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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： David Andrešić Petr Šaloun Ioannis Anagnostopoulos Faculty of Electrical Engineering and Computer Science VŠB - Technical University of Ostrava Ostrava Czech republic Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece

Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries onto a single big data analytical stack and is efficient and fast enough even on a standard single computer. This innovative approach brings the big data analysis to researchers with limited resources. Our genuine idea was experimentally confirmed and is described here. As a case study for our method we we used the available #Brexit data and the sentiment analysis of corresponding tweets and the correlation with the stock exchange data.

关键词： Sparks Stock markets Correlation Twitter Finance Big Data Industries

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Evaluation of Cache for Bandwidth Optimization in ICN Through Software-Defined Networks

Evaluation of Cache for Bandwidth Optimization in ICN Throug...

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IEEE Symposium on computers and Communications

作者： Erick B. Nascimento Douglas D. J. de Macedo Edward David Moreno Luis Carlos Erpen de Bona Miriam A. M. Capretz Dept. of Computing Science (DCOMP) Federal University of Sergipe (UFS) Sãao Cristovãao SE Brazil Dept. of Information Science (CIN) Federal University of Santa Catarina (UFSC) Florianóopolis SC Brazil Dept. of Informatics Federal University of Parana (UFPR) Curitiba PR Brazil Dept. of Electrical and Computer Engineering Western University London ON Canada

Traffic reduction in network segments through cache implementations has become a major research topic due to the exponential increase in data requests through the network. Even with high-speed connections, the conventional model still depends on point-to-point communication between two systems. Throughout the world, more connected devices are, accessing services and obtaining information. To support this activity, servers must have massive storage to support creation, retrieval, updated and deletion of large amounts of data. Therefore, in studies of Information Centric Networks (ICN), this model has been widely discussed as the new content distribution model for the Internet. To provide improved network management many approaches are using software-defined networks (SDN) to develop flexible content-based networks. This paper proposes to use cache replication for ICN through SDN to avoid duplicated requests in the same connection. The redundant cache reduced the bandwidth consumed by duplicated requests, from a maximum of 3.20 Gbps to 2.07 Gbps, reducing the bandwidth consumption by 11.3%.

关键词： Cache Controller Networks ICN SDN

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Diabetic Retinopathy Identification using Deep Believe Network

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Journal of Physics: Conference Series 2019年第1期1235卷

作者： M F Syahputra M Rahmah I Jaya U Andayani D Abdullah S Sriadhi E Y Lalusu M Tongko B D Cahya N Fardian Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Public Health Universitas Tompotika Luwuk Banggai Indonesia Department of Nutrition Universitas Malikussaleh Aceh Utara Indonesia

Diabetic retinopathy is an eye disease caused by swelling in blood vessels. If it gets worse the blood vessels will rupture and this is the main factor of blindness. This disease is rarely found in children and symptoms can be seen during puberty. One way to find out this disease is a wide and comprehensive pupil jerky eye examination performed by an ophthalmologist manually. Manual examination takes a long time and can cause misidentification because the similarity of characteristics of diabetic retinopathy is difficult to see directly. Because of this problem a method is needed that can facilitate the eye doctor in identifying diabetic retinopathy by simply inserting a retinal image into the system. The method proposed in this study is Deep Belief Network (DBN). The steps taken before identification are the image of the retina undergoing pre-processing in the form of grayscale, median filter, contrast stretching, morphological close operation and feature extraction using the Grey level Counselling Matrix (GLCM). In this study it was shown that the proposed method was able to identify diabetic retinopathy with 84% accuracy, sensitivity 93%, and specificity 70%.

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Minimization Response Time Task scheduling Algorithm

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IOP Conference Series: Materials Science and engineering 2019年第1期705卷

作者： Maria Maqsood Saima Anwar Lashari Murtaja Ali Saare Sari Ali Sari Yaqdhan Mahmood Hussein Hatem Oday Hatem Department of Computer Science University of Lahore Sargodha Campus Pakistan. College of Computing and Informatics Saudi Electronic University Dammam Kingdom of Saudi Arabia. Human-Centered Computing Research Lab School of Computing Universiti Utara Malaysia Sintok 06010 Kedah Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia 86400 Parit Raja Batu Pahat Johor Malaysia. Communication Engineering Department Faculty of Electrical Engineering University Technology Malaysia 81310 Johor Bahru Johor Malaysia

Cloud computing is a type of computing that base on shared computer resources for delivering information technology services. Distributed Computational system has been considered as best systematic model for sharing resources. Minimization of response time is the requirement in the distributed computational system. Previous Algorithm belongs to the optimization in which every new Virtual Machine reaching as a request to the cloud computing manager. This creates disturbance in the processing during life cycle of others Virtual Machines. For overcome this problem, there is a proposed an algorithm for minimization response time in distributed computational system by using the multi agents cloud structure. The overall system is architecture as a distributed over multi layered model. This leads to a situation that demands high care in allocating a Virtual Machine (VM) to a server machine in order to improve allocation time and efficiency of resources. Focus of this work remains to decrease time of allocation to optimize response time using a Virtual Machine (VM) placement and allocation algorithm that accounts Virtual. Machines (VM), their types and available resources among the data center server machines. Presented algorithm is implemented by using cloud simulator tool, through this tool, the calculated results of presented algorithm have been quite better with respect to traditional algorithm, and the difference presented with graphs for the both algorithms. Results support proposed methodology.

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Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

arXiv

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arXiv 2018年

作者： Maier-Hein, Lena Eisenmann, Matthias Reinke, Annika Onogur, Sinan Stankovic, Marko Scholz, Patrick Arbel, Tal Bogunovic, Hrvoje Bradley, Andrew P. Carass, Aaron Carolin Feldmann Frangi, Alejandro F. Ful, Peter M. van Ginneken, Bram Hanbury, Allan Honauer, Katrin Kozubek, Michal Landman, Bennett A. Marz, Keno Maier, Oskar Maier-Hein, Klaus Menze, Bjoern H. Müller, Henning Neher, Peter F. Niessen, Wiro Rajpoot, Nasir Sharp, Gregory C. Sirinukunwattana, Korsuk Speidel, Stefanie Stock, Christian Stoyanov, Danail Taha, Abdel Aziz van der Sommen, Fons Wang, Ching-Wei Weber, Marc-André Zheng, Guoyan Jannin, Pierre Kopp-Schneider, Annette Heidelberg Germany Centre for Intelligent Machines McGill University MontrealQC Canada Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna Vienna Austria Science and Engineering Faculty Queensland University of Technology BrisbaneQLD Australia Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore United States CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine University of Sheffield Sheffield United Kingdom Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center Nijmegen Netherlands Institute of Information Systems Engineering TU Wien Vienna Austria Heidelberg University Heidelberg Germany Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Electrical Engineering Vanderbilt University NashvilleTN United States Institute of Medical Informatics Universität zu Lübeck Lübeck Germany Heidelberg Germany Institute for Advanced Studies Department of Informatics Technical University of Munich Munich Germany Information System Institute HES-SO Sierre Switzerland Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC Rotterdam Netherlands Department of Computer Science University of Warwick Coventry United Kingdom Department of Radiation Oncology Massachusetts General Hospital BostonMA United States Institute of Biomedical Engineering University of Oxford Oxford United Kingdom National Center for Tumor Diseases Dresden Dresden Germany Heidelberg Germany Department of Computer Science University College London London United Kingdom Data Science Studio Research Studios Austria FG Vienna Austria Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands AIExplore NTUST Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering National Ta

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Quality control

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Prediction of water quality evaluation for fish ponds of aquaculture 56

Prediction of water quality evaluation for fish ponds of aqu...

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56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017

作者： Yang, Po-Yuan Tsai, Jinn-Tsong Chou, Jyh-Homg Ho, Wen-Hsien Lai, Yueh-Yi Department of Electrical Engineering National Kaohsiung University of Applied Science Kaohsiung Taiwan Department of Computer Science National Pingtung University Pingtung Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung Taiwan Electronic and Optoelectronic System Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (纸本)9784907764579

This study used a regression method to build model for predicting water quality for the fish pond. From aquaculture practitioners' point of view, how to effectively control the water quality for the fish pond is very important. In basis of the experience of aquaculture practitioners, temperature, pH, conductivity, salinity, and last monitored oxygen content influence the water quality (here, called influencing factor). Life and death of fish are determined by water quality as well as water quality is decided by oxygen content. Therefore, the evaluation of the water quality is according to oxygen content. Regression method is often used for statistical analysis and prediction. In regression method, model is established by dependent variables and independent variables. In this study, the five influencing factors are represented as independent variables and the oxygen content is seen as dependent variable. From the experimental result, the oxygen content can be kept in the reasonable range. © 2017 The Society of Instrument and Control Engineers - SICE.

关键词： Water quality

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Dual-Band Slot Dipole with AMC using Textiles

Dual-Band Slot Dipole with AMC using Textiles

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International Applied Computational Electromagnetics Society Symposium

作者： Fatin Nabilah Giman Ping Jack Soh Azremi Abdullah Al-Hadi Mohd Faizal Jamlos Herwansyah Lago Dominique Schreurs Sharul Kamal Abdul Rahim Adalbert Beyer Sch. of Computer and Comm. Eng Universiti Malaysia Perlis Arau Perlis Malaysia Faculty of Mechanical Eng Universiti Malaysia Pahang Pahang Malaysia Faculty of Engineering Universiti Malaysia Sabah Sabah Malaysia ESAT-TELEMIC Research Division KU Leuven 3001 Leuven Belgium Wireless Communication Center Universiti Teknologi Malaysia Johor Malaysia Dept. of Electrical Eng. & Informatics Duisburg-Essen University Duisburg Germany

ISBN: (纸本)9781728115184;9780996007887

A dual band slot dipole antenna integrated with an AMC plane is proposed to reduce SAR when operated on body for WBAN applications. The AMC plane is formed using a 3 x 3 array of unit cells, each consisting of a square patch integrated with diamond-shaped slot. Results indicate that the antenna provides wide upper bandwidth up to 600 MHz (in flat condition) and up to 570 MHz when bent. Besides that, its front-to-back ratio (FBR) is also improved.

关键词： Antennas Artificial magnetic conductor Metamaterial Multiband antennas Wearable antennas

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Deep learning for reliable mobile edge analytics in intelligent transportation systems

arXiv

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arXiv 2017年

作者： Ferdowsi, Aidin Challita, Ursula Saad, Walid Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States School of Informatics University of Edinburgh Edinburgh United Kingdom

Intelligent transportation systems (ITSs) will be a major component of tomorrows smart cities. However, realizing the true potential of ITSs requires ultra-low latency and reliable data analytics solutions that can combine, in realtime, a heterogeneous mix of data stemming from the ITS network and its environment. Such data analytics capabilities cannot be provided by conventional cloud-centric data processing techniques whose communication and computing latency can be high. Instead, edge-centric solutions that are tailored to the unique ITS environment must be developed. In this paper, an edge analytics architecture for ITSs is introduced in which data is processed at the vehicle or roadside smart sensor level in order to overcome the ITS latency and reliability challenges. With a higher capability of passengers mobile devices and intra-vehicle processors, such a distributed edge computing architecture can leverage deep learning techniques for reliable mobile sensing in ITSs. In this context, the ITS mobile edge analytics challenges pertaining to heterogeneous data, autonomous control, vehicular platoon control, and cyber-physical security are investigated. Then, different deep learning solutions for such challenges are proposed. The proposed deep learning solutions will enable ITS edge analytics by endowing the ITS devices with powerful computer vision and signal processing functions. Preliminary results show that the proposed edge analytics architecture, coupled with the power of deep learning algorithms, can provide a reliable, secure, and truly smart transportation environment. Copyright © 2017, The Authors. All rights reserved.

关键词： Intelligent systems

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Smartphone-Based Self-Management of Non-Insulin-Dependent Diabetes: A Japanese System at Use by an Italian Patients' Cohort

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Journal of diabetes science and technology 2018年第4期12卷 903-904页

作者： Sara Pinto Kayo Waki Luca Chiovato Pasquale De Cata Arianna Dagliati Valentina Tibollo Giuseppe Ruvolo Riccardo Bellazzi 1 Postgraduate School of Endocrinology and Metabolism University of Pavia Pavia Italy. 2 Maugeri Clinical & Scientific Institutes Institute of Pavia Pavia Italy. 3 Department of Ubiquitous Health Informatics The University of Tokyo Tokyo Japan. 4 Department of Internal Medicine and Medical Therapy University of Pavia Pavia Italy. 5 University of Manchester Manchester United Kingdom. 6 Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy.

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Learning to teach reinforcement learning agents

arXiv

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arXiv 2017年

作者： Fachantidis, Anestis Taylor, Matthew E. Vlahavas, Ioannis Department of Informatics Aristotle University of Thessaloniki 5412 Greece School of Electrical Engineering and Computer Science Washington State University PullmanWA99164 United States

In this article we study the transfer learning model of action advice under a budget. We focus on reinforcement learning teachers providing action advice to heterogeneous students playing the game of Pac-Man under a limited advice budget. First, we examine several critical factors affecting advice quality in this setting, such as the average performance of the teacher, its variance and the importance of reward discounting in advising. The experiments show the non-trivial importance of the coefficient of variation (CV) as a statistic for choosing policies that generate advice. The CV statistic relates variance to the corresponding mean. Second, the article studies policy learning for distributing advice under a budget. Whereas most methods in the relevant literature rely on heuristics for advice distribution we formulate the problem as a learning one and propose a novel RL algorithm capable of learning when to advise, adapting to the student and the task at hand. Furthermore, we argue that learning to advise under a budget is an instance of a more generic learning problem: Constrained Exploitation Reinforcement Learning. Copyright © 2017, The Authors. All rights reserved.

关键词： Reinforcement learning

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