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Sleep stage classification using advanced intelligent methods 1

12th International Work-Conference on Artificial Neural Networks, IWANN 2013

作者： Pascualvaca, José Manuel Sánchez Fernandes, Carlos Guillén, Alberto Mora, Antonio M. Largo, Rogerio Rosa, Agostinho C. Herrera, Luis Javier Department of Computer Architecture and Technology University of Granada Granada Spain ISR-IST Laseeb Av. Rovisco Pais 1049-001 Lisbon Portugal

ISBN: (数字)9783642386794

ISBN: (纸本)9783642386787

Manual sleep stage classification is a tedious process that takes a lot of time to sleep experts performing data analysis or studies on this field. Moreover errors and inconsistencies between classifications of the same data are frequent. Due to this, there is a great need of automatic classification systems to support reliable classification. This work extends the work by Herrera et al. (International Journal of Neural Systems 10.1142/ S0129065713500123), inspecting the use of two techniques to improve the accuracy of sleep stage classifiers based on support vector machines from electroencephalogram, electrooculogram and electromyogram signals. Moreover, three different support vector machine multi-classifiers have been tested to evaluate and compare their performance. To accomplish these tasks, three different feature extraction techniques are applied to the electroencephalogram signals. First, the joint use of these feature sets, together with the electrooculogram and electromyogram information, is inspected (and compared with the use of each feature extraction method separately). Second the possibility of using nearby stages information to predict the current stage is inspected. Results obtained show significant improvements in the classification rates achieved using the two proposed techniques. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Electroencephalography

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Modeling the competence acquiring process in higher education institution

Modeling the competence acquiring process in higher educatio...

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7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013

作者： Malinowska, Magdalena Kusztina, Emma Zaikin, Oleg Reng, Lars Kofoed, Lise Busk Zylawski, Andrzej Faculty of Management and Economics of Services University of Szczecin Szczecin Poland Faculty of Computer Science and Information Technology Szczecin University of Technology Szczecin Poland Warsaw School of Computer Science Warszawa Poland Department of Architecture Design and Media Technology Aalborg University Denmark

ISBN: (纸本)9783902823359

Changes in human capital management, new requirements regarding knowledge and skills of employees compel higher education institutions to redefine their learning programmes. This requires evaluation of the didactic process realization, which should be oriented on competences. In the article authors presents an approach to competence modeling. New tools and collaboration mechanisms are proposed, which allow defining the structure of competence, analyzing the level of competence development, and assessing the competence process realization in relation "expected benefit-required expense". © IFAC.

关键词： Knowledge based systems

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Classification of MRI Images for Alzheimer's Disease Detection

Classification of MRI Images for Alzheimer's Disease Detecti...

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IEEE International Conference on Social Computing (SocialCom)

作者： Luis Javier Herrera Ignacio Rojas H. Pomares A. Guillén O. Valenzuela O. Baños Computer Architecture and Computer Technology Department University of Granada Granada Spain

ISBN: (纸本)9781479915194

Alzheimer's Disease (AD) is normally identified by several behavioral symptoms often mistakenly associated to age-related concerns or stress. However correct diagnosis and monitoring of the disease requires of additional resources. This paper presents a new methodology for classification of Alzheimer's disease from MR images for medical support. A large database with more than one thousand patients was used. Two different problems are tackled in this work: a first one where a classification method is developed to classify MR images as either normal or with the Alzheimer's disease and a second one for the identification and classification between normal subjects, MCI patients and AD patients. It is noteworthy that with this last study we could offer a tool to assist the early diagnosis of dementia. The outline of the methodology includes wavelet feature extraction from the MRIs, dimensionality reduction, training-test subdivision and classification using Support Vector Machines. Some concerns related to performance evaluation and dimensionality reduction are discussed.

关键词： Principal component analysis Feature extraction Alzheimer's disease Support vector machines Wavelet transforms Atrophy

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SEARCH for HIGH-ENERGY NEUTRINOS from BINARY NEUTRON STAR MERGER GW170817 with ANTARES, ICECUBE, and the PIERRE AUGER OBSERVATORY

arXiv

引用

arXiv 2017年

作者： Albert, A. André, M. Anghinolfi, M. Ardid, M. Aubert, J.-J. Aublin, J. Avgitas, T. Baret, B. Barrios-Martí, J. Basa, S. Belhorma, B. Bertin, V. Biagi, S. Bormuth, R. Bourret, S. Bouwhuis, M.C. Brânzaş, H. Bruijn, R. Brunner, J. Busto, J. Capone, A. Caramete, L. Carr, J. Celli, S. Cherkaoui El Moursli, R. Chiarusi, T. Circella, M. Coelho, J.A.B. Coleiro, A. Coniglione, R. Costantini, H. Coyle, P. Creusot, A. Díaz, A.F. Deschamps, A. de Bonis, G. Distefano, C. Di Palma, I. Domi, A. Donzaud, C. Dornic, D. Drouhin, D. Eberl, T. El Bojaddaini, I. El Khayati, N. Elsässer, D. Enzenhöfer, A. Ettahiri, A. Fassi, F. Felis, I. Fusco, L.A. Gay, P. Giordano, V. Glotin, H. Grégoire, T. Gracia Ruiz, R. Graf, K. Hallmann, S. van Haren, H. Heijboer, A.J. Hello, Y. Hernández-Rey, J.J. Hössl, J. Hofestädt, J. Illuminati, G. James, C.W. de Jong, M. Jongen, M. Kadler, M. Kalekin, O. Katz, U. Kiessling, D. Kouchner, A. Kreter, M. Kreykenbohm, I. Kulikovskiy, V. Lachaud, C. Lahmann, R. Lefèvre, D. Leonora, E. Lotze, M. Loucatos, S. Marcelin, M. Margiotta, A. Marinelli, A. Martínez-Mora, J.A. Mele, R. Melis, K. Michael, T. Migliozzi, P. Moussa, A. Navas, S. Nezri, E. Organokov, M. Pavălăş, G.E. Pellegrino, C. Perrina, C. Piattelli, P. Popa, V. Pradier, T. Quinn, L. Racca, C. Riccobene, G. Sánchez-Losa, A. Saldaña, M. Salvadori, I. Samtleben, D.F.E. Sanguineti, M. Sapienza, P. Schüssler, F. Sieger, C. Spurio, M. Stolarczyk, T.H. Taiuti, M. Tayalati, Y. Trovato, A. Turpin, D. Tönnis, C. Vallage, B. van Elewyck, V. Versari, F. Vivolo, D. Vizzoca, A. Wilms, J. Zornoza, J.D. Zúñiga, J. Aartsen, M.G. Ackermann, M. Adams, J. Aguilar, J.A. Ahlers, M. Ahrens, M. Al Samarai, I. Altmann, D. Andeen, K. Anderson, T. Ansseau, I. Anton, G. Argüelles, C. Auffenberg, J. Axani, S. Bagherpour, H. Bai, X. Barron, J.P. Barwick, S.W. Baum, V. Bay, R. Beatty, J.J. Becker Tjus, J. Becker, K.-H. Benzvi, S. Berley, D. GRPHE Université de Haute Alsace Institut Universitaire de Technologie de Colmar 34 rue du Grillenbreit BP 50568 Colmar68008 France Technical University of Catalonia Laboratory of Applied Bioacoustics Rambla Exposició Vilanova i la Geltrú Barcelona08800 Spain INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Universitat Politècnica de València C/ Paranimf 1 Gandia46730 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France APC Univ Paris Diderot CNRS IN2P3 CEA Irfu Obs de Paris Sorbonne Paris Cité France c/ Catedrático José Beltrán 2 Paterna ValenciaE-46980 Spain LAM - Laboratoire d’Astrophysique de Marseille Pôle de l’Étoile Site de Château-Gombert rue Frédéric Joliot-Curie 38 Marseille Cedex 1313388 France National Center for Energy Sciences and Nuclear Techniques B.P.1382 RabatR. P.10001 Morocco Via S. Sofia 62 Catania95123 Italy Nikhef Science Park Amsterdam Netherlands Huygens-Kamerlingh Onnes Laboratorium Universiteit Leiden Netherlands Institute of Space Science Mağurele BucharestRO-077125 Romania Universiteit van Amsterdam Instituut voor Hoge-Energie Fysica Science Park 105 Amsterdam1098 XG Netherlands INFN Sezione di Roma P.le Aldo Moro 2 Roma00185 Italy Dipartimento di Fisica Università La Sapienza P.le Aldo Moro 2 Roma00185 Italy Gran Sasso Science Institute Viale Francesco Crispi 7 L’Aquila00167 Italy University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco INFN Sezione di Bologna Viale Berti-Pichat 6/2 Bologna40127 Italy INFN Sezione di Bari Via E. Orabona 4 Bari70126 Italy Department of Computer Architecture and Technology CITIC University of Granada Granada18071 Spain Géoazur UCA CNRS IRD Observatoire de la Côte d’Azur Sophia Antipolis France Dipartimento di Fisica dell’Università Via Dodecaneso 33 Genova16146 Italy Université Paris-Sud Orsay Cedex91405 France Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Cent

The Advanced LIGO and Advanced Virgo observatories recently discovered gravitational waves from a binary neutron star inspiral. A short gamma-ray burst (GRB) that followed the merger of this binary was also recorded by the Fermi Gamma-ray Burst Monitor (Fermi-GBM), and the Anticoincidence Shield for the Spectrometer for the International Gamma-Ray Astrophysics Laboratory (INTEGRAL), indicating particle acceleration by the source. The precise location of the event was determined by optical detections of emission following the merger. We searched for high-energy neutrinos from the merger in the GeV–EeV energy range using the ANTARES, IceCube, and Pierre Auger Observatories. No neutrinos directionally coincident with the source were detected within ±500 s around the merger time. Additionally, no MeV neutrino burst signal was detected coincident with the merger. We further carried out an extended search in the direction of the source for high-energy neutrinos within the 14-day period following the merger, but found no evidence of emission. We used these results to probe dissipation mechanisms in relativistic outflows driven by the binary neutron star merger. The non-detection is consistent with model predictions of short GRBs observed at a large off-axis angle. Copyright © 2017, The Authors. All rights reserved.

关键词： Gravity waves

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User Identification Based on Multiple Attribute Decision Making in Social Networks

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China Communications 2013年第12期10卷 37-49页

作者：叶娜张银亮董丽丽边根庆 Enjie LIU Gordon J.Clapworthy School of Electronic and Information Engineering Xi'an Jiaotong University School of Information and Control Engineering Xi'an University of Architecture and Technology Department of Computer Science and Technology University of Bedfordshire

Social networks are becoming increasingly popular and influential,and users are frequently registered on multiple networks simultaneously,in many cases leaving large quantities of personal information on each *** is also a trend towards the personalization of web applications;to do this,the applications need to acquire information about the particular *** maximise the use of the various sets of user information distributed on the web,this paper proposes a method to support the reuse and sharing of user profiles by different applications,and is based on user profile *** realize this goal,the initial task is user identification,and this forms the focus of the current paper.A new user identification method based on Multiple Attribute Decision Making(MADM) is described in which a subjective weight-directed objective weighting,which is obtained from the Similarity Weight method,is proposed to determine the relative weights of the common *** Synthetic Evaluation is used to determine the equivalence of *** results show that the method is both feasible and effective despite the incompleteness of the candidate user dataset.

关键词： weighted algorithm fuzzy match-ing cooperative communication network con-vergence heterogeneous networks

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MULTISCALE DISTILLED SENSING: A SOURCE DETECTION METHOD FOR INFRARED AND RADIO ASTRONOMICAL IMAGES

MULTISCALE DISTILLED SENSING: A SOURCE DETECTION METHOD FOR ...

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IEEE International Conference on Image Processing

作者： Marc Masias Xavier Lladó Marta Peracaula Jordi Freixenet Department of Computer Architecture and Technology University of Girona Girona Spain

ISBN: (纸本)9781479923427

Astronomical images are characterized by having a high component of noise, a non-homogeneous background, and a great number of sources (objects) difficult to identify even by experts. All these factors are especially remarkable in high wavelength images such as infrared and radio. Hence, great efforts have been done to solve the automatic detection of sources in this type of images. In this paper, we propose a new approach based on multiscale decomposition and the recently developed Distilled Sensing method. Their combined use allows the minimization of the complex background effects as well as the highlighting of the sources. The experimental results obtained using public infrared and radio images demonstrate the validity of the approach, detecting a greater number of true sources than the original Distilled Sensing and the well-known SExtractor algorithm.

关键词： Astronomy image processing object detection wavelet transforms Infrared radiation Object detection ASTRONOMY wavelet transforms images Image processing Radio automatic detection

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A scalable approach to column-based low-rank matrix approximation

A scalable approach to column-based low-rank matrix approxim...

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Pi, Yifan Peng, Haoruo Zhou, Shuchang Zhang, Zhihua Institute for Theoretical Computer Science IIIS Tsinghua University Beijing 100084 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Google Inc. Beijing 100084 China College of Computer Science and Technology Zhejiang University Hangzhou 310027 China

ISBN: (纸本)9781577356332

In this paper, we address the column-based low-rank matrix approximation problem using a novel parallel approach. Our approach is based on the divide-and-combine idea. We first perform column selection on submatrices of an original data matrix in parallel, and then combine the selected columns into the final output. Our approach enjoys a theoretical relative-error upper bound. In addition, our column-based low-rank approximation partitions data in a deterministic way and makes no assumptions about matrix coherence. Compared with other traditional methods, our approach is scalable on largescale matrices. Finally, experiments on both simulated and real world data show that our approach is both efficient and effective.

关键词： Matrix algebra

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Numerical analysis of back berm on road engineering with FEM

Numerical analysis of back berm on road engineering with FEM

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2013 4th International Conference on Material and Manufacturing technology, ICMMT 2013

作者： Liu, Jie Qun Wang, Dong Lin Department of Computer Science and Technology Key Lab of Network and Intelligent Information Processing Hefei University Hefei China School of Civil Engineering Anhui Institute of Architecture and Industry Hefei China

ISBN: (纸本)9783037857526

Based on nonlinear finite element method (FEM), the effect of back berm has been systematically studied. It is found that the lateral displacement of embankment could be reduced by back berm effectively, and the stability of embankment increased rapidly with the width of back berm enlarged. There is a critical value of width of back berm, that the stability of embankment is no more increased with the width of back berm enlarged than critical value. © (2013) Trans Tech Publications, Switzerland.

关键词： Safety factor

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Pre-ictal phase detection with SVMs

Pre-ictal phase detection with SVMs

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Julián R. Cózar Vesna Zeljković José Ma González-Linares Nicolás Guil Milena Bojic Ventzeslav Valev Computer Architecture Department University of Málaga Málaga Spain School of Engineering & Computing Sciences New York Institute of Technology Nanjing Campus USA Universidad de Malaga Malaga AndalucÃa ES University Clinic for Internal Diseases Clinical Hospital Center “Dr Dragisa Misovic - Dedinje” Belgrade Republic of Serbia IAPR Fellow School of Computing University of North Florida Florida USA

ISBN: (纸本)9781479951604

Over 50 million persons worldwide are affected by epilepsy. Epilepsy is a brain disorder known for sudden, unexpected transitions from normal to pathological behavioral states called epileptic seizures. Epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. There is a need for a quick screening process that could help neurologist diagnose and determine the patient's treatment. Electroencephalogram has been traditionally used to diagnose patients by evaluating those brain functions that may correspond to epilepsy. The objective of this paper is to implement a novel detection technique of pre-ictal state that announces epileptic seizures from the online EEG data analysis. Unlike most published methods, that are aimed to distinguish only the normal from the epilepsy state, in this work the pre-ictal state is introduced as a new patient status, thus differentiating three possible states: normal (healthy), pre-ictal and epileptic seizure. In this manner, the patient should get timely alert about the possible seizure attack so that she/he can stop with its activities and take safety precautions.

关键词： Electroencephalography Epilepsy Feature extraction Support vector machines Wavelet coefficients Discharges (electric) Educational institutions

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All-flavor search for a diffuse flux of cosmic neutrinos with 9 years of ANTARES data

arXiv

引用

arXiv 2017年

作者： Albert, A. André, M. Anghinolfi, M. Anton, G. Ardid, M. Aubert, J.-J. Aublin, J. Avgitas, T. Baret, B. Barrios-Martí, J. Basa, S. Belhorma, B. Bertin, V. Biagi, S. Bormuth, R. Bourret, S. Bouwhuis, M.C. Brânzaş, H. Bruijn, R. Brunner, J. Busto, J. Capone, A. Caramete, L. Carr, J. Celli, S. El Moursli, R. Cherkaoui Chiarusi, T. Circella, M. Coelho, J.A.B. Coleiro, A. Coniglione, R. Costantini, H. Coyle, P. Creusot, A. Díaz, A.F. Deschamps, A. de Bonis, G. Distefano, C. Di Palma, I. Domi, A. Donzaud, C. Dornic, D. Drouhin, D. Eberl, T. El Bojaddaini, I. El Khayati, N. Elsässer, D. Enzenhöfer, A. Ettahiri, A. Fassi, F. Felis, I. Fusco, L.A. Gay, P. Giordano, V. Glotin, H. Grégoire, T. Ruiz, R. Gracia Graf, K. Hallmann, S. van Haren, H. Heijboer, A.J. Hello, Y. Hernández-Rey, J.J. Hößl, J. Hofestädt, J. Illuminati, G. James, C.W. de Jong, M. Jongen, M. Kadler, M. Kalekin, O. Katz, U. Kießling, D. Kouchner, A. Kreter, M. Kreykenbohm, I. Kulikovskiy, V. Lachaud, C. Lahmann, R. Lefèvre, D. Leonora, E. Lotze, M. Loucatos, S. Marcelin, M. Margiotta, A. Marinelli, A. Martínez-Mora, J.A. Mele, R. Melis, K. Michael, T. Migliozzi, P. Moussa, A. Navas, S. Nezri, E. Organokov, M. Alaş, G.E. Pav Pellegrino, C. Perrina, C. Piattelli, P. Popa, V. Pradier, T. Quinn, L. Racca, C. Riccobene, G. Sánchez-Losa, A. Saldaña, M. Salvadori, I. Samtleben, D.F.E. Sanguineti, M. Sapienza, P. Schüssler, F. Sieger, C. Spurio, M. Stolarczyk, Th. Taiuti, M. Tayalati, Y. Trovato, A. Turpin, D. Tönnis, C. Vallage, B. van Elewyck, V. Versari, F. Vivolo, D. Vizzoca, A. Wilms, J. Zornoza, J.D. Zúñiga, J. GRPHE - Université de Haute Alsace - Institut universitaire de technologie de Colmar 34 rue du Grillenbreit BP Colmar50568 - 68008 France Technical University of Catalonia Laboratory of Applied Bioacoustics Rambla Exposició Vilanova i la Geltrú Barcelona08800 Spain INFN - Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Centre for Astroparticle Physics Erwin-Rommel-Str. 1 Erlangen91058 Germany Universitat Politècnica de València C/ Paranimf 1 Gandia46730 Spain Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France APC Univ Paris Diderot CNRS/IN2P3 CEA/Irfu Obs de Paris Sorbonne Paris Cité France c/ Catedrático José Beltrán 2 PaternaValenciaE-46980 Spain LAM - Laboratoire d’Astrophysique de Marseille Pôle de l’Étoile Site de Château-Gombert rue Frédéric Joliot-Curie 38 Marseille Cedex 1313388 France National Center for Energy Sciences and Nuclear Techniques B.P.1382 R. P. Rabat10001 Morocco Via S. Sofia 62 Catania95123 Italy Nikhef Science Park Amsterdam Netherlands Huygens-Kamerlingh Onnes Laboratorium Universiteit Leiden Netherlands Institute of Space Science Bucharest MagureleRO-077125 Romania Universiteit van Amsterdam Instituut voor Hoge-Energie Fysica Science Park 105 Amsterdam1098 XG Netherlands INFN - Sezione di Roma P.le Aldo Moro 2 Roma00185 Italy Dipartimento di Fisica dell’Università La Sapienza P.le Aldo Moro 2 Roma00185 Italy Gran Sasso Science Institute Viale Francesco Crispi 7 L’Aquila00167 Italy University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 R.P10000 INFN - Sezione di Bologna Viale Berti-Pichat 6/2 Bologna40127 Italy INFN - Sezione di Bari Via E. Orabona 4 Bari70126 Italy Department of Computer Architecture and Technology/CITIC University of Granada Granada18071 Spain Géoazur UCA CNRS IRD Observatoire de la Côte d’Azur Sophia Antipolis France Dipartimento di Fisica dell’Università Via Dodecaneso 33

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