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Robust Learning to Rank Based on Portfolio Theory and AMOSA Algorithm

IEEE Transactions on systems, Man, and Cybernetics: systems 2017年第6期47卷 1007-1018页

作者： Li, Jinzhong Liu, Guanjun Yan, Chungang Jiang, Changjun Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai201804 China Key Laboratory of Watershed Ecology and Geographical Environment Monitoring NASG Department of Computer Science and Technology Jinggangshan University Ji'an343009 China

Effectiveness is the most important factor considered in the ranking models yielded by algorithms of learning to rank (LTR). Most of the related ranking models only focus on improving the average effectiveness but ignore robustness. When a ranking model ignores robustness, the effectiveness for many queries is possibly very poor although the average effectiveness for all queries is relatively high. Therefore, Wang et al. first consider robustness in their ranking models. However, the robustness formula defined by Wang et al. cannot characterize those queries whose effectiveness are hurt seriously in comparison with the baseline model. In order to overcome this shortcoming, we propose a novel formula of characterizing robustness based on portfolio theory, and construct a multiobjective optimization model of the robust LTR in which the formula is used. Based on this model, we propose an approach of risk-sensitive and robust LTR, named as R2Rank, which is based on the framework of archived multiobjective simulated annealing algorithm and the idea of preference ranking organization method for enrichment evaluation. The experimental results show that the ranking models produced by our proposed R2Rank approach are better in both effectiveness and robustness than those produced by three state-of-the-art LTR approaches. © 2016 IEEE.

关键词： Simulated annealing

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Autonomic Performance and Power Control on Virtualized Servers:Survey, Practices, and Trends

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Journal of Computer Science & technology 2014年第4期29卷 631-645页

作者：周笑波蒋昌俊 IEEE ACM Department of Computer Science University of Colorado Colorado Springs U.S.A. The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University CCF Department of Computer Science and Technology Tongji University

Modern datacenter servers hosting popular Internet services face significant and multi-facet challenges in performance and power control. The user-perceived performance is the result of a complex interaction of complex workloads in a very complex underlying system. Highly dynamic and bursty workloads of Internet services fluctuate over multiple time scales, which has a significant impact on processing and power demands of datacenter servers. High-density servers apply virtualization technology for capacity planning and system manageability. Such virtuMized computer systems are increasingly large and complex. This paper surveys representative approaches to autonomic performance and power control on virtualized servers, which control the quality of service provided by virtualized resources, improve the energy efficiency of the underlying system, and reduce the burden of complex system management from human operators. It then presents three designed self-adaptive resource management techniques based on machine learning and control for percentile-based response time assurance, non-intrusive energy-efficient performance isolation, and joint performance and power guarantee on virtualized servers. The techniques were implemented and evaluated in a testbed of virtualized servers hosting benchmark applications. Finally, two research trends are identified and discussed for sustainable cloud computing in green datacenters.

关键词： autonomic computing joint performance and power control virtualized server Internet application sustainable computing

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A Hierarchical Control Scheme for Active Power-assist Lower-limb Exoskeletons

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Journal of Bionic Engineering 2024年第5期21卷 2184-2198页

作者： Jing Deng Wenzheng Jiang Haibo Gao Yapeng Shi Mantian Li State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001HeilongjiangChina Shenzhen Academy of Aerospace Technology Shenzhen518063China Faculty of Computing Harbin Institute of TechnologyHarbin150001HeilongjiangChina Institute of Intelligent Manufacturing Technology Shenzhen Polytechnic UniversityShenzhen518055China

Effectively controlling active power-assist lower-limb exoskeletons in a human-in-the-loop manner poses a substantial chal-lenge,demanding an approach that ensures wearer autonomy while seamlessly adapting to diverse wearer *** paper introduces a novel hierarchical control scheme comprising five integral components:intention recognition layer,dynamics feedforward layer,force distribution layer,feedback compensation layer,as well as sensors and *** intention rec-ognition layer predicts the wearer's movement and enables wearer-dominant movement through integrated force and position *** force distribution layer effectively resolves the statically indeterminate problem in the context of double-foot support,showcasing flexible control *** dynamics feedforward layer mitigates the effect of the exoskeleton itself on ***,the feedback compensation layer provides reliable closed-loop *** approach mitigates abrupt changes in joint torques during frequent transitions between swing and stance phases by decomposed *** this innovative hierarchical control scheme on a hydraulic exoskeleton platform through a series of experiments,the results demonstrate its capability to deliver assistance in various modes such as stepping,squatting,and jumping while adapting seamlessly to different terrains.

关键词： Hierarchical control Active power-assist Exoskeleton robots Dynamics feedforward Force distribution Feedback compensation

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Towards accountable authority attribute-based encryption

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High technology Letters 2013年第1期19卷 82-87页

作者：王永涛 Chen Kefei Long Yu Department of Computer Science and Engineering Shanghai Jiao Tong University China Information Technology Security Evaluation Center Shanghai Key Laboratory of Scalable Computing and System Shanghai JiaoTong University

An accountable authority attribute-based encryption （A-ABE） scheme is presented in this paper. The notion of accountable authority identity-based encryption （A-IBE） was first introduced by Goyal at Crypto＇07. It is a novel approach to mitigate the （inherent） key escrow problem in identity-based cryptosystems. In this work, the concept of accountable authority to attribute-based encryption （ABE） setting is generalized for the first time, and then a construction is given. The scheme non-trivially integrates an A-IBE scheme proposed by Libert et al. with an ABE scheme. In our construction, a user will be identified by a pair （ id, o~）, where id denotes the user＇ s identity and ω denotes the set of attributes associated to the user. In addition, our construction is shown to be secure under some reasonable assumptions.

关键词： cryptography attribute-based encryption accountable authority key escrow traceability

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A framework towards task-based query in personal dataspace

A framework towards task-based query in personal dataspace

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7th International Conference on Semantics, Knowledge, and Grids, SKG 2011

作者： Li, Yukun Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300384 Tianjin China

ISBN: (纸本)9780769545158

With increment of personal data amount, how to allow users to efficiently re-find personal data items becomes an important research issue. According to general experience of persons, task is taken as a popular way to classify personal dataset, and is often taken as a factor to re-access expected items. In this paper, we propose a framework called TaskSpace to help users re-find expected data items based on user task, and present conceptual model of TaskSpace, framework for implementing a task-based system, methods to identify task relationships and interface for users to perform task-based query. TaskSpace framework provides users an alternative way to re-find personal information, and illustrates some interesting research issues. © 2011 IEEE.

关键词： Classification (of information)

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A Dependability Model for TMR system

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International Journal of Automation and computing 2012年第3期9卷 315-324页

作者： Peng, Jun-Jie Liu, Yan-Ping Chen, Yuan-Yuan School of Computer Engineering and Science Shanghai University Shanghai 200072 China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Much research has been done on the dependability evaluation of computer systems. However, much of this is gone no further than study of the fault coverage of such systems, with little focus on the relationship between fault coverage and overall system dependability. In this paper, a Markovian dependability model for triple-modular-redundancy (TMR) system is presented. Having fully considered the effects of fault coverage, working time, and constant failure rate of single module on the dependability of the target TMR system, the model is built based on the stepwise degradation strategy. Through the model, the relationship between the fault coverage and the dependability of the system is determined. What is more, the dependability of the system can be dynamically and precisely predicted at any given time with the fault coverage set. This will be of much benefit for the dependability evaluation and improvement, and be helpful for the system design and maintenance.

关键词： Dependability Markovian model coverage triple-modular-redundancy (TMR) failure rate.

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Backlund Transformations for the Initial Problems of Nizhnich and Nizhnich-Novikov-Veselov Equations

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理论物理通讯(英文版) 2003年第7期40卷 15-18页

作者： SU Hong-Liang WANG Ming-Liang QIN Meng-Zhao State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scien-tific/Engineering Computing Academy of Mathematics and System Science the Chinese Academy of Sciences Beijing 100080 China Mathematical Department Luoyang Institute of Technology Luoyang 471039 China

The homogeneous balance method is a method for solving general partial differential equations (PDEs). Inthis paper we solve a kind of initial problems of the PDEs by using the special Backlund transformations of the initialproblem. The basic Fourier transformation method and some variable-separation skill are used as auxiliaries. Two initialproblems of Nizhnich and the Nizhnich-Novikov-Veselov equations are solved by using this approach.

关键词： Backlund transformation initial problem Nizhnick equation Nizhnich Novikov-Veselov equation homogeneous balance method

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Research and implementation of POI recommendation system integrating temporal feature 3

Research and implementation of POI recommendation system int...

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3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Liu, Jinxin Jiao, Xu Jin, Youzhi Liu, Xinyu Liu, Li Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

ISBN: (纸本)9781538647936

Point-of-Interest is an interesting research topic of personalized recommendation. In this paper, a new position-based recommendation framework is proposing by using the time attribute. We establish a user matrix with user check-in data sets that contain time and location information. The user matrix is divided into the sub-matrices according to the set period and then every sub-matrix is decomposed into the user checking preference matrix and position feature matrix by using the non-negative matrix factorization. The user's attendance preferences at each time are integrated to get the user's final check-in preference for the candidate location to make recommendations more consistent with the needs of users. © 2018 IEEE.

关键词： Non-negative matrix factorization

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MR-COF: A genetic MapReduce configuration optimization framework 15th

MR-COF: A genetic MapReduce configuration optimization frame...

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： Liu, Chao Zeng, Deze Yao, Hong Hu, Chengyu Yan, Xuesong Fan, Yuanyuan Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan430074 China China Services Computing Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271392

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing resources. Hadoop has many configuration parameters, some of which are crucial to the performance of MapReduce jobs. In practice, these parameters are usually set to default or inappropriate values. This severely limits system performance (e.g., execution time). Therefore, it is essential but also challenging to investigate how to automatically tune these parameters to optimize MapReduce job performance. In this paper, we propose an automatic MapReduce configuration optimization framework named as MR-COF. By monitoring and analyzing the runtime behavior, the framework adopts a cost-based performance prediction model that predicts the MapReduce job performance. In addition, we design a genetic search algorithm which iteratively tunes parameters in order to find out the best one. Testbed-based experimental results show that the average MapReduce job performance is increased by 35% with MR-COF compared to the default configuration. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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Visual Pop-can detection method based on adaboost

Visual Pop-can detection method based on adaboost

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3rd International Conference on Manufacturing Engineering and Process, ICMEP 2014

作者： Lin, Xin Yi Xue, Yan Bing Guo, Bao Hong Key Laboratory of Computer Vision and System Ministry of Education University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

ISBN: (纸本)9783038350842

This paper puts forward a visual method of detecting pop-cans based on AdaBoost Algorithm. This method, is basing on the idea of AdaBoost Algorithm, and we use Haar Feature and LBP Feature to extract pop-can characteristics respectively. Finally we compare the differences of the training processes and the experiment results between these two detectors. It shows that these pop-can detectors that are trained by this visual method have high detection rate and speed. © (2014) Trans Tech Publications, Switzerland.

关键词： Adaptive boosting

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