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共 1136 条记录，以下是781-790 订阅

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A preliminary study of the RADOE project

A preliminary study of the RADOE project

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IEEE conference on Cybernetics and Intelligent Systems

作者： Haibin Yan YuanRui Yang Renjun Li Masood Dehghan Marcelo H. Ang Advanced Robotics Center and SIMTech-NUS Joint Laboratory (Industrial Robotics) National University of Singapore Singapore Institute for Infocomm Research (I2R) Singapore Department of Mechanical Engineering National University of Singapore Singapore

ISBN: (纸本)9781467373395

Robotic softwares with convenient operation and programming are desirable to increase the efficiency and efficacy of industrial robots which work in complex and fickle environments. To develop such softwares, we aim to develop a new robotic software called RADOE (Robot Application Development and Operating Environment), under the support from the science and engineering Research Council, Singapore. In this paper, we introduce some of our preliminary results of the RADOE project, particularly on the system architecture design. the key objective of our RADOE is to define robotic tasks in a simple way, communicate with different industrial robots and control them under varying environmental conditions. To achieve this, we employ a hierarchical system structure with state machines to make it modular, extendible, robust, and maintainable. Experimental results on KUKA LBR iiwa robot show that RADOE combined with the developed system architecture demonstrates good performance for motion planning and tasks execution.

关键词： Service robots Robot kinematics Planning Software Graphical user interfaces programming

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Traffic-Aware Application Mapping for Network-on-Chip Based Multiprocessor System-on-Chip

Traffic-Aware Application Mapping for Network-on-Chip Based ...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Lei Yang Weichen Liu Weiwen Jiang Wei Zhang Mengquan Li Juan Yi Duo Liu Edwin H.-M. Sha College of Computer Science Chongqing University Chongqing China Dept. of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong SAR China

Network on Chip (NoC) has become a promising solution for the communication paradigm of the next-generation multiprocessor system-on-chip (MPSoC). As communication has become an integral part of on-chip computing, researchers are paying more attention to its implementation and optimization. Traditional techniques that model inter-processor communication inaccurately will lead to unexpected runtime performance, which is on average 90.8% worse than the predicted results based on an observation. In this paper, we present an application mapping and scheduling technique for NoC-based MPSoCs that integrates fine-grain optimization on inter-processor communications with the objective of minimizing the schedule length. A communication model is proposed to address properly the latency of inter-processor communication with network contention. Performance evaluation results show that solutions obtained by the proposed technique can generate realistic performance that is on average 34.7% higher than traditional techniques, and the Integer-Linear programming (ILP) based approach can outperform the state-of-the-art heuristic algorithms by 31.1%. A case study on H.264 HDTV decoder shows that our approach achieves 22.8% improvement in prediction accuracy, 20.9% improvement in performance and 40% reduction in the number of network contentions.

关键词： Schedules Scheduling Processor scheduling Optimization Program processors System-on-chip Heuristic algorithms

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SmartBackup: An Efficient and Reliable Backup Strategy for Solid State Drives with Backup Capacitors

SmartBackup: An Efficient and Reliable Backup Strategy for S...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Min Huang Yi Wang Liyan Qiao Duo Liu Zili Shao School of Electrical Engineering and Automation Harbin Institute of Technology Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen University College of Computer Science Chongqing University Department of Computing The Hong Kong Polytechnic University

ISBN: (纸本)9781479989386

Unpredictable power outages in NAND flashbased Solid State Drives (SSDs) may cause system failure or reliability problems. Capacitors are widely adopted as the interim power supplier when power interruption happens. However, since the energy provided by backup capacitors is limited, and the capacitance of a capacitor will gradually degrade with time, it is imperative to improve the efficiency and reliability of the backup process for SSDs with capacitors. this paper presents a novel backup scheme called SmartBackupfor MLC NAND flash-based SSDs with backup capacitors. In SmartBackup, by exploiting the feature of the discharge process of capacitors, all available SSD channels are fully utilized and dynamically adjusted based on the available voltage, so data can be efficiently stored in a reliable manner. Moreover, in SmartBackup, to write data in a time/energyefficient manner with better reliability, we adopt a fast and reliable programming strategy by only writing LSB (Least Significant Bit) pages in MLC NAND flash. To the best of our acknowledge, this is the first work to jointly utilize the property of the multi-page architecture of MLC NAND flash and the discharge characteristic of capacitors to improvethe efficiency and reliability of the backup process in SSDswith backup capacitors. the experimental results show thatSmartBackup can effectively accelerate the backup processand improve the reliability.

关键词： Capacitors Ash Reliability programming Arrays Acceleration Discharges (electric)

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international conference on Modelling, Identification and Control (ICMIC)

作者： Nan Pan Jingshu Yang Zeguang Yi Yi Liu Faculty of Mechanical & Electrical Engineering Kunming University of Science and Technology Kunming Yunnan Province China Kunming SNLab Tech Co. Ltd. Xishan District Kunming Yunnan Province China

It's usually not easy to compare linear toolmarks quickly and quantitatively with the current image processing and three-dimensional scanning methods. In order to deal with these kinds of problems, a similarity matching algorithm for laser detection signals of linear marks is proposed. In this method, locally weighted scatterplot smoothing algorithm is used to performs noise reduction on the surface signals of linear marks that are picked up by a laser displacement sensor; followed by the identification of the features of `thick and consistent' trends in the signal data. then the feature vectors are quantized by cosine vector curve fitting to individually calculate the spatial distance of the sample. Results from similarity comparison tests of actual cutting marks validate the accuracy and validity of proposed method.

关键词： Feature extraction Curve fitting Smoothing methods Mathematical model Fitting Surface emitting lasers Dynamic programming

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Control of three-phase grid-connected microgrids using artificial neural networks

Control of three-phase grid-connected microgrids using artif...

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international Joint conference on Computational Intelligence (IJCCI)

作者： Shuhui Li Xingang Fu Ishan Jaithwa Eduardo Alonso Michael Fairbank Donald C. Wunsch Department of Electrical and Computer Engineering University of Alabama Tuscaloosa AL U.S.A. Department of Computer Science City University London London U.K. Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO U.S.A.

ISBN: (纸本)9781509019687

A microgrid consists of a variety of inverter-interfaced distributed energy resources (DERs). A key issue is how to control DERs within the microgrid and how to connect them to or disconnect them from the microgrid quickly. this paper presents a strategy for controlling inverter-interfaced DERs within a microgrid using an artificial neural network, which implements a dynamic programming algorithm and is trained with a new Levenberg-Marquardt backpropagation algorithm. Compared to conventional control methods, our neural network controller exhibits fast response time, low overshoot, and, in general, the best performance. In particular, the neural network controller can quickly connect or disconnect inverter-interfaced DERs without the need for a synchronization controller, efficiently track fast-changing reference commands, tolerate system disturbances, and satisfy control requirements at grid-connected mode, islanding mode, and their transition.

关键词： Neural networks Voltage control Microgrids Density estimation robust algorithm Training Inverters Machine vector control

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A heuristic solution for noisy image segmentation using Particle Swarm Optimization and Fuzzy clustering

A heuristic solution for noisy image segmentation using Part...

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international Joint conference on Computational Intelligence (IJCCI)

作者： Saeed Mirghasemi Ramesh Rayudu Mengjie Zhang School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand

ISBN: (纸本)9781509019687

Introducing methods that can work out the problem of noisy image segmentation is necessary for real-world vision problems. this paper proposes a new computational algorithm for segmentation of gray images contaminated with impulse noise. We have used Fuzzy C-Means (FCM) in fusion with Particle Swarm Optimization (PSO) to define a new similarity metric based on combining different intensity-based neighborhood features. PSO as a computational search algorithm, looks for an optimum similarity metric, and FCM as a clustering technique, helps to verify the similarity metric goodness. the proposed method has no parameters to tune, and works adaptively to eliminate impulsive noise. We have tested our algorithm on different synthetic and real images, and provided quantitative evaluation to measure effectiveness. the results show that, the method has promising performance in comparison with other existing methods in cases where images have been corrupted with a high density noise.

关键词： Noise measurement Image segmentation Clustering algorithms Linear programming Particle swarm optimization Heuristic algorithms Partitioning algorithms

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Multilinear objective function-based clustering

Multilinear objective function-based clustering

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international Joint conference on Computational Intelligence (IJCCI)

作者： Giovanni Rossi Departments of Computer Science and Engineering - DISI and Mathematics University of Bologna Bologna Italy

ISBN: (纸本)9781509019687

the input of most clustering algorithms is a symmetric matrix quantifying similarity within data pairs. Such a matrix is here turned into a quadratic set function measuring cluster score or similarity within data subsets larger than pairs. In general, any set function reasonably assigning a cluster score to data subsets gives rise to an objective function-based clustering problem. When considered in pseudo-Boolean form, cluster score enables to evaluate fuzzy clusters through multilinear extension MLE, while the global score of fuzzy clusterings simply is the sum over constituents fuzzy clusters of their MLE score. this is shown to be no greater than the global score of hard clusterings or partitions of the data set, thereby expanding a known result on extremizers of pseudo-Boolean functions. Yet, a multilinear objective function allows to search for optimality in the interior of the hypercube. the proposed method only requires a fuzzy clustering as initial candidate solution, for the appropriate number of clusters is implicitly extracted from the given data set.

关键词： Maximum likelihood estimation Silicon Clustering algorithms Phase change materials Symmetric matrices Search problems Linear programming

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An Agglomerative Hierarchical Clustering Algorithm Based on Global Distance Measurement

An Agglomerative Hierarchical Clustering Algorithm Based on ...

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IEEE international Symposium on Information (IT) in Medicine and Education, ITME

作者： Fang Liu Yongqing Wei Min Ren Xiuyan Hou Yingying Liu School of Information Science and Engineering Shandong Normal University Jinan China Shandong Police College Jinan Shandong CN School of Mathematics and Quantitative Economics Shandong University of Finance and Economics Jinan China

the accuracy of existing hierarchical clustering algorithms in distance measurement is not high, in order to improve it, this paper proposes a condensing hierarchical clustering algorithm based on global distance measurement. this method puts forward the concept of global distance and local distance for the distance measurement, effectively depicting the distance between the data objects, in the merger of the clusters, it also proposes two new concepts: the cohesion within the class and the separability between classes, at the same time, on the basis of these two concepts, it constructs an objective function and maximizes the objective function to reach the purpose that the cohesion within the class be as large as possible, the separability between classes be as small as possible, in order to obtain the optimal clustering results. the experimental accuracy of this algorithm is higher than traditional hierarchical clustering algorithms both on the artificial data and real data sets, which shows that the algorithm has higher clustering validity.

关键词： Clustering algorithms Euclidean distance Algorithm design and analysis Linear programming Merging Iris

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Fast Numerical Evaluation for Symbolic Expressions in Java

Fast Numerical Evaluation for Symbolic Expressions in Java

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Yueming Liu Peng Zhang Meikang Qiu Department of Mathematics University of Texas at Arlington Arlington TX United States Biomedical Engineering Department Stony Brook University Stony Brook NY United States Computer Science Department Pace University New York NY United States

ISBN: (纸本)9781479989386

the symbolic-numeric computation has been extensively developed in scientific computing for experimenting mathematics in numerical programs, like in optimization problems and finite element methods. Many software and libraries have been developed to support symbolic-numeric computation especially in the recent years. However, most of the implementations are cumbersome and inefficient for numerically evaluating symbolic expressions. the popular implementation chooses the way that generates C/C++/FORTRAN source codes for symbolic expressions and compiles the source files using the external compilers. the compiled machine codes are then linked back to the symbolic manipulation language environment. thi sprocess suffers from slow compilation and significant overhead of external function calls. To address this problem, this paper presents a handy approach that provides fast numerical evaluation for symbolic expressions in Java. In our approach, Java bytecode is generated in memory for symbolic expressions and further Just-In-Time (JIT) compiled to machine codes onJava Virtual Machine (JVM) at runtime. We have developedSymJava (https://***/yuemingl/SymJava) to implement our approach and tested a range of benchmark problems. the results show that SymJava is 1~3 orders of magnitude faster than the existing implementations including Matlab, Mathematica, Sage, theano and SymPy. Additionally, SymJava offers a human friendly programming style for symbolic expressions by overloading operators in Java. Our approach opens up a new avenue for the development of next generation symbolic-numeric software.

关键词： Java Libraries MATLAB Benchmark testing Mathematics Runtime

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Green Energy Aware Avatar Migration Strategy in Green Cloudlet Networks

Green Energy Aware Avatar Migration Strategy in Green Cloudl...

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IEEE international conference on Cloud Computing Technology and science (CloudCom)

作者： Xiang Sun Nirwan Ansari Qiang Fan Department of Electrical & Computer Engineering New Jersey Institute of Technology Newark NJ USA

We propose a Green Cloudlet Network (GCN) architecture to provide seamless Mobile Cloud Computing (MCC) services to User Equipments (UEs) with low latency in which each cloudlet is powered by both green and brown energy. Fully utilizing green energy can significantly reduce the operational cost of cloudlet providers. However, owing to the spatial dynamics of energy demand and green energy generation, the energy gap among different cloudlets in the network is unbalanced, i.e., some cloudlets' energy demands can be fully provided by green energy but others need to utilize on-grid energy (i.e., brown energy) to satisfy their energy demands. We propose a Green-energy awarE Avatar migRation (GEAR) strategy to minimize the on-grid energy consumption in GCN by redistributing the energy demands via Avatar migration among cloudlets according to cloudlets' green energy generation. Furthermore, GEAR ensures the Service Level Agreement (SLA) in terms of the maximum Avatar propagation delay by avoiding Avatars hosted in the remote cloudlets. We formulate the GEAR strategy as a mixed integer linear programming problem, which is NP-hard, and thus apply the Branch and Bound search to find its sub-optimal solution. Simulation results demonstrate that GEAR can save on-grid energy consumption significantly as compared to the Follow me AvataR (FAR) migration strategy, which aims to minimize the propagation delay between an UE and its Avatar.

关键词： Avatars Cloud computing Servers Green products Power demand Propagation delay Energy consumption

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