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Simulation Winter Conference

作者： Daniel Guimarans Oscar Dominguez Angel A. Juan Enoc Martinez Aviation Academy Amsterdam University of Applied Sciences Amsterdam NETHERLANDS Institute of Intelligent Systems and Numerical Applications in Engineering University of Las Palmas de Gran Canaria Las Palmas de Gran Canaria SPAIN Computer Science Dept. - IN3 Open University of Catalonia SPAIN

ISBN: (纸本)9781509044849

The two-dimensional vehicle routing problem (2L-VRP) is a realistic extension of the classical vehicle routing problem where customers' demands are composed by sets of non-stackable items. Examples of such problems can be found in many real-life applications, e.g. furniture or industrial machinery transportation. Often, these real-life instances have to deal with uncertainty in many aspects of the problem, such as variable traveling times due to traffic conditions or customers availability. We present a hybrid simheuristic algorithm that combines biased-randomized routing and packing heuristics within a multi-start framework. Monte Carlo simulation is used to deal with uncertainty at different stages of the search process. With the goal of minimizing total expected cost, we use this methodology to solve a set of stochastic instances of the 2L-VRP with unrestricted oriented loading. Our results show that accounting for systems variability during the algorithm search yields more robust solutions with lower expected costs.

关键词： Routing Vehicles Loading Vehicle routing Computational modeling Heuristic algorithms Cache memory

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Optimizing FPGA-based accelerator design for deep convolutional neural networks 15

Optimizing FPGA-based accelerator design for deep convolutio...

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ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, FPGA 2015

作者： Zhang, Chen Li, Peng Sun, Guangyu Guan, Yijin Xiao, Bingjun Cong, Jason Center for Energy-Efficient Computing and Applications Peking University China Computer Science Department University of California Los Angeles United States PKU UCLA Joint Research Institute in Science and Engineering United States

ISBN: (纸本)9781450333153

Convolutional neural network (CNN) has been widely employed for image recognition because it can achieve high accuracy by emulating behavior of optic nerves in living creatures. Recently, rapid growth of modern applications based on deep learning algorithms has further improved research and implementations. Especially, various accelerators for deep CNN have been proposed based on FPGA platform because it has advantages of high performance, reconfigurability, and fast development round, etc. Although current FPGA accelerators have demonstrated better performance over generic processors, the accelerator design space has not been well exploited. One critical problem is that the computation throughput may not well match the memory bandwidth provided an FPGA platform. Consequently, existing approaches cannot achieve best performance due to underutilization of either logic resource or memory bandwidth. At the same time, the increasing complexity and scalability of deep learning applications aggravate this problem. In order to overcome this problem, we propose an analytical design scheme using the rooine model. For any solution of a CNN design, we quantitatively analyze its computing throughput and required memory bandwidth using various optimization techniques, such as loop tiling and transformation. Then, with the help of rooine model, we can identify the solution with best performance and lowest FPGA resource requirement. As a case study, we implement a CNN accelerator on a VC707 FPGA board and compare it to previous approaches. Our implementation achieves a peak performance of 61.62 GFLOPS under 100MHz working frequency, which outperform previous approaches significantly.

关键词： Field programmable gate arrays (FPGA)

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An effective time based load balancer for an academic cloud environment

An effective time based load balancer for an academic cloud ...

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International Conference on computer Communication and Informatics (ICCCI)

作者： C. Madhumathi Gopinath Ganapathy School of Computer Science Engineering and Applications Bharathidasan University Trichy India

The proliferation of Internet and mobile phone usage among students led to the state-of-the-art technology in cloud based e-Learning. An academic cloud based e-Learning at its initial stage will act as a private cloud with certain Service Level Agreements (SLA) and limited resources. Therefore, only limited virtualized resources available in an infrastructure can be utilized by the end-users of an academic institution. In order to provide an effective utilization, a proper balancing of workload is needed. Hence in the adduced work, mapping of the user's requested Virtual Machine (VM) configuration exactly with host configuration is done using Three Phase Filtering Protocol (3PFP). An efficient time based load balancer (TBLB) algorithm is also developed in order to distribute the load evenly among the host machines based on last virtual machine executed date and time (LVMEDT). The performance of the proposed algorithm is analyzed using the cloud testbed.

关键词： Cloud computing Virtual machining Electronic learning computers Load management Informatics

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Author Correction: National identity predicts public health support during a global pandemic

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Nature communications 2022年第1期13卷 1949页

作者： Jay J Van Bavel Aleksandra Cichocka Valerio Capraro Hallgeir Sjåstad John B Nezlek Tomislav Pavlović Mark Alfano Michele J Gelfand Flavio Azevedo Michèle D Birtel Aleksandra Cislak Patricia L Lockwood Robert Malcolm Ross Koen Abts Elena Agadullina John Jamir Benzon Aruta Sahba Nomvula Besharati Alexander Bor Becky L Choma Charles David Crabtree William A Cunningham Koustav De Waqas Ejaz Christian T Elbaek Andrej Findor Daniel Flichtentrei Renata Franc Biljana Gjoneska June Gruber Estrella Gualda Yusaku Horiuchi Toan Luu Duc Huynh Agustin Ibanez Mostak Ahamed Imran Jacob Israelashvili Katarzyna Jasko Jaroslaw Kantorowicz Elena Kantorowicz-Reznichenko André Krouwel Michael Laakasuo Claus Lamm Caroline Leygue Ming-Jen Lin Mohammad Sabbir Mansoor Antoine Marie Lewend Mayiwar Honorata Mazepus Cillian McHugh John Paul Minda Panagiotis Mitkidis Andreas Olsson Tobias Otterbring Dominic J Packer Anat Perry Michael Bang Petersen Arathy Puthillam Julián C Riaño-Moreno Tobias Rothmund Hernando Santamaría-García Petra C Schmid Drozdstoy Stoyanov Shruti Tewari Bojan Todosijević Manos Tsakiris Hans H Tung Radu G Umbreș Edmunds Vanags Madalina Vlasceanu Andrew Vonasch Meltem Yucel Yucheng Zhang Mohcine Abad Eli Adler Narin Akrawi Hamza Alaoui Mdarhri Hanane Amara David M Amodio Benedict G Antazo Matthew Apps F Ceren Ay Mouhamadou Hady Ba Sergio Barbosa Brock Bastian Anton Berg Maria P Bernal-Zárate Michael Bernstein Michał Białek Ennio Bilancini Natalia Bogatyreva Leonardo Boncinelli Jonathan E Booth Sylvie Borau Ondrej Buchel C Daryl Cameron Chrissie F Carvalho Tatiana Celadin Chiara Cerami Hom Nath Chalise Xiaojun Cheng Luca Cian Kate Cockcroft Jane Conway Mateo Andres Córdoba-Delgado Chiara Crespi Marie Crouzevialle Jo Cutler Marzena Cypryańska Justyna Dabrowska Michael A Daniels Victoria H Davis Pamala N Dayley Sylvain Delouvee Ognjan Denkovski Guillaume Dezecache Nathan A Dhaliwal Alelie B Diato Roberto Di Paolo Marianna Drosinou Uwe Dulleck Jānis Ekmanis Arhan S Ertan Tom W Etienne Hapsa Hossain Farhana Fahima Farkhari Har Department of Psychology and Neural Science New York University New York NY USA. jay.vanbavel@nyu.edu. School of Psychology University of Kent Canterbury England. Department of Economics Middlesex University London London England. Department of Strategy and Management Norwegian School of Economics Bergen Norway. SWPS University of Social Sciences and Humanities Poznań Poland. Department of Psychological Sciences College of William and Mary Williamsburg VA USA. Institute of Social Sciences Ivo Pilar Zagreb Croatia. Department of Philosophy Macquarie University Sydney NSW Australia. Stanford Graduate School of Business Stanford University Stanford CA USA. Institute of Communication Science Friedrich-Schiller University Jena Jena Germany. flavio.azevedo@uni-jena.de. School of Human Sciences Institute for Lifecourse Development University of Greenwich London England. Department of Experimental Psychology University of Oxford Oxford England. Center for Human Brain Health School of Psychology University of Birmingham Birmingham England. Department of Psychology Macquarie University Sydney NSW Australia. KU Leuven Leuven Belgium. National Research University Higher School of Economics (HSE) Moscow Russia. De La Salle University Manila Philippines. Department of Psychology University of the Witwatersrand Johannesburg South Africa. Department of Political Science Aarhus University Aarhus Denmark. X University Toronto ON Canada. Department of Government Dartmouth College Hanover NH USA. Department of Psychology University of Toronto Toronto ON Canada. Gatton College of Business and Economics University of Kentucky Lexington KY USA. Department of Mass Communication National University of Science and Technology (NUST) Islamabad Pakistan. Department of Management Aarhus University Aarhus Denmark. Faculty of Social and Economic Sciences Comenius University Bratislava Slovakia. IntraMed Buenos Aires Argentina. Macedonian Academy of Sciences and

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Cluster based hybrid key management scheme for ad hoc networks

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ICIC Express Letters, Part B: applications 2016年第6期7卷 1329-1334页

作者： Zhang, Jing Xu, Li Tang, Rongmei Zhang, Shunmiao School of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China School of Mathematics and Computer Science Fujian Normal University Fuzhou University Town Minhou Fuzhou350118 China

Secure communication is part of the most important aspects for ad hoc networks. One cluster based Hybrid Key Management Scheme is proposed in this paper for ad hoc networks. The clusters are constructed by the R-hop connected dominating sets based Partition Algorithm, which is only with the knowledge of local connectivity information. Furthermore, Hybrid Key Management Scheme can be seen as an integration of both the asymmetric key and symmetric key cryptography. The asymmetric one is based on the elliptic curve cryptosystem, which is an asymmetric one. However, inter cluster key management is based on symmetric key encryption. Experimental results show this scheme is reliable and it is able to achieve higher success of landing ratio than other comparable algorithms. © 2016 ICIC International.

关键词： Ad hoc networks

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Gracefully Cultivating Trees on a Cycle

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Electronic Notes in Discrete Mathematics 2015年 48卷 143-150页

作者： Figueroa-Centeno, Ramon M. Ichishima, Rikio Muntaner-Batle, Francesc A. Oshima, Akito Mathematics Department University of Hawaii at Hilo 200 W. Kawili St. Hilo 96720 HI United States College of Humanities and Sciences Nihon University 3-25-40 Sakurajosui Setagaya-ku Tokyo 156-8550 Japan Graph Theory and Applications Research Group School of Electrical Engineering and Computer Science Faculty of Engineering and Built Environment The University of Newcastle 2308 NSW Australia Graph Theory and Applications Research Group School of Electrical Engineering and Computer Science Faculty of Engineering and Built Environment The University of Newcastle 2308 NSW Australia

A graph G of size q is graceful if there exists an injective function f:V(G)→{0, 1, ..., q} such that each uv∈E(G) is labeled |f(u)-f(v)| and the resulting edge labels are distinct. Truszczyński conjectured that all unicyclic graphs except the cycle C_n, where n≡1or2(mod4), are graceful. In this paper, we present two methods to construct certain graceful unicyclic graphs when the length of cycles are congruent to 0 or 3 (mod 4). © 2015.

关键词： Graceful labellings Truszczyński's conjecture Unicyclic graphs

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Phase Congruency and Morphology Based Approach for Text Localization in Videos

Phase Congruency and Morphology Based Approach for Text Loca...

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International Conference on Advances in Computing, Communications and Informatics

作者： B. H. Shekar Smitha, M. L. Department of Computer Science Mangalore University Department of Master of Computer Applications KVG College of Engineering

ISBN: (纸本)9781479987931

In this knowledge era, cognitive learning and media technologies promote high visual orientation through videos which appears in the form of text, graphics, animations, audio or still images. Text present in videos carry important semantic information which is indeed essential for video comprehension. In this context, we propose a novel method of detecting the text clusters in video frames based on the phase congruency model and morphology based approaches. We investigate the matching features extracted from both these methods and devise a set of rules using morphological operators for false positive elimination. The text regions are detected using connected component analysis and finally the text is localized. We have evaluated the performance of the proposed method on the standard datasets and the results highlight the effectiveness in localizing the text in videos and scene images.

关键词： Phase Congruency Morphology Text Detection Text Localization

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Intelligent Classification Model for Cashew Kernel Grades Based on Colour, Texture, and Morphological Features

Intelligent Classification Model for Cashew Kernel Grades Ba...

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2015 International Conference on Agricultural and Biological sciences

作者： Narendra V G Hareesh K S Department of Computer Science and Engineering Department of Computer ApplicationsManipal Institute of Technology Manipal University

In this paper, the method for building a supervised intelligent classification model for white wholes(WW) grades of cashew kernel using different images was discussed. The morphological, colour, and texture features were used to train or test different classifiers for recognition and classification. In order to achieve the best prediction accuracy, the subsets of features from feature sets were selected using a correlation-based feature selection(CFS) algorithm. In this study, the best prediction accuracy was obtained using multilayer perceptron, simple logistic, support vector machines, sequential minimal optimization, and logistic classifiers. The percentage of classification models that were correctly classified for the training/test set of WW grades ranged from 70% to 90%, and the validation set was as high as 86%. Receiver operating characteristics(ROC) were used to present the studied classifier performances in recognition and classification of WW grade cashew kernels.

关键词： Classification Model White Wholes Cashew Kernel Grad Morphological Features Colour Features Texture Features

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Graphene Flakes: Orientation Control of Graphene Flakes by Magnetic Field: Broad Device applications of Macroscopically Aligned Graphene (Adv. Mater. 1/2017)

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Advanced Materials 2017年第1期29卷

作者： Feng Lin Zhuan Zhu Xufeng Zhou Wenlan Qiu Chao Niu Jonathan Hu Keshab Dahal Yanan Wang Zhenhuan Zhao Zhifeng Ren Dimitri Litvinov Zhaoping Liu Zhiming M. Wang Jiming Bao Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu Sichuan 610054 China Department of Electrical and Computer Engineering University of Houston Houston TX 77204 USA Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo Zhejiang 315201 China Key Laboratory of Graphene Technologies and Applications of Zhejiang Province Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo Zhejiang 315201 China Materials Science and Engineering University of Houston Houston TX 77204 USA Department of Electrical and Computer Engineering Baylor University Waco TX 76798 USA Department of Physics and TcSUH University of Houston Houston TX 77204 USA State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Chengdu Sichuan 610054 China

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Tagging event image set using face identification

Tagging event image set using face identification

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International Conference on Soft-Computing and Networks Security (ICSNS)

作者： Hanumanthappa M. S. Regina LourdhuSuganthi S. Karthik Department of Computer Science and Applications Bangalore University Bangalore Department of Computer Science & Engineering SNS College of Technology Coimbatore

Events are organized by various Institutions round the year to encourage and enhance skills in academic and non-academic horizons. These events include seminar, workshop, cultural fest, product launch and the like. Event venues host digital devices to capture the proceedings. These devices generateenormous Video and Image data. These events are documented for auditing, evaluation and for future reference. Tagging these images based on the content and event context would facilitate and fasten the retrieval of these images. The tagged images could then be accessed based on a query. The objects of interest for tagging would include important personalities and key objects that describe a scene. Face detection based on training data set at large would aid in identifying persons.

关键词： Face Feature extraction Face detection Tagging Face recognition Mouth Security

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