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Wiki-supported distributed requirements engineering for big stakeholder groups

Wiki-supported distributed requirements engineering for big ...

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Gemeinschaften in Neuen Medien, GeNeMe 2007 - Communities in New Media, GeNeMe 2007

作者： Hagen, Mariele Jungmann, Berit Lauenroth, Kim PRO DV Software AG Hauert 6 Dortmund Germany T-Systems Multimedia Solutions GmbH Riesaer Str. 5 Dresden Germany Dept. of Software Systems Engineering Institut for Computer Science and Business Information System University of Duisburg-Essen Essen Germany

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Biologically inspired hierarchical model for traffic sign recognition 24

Biologically inspired hierarchical model for traffic sign re...

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24th International Conference on computer Theory and Applications, ICCTA 2014

作者： Aziz, Amr Abdel Imam, Ibrahim F. Shoukry, Amin College of Computing and Information Technology Arab Academy for Science Technology and Maritime Transport Cairo Egypt Computer and Systems Engineering Dept. Faculty of Engineering Alexandria University Alexandria Egypt

ISBN: (纸本)9781479974757

In this research, a study of the Hierarchical Temporal Memory (HTM) model using the Numenta Implementation 'Nupic v1.7' and an investigation of its performance in solving the German traffic sign recognition task using standard benchmark data is conducted. Its performance is compared to that of a state of the art Multi-Column Deep Neural Network (MCDNN) that has been proved to exceed the human recognition accuracy for the same task. © 2014 IEEE.

关键词： Image classification

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Contextual combinatorial bandit and its application on diversified online recommendation 14

Contextual combinatorial bandit and its application on diver...

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14th SIAM International Conference on Data Mining, SDM 2014

作者： Qin, Lijing Chen, Shouyuan Zhu, Xiaoyan State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Dept. of Computer Science and Technology Tsinghua University Beijing China Dept. of Computer Science and Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

ISBN: (纸本)9781510811515

Recommender systems are faced with new challenges that are beyond traditional techniques. For example, most traditional techniques are based on similarity or overlap among existing data, however, there may not exist sufficient historical records for some new users to predict their preference, or users can hold diverse interest, but the similarity based methods may probably over-narrow it. To address the above challenges, we develop a principled approach called contextual combinatorial bandit in which a learning algorithm can dynamically identify diverse items that interest a new user. Specifically, each item is represented as a feature vector, and each user is represented as an unknown preference vector. On each of n rounds, the bandit algorithm sequentially selects a set of items according to the item-selection strategy that balances exploration and exploitation, and collects the user feedback on these selected items. A reward function is further designed to measure the quality (e.g. relevance or diversity) of the selected set based on observed feedback, and the goal of the algorithm is to maximize the total rewards of n rounds. The reward function only needs to satisfy two mild assumptions that is general enough to accommodate a large class of nonlinear functions. To solve this bandit problem, we provide algorithm that achieves Õ(√n) regret after playing n rounds. Experiments conducted on real-wold movie recommendation dataset demonstrate that our approach can effectively address the above challenges and hence improve the performance of recommendation task. Copyright © SIAM.

关键词： Data mining

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Mining contrast subspaces

Mining contrast subspaces

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18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014

作者： Duan, Lei Tang, Guanting Pei, Jian Bailey, James Dong, Guozhu Campbell, Akiko Tang, Changjie School of Computer Science Sichuan University China School of Computing Science Simon Fraser University Canada Dept. of Computing and Information Systems University of Melbourne Australia Dept. of Computer Sci. and Engr. Wright State University United States Pacific Blue Cross Canada State Key Laboratory of Software Engineering Wuhan University China

ISBN: (纸本)9783319066073

In this paper, we tackle a novel problem of mining contrast subspaces. Given a set of multidimensional objects in two classes C+ and C - and a query object o, we want to find top-k subspaces S that maximize the ratio of likelihood of o in C+ against that in C -. We demonstrate that this problem has important applications, and at the same time, is very challenging. It even does not allow polynomial time approximation. We present CSMiner, a mining method with various pruning techniques. CSMiner is substantially faster than the baseline method. Our experimental results on real data sets verify the effectiveness and efficiency of our method. © 2014 Springer International Publishing.

关键词： Mining

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Malware detection in big data using fast pattern matching: A hadoop based comparison on GPU 2

Malware detection in big data using fast pattern matching: A...

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2nd International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2014

作者： Panigrahi, Chhabi Rani Tiwari, Mayank Pati, Bibudhendu Prasath, Rajendra Dept. of Information Technology C.V. Raman College of Engineering Bhubaneswar Odisha752 054 India Dept. of Computer Science and Engineering C.V. Raman College of Engineering Bhubaneswar Odisha752 054 India Business Information Systems University College Cork Cork Ireland

ISBN: (纸本)9783319138169

In big data environment, hadoop stores the data in distributed file systems called hadoop distributed file system and process the data using parallel approach. When the cloud users store unstructured data in cloud storage, it becomes very important for cloud providers to secure those data. To provide malware security, cloud service providers should scan the whole contents of the database, which is a very time intensive job. It may even take days to complete the tasks. The main aim of the proposed work is to reduce the processing time by introducing Graphics Processing Unit (GPU) in hadoop cluster. The proposed work integrates two text pattern matching algorithms with the map-reduce programming model for faster detection of malware in big data. The results of our study indicate that use of GPU decreases the processing time of text pattern matching algorithms in big data hadoop. © Springer International Publishing Switzerland 2014.

关键词： Graphics processing unit

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A spatio-temporal multimedia big data framework for a large crowd

A spatio-temporal multimedia big data framework for a large ...

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IEEE International Conference on Big Data

作者： Bilal Sadiq Faizan Ur Rehman Akhlaq Ahmad Md. Abdur Rahman Sohaib Ghani Abdullah Murad Saleh Basalamah Ahmad Lbath KACST GIS Technology Innovation Center Umm Al Oura University Saudi Arabia Dept. of Computer Science University of Grenoble Alpes France College of Engineering and Islamic Architecture Umm Al Qura University Saudi Arabia Kulliyah of Information and Communication Technology International Islamic University Kuala Lumpur Malaysia College of Computer and Information Systems Umm Al Qura University Saudi Arabia Innovation and Entrepreneurship Institute Umm Al Qura University Saudi Arabia

Crowdsourced multimedia data poses several challenges when it is collected, stored, indexed, retrieved, and visualized. Examples of crowd source multimedia data are social sensors, vehicle sensors, physical sensors, human sensors, etc. Analyzing such multimodal and diversified crowdsourced data provides very rich understanding about the need of individuals within a crowd. Such understanding makes it possible to tailor services to individuals' needs, also called context-aware services. In this paper, we propose a spatial multimedia big data framework that can collect multimedia data from 1) a very large crowd equipped with multi-sensory smartphones, 2) vehicles, and 3) social networks. A set of multimedia services are offered to users to support their spatio-temporal activities. These include but not limited to 1) simple user interfaces to utilize multimedia services for instant guidance, 2) navigation to points of interests (POI), and 3) efficient and cost effective intra-city rides to users. The big data framework is designed to handle a very large number of multimedia spatio-temporal queries in real-time. The system is a pilot project and will be deployed during the event of Hajj 2015 when over three million pilgrims from all over the world will visit Makkah, Saudi Arabia to perform their Hajj rituals.

关键词： Multimedia communication Big data Sensors Streaming media Multimedia databases Crowdsourcing Semantics

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A proof-of-concept study for predicting the region of atherosclerotic plaque development based on plaque growth modeling in carotid arteries

A proof-of-concept study for predicting the region of athero...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Antonis I. Sakellarios Paschalis Bizopoulos Kostas Stefanou Lambros S. Athanasiou Michail I. Papafaklis Christos V. Bourantas Katerina K. Naka Lampros K. Michalis Dimitrios I. Fotiadis the Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering University of Ioannina GR 45110 the Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens (NTUA) GR-157 73 Zografou Athens Greece the Institute of Molecular Biology and Biotechnology Dept. of Biomedical Research FORTH GR45110 Ioannina Greece the Michaelideion Cardiac Center Dept. of Cardiology in Medical School University of Ioannina GR 45110 Ioannina Greece the Dept. of Interventional Cardiology Erasmus MC Thoraxcenter Rotterdam The Netherlands the Biomedical Research Institute - FORTH University Campus of Ioannina 45110 Ioannina Greece

ISBN: (纸本)9781424492695

In this work, we present a computational model for plaque growth utilizing magnetic resonance data of a patient's carotid artery. More specifically, we model blood flow utilizing the Navier-Stokes equations, as well as LDL and HDL transport using the convection-diffusion equation in the arterial lumen. The accumulated LDL in the arterial wall is oxidized considering the protective effect of HDL. Macrophages recruitment and foam cells formation are the final step of the proposed multi-level modeling approach of the plaque growth. The simulated results of our model are compared with the follow-up MRI findings in 12 months regarding the change to the arterial wall thickness. WSS and LDL may indicate potential regions of plaque growth (R~2=0.35), but the contribution of foam cells formation, macrophages and oxidized LDL increased the prediction significantly (R~2=0.75).

关键词： LDL HDL MRI Low-Density Lipoproteins Hardware design languages High-density lipoproteins Carotid Arteries atherosclerotic plaque convection-diffusion equation Foam Cells C7orf49 gene Magnetic Resonance Imaging oxidized low density lipoprotein Blood Flow Blood Circulation Arteriosclerosis Computational modeling

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Path Metrics for Lower Throughput Fluctuation for Video Streaming Service in Wireless Mesh Networks

Path Metrics for Lower Throughput Fluctuation for Video Stre...

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Asia-Pacific Conference on Communications

作者： Hiromu Asahina Hisao Yamamoto Kentaroh Toyoda Iwao Sasase Dept. of Information and Computer Science Keio University 3-14-1 Hiyoshi Kohoku Yokohama 223-8522 Japan Dept. of Systems Information Engineering Tokyo City University 1-28-1 Tamadutsumi Setagaya Tokyo 158-8557 Japan

ISBN: (纸本)9781467366533

The video streaming service over Wireless Mesh Networks (WMNs) is an attractive feature for live streaming and video conversation when disaster occurs. The path construction with the conventional metrics e.g., throughput, latency, or packet loss rate, suffers from the repeated waiting time due to the CSMA/CA since paths are concentrated on nodes with good metric. As a consequence, it brings about throughput fluctuation of video streaming service. We propose two metrics that reflect on the magnitude of CSMA/CA interference around a node in order to select a path that the throughput of video streaming session will get stable. The first metric is calculated from the number of received Request To Send (RTS)/Clear To Send (CTS) frames. Since the number of RTS/CTS reflects on the frequency of the packet transmission around a node, a source node can chooses a path which does not make a node waiting for constant time due to the CSMA/CA on the existing path that might use streaming service. The second metric uses the number of neighbor nodes and we set the larger metric value as more nodes exist. The idea comes from the fact that a node which has few neighbor nodes does not much interfere other established paths. The proposed metrics can be easily installed into Hybrid Wireless Mesh Protocol (HWMP) which is a de facto standard path selection protocol defined in IEEE802.11s. We show that the proposed metrics can achieve lower rate of throughput fluctuation than that of conventional metric by using the networks simulator Qualnet.

关键词： WMNs RTS CTS

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2014 Conference on Research in Adaptive and Convergent systems, RACS 2014

作者： Kim, TaeGuen Park, Jung Bin Cho, In Gyeom Im, Eul Gyu Kang, Boojoong Kang, SooYong Dept. of Computer and Software Hanyang University Seoul Korea Republic of Div. of Computer Science and Engineering Hanyang University Seoul Korea Republic of Institute of Electronics Communications and Information Technology Queen's University of Belfast Belfast United Kingdom

ISBN: (纸本)9781450330602

The number of malware has sharply increased over years, and it caused various damages on computing systems and data. In this paper, we propose techniques to detect malware variants. Malware authors usually reuse malware modules when they generate new malware or malware variants. Therefore, malware variants have common code for some functions in their binary files. We focused on this common code in this research, and proposed the techniques to detect malware variants through similarity calculation of user-defined function. Since many malware variants evade malware detection system by transforming their static signatures, to cope with this problem, we applied pattern matching algorithms for DNA variations in Bioinformatics to similarity calculation of malware binary files. Since the pattern matching algorithm we used provides the local alignment function, small modification of functions can be overcome. Experimental results show that our proposed method can detect malware similarity and it is more resilient than other methods. © 2014 ACM.

关键词： Malware

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Towards energy-aware optimisation of business processes

Towards energy-aware optimisation of business processes

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3rd International Conference on Smart Grids and Green IT systems, SMARTGREENS 2014

作者： López, Beatriz Ghose, Aditya Savarimuthu, Tony Nowostawski, Mariusz Winikoff, Michael Cranefield, Stephen EXiT research group University of Girona Girona Spain School of Computer Science and Software Engineering University of Wollongong Wollongong Australia Dept. of Information Science University of Otago Dunedin New Zealand Faculty of Computer Science and Media Technology Gjøvik University College Gjøvik Norway

ISBN: (纸本)9789897580253

Time dependent energy tariffs are a matter of concern to managers in organisations, who need to rethink how to allocate resources to business processes so that they take into account energy costs. However, due to the time-dependent costs, the resource optimisation problem needs to be redesigned. In this paper we formalise the energy-aware resource allocation problem, including time-dependent variable costs;and present a case study in which an auction mechanism is used to find a solution. Our results show how the choice of cost (energy, monetary, or duration) affects the schedules obtained.

关键词： Constrained optimization

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