes a new regularization matrix at each iteration that penalizes big cluster sizes, with the size of the penalty being tunable using a balance parameter. This algorithm also naturally fits in a Multi level framework that allows great improvements in speed. We perform experiments on three real protein interaction networks and show significant improvements over MCL in quality, balance and execution speed. Copyright 2010 ACM.

关键词： Proteins

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Skull-based registration of intra-subject CT images: The effects of different resolutions and partial contents

Skull-based registration of intra-subject CT images: The eff...

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2010 International Conference on Bioinformatics and biomedical Technology, ICBBT 2010

作者： Liao, Yuan-Lin Sun, Yung-Nien Lu, Chia-Feng Wu, Yu-Te Wu, Chieh-Tsai Lee, Shih-Tseng Lee, Jiann-Der Dept. of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Dept. of Biomedical Imaging and Radiological Sciences National Yang-Ming University Taipei Taiwan Medical Augmented Reality Research Center Chang Gung University Taoyuan Taiwan Department of Electrical Engineering Chang Gung University Taoyuan Taiwan

ISBN: (纸本)9781424467761

The performance of a skull-based image registration is assessed for aligning intra-subject computed tomography (CT) images. Images with six levels of resolution are provided. The images with coarser resolution are resampled, followed by thresholding all images to extract the skull as the matching feature. Using the finest image as the reference, the skull-based registration is processed with sum of squared difference (SSD) criterion. In addition, images with partial contents are simulated and served as the floating image to investigate the interaction between different levels of resolution and partial contents. We conclude that a successful registration requires that more than half of the content should be preserved and the differences of image resolution between two images should be less than 16 times. © 2010 IEEE.

关键词： Image registration

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