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IEEE Symposium on computers and Communications

作者： Youshi Wang Fa Zhang Rui Wang Yangguang Shi Hua Guo Zhiyong Liu Chinese Academy of Sciences (CAS) Institute of Computing Technology (ICT) Beijing China University of Chinese Academy of Sciences Beijing China ICT Key Laboratory of Intelligent Information Processing Beijing China Hong Kong University of Science and Technology Hong Kong China Technion - Israel Institute of Technology Haifa Israel State Grid Jingzhou Electric Power Company Jingzhou Hubei China ICT State Key Laboratory for Computer Architecture Beijing China

The high energy consumption has become one bottleneck in the development of the data centers (DCs), where the main energy consumers are the cooling system and the servers. Therefore, the joint optimization for the energy efficiency of the cooling system and the servers is a crucial problem, while most of previous works on energy saving only studies one of these two components in an isolated manner. In this paper, we propose a real-time strategy, rTCS (real-time Task Classification and Scheduling strategy), to jointly optimize the energy efficiency of these two components in the scenario where the tasks arrive dynamically. Strategy rTCS first labels the tasks to classify them according to their run time and end time with a time complexity of O(1) and a bounded space complexity. Then, rTCS schedules the tasks in real time based on their labels and the energy consumption model of the DC. Simulation results show that rTCS can effectively improve the energy efficiency of DCs.

关键词： Energy efficiency Data center Cooling system Task classification Real-time scheduling algorithm

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EasyHPC: An online programming platform for learning high performance computing

EasyHPC: An online programming platform for learning high pe...

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IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Zhepeng Zou Yuxiao Zhang Jiang Li Xiaojun Hei Yunfei Du Di Wu Guangdong Province Key Laboratory of Big Data Analysis and Processing Guangzhou China School of Data and Computer Science Sun Yat-sen University Guangzhou China National Supercomputer Center in Guangzhou Guangzhou China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China

Lacking of appropriate learning facilities, the traditional approach to learn high-performance computing (HPC) is commonly theory-oriented without sufficient hands-on programming experiences. To improve the hands-on experiences of HPC learners, we design and implement a flexible and adaptive online HPC learning platform in this paper, called EasyHPC. This platform contains various online course modules such as quiz bank, interactive community, and virtual laboratory. In our system, various HPC theoretical and experimental learning activities can be conducted online, such as assigning HPC parallel programming tasks, and creating HPC questions and collecting students' submissions. It is convenient for students to study HPC-related courses in our platform, submit course assignments, exchange ideas, and complete HPC programming tasks. Our preliminary learning trials have shown that our system can effectively improve the hands-on experience of our students by providing an integrated HPC learning and programming environment. Our students are able to achieve various HPC capstone projects in our platform to develop their system capability.

关键词： Programming profession Servers High performance computing Education Supercomputers

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Ranking Node Influence in Social Networks

Ranking Node Influence in Social Networks

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International Symposium on Parallel and Distributed Computing

作者： Zheyi Chen Yuli Liu Weiping Zhu Department of Computer Science National Laboratory for Information Science and Technology Beijing China College of Mathematics and Computer Science Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou China

ISBN: (纸本)9781509041534

In the study of social networks, analyzing node influence and identifying influential nodes in social networks is of great theoretical and practical significance. To effectively evaluate node influence, a novel concept of influence label is introduced, which can measure node influence through two label attributes called influence level and node degree. Then, a novel influence model called LDM (Level and Degree Model) is proposed. LDM updates the influence label of each node iteratively by the quality of neighbors and the number of neighbors. A gain function that conforms to power-law distribution is also introduced to further optimize the accuracy of LDM. In the experiment part, to prove the effectiveness of LDM, LDM is compared with other typical methods by employing IC model to simulate the information diffusion process on four real-world social networks. Experimental results show that LDM can rank node influence more accurately than other methods.

关键词： social networking (online) CYP51A1 gene LDM Social Networks Line of nodes Social Capital

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Finite-horizon H∞ control for discrete time-varying nonlinear systems under earliest deadline first schedule

Finite-horizon H∞ control for discrete time-varying nonline...

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Chinese Control Conference (CCC)

作者： Yuxuan Shen Zidong Wang Bo Shen Hongli Dong School of Information Science and Technology Donghua University Shanghai China Department of Computer Science Brunel University London Uxbridge Middlesex United Kingdom Institute of Complex Systems and Advanced Control Northeast Petroleum University Daqing China Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Daqing China

This paper is concerned with the finite-horizon H ∞ quantized control problem for a class of discrete time-varying nonlinear networked control systems with earliest deadline first (EDF) schedule. EDF schedule is employed in the channels both from sensor to controller and controller to actuator. Moreover, the measurement output signal and control signal are quantized by a logarithmic quantizer before they enter the controller and system, respectively. The main purpose of the problem addressed is to design a dynamical output-feedback controller such that the prespecified H ∞ performance of the system is guaranteed over a given finite time-horizon. To this end, a sufficient condition is firstly established for the existence of the desired output-feedback controller. Then, the controller parameters are characterized by solving a recursive linear matrix inequality. Finally, a numerical example is given to illustrate the effectiveness of the proposed control approach.

关键词： Schedules Quantization (signal) Time-varying systems Networked control systems Actuators Nonlinear systems

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Analysis of smart glucose meter stability from the economic perspective

Boletin Tecnico/Technical Bulletin

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Boletin Tecnico/Technical Bulletin 2017年第9期55卷 457-462页

作者： Lin, Zhongyan Song, Libin Zheng, Dachuan Li, Zuoyong Internet Innovation Research Center College's Research Base of Humanities and Social Science in Fujian Province Minjiang University Fuzhou Fujian350108 China Fuzhou Digital Health Industry Technology Innovation Center Minjiang University Fuzhou Fujian350108 China Fuzhou Comvee Network Technology Co. Ltd. Fuzhou Fujian350001 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou Fujian350108 China

Objective: to explore and interpret the model of diabetes mobile online management from the perspective of web model. Methods: from the interdisciplinary perspective, combined with economics, management science and computer science, with the only dynamic model in microeconomics—the cobweb model, from chronic disease management, Internet + medical application, analyze the application of Internet technology in diabetes management. Results: through mobile Internet technology, optimized the unit of diabetes management and realized the "monitoring - assessment - intervention" closed-loop management. Conclusion: explore the digital medical health industry in periodic production commodity price fluctuations and other activities, can establish early warning system and mechanism, to improve patients and their families to the cognitive level of diabetes, according to the medical behavior and self management ability.

关键词： Medical applications

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A Novel User Behavior Prediction and Optimization Algorithm for Single-User Multi-terminal Scenario

A Novel User Behavior Prediction and Optimization Algorithm ...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Hui Zhang Juan Chen Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781509035595

For the single-user multi-terminal scenario, a novel user service behavior prediction and optimization algorithm is proposed in this paper, which can realize the accurate prediction of service requirements and optimal selection of service terminals, so as to improve user QoE effectively. Firstly, by using an adaptive feedback based weight correction method, a modified entropy weighted Markov model is formulated to accurately predict user future service states. Secondly, according to the above prediction results, the corresponding heavy-tailed model is used to estimate the service duration. Moreover, by integrating service preferences and terminal attributes, a matching metric of services and terminals is established, and then a terminal selection model is proposed for recommending the optimal service terminal to each user. Simulation results show the effectiveness of proposed algorithm.

关键词： Predictive models Markov processes Optimization Entropy Adaptation models Prediction algorithms Measurement

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Scene recognition with CNNs: objects, scales and dataset bias

Scene recognition with CNNs: objects, scales and dataset bia...

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IEEE Conference on computer Vision and Pattern Recognition

作者： Luis Herranz Shuqiang Jiang Xiangyang Li Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computer Technology

ISBN: (纸本)9781467388528

Since scenes are composed in part of objects, accurate recognition of scenes requires knowledge about both scenes and objects. In this paper we address two related problems: 1) scale induced dataset bias in multi-scale convolutional neural network (CNN) architectures, and 2) how to combine effectively scene-centric and object-centric knowledge (i.e. Places and ImageNet) in CNNs. An earlier attempt, Hybrid-CNN[23], showed that incorporating ImageNet did not help much. Here we propose an alternative method taking the scale into account, resulting in significant recognition gains. By analyzing the response of ImageNet-CNNs and Places-CNNs at different scales we find that both operate in different scale ranges, so using the same network for all the scales induces dataset bias resulting in limited performance. Thus, adapting the feature extractor to each particular scale (i.e. scale-specific CNNs) is crucial to improve recognition, since the objects in the scenes have their specific range of scales. Experimental results show that the recognition accuracy highly depends on the scale, and that simple yet carefully chosen multi-scale combinations of ImageNet-CNNs and Places-CNNs, can push the state-of-the-art recognition accuracy in SUN397 up to 66.26% (and even 70.17% with deeper architectures, comparable to human performance).

关键词： Recognition (Psychology) ON-SCENE different scale Dermal denticles scales Dataset BALANCES Bias Bias Bias Statistical Biases bias(electronics) Scale HUMAN PERFORMANCE Scale formation

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Tri-level combination for image representation 17th

Tri-level combination for image representation

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Li, Ruiying Zhang, Chunjie Huang, Qingming School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783319488899

The context of objects can provide auxiliary discrimination beyond objects. However, this effective information has not been fully explored. In this paper, we propose Tri-level Combination for Image Representation (TriCoIR) to solve the problem at three different levels: object intrinsic, strongly-related context and weakly-related context. Object intrinsic excludes external disturbances and more focuses on the objects themselves. Strongly-related context is cropped from the input image with a more loose bound to contain surrounding context. Weaklyrelated one is recovered from the image other than object for global context. First, strongly and weakly-related context are constructed from input images. Second, we make cascade transformations for more intrinsical object information, which depends on the consistency between generated global context and input images in the regions other than object. Finally, a joint representation is acquired based on these three level features. The experiments on two benchmark datasets prove the effectiveness of TriCoIR. © Springer International Publishing AG 2016.

关键词： Image representation

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Opposition-based artificial bee colony using different learning models

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Journal of information Hiding and Multimedia Signal processing 2016年第6期7卷 1206-1214页

作者： Zhao, Jia Fu, Xue-Feng Lv, Li Wu, Run-Xiu Wang, Hui Yu, Xiang Fan, Tang-Huai Provincial Key Laboratory for Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang330099 China School of Information Engineering Nanchang Institute of Technology Nanchang330099 China

Artificial Bee Colony (ABC) is easy to fall into the local optimum area and has slow convergence velocity when solving some optimization problems. We propose a new method, called opposition-based ABC to improve the performance of ABC in this paper. In the process of evolution, according to the greedy selection strategy, the modified algorithm chooses the best solution as the new location of the employed bee and the onlooker bee from their present solution, new generated solution and opposition solution are used to enlarge the searching area;in addition, when the employed bee and the onlooker bee change into the scouter, the new approach proposes a new update rule, where the new location of the scouter is decided by the location of the employed bee to enhance local exploitation of the scouter. We introduce 4 common kinds of opposition-based models into our new approach and they form 4 kinds of opposition-based ABC algorithms. Then we use 8 famous benchmark functions to test the 4 different models;the results demonstrate that 4 kinds of opposition-based ABC have better performance than ABC, but there are differences on efficiency and precision among them. © 2016.

关键词： Optimization

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Automatic generation of semantic data for event-related medical guidelines 5th

Automatic generation of semantic data for event-related medi...

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5th Joint International Conference on Semantic technology, JIST 2015

作者： Fan, Yuling Qiao, Rui Gu, Jinguang Huang, Zhisheng College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430065 China Departments of Computer Science VU University Amsterdam Amsterdam1081HV Netherlands

ISBN: (纸本)9783319316758

Medical Guidelines pay an important role in medical decision making systems. Medical guidelines are usually involved with event-related actions or procedure. However, little research has been done on how event-related medical guidelines can be converted into its semantic representation such as RDF/OWL data. This paper proposes an approach of automatic generation of semantic data for event-related medical guidelines. This generation is achieved by using the logic programming language Prolog with the support of medical ontologies such as SNOMED CT. We will report the experiments with the automatic generation of the semantic data for event-related Chinese medical guidelines, and show the relevant results. © Springer International Publishing Switzerland 2016.

关键词： Decision making

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