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International Conference on Network-Based Information Systems (NBIS)

作者： Malik Najmus Siraj Nadeem Javaid Qaisar Shafi Zaheer Ahmed Umar Qasim Zahoor Ali Khan Center for Advanced Studies in Engineering (CASE) Islamabad Pakistan Pakistan COMSATS Institute of Information Technology Islamabad Pakistan School of Electrical Engineering and Computer Science (SEECS) NUST Islamabad Pakistan University of Alberta Edmonton AB Canada CIS Higher Colleges of Technology UAE Internetworking Program Dalhousie University Halifax NS Canada

ISBN: (纸本)9781509009800

Increase in traffic over internet by large number of mobile devices results into high energy consumption on network devices. In this paper, we address the necessity to reduce the energy consumption in a campus network that includes both wired and wireless network devices. Specifically, we propose dynamic link rate adaptation mechanism on Software Defined Network (SDN) switches and control power consumption on Access Points (APs) by using users association to an AP. Moreover, our online flow routing approach dynamically routes user traffic in order to decrease the overall energy consumption of whole network while taking in consideration Quality of Service (QoS), acceptance ratio on forwarding table and link BandWidth (BW) constraints. Our simulation result shows that our approach results in 3.69% less power consumption, and furthermore, there is no congested links nor overflow in flow table as compared to Dijkstra Ant colony Power (DAPower) that has 2 congested links for 150 users in a network, each generating 34 flows.

关键词： Power demand Routing Energy consumption Control systems Software Wireless communication Ports (computers)

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Simulation and implementation of solar power battery charger using Perturb & Observe algorithm

Simulation and implementation of solar power battery charger...

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Power Generation System and Renewable Energy Technology (PGSRET)

作者： Jehanzaib Ali Usama Ijaz M. Hasan Khan Niazi M. Shahroze Amer M. Mobeen Younis Waqas Hassan Department of Electrical and Computer Engineering Center for Advanced Studies in Engineering Islamabad Pakistan

As solar energy is a renewable energy that has the capacity to lessen the energy crisis in the world, so there is a strong need to harvest and utilize this energy. Solar power is readily available in the regions like UAE, South Asia, etc. so there is a strong need to implement solar power harvesting techniques to lower the energy crisis. This paper describes the simulation and implementation of a solar energy based MPPT battery charger. The proposed design uses a microcontroller (Arduino Mega 2560 based upon ATmega2560) that works on feedback from a PV panel and voltage of a battery, which is to be charged, and controls the operation of a buck-boost DC-DC converter in order to draw maximum power from the PV panel. Perturb and Observe algorithm is used to operate the circuit at maximum power point irrespective of the present humidity, temperature and irradiance conditions of the PV panel. The battery is used to store the solar power so as to get energy when required and as per use i.e. if AC, then an inverter can be connected after the battery and if DC, then a DC-DC converter can be used according to need. The proposed design is simulated in MATLAB/Simulink and implemented on hardware.

关键词： Batteries Microcontrollers Voltage control Hardware Maximum power point trackers DC-DC power converters Inductors

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Application of pattern spectra and convolutional neural networks to the analysis of simulated Cherenkov Telescope Array data

arXiv

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arXiv 2021年

作者： Aschersleben, Jann Peletier, R.F. Vecchi, M. Wilkinson, M.H.F. Abdalla, H. Abe, H. Abe, S. Abusleme, A. Acero, F. Acharyya, A. Portella, V. Acín Ackley, K. Adam, R. Adams, C. Adhikari, S.S. Aguado-Ruesga, I. Agudo, I. Aguilera, R. Aguirre-Santaella, A. Aharonian, F. Alberdi, A. Alfaro, R. Alfaro, J. Alispach, C. Aloisio, R. Batista, R. Alves Amans, J.-P. Amati, L. Amato, E. Ambrogi, L. Ambrosi, G. Ambrosio, M. Ammendola, R. Anderson, J. Anduze, M. Angüner, E.O. Antonelli, L.A. Antonuccio, V. Antoranz, P. Anutarawiramkul, R. Gutierrez, J. Aragunde Aramo, C. Araudo, A. Araya, M. Arbet-Engels, A. Arcaro, C. Arendt, V. Armand, C. Armstrong, T. Arqueros, F. Arrabito, L. Arsioli, B. Artero, M. Asano, K. Ascasíbar, Y. Ashley, M. Attinà, P. Aubert, P. Singh, C.B. Baack, D. Babic, A. Backes, M. Baena, V. Bajtlik, S. Baktash, A. Balazs, C. Balbo, M. Ballester, O. Ballet, J. Balmaverde, B. Bamba, A. Bandiera, R. Larriva, A. Baquero Barai, P. Barbier, C. Martins, V. Barbosa Barcelo, M. Barkov, M. Barnard, M. Baroncelli, L. de Almeida, U. Barres Barrio, J.A. Bastieri, D. Batista, P.I. Batkovic, I. Bauer, C. Bautista-González, R. Baxter, J. Becciani, U. González, J. Becerra Becherini, Y. Beck, G. Tjus, J. Becker Bednarek, W. Belfiore, A. Bellizzi, L. Belmont, R. Benbow, W. Berge, D. Bernardini, E. Bernardos, M.I. Bernlöhr, K. Berti, A. Berton, M. Bertucci, B. Beshley, V. Bhatt, N. Bhattacharyya, S. Bhattacharyya, W. Bhattacharyya, S. Bi, B. Bicknell, G. Biederbeck, N. Bigongiari, C. Biland, A. Bird, R. Bissaldi, E. Biteau, J. Bitossi, M. Blanch, O. Blank, M. Blazek, J. Bobin, J. Boccato, C. Bocchino, F. Boehm, C. Bohacova, M. Boisson, C. Boix, J. Bolle, J.-P. Bolmont, J. Bonanno, G. Bonavolontà, C. Arbeletche, L. Bonneau Bonnoli, G. Bordas, P. Borkowski, J. Bórquez, S. Bose, R. Bose, D. Bosnjak, Z. Bottacini, E. Böttcher, M. Botticella, M.T. Boutonnet, C. Bouyjou, F. Bozhilov, V. Bozzo, E. Brahimi, L. Braiding, C. Brau-Nogué, S. Breen, S. Kapteyn Astronomical Institute University of Groningen PO Box 800 Groningen9700 AV Netherlands Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen PO Box 407 AK GroningenNL-9700 Netherlands Centre for Space Research North-West University Potchefstroom2520 South Africa Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Pontificia Universidad Católica de Chile Av. Libertador Bernardo O'Higgins 340 Santiago Chile AIM CEA CNRS Université Paris-Saclay Université Paris Diderot Sorbonne Paris Cité CEA Paris-Saclay IRFU/DAp Bat 709 Orme des Merisiers Gif-sur-Yvette91191 France Centre for Advanced Instrumentation Dept. of Physics Durham University South Road DurhamDH1 3LE United Kingdom Port d'Informació Científica Edifici D Carrer de l'Albareda Cerdanyola del Vallès Bellaterrra08193 Spain School of Physics and Astronomy Monash University MelbourneVIC3800 Australia Palaiseau91128 France Department of Physics Columbia University 538 West 120th Street New YorkNY10027 United States University of Oslo Department of Physics Sem Saelandsvei 24 - PO Box 1048 Blindern OsloN-0316 Norway EMFTEL Department IPARCOS Universidad Complutense de Madrid Madrid28040 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Campus UAB Carrer de Can Magrans s/n Cerdanyola del Vallés08193 Spain Instituto de Física Teórica UAM/CSIC Departamento de Física Teórica Universidad Autónoma de Madrid Campus de Cantoblanco UAM c/ Nicolás Cabrera 13-15 Madrid28049 Spain Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Universidad Nacional Autónoma de México Delegación Coyoacán Ciudad de México04510 Mexico University of Geneva Département de Physique Nucléaire et Corpusculaire 24 rue du Général-Dufour Genève 41211 Switzerland INFN Dipartimento di Scienze Fisiche e Chimiche Università

The Cherenkov Telescope Array (CTA) will be the next generation gamma-ray observatory and will be the major global instrument for very-high-energy astronomy over the next decade, offering 5 - 10 × better flux sensitivity than current generation gamma-ray telescopes. Each telescope will provide a snapshot of gamma-ray induced particle showers by capturing the induced Cherenkov emission at ground level. The simulation of such events provides images that can be used as training data for convolutional neural networks (CNNs) to determine the energy of the initial gamma rays. Compared to other state-of-the-art algorithms, analyses based on CNNs promise to further enhance the performance to be achieved by CTA. Pattern spectra are commonly used tools for image classification and provide the distributions of the shapes and sizes of various objects comprising an image. The use of relatively shallow CNNs on pattern spectra would automatically select relevant combinations of features within an image, taking advantage of the 2D nature of pattern spectra. In this work, we generate pattern spectra from simulated gamma-ray events instead of using the raw images themselves in order to train our CNN for energy reconstruction. This is different from other relevant learning and feature selection methods that have been tried in the past. Thereby, we aim to obtain a significantly faster and less computationally intensive algorithm, with minimal loss of performance. © 2021, CC BY.

关键词： Gamma rays

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Robust control of a customized robotic arm with unstructured uncertainties

Robust control of a customized robotic arm with unstructured...

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International Conference on Emerging Technologies, ICET

作者： Tayyaba Qaisar A. Mahmood Department of Electrical Engineering Bahria University Islamabad Pakistan Department of Electrical and Computer Engineering Center for Advanced Studies in Engineering Islamabad

Owing to the recent advancement in the field of `Robotics', the use of robots can now be modified to fit our own requirements. A potential field of expansion in this domain is the design and implementation of prosthetic limbs. In this paper we discuss the robust control of a customized robotic gripper arm. We also incorporate unstructured uncertainties and analyze responses of both H 2 and H ∞ compensators. This comparison show the advantage of integrating the aforementioned compensators on system stability.

关键词： Uncertainty Service robots Robustness Mathematical model Grippers Stability analysis

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Erratum to: Search for heavy Higgs bosons decaying to a top quark pair in proton-proton collisions at s = 13 TeV

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Journal of High Energy Physics 2022年第3期2022卷 1-21页

作者： Sirunyan, A. M. Tumasyan, A. Adam, W. Ambrogi, F. Bergauer, T. Brandstetter, J. Dragicevic, M. Erö, J. Escalante Del Valle, A. Flechl, M. Frühwirth, R. Jeitler, M. Krammer, N. Krätschmer, I. Liko, D. Madlener, T. Mikulec, I. Rad, N. Schieck, J. Schöfbeck, R. Spanring, M. Spitzbart, D. Waltenberger, W. Wulz, C.-E. Zarucki, M. Drugakov, V. Mossolov, V. Suarez Gonzalez, J. Darwish, M. R. De Wolf, E. A. Di Croce, D. Janssen, X. Lauwers, J. Lelek, A. Pieters, M. Rejeb Sfar, H. Van Haevermaet, H. Van Mechelen, P. Van Putte, S. Van Remortel, N. Blekman, F. Bols, E. S. Chhibra, S. S. D’Hondt, J. De Clercq, J. Lontkovskyi, D. Lowette, S. Marchesini, I. Moortgat, S. Moreels, L. Python, Q. Skovpen, K. Tavernier, S. Van Doninck, W. Van Mulders, P. Van Parijs, I. Beghin, D. Bilin, B. Brun, H. Clerbaux, B. De Lentdecker, G. Delannoy, H. Dorney, B. Favart, L. Grebenyuk, A. Kalsi, A. K. Luetic, J. Popov, A. Postiau, N. Starling, E. Thomas, L. Vander Velde, C. Vanlaer, P. Vannerom, D. Cornelis, T. Dobur, D. Khvastunov, I. Niedziela, M. Roskas, C. Trocino, D. Tytgat, M. Verbeke, W. Vermassen, B. Vit, M. Zaganidis, N. Bondu, O. Bruno, G. Caputo, C. David, P. Delaere, C. Delcourt, M. Giammanco, A. Lemaitre, V. Magitteri, A. Prisciandaro, J. Saggio, A. Vidal Marono, M. Vischia, P. Zobec, J. Alves, F. L. Alves, G. A. Correia Silva, G. Hensel, C. Moraes, A. Rebello Teles, P. Belchior Batista Das Chagas, E. Carvalho, W. Chinellato, J. Coelho, E. Da Costa, E. M. Da Silveira, G. G. De Jesus Damiao, D. De Oliveira Martins, C. Fonseca De Souza, S. Huertas Guativa, L. M. Malbouisson, H. Martins, J. Matos Figueiredo, D. Medina Jaime, M. Melo De Almeida, M. Mora Herrera, C. Mundim, L. Nogima, H. Prado Da Silva, W. L. Sanchez Rosas, L. J. Santoro, A. Sznajder, A. Thiel, M. Tonelli Manganote, E. J. Torres Da Silva De Araujo, F. Vilela Pereira, A. Ahuja, S. Bernardes, C. A. Calligaris, L. Fernandez Perez Tomei, T. R. Gregores, E. M. Lemos, D. S. Mercadante, P. G. Novaes, S. F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Vienna University of Technology Vienna Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Federal de Pelotas Pelotas Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of NRC ‘Kurchatov Institute’ Moscow Russia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Joint Institute for Nuclear Research Dubna Russia Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Cairo University Cairo Egypt Academy of Scientific Research and Technolog

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Erratum to: Search for dark matter produced in association with a leptonically decaying Z boson in proton–proton collisions at s = 13 Te

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The European Physical Journal C 2021年第4期81卷 1-16页

作者： A. M. Sirunyan A. Tumasyan W. Adam T. Bergauer M. Dragicevic J. Erö A. Escalante Del Valle R. Frühwirth M. Jeitler N. Krammer L. Lechner D. Liko T. Madlener I. Mikulec F. M. Pitters N. Rad J. Schieck R. Schöfbeck M. Spanring S. Templ W. Waltenberger C.-E. Wulz M. Zarucki V. Chekhovsky A. Litomin V. Makarenko J. Suarez Gonzalez M. R. Darwish E. A. De Wolf D. Di Croce X. Janssen T. Kello A. Lelek M. Pieters H. Rejeb Sfar H. Van Haevermaet P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols S. S. Chhibra J. D’Hondt J. De Clercq D. Lontkovskyi S. Lowette I. Marchesini S. Moortgat A. Morton Q. Python S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker B. Dorney L. Favart A. Grebenyuk A. K. Kalsi I. Makarenko L. Moureaux L. Pétré A. Popov N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom L. Wezenbeek T. Cornelis D. Dobur M. Gruchala I. Khvastunov M. Niedziela C. Roskas K. Skovpen M. Tytgat W. Verbeke B. Vermassen M. Vit G. Bruno F. Bury C. Caputo P. David C. Delaere M. Delcourt I. S. Donertas A. Giammanco V. Lemaitre K. Mondal J. Prisciandaro A. Taliercio M. Teklishyn P. Vischia S. Wuyckens J. Zobec G. A. Alves C. Hensel A. Moraes W. L. Aldá Júnior E. Belchior Batista Das Chagas H. BRANDAO MALBOUISSON W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza J. Martins D. Matos Figueiredo M. Medina Jaime C. Mora Herrera L. Mundim H. Nogima P. Rebello Teles L. J. Sanchez Rosas A. Santoro S. M. Silva Do Amaral A. Sznajder M. Thiel F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov G. Antchev I. Atanasov R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov M. Bonchev A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov W. Fang Q. Guo H. Wang L. Yuan M. Ahmad Z. Hu Y. Wang E. Chapon G. M. Chen H. S. Chen M. Chen A. Kapoor D. Leggat H. Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Vienna University of Technology Vienna Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Department of Basic and Applied Sciences Faculty of Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Université Libre de Bruxelles Bruxelles Belgium Vrije Universiteit Brussel Brussel Belgium Ghent University Ghent Belgium IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Federal de Pelotas Pelotas Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of NRC ‘K

A Correction to this paper has been published: https://***/10.1140/epjc/s10052-020-08739-5

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Review of OCT and fundus images for detection of Macular Edema

Review of OCT and fundus images for detection of Macular Ede...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Taimur Hassan M. Usman Akram Bilal Hassan Ammara Nasim Shafaat Ahmed Bazaz Department of Electrical Engineering Bahria University Islamabad Pakistan Department of Computer Engineering National University of Science and Technology Rawalpindi Pakistan Department of Electrical Engineering University of Engineering & Technology Taxila Pakistan Department of Computer Science Center for Advanced Studies in Engineering Islamabad Pakistan

Macula is an oval shaped area near the center of human retina that covers the area of 5500 microns and at its center, there is a small pit known as fovea with the diameter of 1500 microns. Macular disorders involve group of diseases that damages macula resulting in blindness or vision loss. Macular Edema `ME' is the most common disease related to macula. The symptoms for this disease usually appear in final stages to patient when it is very difficult to cure it and at that time it causes severe damage to central vision. However if it is detected in early stages then it can be easily cured. Different techniques that are used to detect ME are Fundus Photography (also known as Fundography), Fundus Fluorescein Angiography `FFA' and Optical Coherence Tomography `OCT'. Earlier, Fundography was the most widely used test to detect ME. But now a days OCT is being widely used for detecting ME due to its ability to detect small changes in sub-retinal layers. In this paper, we present a detailed comparison between Fundography and OCT imaging technology for the detection of Macular Edema using our own dataset provided to us by Armed Forces Institute of Ophthalmology (AFIO) Rawalpindi. Total 64 patients were studied in this experiment by examining their fundus and OCT images where 15 patients had ME while 49 were healthy persons. OCT images provide an objective evaluation of early macular edema as compared to Fundography.

关键词： Retina Diabetes Optical imaging Coherence Diseases Photography

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Voice morphing based on spectral features and prosodic modification

Voice morphing based on spectral features and prosodic modif...

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IEEE International Conference on Multi Topic

作者： Abdul Qavi Shoab Ahmad Khan Kashif Basir Department of Electrical and Computer Engineering Center for Advanced Studies in Engineering (CASE) Islamabad Pakistan College of Electrical and Mechanical Engineering (CEME) National University of Science and Technology (NUST) Islamabad Pakistan

This paper is aimed at morphing the speech uttered by a source speaker in a manner that it seems to be spoken by another target speaker - a new identity is given while preserving the original content. The proposed method transforms the vocal tract parameters and glottal excitation of the source speaker into target speaker's acoustic characteristics. It relates to the development of appropriate vocal tract models that can capture information specific to the speaker and estimate the model parameters that closely relate to the model of the target speaker. It detects the pitch, separates the glottal excitation and vocal tract spectral features. The glottal excitation of the source is taken, voice/un-voice decision is made, the prosody information is found, PSOLA (Pitch Synchronous OverLap Add) is used to modify the pitch, the spectral features are found, and finally speech is modified using target spectral features and prosody. The subjective experiment shows that the proposed method improves the quality of conversion and contains the original vocal and glottal characteristics of the target speaker.

关键词： Speech Feature extraction Frequency response Hidden Markov models Production Frequency-domain analysis Mel frequency cepstral coefficient

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