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A simulation study of evaluation heuristics for tug fleet optimisation algorithms 4th

A simulation study of evaluation heuristics for tug fleet op...

引用

4th International Conference on Operations Research and Enterprise Systems, ICORES 2015

作者： Bye, Robin T. Schaathun, Hans Georg Software and Intelligent Control Engineering Laboratory Aalesund University College Postboks 1517 Åalesund6025 Norway

ISBN: (纸本)9783319276793

Tug fleet optimisation algorithms can be designed to solve the problem of dynamically positioning a fleet of tugs in order to mitigate the risk of oil tanker drifting accidents. In this paper, we define the 1D tug fleet optimisation problem and present a receding horizon genetic algorithm for solving it. The algorithm can be configured with a set of cost functions such that each configuration effectively constitute a unique tug fleet optimisation algorithm. To measure the performance, or merit, of such algorithms, we propose two evaluation heuristics and test them by means of a computational simulation study. Finally, we discuss our findings and some of our related work on a parallel implementation and an alternative 2D nonlinear mixed integer programming formulation of the problem. © Springer International Publishing Switzerland 2015.

关键词： Genetic algorithms

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Efficient triangle listing for billion-scale graphs

Efficient triangle listing for billion-scale graphs

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IEEE International Conference on Big Data

作者： Hao Zhang Yuanyuan Zhu Lu Qin Hong Cheng Jeffrey Xu Yu †State Key Laboratory of Software Engineering Wuhan University China Centre for Quantum Computation and Intelligent Systems University of Technology Sydney Australia The Chinese University of Hong Kong Hong Kong China

ISBN: (纸本)9781467390064

This paper addresses the classical triangle listing problem, which aims at enumerating all the tuples of three vertices connected with each other by edges. This problem has been intensively studied in internal and external memory, but it is still an urgent challenge in distributed environment where multiple machines across the network can be utilized to achieve good performance and scalability. As one of the de facto computing methodologies in distributed environment, MapReduce has been used in some of existing triangle listing algorithms. However, these algorithms usually need to shuffle a huge amount of intermediate data, which seriously hinders the scalability on large scale graphs. In this paper, we propose a new triangle listing algorithm in MapReduce, FTL, which utilizes a light weight data structure to substantially reduce the intermediate data transferred during the shuffle stage, and also is equipped with multiple-round techniques to ease the burden on memory and network bandwidth when dealing with graphs at billion scale. We prove that the size of the intermediate data can be well bounded near to the number of triangles in the graph. To further reduce the shuffle size in each round, we also devise a compact data structure to store the intermediate data, which can save space up to 2/3. The extensive experimental results show that our algorithms outperform existing competitors by several times on large real world graphs.

关键词： Partitioning algorithms Data structures Algorithm design and analysis Scalability Big data Clustering algorithms Twitter

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A Multi-level intelligent Selective Encryption Control Model for Multimedia Big Data Security in Sensing System with Resource Constraints

A Multi-level Intelligent Selective Encryption Control Model...

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IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Chen Xiao Lifeng Wang Zhu Jie Tiemeng Chen Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China Department of Electronic and Information Engineering Beijing Electronic Science and Technology Institute Beijing China

ISBN: (纸本)9781509009473

The multimedia big data in multimedia sensing and other IoT (Internet of Things) systems are high-volume, real-time, dynamic and heterogeneous. These characteristics lead to new challenges of data security. When computation and power resources in some IoT nodes are very scarce, these challenges become more serious that complex data security process on multimedia data is restricted by the aforementioned limited resources. Hence, the confidentiality of multimedia big data under resources constraints is investigated in this paper. Firstly, the growth trend of data volume compared with computational resources is discussed, and an analysis model for multimedia data encryption optimization is proposed. Secondly, a general-purpose lightweight speed tunable video encryption scheme is introduced. Thirdly, a series of intelligent selective encryption control models are proposed. Fourthly, the performance of proposed schemes is evaluated by experimental analyses and proves that schemes are effective enough to support real-time encryption of multimedia big data. Additionally, in the age of big data and cloud computing, the aforementioned analysis method can also be applied to other systems with limited resources.

关键词： Encryption Multimedia communication Streaming media Internet of things Data models

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SiC devices performance overview in EV DC/DC converter: A case study in a Nissan Leaf

SiC devices performance overview in EV DC/DC converter: A ca...

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IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Y. Attia A. Abdelrahman M. Hamouda M. Youssef Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China Department of Electronic and Information Engineering Beijing Electronic Science and Technology Institute Beijing China

ISBN: (纸本)9781509012732

This paper presents the technical and economical merits of using low losses fast switching Silicon Carbide (SiC) accumulated gate field effect transistor (ACCUFET) switches in comparison with a Hybrid module of Silicon (Si) IGBT with anti-parallel schottky barrier diode (SBD) in DC/DC converter applications of the Nissan Leaf electric vehicle (EV) motor drive. The performance of the car, at steady state conditions, is studied at different temperatures. The power losses, current, voltage, torque and speed results are given. The results showed lower total switching power losses with the SiC ACCUFET. This reduction in losses was recorded at different switching frequencies in comparison to the hybrid switch. The fast switching of SiC Trench ACCUFET reduces current-voltage cross-over losses and enables high frequency operation thus achieving high record efficiency. The high frequency operation will result in a smaller foot print of the converter together with a weight reduction; thus making the car lighter. It is expected that a lighter car will result in a longer range Nissan Leaf with the same battery. Increasing the car mileage of the battery and lowering the cost of magnetic components in the EV will surpass the higher cost of the SiC ACCUFET from an economical point of view.

关键词： Switches Silicon carbide Silicon Insulated gate bipolar transistors Voltage control

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Idea creation of creative computing based on embedding features and ontology 2016

Idea creation of creative computing based on embedding featu...

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3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016

作者： Zhang, Fuquan Mao, Zijing Ding, Gangyi Zhang, Rui Lai, Junjiang School of software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Ji Yuan Ju Yuan Jin Shan Fuzhou Fujian350121 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States Software Building Beijing Institute of Technology 5 South Zhongguancun Street Haidian Beijing100081 China Department of Mathematics Minjiang University Fuzhou No.150 Binzhou Road Jin Shan Fuzhou Fujian350108 China

ISBN: (纸本)9781450341295

This paper used clustering to embed features and use ontology to simulate the process of idea creation from human brain. All the technologies are applied on the frame of creative computing. We are try to display the emergence, the self-organization, the self-coordination of idea creation process of human brain. By creative computing we will try to discover how the idea coming from step by step. From this paper, you will see the process in five steps from blurry motivation to clear creative idea. © 2016 ACM.

关键词： Ontology

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VIDEO SUPER-RESOLUTION BASED ON NONLINEAR MAPPING AND PATCH SIMILARITY

VIDEO SUPER-RESOLUTION BASED ON NONLINEAR MAPPING AND PATCH ...

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2016 4th IEEE International Conference on Cloud Computing and Intelligence Systems（IEEE CCIS2016）

作者： Linghui Li Junping Du Meiyu Liang JangM yung Lee Luoming Meng Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications Department of Electronics Engineering Pusan National University State Key Laboratory Network & Switching Technology Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509012572

Aiming at recovering lost detailed information in low-resolution videos, a novel video super-resolution algorithm based on nonlinear mapping and patch similarity was proposed in this paper. Taking advantage of the strong fitting ability of the convolutional neural network for the nonlinear relationship, this algorithm utilizes the learned reconstruction parameters to pad missing structures and make the low-resolution video approach to the ground truth. However, it is unavoidable to introduce irrelevant information and amplify noises in this process. The patch similarity is imported to improve the spatial-temporal consistency and anti-noise ability of this algorithm. Moreover, instead of considering the nonlocal self-similarity only, this algorithm combines the nonlocal external sparsity and spatial-temporal similarity to enrich the prior information. All these patch similarities are used to optimize the intermediate video achieved from the mapping process. Experimental results demonstrated that the proposed algorithm achieves a competitive super-resolution quality on both the subjective and the objective evaluations, when compared to other state-of-the-art algorithms.

关键词： video super-resolution reconstruction convolutional neural network nonlocal similarity

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A computer-automated design tool for intelligent virtual prototyping of offshore cranes 29

A computer-automated design tool for intelligent virtual pro...

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29th European Conference on Modelling and Simulation, ECMS 2015

作者： Bye, Robin T. Osen, Ottar L. Pedersen, Birger Skogeng Software and Intelligent Control Engineering Laboratory Faculty of Engineering and Natural Sciences Aalesund University College Postboks 1517 ÅlesundNO-6025 Norway ICD Software AS Hundsværgata 8 ÅlesundNO-6008 Norway

ISBN: (纸本)9780993244001

In close collaboration with the maritime industry, virtual prototyping with maritime application has been an important research topic for Aalesund University College for some years. In this paper, we describe the development of a computer-automated design tool for intelligent virtual prototyping of offshore cranes. Our work is part of a research project funded by the Research Council of Norway and takes place in close cooperation with two partners from the maritime industry. A literature review of virtual prototyping, computer-automated design, and modelling and simulation of offshore cranes sets the stage for the description of a design tool whose main components consist of a computational model, a simulator, and a genetic algorithm. We show how domain-specific constraints can be accounted for in conjunction with an automated optimisation procedure of design parameters to yield crane specifications that closely match the desired design criteria. Limitations of slewing rings and hydraulic cylinders are of particular importance in offshore crane design and are used as an example of the multitude of design calculations that form the computational model. Being work in progress, we report on completed parts and the work that remains. © ECMS Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova (Editors).

关键词： Genetic algorithms

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Sparse Tensor Discriminative Locality Alignment for Gait Recognition

Sparse Tensor Discriminative Locality Alignment for Gait Rec...

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International Joint Conference on Neural Networks

作者： Nengwen Zhao Lefei Zhang Bo Du Liangpei Zhang Dacheng Tao Jane You State Key Laboratory of Software Engineering School of Computer Wuhan University Department of Computing The Hong Kong Polytechnic University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781509006212

Gait recognition is a rising biometric technology which aims to distinguish people purely through the analysis of the way they walk, while the problem is that the dimensionality of the gait data is too high, so it is necessary to carry on dimensionality reduction task. Up to date, in the area of computer vision and pattern recognition, various dimensionality reduction algorithms have been employed for gait data, including the conventional vector representation based methods principal components analysis (PCA) and, locality preserving projection (LPP), and the recently proposed multi-linear subspace learning based approaches such as multilinear principal component analysis (MPCA). In this paper, inspired by the advantages of the tensor representation and manifold learning, we propose a novel sparse tensor discriminative locality alignment for human gait feature representation and dimensionality reduction algorithm, and sub-sequently apply the refined feature for gait recognition by a lazy classifier of the KNN. The proposed method adopts sparse multi-way projection based on the high-order version of discriminative locality alignment, by which the class separability is enhanced and the potential model overfitting is simultaneously avoided. Extensive experiments on the University of South Florida (USF) HumanID Gait Database show that the proposed method achieves better recognition rate compared with some existing classical dimensionality reduction algorithms.

关键词： Gait recognition dimensionality reduction images computer vision Tensor Locomotion Gait principal components analysis vector representation Alignment

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Toward a Semantic Cache Supporting Version-Based Consistency

Toward a Semantic Cache Supporting Version-Based Consistency

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International Conference on Complex, intelligent and software Intensive Systems, CISIS

作者： Zhe Yang Kun Ma Jialin Zhong School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China Shandong: Provincial Key Laboratory of Software Engineering Shandong University Jinan China Shool of Automation and Electrical Engineering University of linan Jinan China

ISBN: (纸本)9781509009886

In an era of mobile internet and big data, how to make the data access more efficient is worth researching because the mobile computing environments have some limitations such as the narrow bandwidth, the frequent disconnections of network and so on. To improve the response time of query, a good cache system is of vital importance. Besides, a good cache consistency method is essential to ensure the correctness. In this paper, a semantic cache supporting version-based consistency is proposed. This cache mainly have two advantages. On one hand, it can obviously improve the response time of query and the hit ratio of the cache. On the other hand, the version-based consistency enhances the stability of the system especially in high-concurrency situations. Several experiments has been carried out and the results are presented to show the performance of the cache.

关键词： Semantics Servers Mobile computing Algorithm design and analysis Databases Time factors Concurrent computing

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Novel Detection Service Method for Moving Object in IOT

Novel Detection Service Method for Moving Object in IOT

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2016 3rd International Conference on Materials engineering,Manufacturing Technology and Control(ICMEMTC 2016)

作者： Jie Chen Degan Zhang School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education

In embedded Internet of Things(IOT) environment, there are the troubles such as complex background, illumination changes, shadows and other factors for detecting moving object, so we put forward a new detection service method through mixing Gaussian Mixture Model(GMM), edge detection service method and continuous frame difference method in this paper. In time domain, the new method uses GMM to model and updates the background. In spatial domain, it uses the hybrid detection service method which mixes edge detection service method, continuous frame difference method and GMM to get initial contour of moving object, and gets ultimate moving object. This method not only can well adapt to the illumination gradients and background disturbance occurred on scene, but also can well solve some problems such as inaccurate target detection, incomplete edge detection, cavitation and ghost which usually appears in traditional method. As experimental result showing, this method holds better real-time and robustness. It is not only easily implemented, but also can accurately detect moving object.

关键词： GMM embedded IOT moving object detection service

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