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7th European Congress on Computational Methods in Applied sciences and Engineering, ECCOMAS Congress 2016

作者： Veldman, Arthur E.P. Luppes, Roel Van Der Plas, Peter Van Der Heiden, Henri Düz, Bülent Seubers, Henk Helder, Joop Bunnik, Tim Huijsmans, René Institute for Mathematics and Computer Science University of Groningen Groningen Netherlands Department of Ship Hydrodynamis Delft University of Technology Delft Netherlands Maritime Reseach Institute MARIN Wageningen Netherlands Multiscale Modeling and Simulation University of Twente Enschede Netherlands

ISBN: (纸本)9786188284401

During the development of the ComFLOW simulation method many challenges have to be tackled concerning the flow modelling and the numerical solution algorithm. Examples here of are wave propagation, absorbing boundary conditions, fluid-solid body interaction, turbulence modeling and numerical efficiency. Some of these challenges will be discussed in the paper, in particular the design of absorbing boundary conditions and the numerical coupling for fluid-solid body interaction. As a demonstration of the progress made, a number of simulation results for engineering applications from the offshore industry will be presented: a wave-making oscillating buoy, a free-fall life boat dropping into wavy water, and wave impact against a semi-submersible offshore platform. For those applications, MARIN has carried out several validation experiments.

关键词： Computational fluid dynamics

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Virtual Page Behavior Based Page Management Policy for Hybrid Main Memory in Cloud Computing 12

Virtual Page Behavior Based Page Management Policy for Hybri...

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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Huang, Jie Zhang, Xuan Han, Guangjie Jia, Gangyong Liyou, Huizi Wan, Jian Department of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China Department of Information and Communication Systems Hohai University Changzhou213022 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9781509056965

A new generation memory, Non-Volatile Memory (NVM), such as Phase-Change Memory (PCM), has been adopted together with DRAM in the main memory to form the hybrid main memory for low energy consumption and high capacity. The biggest challenge of hybrid memory is how to decrease the average memory access cost for the higher cost of NVM's read/write operation. Currently, most researches are based on migration. However, the page migration itself is a high cost operation. And the migration based policy produces many migration operations, which induces high cost in memory access. Therefore, in order to decrease the cost, we present a virtual page behavior based page management policy (VBPM) in this paper. According to the virtual pages' behavior, we allocate virtual pages into DRAM or PCM physical pages correspondingly. The whole process is migration independent. The experimental results show our VBPM decreases the average memory access time by 24%, moreover, VBPM improves real-time performance in critical path. © 2016 IEEE.

关键词： Phase change memory

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Investigation on Suitability of Pulse Duration Parameter for HeLa Cells Line Proliferation Properties towards Anti-Cancer Application

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Journal of Physics: Conference Series 2018年第1期1019卷

作者： Azra Hazwanie Azizulkarim Muhammad Mahadi Abdul Jamil Mohamad Nazib Adon Muhammad Shukri Ahmad Johan Mohamad Sharif Md Asri Ngadi Radzi Ambar Biomedical Modelling and Simulation (BIOMEMS) Research Group Faculty of Electric and Electronic Engineering Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia Department of Computing Science Faculty of Computing Universiti Teknologi of Malaysia 81310 Skudai Johor Malaysia Embedded Computing System (EmbCoS) Research Group Department of Computer Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia

In order to bring up a cells or tissue with a gene or DNA, Electroporation parameter such as pulse duration, field strength and number of pulse plays the most important aspect. Thus, the aim of this paper is to optimize the pulse duration parameter for HeLa cells line. This is very important because nowadays, research on EP factors is still in limited mode. Moreover, suitable and applicable pulse duration parameter would ensure successful treatment with least possible side effect. In this paper, HeLa cells or known as cervical cancer cells was used to induce into a single pulse electric field. Therefore, to achieve the aim of this study, field strength of 500V/cm was preferred and the pulse duration was varied in the range of 100µs, 500µs, 1ms, 2ms and 5ms to obtain lowest proliferation rate and inhibit growth of HeLa cells. The result obtained shows that HeLa cell induced to 500V/cm with pulse duration of 100µs, induced the lowest proliferation rate (45%) as compared to initial reading density (control) after 48 hours of culture. Thus, further research based on this work may pave the way for an anti-cancer application through the study of the effect of pulse duration parameter on HeLa cells.

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The development of China's Yangtze River Economic Belt:how to make it in a green way?

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science Bulletin 2017年第9期62卷 648-651页

作者： Yushun Chen Shuanghu Zhang Desheng Huang Bai-Lian Li Junguo Liu Wenjin Liu Jing Ma Fang Wang Yong Wang Shengjun Wu Yegang Wu Jinyue Yan Chuanbo Guo Wei Xin Hao Wang Institute of Hydrobiology & State Key Laboratory of Freshwater Ecology and Biotechnology Chinese Academy of Sciences Wuhan 430072 China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing 100038 China Policy Research Center for Environment and Economy Ministry of Environmental Protection of P.R. China Beijing 100029 China Ecological Complexity and Modeling Laboratory University of California Riverside CA 92521-0124 USA School of Environmental Science and Engineering Southern University of Science and Technology of China Shenzhen 518055 China Orient Landscape Industry Group Ltd. Beijing 100015 China Department of Biological and Environmental Sciences Alabama A&M University Normal AL 35762 USA Key Laboratory of Reservoir Aquatic Environment & Research Center for Ecological Process of Three Gorges' Eco-Environment Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing 400714 China Institute of Eco-city Planning and Design Shanghai BoDa Development Corporation Shanghai 200333 China KTH-Royal Institute of Technology SE-10044 Stockholm Sweden & Malardalen University SE-72123 Vasteras Sweden

The Yangtze River is one of the largest and longest rivers in *** river originates in the Tibet-Qinghai Plateau(headwater reach),passes through the mountainous provinces of Sichuan,Yunnan and Chongqing(upper reach),flows into the Central Plain(middle reach)and Lower Plain(lower reach),and finally empties into the East China Sea in Shanghai(estuary).The Yangtze River Economic Belt(YREB;Fig.1)has a surface area of 2.1

关键词： In The development of China’s Yangtze River Economic Belt:how to make it in a green way

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SELECTION AND COMBINATION OF HYPOTHESES FOR DIALECTAL SPEECH RECOGNITION

SELECTION AND COMBINATION OF HYPOTHESES FOR DIALECTAL SPEECH...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Victor Soto Olivier Siohan Mohamed Elfeky Pedro Morenot Columbia University Computer Science Department New York Google Inc. Languages Modeling Group New York

ISBN: (纸本)9781479999897

While research has often shown that building dialect-specific Automatic Speech Recognizers is the optimal approach to dealing with dialectal variations of the same language, we have observed that dialect-specific recognizers do not always output the best recognitions. Often enough, another dialectal recognizer outputs a better recognition than the dialect-specific one. In this paper, we present two methods to select and combine the best decoded hypothesis from a pool of dialectal recognizers. We follow a Machine Learning approach and extract features from the Speech Recognition output along with Word Embeddings and use Shallow Neural Networks for classification. Our experiments using Dictation and Voice Search data from the main four Arabic dialects show good WER improvements for the hypothesis selection scheme, reducing the WER by 2.1 to 12.1% depending on the test set, and promising results for the hypotheses combination scheme.

关键词： speech recognition dialects system combination system selection Speech recognition Dialect TEST SETS

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Advancing global and regional reanalyses

Advancing global and regional reanalyses

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作者： Buizza, Roberto Poli, Paul Rixen, Michel Alonso-Balmaseda, Magdalena Bosilovich, Michael BrönniMann, Stefan Compo, Gilbert P Dee, Dick P Desiato, Franco Doutriaux-Boucher, Marie Fujiwara, Masatomo Kaiser-Weiss, Andrea Kobayashi, Shinya Liu, Zhiquan Masina, Simona Mathieu, Pierre-PhiliPPe Rayner, Nick Richter, Carolin Seneviratne, Sonia Simmons, Adrian ThéPaut, Jean-Noel Auger, Jeffrey Bechtold, Michel Berntell, Ellen Dong, Bo Kozubek, Michal Sharif, Khaled Thomas, Christopher Schimanke, Semjon Storto, Andrea Tuma, Matthias Välisuo, Ilona Vaselali, Alireza European Centre for Medium-Range Weather Forecasts Reading United Kingdom Météo-France Brest France World Climate Research Programme World Meteorological Organization Geneva Switzerland Global Modeling and Assimilation Office NASA GSFC GreenbeltMD United States Institute of Geography University of Bern Bern Switzerland University of Colorado Boulder Cooperative Institute for Research in Environmental Sciences NOAA ESRL Physical Sciences Division BoulderCO United States European Commission Reading United Kingdom Istituto Superiore per la Protezione e la Ricerca Ambientale Rome Italy European Organisation for the Exploitation of Meteorological Satellites Darmstadt Germany Faculty of Environmental Earth Science Hokkaido University Hokkaidō Japan Deutscher Wetterdienst Offenbach Germany Japan Meteorological Agency Tokyo Japan National Center for Atmospheric Research BoulderCO United States Istituto Nazionale di Geofisica e Vulcanologia Bologna Italy European Space Agency Frascati Italy Met Office Exeter United Kingdom Global Climate Observing System World Meteorological Organization Geneva Switzerland Zurich Switzerland Climate Change Institute University of Maine OronoME United States Department of Earth and Environmental Sciences Department of Computer Science Katholieke Universiteit Leuven Leuven Belgium Stockholm University Stockholm Sweden Department of Meteorology University of Reading Reading United Kingdom Institute of Atmospheric Physics Academy of Sciences of the Czech Republic Prague Czech Republic ArabiaWeather Inc. Amman Jordan Swedish Meteorological and Hydrological Institute Norrköping Sweden CMCC Bologna Italy Finnish Meteorological Institute Helsinki Finland Beta Group Consulting Engineers Tehran Iran

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Optimal maximum likelihood estimates fusion in distributed network of sensors

Optimal maximum likelihood estimates fusion in distributed n...

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IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Bharat Madan Doina Bein Dept. of Modeling Simulation & Visualization Engineering Old Dominion University Norfolk USA Department of Computer Science California State University Fullerton Fullerton USA

ISBN: (纸本)9781509039005

A distributed network of sensors leverages its performance by aggregating information gathered by individual sensors through the process of sensor data fusion. Estimating parameters using a centralized scheme entails transporting data from multiple sensors to a centralized fusion center, leading to high network bandwidth consumption. Additionally, fusing raw sensor data from sensors with different sensing modalities may not be feasible. We propose an alternative approach in which each sensor first individually estimates the unknown parameters based solely on its own sensor data. Since sensors may not have a-priori knowledge of the probability distribution of the unknown parameters, each sensor independently computes its individual maximum likelihood estimates. Individual estimates along with their sufficient statistics are then communicated to the fusion center, which treats these estimates as observations to compute the optimum aggregated maximum likelihood estimates by maximizing the new likelihood function of these observations. The proposed technique offers two significant advantages: (i) Since each sensor computes its individual estimates based solely on its own sensed data, it is easily applicable to sensor networks having multi-modal sensors, and (ii) As compared to raw sensor data, communicating estimates and their sufficient statistics to the fusion center requires substantially less network bandwidth. Performance of the aggregated estimates is evaluated through simulations and by computing the Cramer-Rao lower bound.

关键词： Maximum likelihood estimation Sensor fusion Bandwidth Sensor phenomena and characterization Computational modeling

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A novell approach on evolutionary dynamics analysis - A progress report 1

A novell approach on evolutionary dynamics analysis - A prog...

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1st EAI International Conference on computer science and Engineering, COMPSE 2016

作者： Zelinka, Ivan Vasant, Pandian Dao, Tran Trong Hoang, Duy Vo Department of Computer Science VSB Technical University of Ostrava FEI Tr. 17. Listopadu 15 Ostrava Czech Republic Department of Fundamental and Applied Sciences Universiti Teknologi PETRONAS Seri Iskandar32610 Malaysia Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9781631901362

In this paper we discuss the possibility of novel mutual fusion of evolutionary algorithms, complex networks, strange dynamics and hidden attractors. As demonstrated in previous research papers, evolutionary algorithms are capable of very complex tasks such as chaotic system control, identification or synthesis and vice versa, chaos can be observed also in the evolutionary dynamics. We pro-pose a novel approach non how to analyze and control dynamic of evolutionary algorithm and also discuss possibility on strange dynamics analysis that is a part of dynamic of evolutionary algorithms. In any words, we propose to understand algorithms as a discrete dynamical system that exhibit wide spectra behavior that can be controlled and analyzed.

关键词： Evolutionary algorithms

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Space-charge effect of the time-varying electron injection in a diode: classical and relativistic regimes

arXiv

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arXiv 2017年

作者： Liu, Yangjié Tang, Qi Wu, Biyi Faculty of Physics and Electronic Science Hubei University Hubei Collaboration Innovation Centre for Advanced Organic Chemical Materials Hubei Key Laboratory of Ferro & Piezoelectric Materials and Devices WuhanHubei Province430062 China Antennas Group School of Electrical Engineering and Computer Science Queen Mary University of London E1 4NS Mile End East London United Kingdom Department of Mathematical Sciences Rensselaer Polytechnic Institute United States Center for Electromagnetic Simulation Beijing Institute of Technology Haidian District Beijing China

Conventionally, space-charge (SC) limited current density is defined as the maximal current density allowed to traverse a diode under a DC voltage when a time-invariant flow is injected from the cathode. In this work, we study the SC limited current density under a time-varying injection for both classical and relativistic regimes and determine the maximal amount of limited current density under certain conditions. Our simulations show that it is unlikely that a time-varying injection emitted from cathode exceeds the known SC limits, in either classical or relativistic regime. Copyright © 2017, The Authors. All rights reserved.

关键词： Current density

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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