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A group key distribution system based on the generalized aryabhata remainder theorem for enterprise digital rights management

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Journal of Information Hiding and Multimedia signal processing 2015年第1期6卷 140-153页

作者： Liu, Yanjun Chang, Chin-Chen Chang, Shih-Chang Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University No.111 Jiulong Rd Hefei230601 China Department of Computer Science and Information Engineering Asia University No.500 Lioufeng Rd Wufeng Taichung413 Taiwan Department of Information Engineering and Computer Science Feng Chia University No.100 Wenhwa Rd Seatwen Taichung407 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University No.168 Sec.1 University Rd Min-Hsiung Township Chiayi621 Taiwan

Digital Rights Management (DRM) is a type of access-control technology that is used by diverse content providers to restrict the use of digital content. Enterprise Digital Rights Management (E-DRM) is an application of DRM techniques for managing the control of access to sensitive documents in an enterprise. In this paper, we propose a group key distribution system for E-DRM based on the concept of a secret-sharing mechanism and the generalized Aryabhata remainder theorem (GART). To the best of our knowledge, no previous publications related to E-DRM technologies have presented the group key distribution system that we propose. In our system, different groups of enterprise members within the enterprise obtain different digital content in parallel without collision by using their group’s unique session key;all members within each group share a common session key to decrypt the same digital documents to acquire the correct content. We proved that our system achieves the goal of providing high security, which includes preventing inside and outside attacks and offering forward and backward secrecy. © 2015.

关键词： Copyrights

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Fast Multi-Baseline In SAR Phase Ambiguity Resolving Method with Low Computational Complexity

Fast Multi-Baseline In SAR Phase Ambiguity Resolving Method ...

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2014 International Conference on Computer,Communications and Information technology(CCIT 2014)

作者： Ming Li Haiping Wei Liping Xiao Zhiyong Suo Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligent Control National Lab.of Radar Signal Processing Xidian Univ.

ISBN: (纸本)9781629939865

A fast multi-baseline Interferometric synthetic aperture radar(In SAR) phase ambiguity resolving method is presented. The ambiguity solution vector of the shortest baseline is first computed and used as a reference, and then the ambiguity solutions of all the other baselines are selected with logical judgment of phase difference between the measured phase and the wrapped phase, which is obtained by rewrapping the product of the referenced phase and the ratios of the other baselines to the referenced baseline. 1-dimensional searching is then executed on the same index of the reserved ambiguity solutions vectors. Furthermore, the wrong estimates affected by noise are eliminated by taking the largest frequency of the ambiguity numbers counted in a window. Compared to the conventional Chinese remainder theory(CRT), the proposed method is more robust and has much less computational complexity. The validity is investigated with simulated results.

关键词： multi-baseline interferometric synthetic aperture radar(In SAR),phase ambiguity resolving,Chinese remainder theory(CRT)

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Effect of channel aging on the sum rate of uplink massive MIMO systems

Effect of channel aging on the sum rate of uplink massive MI...

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IEEE International Symposium on Information Theory

作者： Chuili Kong Caijun Zhong Anastasios K. Papazafeiropoulos Michail Matthaiou Zhaoyang Zhang Institute of Information and Communication Engineering Zhejiang University Hangzhou China National Mobile Communications Research Laboratory Southeast University Nanjing China Communications and Signal Processing Group Imperial College London London U.K Department of Signals and Systems Chalmers University of Technology Gothenburg Sweden Electrical Engineering and Computer Science Queen's University Belfast Belfast U.K

ISBN: (纸本)9781467377058

This paper investigates the achievable sum-rate of uplink massive multiple-input multiple-output (MIMO) systems considering a practical channel impairment, namely, aged channel state information (CSI). Taking into account both maximum ratio combining (MRC) and zero-forcing (ZF) receivers at the base station, we present tight closed-form lower bounds on the sum-rate for both receivers, which provide efficient means to evaluate the sum-rate of the system. More importantly, we characterize the impact of channel aging on the power scaling law. Specifically, we show that the transmit power of each user can be scaled down by 1/√(M), which indicates that aged CSI does not affect the power scaling law; instead, it causes only a reduction on the sum rate by reducing the effective signal-to-interference-and-noise ratio (SINR).

关键词： Aging MIMO Receivers Uplink Channel estimation Antennas Training

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Tensor-based Gaussian processes regression using a probabilistic kernel with information divergence

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International Journal of Simulation: Systems, science and technology 2015年第5期16卷 13.1-13.7页

作者： Tang, Lingbing Peng, Pin Zhao, Qibin Gui, Lihua Qing, Luochang Mobile E-business Collaborative Innovation Center of Hunan Province Hunan University of Commerce ChangshaHunan410205 China Key Laboratory of Hunan Province for Mobile Business Intelligence ChangshaHunan410205 China Lab.for Advanced Brain Signal Processing Brain Science Institute RIKEN 2-1 Hirosawa WakoshiSaitama Japan Graduate School of Engineering Saitama Institute of Technology Japan School of Finance and Banking Hunan University of Commerce ChangshaHunan410205 China

We present a Gaussian processes regression for tensor-valued inputs, which is based on a coherent treatment of a prior for the latent function with a covariance function defined on a tensor representation of multivariate data. Such a rigorous account of the underlying data dependencies within the model is also the basis for a new and powerful framework for structural data analysis. This is achieved under the assumption of generative models, and by introducing a family of probabilistic kernels with tensor arguments. By equipping these product kernels with the Jensen-Shannon divergence measure for tensorial data, the proposed model can be considered as both a generative and discriminative model. Further, a fully Bayesian treatment is used to estimate the hyperparameters and infer the predictive distributions. Experimental results on a real world application of decoding 3D movement trajectory based on electrocorticography (ECoG) signals recorded from a monkey brain demonstrate the effectiveness and performance advantage of the proposed framework. © 2015, UK Simulation Society. All rights reserved.

关键词： Tensors

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Adaptive optimal trajectory tracking control of nonlinear affine in control system with unknown internal dynamics

Adaptive optimal trajectory tracking control of nonlinear af...

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Chinese Control Conference (CCC)

作者： Yang Tian Haoping Wang Christian Vasseur Sino-French Joint Laboratory of Automation and Signal Processing School of Automation Nanjing University of Science and Technology Nanjing Jiangsu CN Sino-French Joint Laboratory of Automation and Signal Processing School of Automation Lille University of Science and Technology France

This paper presents a new adaptive optimal nonlinear control for trajectory tracking of nonlinear affine-in control systems with unknown internal dynamics. The referred proposed controller which is based on a L 2 norm prescribed to minimized a trajectory tracking error and a time-delay estimation technique based nonlinear systems unknown dynamics estimations has adaptive and optimal characters. Moreover with the systems output feedback, the proposed controller dose not require any knowledge of nonlinear internal dynamics ensuring the trajectory tracking of systems multi-outputs. Finally, to validate the proposed method, a satellite numerical example illustrates the performance and robustness.

关键词： Trajectory Estimation Adaptive systems Nonlinear dynamical systems Equations

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A secure broadcasting method based on the generalized aryabhata remainder theorem

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Journal of Information Hiding and Multimedia signal processing 2014年第4期5卷 709-718页

作者： Liu, Yanjun Chang, Chin-Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University No.111 Jiulong Rd Hefei230601 China Department of Computer Science and Information Engineering Asia University No.500 Lioufeng Rd Wufeng Taichung413 Taiwan Department of Information Engineering and Computer Science Feng Chia University No.100 Wenhwa Rd Seatwen Taichung407 Taiwan

With the prevalence of group communications, how to implement secure broadcasting among group members has become one of the most important issues. Broadcasting is a point-to-multipoint communication, and secure broadcasting should ensure that only authorized group members can obtain the correct content of the message that is broadcast by a sender. In this paper, we propose a secure broadcasting method based on the generalized Aryabhata remainder theorem (GART). By the use of the RSA public-key scheme, the proposed scheme allows the sender to send one copy of an encrypted message to all group members, but only the authorized members can recover the plaintext. Analysis showed that our scheme is secure and efficient. © 2014.

关键词： Cryptography

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Adaptive Optimal Trajectory Tracking Control of Nonlinear Affine in Control System with unknown Internal Dynamics

Adaptive Optimal Trajectory Tracking Control of Nonlinear Af...

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第三十三届中国控制会议

作者： Tian Yang Wang Haoping Christian Vasseur Sino-French Joint Laboratory of Automation and Signal Processing School of Automation Nanjing University of Science and Technology Sino-French Joint Laboratory of Automation and Signal Processing LAGIS- CNRS UMR 8219 Lille University of Science and Technology Villeneuve d’Ascq France

ISBN: (纸本)9781479947249

This paper presents a new adaptive optimal nonlinear control for trajectory tracking of nonlinear affine-in control systems with unknown internal dynamics. The referred proposed controller which is based on a L2 norm prescribed to minimized a trajectory tracking error and a time-delay estimation technique based nonlinear systems unknown dynamics estimations has adaptive and optimal characters. Moreover with the systems output feedback, the proposed controller dose not require any knowledge of nonlinear internal dynamics ensuring the trajectory tracking of systems multi-outputs. Finally, to validate the proposed method, a satellite numerical example illustrates the performance and robustness.

关键词： Adaptive optimal control,uncertain nonlinear affine in control systems,uncertain dynamic estimation,time-delay estimation

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Lattice Reduction Aided Blind signal Separation Algorithm

Lattice Reduction Aided Blind Signal Separation Algorithm

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IEEE International Conference on Computational science and Engineering, CSE

作者： Kun Zhang Yourong Lu Wei Wang National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu P. R. China

ISBN: (纸本)9781479979820

Multi-antenna blind signal separation (BSS) provides a useful method for co-channel mixed signal processing. But the performance of BSS is limited by the condition number of channel matrix in the presence of noise. To overcome this problem, a new BSS algorithm with the aid of lattice reduction (LR) is proposed for synchronous communication systems. Simulation results show that the proposed algorithm improves the symbol error rate (SER) performance in noise environment while keeping the same complexity level.

关键词： Lattices Noise signal processing algorithms Complexity theory Algorithm design and analysis Vectors Blind source separation

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Quantitative identification of yellow rust, powdery mildew and fertilizer-water stress in winter wheat using In-Situ hyperspectral data

Quantitative identification of yellow rust, powdery mildew a...

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作者： Guan, Qingsong Huang, Wenjiang Zhao, Jinling Liu, Liangyun Liang, Dong Huang, Linsheng Wang, Li Yang, Guijun Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China Beijing Agriculture Information Technology Research Center Beijing China

As the progressive effects of global warming, the yield loss caused by diseases and pests are increasing in winter wheat. It is necessary to distinguish different diseases for guiding variable rate spraying in wheat. Nevertheless, it is very difficult to quantitatively identify different diseases and fertilizer-water stress by specific sensitive bands selected from multi spectral data over a large area. Conversely, hyper spectral data contain more information, and provide the potential for quantitative identification of different stresses. This study focused on identification and distinction of yellow rust, powdery mildew and fertilizer-water stress by canopy spectral reflectance. Fifteen commonly used vegetation indices were selected, and independent t-test was done to get sensitivity index for each stress. Finally, a combination index was optimally selected to distinguish the three stresses. The results showed that the integrative index (NDVI-PhRI) combining normalized difference vegetation index (NDVI) and physiological reflectance index (PhRI) could be used to identify powdery mildew and yellow rust (PM-YR). A 2-dimensional spatial coordinate was established based on the NDVI and PhRI derived from hyper spectral data, then the different stress data were displayed in the spatial coordinate and the classification boundary could be used to identify the powdery mildew and yellow rust stress. Similarly, yellow rust and fertilizer-water stress (YR-n0w0) can be distinguished by the combination index (MSR-PhRI) derived from modified simple ratio (MSR) and physiological reflectance index (PhRI);and the combination index (NRI-RVSI) derived from nitrogen reflectance index (NRI) and red-edge vegetation stress index (RVSI) was accurate to identify powdery mildew and fertilizer-water stress (PM-n0w0). For the PM-YR, YR-n0w0 and PM-n0w0 models, their verification accuracies were 83.3%, 88%, 88.75%, and the kappa accuracies were 63.41%, 74.79%, 71.43%, respectively. It indicate

关键词： Physiology

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Author Correction: The challenge of mapping the human connectome based on diffusion tractography

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Nature communications 2019年第1期10卷 5059页

作者： Klaus H Maier-Hein Peter F Neher Jean-Christophe Houde Marc-Alexandre Côté Eleftherios Garyfallidis Jidan Zhong Maxime Chamberland Fang-Cheng Yeh Ying-Chia Lin Qing Ji Wilburn E Reddick John O Glass David Qixiang Chen Yuanjing Feng Chengfeng Gao Ye Wu Jieyan Ma Renjie He Qiang Li Carl-Fredrik Westin Samuel Deslauriers-Gauthier J Omar Ocegueda González Michael Paquette Samuel St-Jean Gabriel Girard François Rheault Jasmeen Sidhu Chantal M W Tax Fenghua Guo Hamed Y Mesri Szabolcs Dávid Martijn Froeling Anneriet M Heemskerk Alexander Leemans Arnaud Boré Basile Pinsard Christophe Bedetti Matthieu Desrosiers Simona Brambati Julien Doyon Alessia Sarica Roberta Vasta Antonio Cerasa Aldo Quattrone Jason Yeatman Ali R Khan Wes Hodges Simon Alexander David Romascano Muhamed Barakovic Anna Auría Oscar Esteban Alia Lemkaddem Jean-Philippe Thiran H Ertan Cetingul Benjamin L Odry Boris Mailhe Mariappan S Nadar Fabrizio Pizzagalli Gautam Prasad Julio E Villalon-Reina Justin Galvis Paul M Thompson Francisco De Santiago Requejo Pedro Luque Laguna Luis Miguel Lacerda Rachel Barrett Flavio Dell'Acqua Marco Catani Laurent Petit Emmanuel Caruyer Alessandro Daducci Tim B Dyrby Tim Holland-Letz Claus C Hilgetag Bram Stieltjes Maxime Descoteaux Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg 69120 Germany. k.maier-hein@dkfz.de. Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg 69120 Germany. Sherbrooke Connectivity Imaging Lab (SCIL) Université de Sherbrooke Sherbrooke QC J1K 0A5 QC Canada. Department of Intelligent Systems Engineering School of Informatics and Computing Indiana University Bloomington IN 47408 USA. Krembil Research Institute University Health Network Toronto Canada M5G 2C4. Department of Neurological Surgery University of Pittsburgh School of Medicine Pittsburgh PA 15213 USA. IMT-Institute for Advanced Studies Lucca 55100 Italy. Department of Diagnostic Imaging St. Jude Children's Research Hospital Memphis TN 38105 USA. University of Toronto Institute of Medical Science Toronto Canada M5S 1A8. Institute of Information Processing and Automation Zhejiang University of Technology Hangzhou 310023 Zhejiang China. United Imaging Healthcare Co Shanghai 201807 China. Shanghai Advanced Research Institute Shanghai 201210 China. Laboratory of Mathematics in Imaging Harvard Medical School Boston MA 02215 USA. Center for Research in Mathematics Guanajuato 36023 Mexico. PROVIDI Lab Image Sciences Institute University Medical Center Utrecht Utrecht 3508 The Netherlands. Cardiff University Brain Research Imaging Centre School of Psychology Cardiff University Maindy Road Cardiff CF24 4HQ UK. Department of Radiology University Medical Center Utrecht Utrecht 3508 The Netherlands. Centre de recherche institut universitaire de geriatrie de Montreal (CRIUGM) Université de Montréal Montreal QC Canada H3W 1W5. Sorbonne Universités UPMC Univ Paris 06 CNRS INSERM Laboratoire d'Imagerie Biomédicale (LIB) 75013 Paris France. Center for Advanced Research in Sleep Medicine Hôpital du Sacré-Coeur de Montréal Montreal Canada H4J 1C5. Neuroimaging Unit Institute of Bioimaging and Molecular Physiology (IBFM) Nat

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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