检索结果-内蒙古大学图书馆

作者： Pan, Gaofeng Lei, Hongjiang Deng, Yansha Fan, Lisheng Yang, Jing Chen, Yunfei Ding, Zhiguo Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing400715 China School of Computing and Communications Lancaster University LancasterLA14YW United Kingdom Chongqing Key Laboratory of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Centre for Telecommunications King's College London LondonWC2R2LS United Kingdom School of Computer Science and Educational Software Guangzhou University Guangzhou510000 China Department of Electronic Engineering Shantou University Guangdong515063 China School of Information Engineering Yangzhou University Yangzhou225009 China School of Engineering University of Warwick CoventryCV47AL United Kingdom

In this paper, a multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system, including one base station (BS) equipped with multiple antennas, one desired single-antenna information receiver (IR), and N (N > 1) single-antenna energy-harvesting receivers (ERs) is considered. Assuming that the information signal to the desired IR may be eavesdropped by ERs if ERs are malicious, we investigate the secrecy performance of the target MISO SWIPT system when imperfect channel state information (CSI) is available and adopted for transmit antenna selection at the BS. Considering that each eavesdropping link experiences independent but not necessarily identically distributed Rayleigh fading, the closed-form expressions for the exact and the asymptotic secrecy outage probability, and the average secrecy capacity are derived and verified by simulations. Furthermore, the optimal power splitting factor is derived for each ER to realize the tradeoff between the energy harvesting and the information eavesdropping. Our results reveal the impact of the imperfect CSI on the secrecy performance of MISO SWIPT systems in the presence of multiple wiretap channels. © 2016 IEEE.

关键词： Energy harvesting

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The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Exploration of Semantic-aware Approach for Contextual Suggestion Using Knowledge from The Open Web 24

Exploration of Semantic-aware Approach for Contextual Sugges...

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24th Text REtrieval Conference, TREC 2015

作者： Wang, Yuan Zhang, Yongfeng Zhang, Yi Zhang, Xintong Liu, Jie Huang, Yalou College of Computer and Control Engineering Nankai University Tianjin300071 China College of Software Nankai University Tianjin300071 China State Key Laboratory of Intelligent Technology and Systems Department of Computer Science Tsinghua University Beijing100084 China School of Engineering University of California Santa Cruz95060 United States

This paper describes our group’s first attempt on the Contextual Suggestion Track of the Twenty-fourth Text REtrieval Conference (TREC 2015). The task aims to provide recommendations on attractions for various kinds of users under different and complex contexts. TREC provides two ways to participate in the track: one is to create a web server that can respond to contextual related queries called "Live Experiment", the other is to submit run files that have all the responses to the released requests called "Batch Experiment". For Live Experiment, due to lack of training data, our approach sticks closely to the defined relevance judgement criteria and context knowledge. We take linear interpolation to combine a variety of factors and contextual related knowledge. For Batch Experiment, we further consider domain preference under user attributes, and take existing Machine Learning based methods in principle. We show that feature engineering is a vital part for attraction suggestions. We find that the performance of suggestions to the provided user profiles and contexts has been improved using domain preference analysis. © 2015 24th Text REtrieval Conference, TREC 2015 - Proceedings. All Rights Reserved.

关键词： User profile

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Tomography is Necessary for Universal Entanglement Detection with Single-Copy Observables

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Physical Review Letters 2016年第23期116卷 230501-230501页

作者： Dawei Lu Tao Xin Nengkun Yu Zhengfeng Ji Jianxin Chen Guilu Long Jonathan Baugh Xinhua Peng Bei Zeng Raymond Laflamme Institute for Quantum Computing University of Waterloo Waterloo N2L 3G1 Ontario Canada State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics Tsinghua University Beijing 100084 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney NSW 2007 Australia Department of Mathematics and Statistics University of Guelph Guelph Ontario N1G 2W1 Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China Hefei Anhui 230036 China Canadian Institute for Advanced Research Toronto Ontario M5G 1Z8 Canada Perimeter Institute for Theoretical Physics Waterloo Ontario N2L 2Y5 Canada

Entanglement, one of the central mysteries of quantum mechanics, plays an essential role in numerous tasks of quantum information science. A natural question of both theoretical and experimental importance is whether universal entanglement detection can be accomplished without full state tomography. In this Letter, we prove a no-go theorem that rules out this possibility for nonadaptive schemes that employ single-copy measurements only. We also examine a previously implemented experiment [H. Park et al., Phys. Rev. Lett. 105, 230404 (2010)], which claimed to detect entanglement of two-qubit states via adaptive single-copy measurements without full state tomography. In contrast, our simulation and experiment both support the opposite conclusion that the protocol, indeed, leads to full state tomography, which supplements our no-go theorem. These results reveal a fundamental limit of single-copy measurements in entanglement detection and provide a general framework of the detection of other interesting properties of quantum states, such as the positivity of partial transpose and the k-symmetric extendibility.

关键词： Entanglement detection Entanglement measures Quantum tomography Nuclear magnetic resonance

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Context-aware Estimation Approach based on Participatory Sensing

Context-aware Estimation Approach based on Participatory Sen...

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IEEE Global Communications Conference

作者： Yingying Guo Yan Sun Tin-Yu Wu Mohammad S. Obaidat Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Department of Computer Science and Information Engineering National Ilan University Department of Computer and Information Science Fordham University

ISBN: (纸本)9781479959532

In participatory sensing applications, the inaccuracy and conflict of the reported data, commonly caused by the error rate of participants or the differences of observation context, have received more and more attention. Estimating the real status of facilities according to observations becomes a big challenge for participatory sensing. Towards this end, we propose a context-aware estimation approach based on participatory sensing in this paper. We first model the effects of observation context, and then propose an iterative method to infer the error rate of participants and estimate the real status with high precision. Our method is verified using a public facilities monitoring application in our campus, and tested via extensive simulations. The results demonstrate that the proposed method outperforms recent popular three-estimates algorithm and OtO EM algorithm.

关键词： Participatory sensing Context Estimation Simulation Error analysis simulating Context awareness Public utilities iterative methods

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A PSNR-Controllable Data Hiding Algorithm Based on LSBs Substitution

A PSNR-Controllable Data Hiding Algorithm Based on LSBs Subs...

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IEEE Global Communications Conference

作者： Huaibo Sun Hong Luo Tin-Yu Wu Mohammad S. Obaidat Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Department of Computer Science and Information Engineering National Ilan University Department of Computer and Information Science Fordham University

ISBN: (纸本)9781479959532

There are more and more systems using mobile devices to perform sensing tasks, but these increase the risk of leakage of personal privacy and data. Data hiding is one of the important ways for information security. Even though many data hiding algorithms have worked on providing more hiding capacity or higher PSNR, there are few algorithms that can control PSNR effectively while ensuring hiding capacity. In this paper, with controllable PSNR based on LSBs substitution - PSNR-Controllable Data Hiding (PCDH), we first propose a novel encoding plan for data hiding. In PCDH, we use the remainder algorithm to calculate the hidden information, and hide the secret information in the last x LSBs of every pixel. Theoretical proof shows that this method can control the variation of stego image from cover image, and control PSNR by adjusting parameters in the remainder calculation. Then, we design the encoding and decoding algorithms with low computation complexity. Experimental results show that PCDH can control the PSNR in a given range while ensuring high hiding capacity. In addition, it can resist well some steganalysis. Compared to other algorithms, PCDH achieves better tradeoff among PSNR, hiding capacity, and computation complexity.

关键词： Data Hiding PSNR Steganalysis Hiding Capacity Hidden data Peak signal-to-noise ratio adjustable parameter

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Regression based on neural incremental attribute learning with correlation-based feature ordering

Regression based on neural incremental attribute learning wi...

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IEEE Conference on Cybernetics and intelligent Systems

作者： Ting Wang Xiaoyan Zhu Sheng-Uei Guan Ka Lok Man T. O. Ting State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing Wuxi China Department of {Computer Science and Software Engineering Electrical and Electronic Engineering} Xi'an Jiaotong-Liverpool University Suzhou China

Incremental Attribute Learning (IAL) gradually trains features in one or more size, which can be used to solve regression problems. Previous studies showed that feature ordering is crucial to IAL, and features should be sorted by some criteria. This study proposed two new feature ordering methods based on feature's group correlation and individual correlation for different situations. Experimental results show that grouped correlation-based feature ordering approach can exhibit better performance than others based on IAL neural networks in regression. Moreover, the performance of this approach is more stable than individual correlation-based approaches and some other approaches.

关键词： Correlation Correlation coefficient Neural networks Regression analysis Training Error analysis Pattern recognition

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Distributed Adaptive Two-stage Kalman Filter for Target Tracking in the Presence of Unknown Dynamic Bias 33

Distributed Adaptive Two-stage Kalman Filter for Target Trac...

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第三十三届中国控制会议

作者： ZHANG Cui JIA Yingmin DU Junping ZHANG Jun The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications School of Electronic and Information Engineering Beihang University (BUAA)

ISBN: (纸本)9781479947249

This paper is concerned with the problem of tracking target with multiple sensors in the presence of unknown dynamic bias. A suboptimal adaptive two-stage Kalman filter(ATKF) is designed with two reduce-order filters to estimate the target state and the dynamic bias in parallel when the bias model information is incomplete. Moreover, a distributed adaptive two-stage Kalman filter(DATKF) is developed for multi-sensor system based on the ATKF. The effectiveness of the ATKF and the DATKF are illustrated by the Monte Carlo simulation results.

关键词： Dynamic Bias,Adaptive Two-stage Kalman Filter,Distributed Fusion,Multi-sensor System

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New Kinematic Notation and Automatic Generation of Symbolic Dynamics Equations for Space Robots 33

New Kinematic Notation and Automatic Generation of Symbolic ...

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第三十三届中国控制会议

作者： ZHANG Hui JIA Yingmin DU Junping ZHANG Jun The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications School of Electronic and Information Engineering Beihang University (BUAA)

ISBN: (纸本)9781479947249

To verify and evaluate the performance of a space robot controller,kinematics and dynamics of the system have to be formed beforehand for computer *** paper is devoted to develop a new kinematic notation for space robots and to come up with an open source of Matlab subroutines for the propose of obtaining the proper dynamics equations of space robots in symbolic forms *** the new kinematic notation,we will present the general form and two special *** is then demonstrated through an example the advantages such as flexible assignment of frames on space robots,being able to describe multi-DOF joint and achieve a consistent description for multi-arm space *** the second part,we adopt the Lagrangian Formulation for forming the procedures to automatically generate the dynamics equations of space robots in symbolic *** example is then provided to demonstrate the effectiveness of closed-loop simulation adopting the obtained symbolic equations.

关键词： Space Robots,Kinematics,Dynamics,Symbolic Dynamics Equations,Lagrangian

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Positional translation language model for ad-hoc information retrieval

Positional translation language model for ad-hoc information...

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

作者： Tu, Xinhui Luo, Jing Li, Bo He, Tingting Gu, Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Department of Computer Science Central China Normal University Wuhan China State Key Lab. of Software Engineering Wuhan University Wuhan China

ISBN: (纸本)9783319066042

Most existing language modeling approaches are based on the term independence hypothesis. To go beyond this assumption, two main directions were investigated. The first one considers the use of the proximity features that capture the degree to which search terms appear close to each other in a document. Another one considers the use of semantic relationships between words. Previous studies have proven that these two types of information, including term proximity features and semantic relationships between words, are both useful to improve retrieval performance. Intuitionally, we can use them in combination to further improve retrieval performance. Based on this idea, this paper propose a positional translation language model to explicitly incorporate both of these two types of information under language modeling framework in a unified way. In the first step, we present a proximity-based method to estimate word-word translation probabilities. Then, we define a translation document model for each position of a document and use these document models to score the document. Experimental results on standard TREC collections show that the proposed model achieves significant improvements over the state-of-the-art models, including positional language model, and translation language models. © 2014 Springer International Publishing.

关键词： Information retrieval

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