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2013 38th IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2013

作者： Altaf, M. Umair Bin Butko, Taras Juang, Biing-Hwang Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9781479903566

Real world sounds are ubiquitous and form an important part of the edifice of our cognitive abilities. Their perception combines signatures from spectral and temporal domains, among others, yet traditionally their analysis is focused on the frame based spectral properties. We consider the problem of sound analysis from perceptual perspective and investigate the temporal properties of a 'footsteps' sound, which is a particularly challenging from the time-frequency analysis viewpoint. We identify the irregular repetition of the self similarity and the sense of duration as significant to its perceptual quality and extract features using the Teager-Kaiser energy operator. We build an acoustic event detection system for 'footsteps' which shows promising results for detection in cross-environmental conditions when compared with conventional approach. © 2013 IEEE.

关键词： acoustic analysis acoustic signal detection acoustics feature extraction time-frequency analysis

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Person identification using biometric markers from footsteps sound

Person identification using biometric markers from footsteps...

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14th Annual Conference of the International Speech Communication Association, INTERSPEECH 2013

Human identification using unobtrusive methods is a challenging problem that has many applications in surveillance tasks. In this work we propose a set of biometric features extracted from a footstep audio signal that can be used to identify a person. Instead of using short-time spectral domain, Teager-Kaiser energy operator is employed to transform a time-domain signal into a representational domain where the intrinsic properties of the walking style of each individual become apparent. We show that these features are biometrically significant as they are physical correlates of human gait. The experimental results obtained using a recently recorded publicly available database show prominent results in a human identification task. Copyright © 2013 ISCA.

关键词： Biometrics

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Expectation propagation based iterative group wise detection for large-scale multiuser MIMO-OFDM systems

Expectation propagation based iterative group wise detection...

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IEEE Conference on Wireless Communications and Networking

作者： Sheng Wu Linling Kuang Zuyao Ni Jianhua Lu Defeng David Huang Qinghua Guo Shenzhen Key Laboratory of Wireless Broadband Communication and Signal Processing Shenzhen China Department of Electronic Engineering Tsinghua University Beijing China Tsinghua Space Center Tsinghua University Beijing China Research Institute of Information Technology Tsinghua University Beijing China School of Electrical Electronic and Computer Engineering University of Western Australia Australia School of Electrical Computer and Telecommunications Engineering University of Wollongong Australia

For the spatially correlated multiuser MIMO-OFDM channels, the conventional iterative MMSE-SIC detection suffers from a considerable performance loss. In this paper, we use the factor graph framework to design robust detection algorithms by clustering a group of symbols to combat the spatial correlation and using the principle of expectation propagation to improve message passing. Furthermore, as the complexity of detection becomes one of the issues in the design of large-scale multiuser MIMO-OFDM systems, we propose a low-complexity approximate message-passing algorithm by opening the channel transition node, which eliminates the expensive matrix inversions involved in the MMSE-SIC based algorithms. Finally, numerical results are presented to verify the proposed algorithms.

关键词： Complexity theory MIMO Educational institutions Algorithm design and analysis Vectors OFDM Correlation

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On the optimal precoding for MIMO gaussian wire-tap channels

On the optimal precoding for MIMO gaussian wire-tap channels

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10th IEEE International Symposium on Wireless Communication Systems 2013, ISWCS 2013

作者： Khabbazibasmenj, Arash Girnyk, Maksym A. Vorobyov, Sergiy A. Vehkaperä, Mikko Rasmussen, Lars K. Department of Electrical and Computer Engineering University of Alberta AB Canada ACCESS Linnaeus Center KTH Royal Institute of Technology School of Electrical Engineering Sweden Department of Signal Processing and Acoustics School of Electrical Engineering Aalto University Finland

ISBN: (纸本)9783800735297

We consider the problem of finding secrecy rate of a multiple-input multiple-output (MIMO) wire-tap channel. A transmitter, a legitimate receiver, and an eavesdropper are all equipped with multiple antennas. The channel states from the transmitter to the legitimate user and to the eavesdropper are assumed to be known at the transmitter. In this contribution, we address the problem of finding the optimal precoder/transmit covariance matrix maximizing the secrecy rate of the given wiretap channel. The problem formulation is shown to be equivalent to a difference of convex functions programming problem and an efficient algorithm for addressing this problem is developed. © VDE Verlag GMBH.

关键词： Transmitters

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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PERCEPTUALLY MOTIVATED TEMPORAL MODELING OF FOOTSTEPS IN A CROSS-ENVIRONMENTAL DETECTION TASK

PERCEPTUALLY MOTIVATED TEMPORAL MODELING OF FOOTSTEPS IN A C...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： M. Umair Bin Altaf Taras Butko Biing-Hwang (Fred) Juang Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia.

ISBN: (纸本)9781479903573

Real world sounds are ubiquitous and form an important part of the edifice of our cognitive abilities. Their perception combines signatures from spectral and temporal domains, among others, yet traditionally their analysis is focused on the frame based spectral properties. We consider the problem of sound analysis from perceptual perspective and investigate the temporal properties of a "footsteps" sound, which is a particularly challenging from the time-frequency analysis viewpoint. We identify the irregular repetition of the self similarity and the sense of duration as significant to its perceptual quality and extract features using the Teager-Kaiser energy operator. We build an acoustic event detection system for "footsteps" which shows promising results for detection in cross-environmental conditions when compared with conventional approach.

关键词： Temporal modeling HMM Teager-Kaiser operator Acoustic event detection Hidden Markov models Event detection SOUND KCNK3 gene edifices time characteristic Modeling Vibration Hearing signatures

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Erratum to: Methods for evaluating medical tests and biomarkers

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Diagnostic and prognostic research 2017年第1期1卷 11页

作者： Gowri Gopalakrishna Miranda Langendam Rob Scholten Patrick Bossuyt Mariska Leeflang Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Richard Riley Marie Westwood Jos Kleinen Gary Collins Hans Reitsma Karel Moons Antonia Zapf Annika Hoyer Katharina Kramer Oliver Kuss J Ensor J J Deeks E C Martin R D Riley Gerta Rücker Susanne Steinhauser Martin Schumacher Joie Ensor Kym Snell Brian Willis Thomas Debray Jon Deeks Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Jan Verbakel Sabine Van Huffel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O'Sullivan Rafael Perera Brian Nicholson Hannah L Bromley Tracy E Roberts Adele Francis Denniis Petrie G Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Doug Altman William Rosenberg Peter Selby Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Anne Rutjes Johannes Reitsma Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Daan Nieboer Bavo De Cock Micael J Pencina Ewout W Steyerberg Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Andrew Mumford Zoe Plummer Kurtis Lee Barnaby Reeves Chris Rogers Veerle Verheyden Gianni D Angelini Gavin J Murphy Jeremy Huddy Melody Ni Katherine Good Graham Cooke 1Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 2Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands. 234Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 49Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 3Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK. 4EPPI-Centre Department of Social Science University College London London UK. 5Division of Health and Social Care Research King's College London London UK. 6College of Computer and Information Science Northeastern University Boston USA. 13University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK. 275Institute of Applied Health Research University of Birmingham Birmingham UK. 9Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 10School of Social and Community Medicine University of Bristol Bristol UK. 179Institute of Applied Health Research University of Birmingham Birmingham UK. 12Kleijnen Systematic Reviews Ltd York UK. 25Research Institute for Primary Care and Health Sciences Keele University Keele UK. 188Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK. 191Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 237Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 18Department of Medical Statistics University Medical Center Göttingen Göttingen Germany. 19Institute for B

[This corrects the article DOI: 10.1186/s41512-016-0001-y.].

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VESSEL centerLINES EXTRACTION FROM FUNDUS FLUORESCEIN ANGIOGRAM BASED ON HESSIAN ANALYSIS OF DIRECTIONAL CURVELET SUBBANDS

VESSEL CENTERLINES EXTRACTION FROM FUNDUS FLUORESCEIN ANGIOG...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： Asieh Soltanipour Saeed Sadri Hossein Rabbani Mohammadreza Akhlaghi Alimohammad Doost-Hosseini Department of Electrical and Computer Engineering Isfahan University of Technology Department of Biomedical Engineering Medical Image and Signal Processing Research Center Isfahan University of Medical Sciences Ophthalmology Department Isfahan University of Medical Sciences

ISBN: (纸本)9781479903573

This paper presents a novel algorithm for automatic extraction of the blood vessels centerline in Fundus Fluorescein Angiography (FFA) images in different diabetic retinopathy (DR) stages. First, the background normalized images are enhanced by applying a morphological edge detector. Then each of the directional images resulting from curvelet sub-bands is individually processed using Hessian matrix and first order derivative of the directional images information in a multi-scale framework for extracting initial centerline segments. Every resulted candidate segment in previous step is confirmed or rejected based on the length and intensity features and eigenvalues analysis. The final vessels centerline segmentation is obtained by connecting the images subsets in a binary image. The proposed algorithm is tested on 70 FFA images from different DR stages and the performance of method in terms of true positive ratio (TPR) and false positive ratio (FPR) that are obtained .9017 and .0983 respectively.

关键词： Fundus Fluorescein Angiography Curvelet transform Match filter Hessian matrix Eigenvalues analysis

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A two-piece R-D model for hybrid video coding and its application in fast mode decision

A two-piece R-D model for hybrid video coding and its applic...

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2012 13th IEEE International Conference on Multimedia and Expo, ICME 2012

作者： Aminlou, Alireza Fahim-Hashemi, Hana Hashemi, Mahmoud Reza Gabbouj, Moncef Fatemi, Omid Multimedia Processing Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Signal Processing Tampere University of Technology Tampere Finland Viterbi School of Engineering University of Southern California Los Angeles CA United States Nano-Electronic Center of Excellence University of Tehran Tehran Iran

ISBN: (纸本)9781467316590

The mode decision process has a significant effect on the quality and complexity of a video encoder. The conventional method that fully codes each macro block for different modes results in the best quality performance, but it suffers from high computational complexity. On the other hand, some other methods ignore the residual part and use the prediction data, or adopt early mode selection approaches in order to reduce the computational cost. These approaches have a negative impact on the coding performance. In this paper, we have used a simple model for the residual coding part and proposed a two-piece R-D model for a macro block. Based on this model, we have introduced a mode decision algorithm that reduces the bit-rate by up to 11.62% at the expense of just 0.5% computational overhead. © 2012 IEEE.

关键词： Cost reduction

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High-speed SSVEP-based BCI: Study of various frequency pairs and inter-sources distances

High-speed SSVEP-based BCI: Study of various frequency pairs...

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

作者： Seyed Navid Resalat Valiallah Saba Fardin Afdideh Ali Heidarnejad Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran AJA University of Medical Sciences Iran Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering College of Engineering Sharif University of Technology Tehran Iran

Brain computer Interface provides a new communication channel for people who have severe brain injuries. Among different types of BCIs, SSVEP-based one has been focused in recent years. In this type of BCI, selection of twinkling frequency of external visual stimulant and the distance between stimulants (in case of more than one stimulant) is so important. In this work, a SSVEP-based BCI with two external stimulants was designed. In order to determine the best twinkling frequency of stimulants and the best distance between them, the classification accuracy for seven different twinkling frequency pairs and five different stimulants distances was calculated. Two methods for feature extraction step were proposed and the Max classifier was used for classification in order to speed up the computational burden of classification step. Features were extracted from four different segment lengths (sweeps). The results showed that nearly in all sweeps and all inter-sources distances the frequency pair of 10-15 Hz has the highest classification accuracy among other frequency pairs, which is 92% in the inter-sources distance of 24 cm and sweep length of 3 seconds. In addition, the results demonstrated that the method 2 feature extraction technique outperforms the method 1. In addition, for determining the best sweep length, Information Transfer Rate (ITR) was computed and the results indicated that the sweep length of 0.5 second has the highest ITR, so would be practical in real-time applications of BCI.

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