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检索条件"机构=Key Laboratory of Trustworthy Distributed Computing and Service"

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A method indoor multi-path IR-UWB location based on multi-task compressive sensing 4

A method indoor multi-path IR-UWB location based on multi-ta...

引用

4th International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based services, IEEE UPINLBS 2016

作者： Li, Xiaofei He, Di Jiang, Lingge Yu, Wensheng Chen, Xiaohua College of Mathematics and Computer WuYi University FuJian China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China National Mobile Communications Research Laboratory Southeast University Nanjing China Shanghai Key Laboratory of Navigation and Location Based Service Shanghai Jiao Tong University Shanghai China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China School of Information and Engineering HuZhou University Zhejiang China

ISBN: (纸本)9781509028788

In the paper, the ultra-wideband (UWB) localization method based on multi-task compressive sensing (MT-CS) is proposed to solve the UWB localization accuracy performance problem. In the indoor multi-path NLOS environment, the transmission channel pulse response (CIR) is estimated precisely by use of the MT-CS algorithm, and least square error (LSE) algorithm are calculated to estimate the target location. The simulation results illustrate that the MT-CS algorithm compared with the BCS algorithm can estimate the localization more precisely, and approximate the CRLB algorithm. Meanwhile, the MT-CS algorithm possesses advantage to apply in the UWB location. © 2016 IEEE.

关键词： Compressed sensing

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Multi-features based classification for automatic summarization

Multi-features based classification for automatic summarizat...

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International Conference on Multimedia, Communication and computing Application, MCCA 2014

作者： Li, H.Y. Liu, R.F. Xu, W.R. Shi, R.S. School of Information and Communication Engineering Beijing University of Posts and Telecommunication Beijing China Education Ministry Key Laboratory of Trustworthy Distributed Computing and Service BUPT School of Humanities BUPT Beijing China

ISBN: (纸本)9781138027756

That the summary of an article can be automatically generated is an important text processing technique. The technique can automatically extract the most useful information of the text and present that information, which makes it easy to navigate and judge the importance to readers. This paper is based on a variety of texts and structure features. Supporting vector-machine classification method is used to identify summary sentences, which abandoned the traditional experience weight setting to optimize. The effective system that combines keywords density and document structure with the best weights is implemented for automatic summarization. The experimental results show that our Density and Structure Based Summary system improves the automatic summarization results. It’s better than the other two systems and has a big promotion on the precision, recall and F score. © 2015 Taylor & Francis Group, London.

关键词： Text processing

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Deep learning based primary user classification in Cognitive Radios

Deep learning based primary user classification in Cognitive...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Yuanhao Cui Xiao jun Jing Songlin Sun Xiaohan Wang Dongmei Cheng Hai Huang Key Laboratory of Trustworthy Distributed Computing and service (BUPT) Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and service (BUPT) Beijing University of Posts and Telecommunications Beijing Beijing CN Key Laboratory of Trustworthy Distributed Computing and service (BUPT) School of Software and Microelectronics Beijing China

Deep Belief Networks (DBN) is a very powerful algorithm in deep learning. The DBN has been effectively applied in many areas of machine learning, such as computer vision (CV) and natural language processing (NLP). With the help of deep architecture, their accuracy has been largely improved and their human annotation data which traditional machine learning algorithm extremely rely on could be reduced. In Cognitive Radios (CRs), learning is necessary for its cognition, while two of the key challenges are how to classify primary user agents with their performances and predict their behaviors. The CRs' performance has a positive correlation with the hit rate of learning algorithm's classification and prediction results. In this paper, we study the questions of classification and prediction of user agents. We apply the DBN model to improve accuracy rating of user agent's recognition in CRs with user-centered model, it's the first application of deep learning structure in CRs. The DBN model provides a primary user agent's classification, which is the foundation of the prediction to both idle frequency spectrums and time slots. Experimental results show that the cognitive engine finds a much better detection rate than the CRs engine with shallow learning and other traditional strategy. The simulation results are also tested on the WIFI channel with 5GHz and 2.4GHz.

关键词： Training Machine learning algorithms Classification algorithms Prediction algorithms Machine learning Sensors Artificial neural networks

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Discount rate hurts group buying? An empirical study from catering industry

Discount rate hurts group buying? An empirical study from ca...

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International Conference on services Systems and services Management, ICSSSM

作者： Rujin Zhang Xiangling Fu Jiayin Qi Sam Seongmin Jeon School of Economics and Management Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing China School of Management Shanghai University of International Business and Economics Shanghai China School of Software Beijing University of Posts and Telecommunications Beijing China Business School Gachon University Seongnam

ISBN: (纸本)9781509028436

With the development of online group buying, more and more experts are beginning to focus on this emerging e-commerce model. Based on the data from ***, our study examined the impact of discount rate on the consumers' group buying behavior, considering the star, the score, the location and other factors as control variables. Our results suggest that the discount rate has a significant negative impact on the consumers' group buying behavior, and selling price, the effective period, the number of restaurant and the locations will reduce this effect, and the score and the star will increase this effect. The findings of our research can help online group buying restaurants to make a reasonable price decision.

关键词： Economics Indexes

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X-Prcaf : Xposed Based Protecting Cache File from Leaks in Android Social Applications

X-Prcaf : Xposed Based Protecting Cache File from Leaks in A...

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International Conference on trustworthy Systems and their Applications (TSA)

作者： Qi Tang Wen Zhang Xiaoyong Li Bin Wang Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing University of Posts and Telecommunications Beijing P.R. China Beijing Key Lab of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications Beijing P.R. China School of Computer Science Beijing University of Posts and Telecommunications Beijing P.R. China

ISBN: (纸本)9781509035403

With the high frequent use of social applications on Android platform, the cache file privacy disclosure issues have become increasingly serious. To our best knowledge, there is no effective privacy protection solution for social applications cache files. In this paper, we analyze the present situation of social applications cache file leaks on Android platform, and provide a privacy disclosure assessment criterion based on file storage directories and security state machines. And a cache file privacy protection framework, X-Prcaf (Xposed-based-Protecting-Cache-File), is proposed, which can make social applications avoid privacy data leaks in running process. This framework mainly uses taint tracking technology, operating system hook technology, and cryptographic technology. It aims to protect the entire life cycle of the social applications cache files, by strategy pre-generation, real-time monitoring and security reinforcement. Experiments demonstrate that X-Prcaf has a good effect on the cache file leaks of social software.

关键词： Data privacy Software Cryptography Smart phones Privacy Telecommunications

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Multilayer Feed-forward Neural Network learning based Dynamic Chinese restaurant model for dynamic spectrum access in cognitive radio networks

Multilayer Feed-forward Neural Network learning based Dynami...

引用

International Symposium on Communications and Information Technologies (ISCIT)

作者： Jianlan Liu Xiao jun Jing Songlin Sun Xiaohan Wang Dongmei Cheng Hai Huang Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing University of Posts and Telecommunications Beijing Beijing CN

As an effective approach to improve spectrum efficiency, cognitive radio network make it possible for secondary users (SU) to share the spectrum with primary users (PU), on the condition that the primary users have preemptive priority. In this paper, we applied the Dynamic Chinese restaurant game, which ideally modeled the spectrum sensing and access in cognitive network. We propose the use of Multilayer Feed-forward Neural Networks (MFNN) as an effective method for users to learn the network state, which can be regarded as how a customer learn the table state in the restaurant. Moreover, in order to select an optimal table for a secondary user, subsequent secondary users' sequential decisions are considered. The effectiveness and efficiency of the proposed scheme is verified in the simulation.

关键词： Cognitive radio Neurons Games Sensors Neural networks Information and communication technology Nonhomogeneous media

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Antenna calibration method for MMSE-based network MIMO system

Antenna calibration method for MMSE-based network MIMO syste...

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2015 IEEE/CIC International Conference on Communications in China - Workshops, CIC/ICCC 2015

作者： Liu, Qiang Su, Xin Zeng, Jie Liu, Lili Lv, Tiejun Tsinghua National Laboratory for Information Science and Technology Research Institute of Information Technology Tsinghua University Beijing China Key Laboratory of Trustworthy Distributed Computing and Service School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781467397018

In this paper, we propose a new channel reciprocity calibration method based on minimum mean square error (MMSE) in network multiple-input and multiple-output (MIMO) system. Network MIMO system can mitigate the inter-cell interference by joint precoding techniques. The system is assumed to operate in time division duplex (TDD). However, the generalized channeles do not only consist of free-space electromagnetic channel, but also include transceiver modules, the mismatches between the transceiver modules of the antennas destroy the channel reciprocity. Therefore the mismatches should be calibrated before channel reciprocity can be utilized. An effective method for calculating the calibration coefficients in the network MIMO system whose BSs are equipped with multiple antennas is proposed. The network MIMO system is divided into M independent centralized MIMO systems and one distributed MIMO system, then the calibration coefficients of the two systems can be combined to calculate the calibration coefficients of the network MIMO system. The validity of the method is proved by the simulation results. © 2015 IEEE.

关键词： Mean square error

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Secure beamforming and artificial noise design in interference networks with imperfect ECSI

Secure beamforming and artificial noise design in interferen...

引用

IEEE International Conference on Communications Workshops, ICC

作者： Jian Zhou Ruohan Cao Hui Gao Cong Zhang Tiejun Lv Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781467363068

This paper investigates the joint robust beamforming and artificial noise design in two-user interference networks, where one of the two pairs is wiretapped by an external eavesdropper, and only imperfect eavesdropper's channel state information (ECSI) is available for the two pairs. Under individual transmission power constraint, our goal is to maximize the worst-case achievable secrecy rate of the wiretapped node and guarantee the signal-to-interference-plus-noise ratio (SINR) requirement at the wiretap-free node. In particular, considering the channel vectors and channel covariance matrices errors, we first model the imperfect ECSI in the sense of ellipsoidal uncertainties. In the sequel, our design goal is transformed into solving a non-convex optimization problem which can be further reformulated as a two-stage problem. With the help of rank relaxation and one dimensional line search, the considered two-stage problem is solved efficiently. Simulation results demonstrate the effectiveness of the proposed design in different scenarios.

关键词： Array signal processing Interference Uncertainty Transmitters Security Noise Joints

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Mining the relation between dorm arrangement and student performance

Mining the relation between dorm arrangement and student per...

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IEEE International Conference on Big Data

作者： Man Li Ruisheng Shi Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts & Telecommunications Beijing China

This paper discusses the relation between dorm arrangement and student performance. One of the unsupervised learning algorithms, k-means algorithm, is mainly used in the process of analysis. Students are clustered into several clusters according to their similarity of performance scores. This paper analyzes the result of clustering by comparing it with actual dorm arrangement. In the end, drawbacks of k-means and reliability of this student dorm-performance relation are evaluated. Finally, this paper draws a conclusion that student performances are influenced by dorm arrangement.

关键词： Clustering algorithms Algorithm design and analysis Data mining Data analysis Image color analysis Telecommunications Unsupervised learning

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Scheme to Improve Integrity Verification of Cloud Storage Based on Diffie-Hellman Algorithm

Scheme to Improve Integrity Verification of Cloud Storage Ba...

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第十届中国通信学会学术年会

作者： Li Jiaqi Liu Jianyi Zhang Ru National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and Telecommunication Key Laboratory of Trustworthy Distributed Computing and Service

Focusing on current communication overspending in the integrity verification scheme based on the Merkel Tree,using the difficulty of factoring large integers,an integrity verification scheme based on Diffie-Hellman algorithm is *** improved scheme has resolved communication overspending and greatly improved the integrity verification efficiency.

关键词： Cloud storage Integrity verification Diffie-Hellman Algorithm Merkel Tree

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