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2012年全国理论计算机科学学术年会(NCTCS2012)

作者： Licai Guo Zhangjin Huang School of Computer Science and Technology University of Science and Technology of China PR China USTC-SICT Joint Laboratory on Network and Key Laboratory of Software in Computing and Communication Anhui Province PR China USTC-SICT Joint Laboratory on Network and Communication PR China School of Computer Science and Technology University of Science and Technology of China PR China

parallel framework for NURBS-based isogeometric analysis on multi-core cpus is presented in this *** framework is composed of two parts:(1) construction of the stiffness matrix and right hand side vector; (2) a parall...

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Practical privacy-preserving mixing protocol for Bitcoin

Practical privacy-preserving mixing protocol for Bitcoin

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International Conference on Computer Supported Cooperative Work in Design

作者： Qianqian Chang Lin Xu Lei Zhang Shanghai Key Laboratory of Trustworthy Computing East China Normal University China Science and Technology on Communication Security Laboratory Chengdu China Ministry of Education Engineering Research Center of Software/Hardware Co-Design Technology and Application China

The privacy of Cryptocurrencies are of great concern in various fields. Researches has shown that pseudonyms, which are used in Bitcoin, only provide weak privacy. The privacy of users may be put at risk under deanonymization attacks. The exisiting schemes typically require a trusted-third party to achieve anonymity, however this usually faces a single-point fault. In addition, existing schemes suffer from high communication complexity and impracticality. This paper proposes a practical privacy-preserving mixing protocol for Bitcoin to achieve unlink-ability of input and output address of transactions. Compared to existing schemes, our protocol improves practicality. The communication complexity of our protocol is linearly related to the number of peers. Moreover, our protocol is scalable as it works not only for Bitcoin, but also for other cryptocurrencies.

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ALOHA-like neighbor discovery in low-duty-cycle wireless sensor networks

ALOHA-like neighbor discovery in low-duty-cycle wireless sen...

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IEEE Conference on Wireless communications and Networking

作者： Lizhao You Zimu Yuan Panlong Yang Guihai Chen State Key Laboratory of Novel Software Technology Nanjing University China Institute of Computing Technology Chinese Academy and Sciences China Institute of Communication Engineering People''s Liberation Army University of Science and Technology China

Neighbor discovery is an essential step for the self-organization of wireless sensor networks. Many algorithms have been proposed for efficient neighbor discovery. However, most of those algorithms need nodes to keep active during the process of neighbor discovery, which might be difficult for low-duty-cycle wireless sensor networks in many real deployments. In this paper, we investigate the problem of neighbor discovery in low-duty-cycle wireless sensor networks. We give an ALOHA-like algorithm and analyze the expected time to discover all n - 1 neighbors for each node. By reducing the analysis to the classical K Coupon Collector's Problem, we show that the upper bound is ne(log 2 n + (3 log 2 n - 1) log 2 log 2 n + c) with high probability, for some constant c, where e is the base of natural logarithm. Furthermore, not knowing number of neighbors leads to no more than a factor of two slowdown in the algorithm performance. Then, we validate our theoretical results by extensive simulations, and explore the performance of different algorithms in duty-cycle and non-duty-cycle networks. Finally, we apply our approach to analyze the scenario of unreliable links in low-duty-cycle wireless sensor networks.

关键词： Wireless sensor networks Algorithm design and analysis Upper bound Simulation Random variables Equations Synchronization

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Interactive reflection simulation via physical shading model and fast environment mapping

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ICIC Express Letters, Part B: Applications 2016年第2期7卷 351-356页

作者： Xu, Jie Fu, Jinhua School of Software Zhengzhou University of Light Industry China School of Computer and Communication Engineering Zhengzhou University of Light Industry No. 5 Dongfeng Road Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute Zhengzhou China

In order to enhance realistic reflection effects on some objects and realize faster rendering to meet interactive requirements, we present a novel method to produce interactive reflection simulation using physical shading model and fast environment mapping. The physical shading model could efficiently express ambient lighting, specular lighting and diffuse lighting. Also the model is based on the microfacet distribution function, which can describe physics-based characteristics. Fast environment mapping is realized by Spherical Harmonics (SH) transformation, and the rendering equation can be rewritten as a simple dot product of SH coefficients, which fits for GPU (Graphics Processing Unit) computation. The results show that we can realize faster rendering and acquire realistic reflection effects such as glossy and mapping scene on the surface. © 2016 ICIC International.

关键词： Lighting

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New Framework for Code-Mapping-based Reversible Data Hiding in JPEG Images

arXiv

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arXiv 2020年

作者： Du, Yang Yin, Zhaoxia Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Anhui Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China School of Communication & Electronic Engineering East China Normal University Shanghai200241 China

Code mapping (CM) is an efficient technique for reversible data hiding (RDH) in JPEG images, which embeds data by constructing a mapping relationship between the used and unused codes in the JPEG bitstream. This study presents a new framework for designing a CM-based RDH method. First, a new code mapping strategy is proposed to suppress file size expansion and improve applicability. Based on our proposed strategy, the mapped codes are redefined by creating a new Huffman table rather than selecting them from the unused codes in the original Huffman table. The critical issue of designing the CM-based RDH method, that is, constructing code mapping, is converted into a combinatorial optimization problem. This study proposes a novel CM-based RDH method that utilizes a genetic algorithm (GA). The experimental results demonstrate that the proposed method achieves a high embedding capacity with no signal distortion while suppressing file size expansion. Copyright © 2020, The Authors. All rights reserved.

关键词： Mapping

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A Method to Verify Internal Parameters of Camera Calibration in World Coordinate System

A Method to Verify Internal Parameters of Camera Calibration...

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IEEE International Conference on Electronic Information and communication Technology (ICEICT)

作者： Zheng Xing Qingchun Wang Yingsong Li Junwei Qi College of Information and Communication Engineering Harbin Engineering University Harbin China Shanghai Yanding Information Technology Co. Ltd. Shanghai China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

Aiming at the problem that reprojection error (RE) cannot reflect the camera calibration accuracy intuitively, this paper proposes a method to verify the camera calibration results in world coordinate system. Firstly, the checkerboard calibration target is photographed with the camera under test, and the internal parameters and distortion parameters of the camera are calculated by using the pinhole model and the Kannala-Brandt (KB) fisheye model, respectively. Then, the same camera is used to shoot two targets in the field of view (FOV), and the pixel coordinates of the two target points are detected from the image. Thirdly, the inverse projection model is used to calculate the distance between the two objects and the angle between the camera and the two objects, and the real distance and angle are compared. The experimental results show that the average distance errors of the pinhole model and the KB fisheye model are 0.34% and 0.35%, respectively, and the angle errors are 0.40% and 0.12%, respectively, which proves that the verification method can effectively characterize the calibration accuracy of the camera.

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DETECTING THE RUN TIME ATTACKS IN THE CLOUD WITH AN EVIDENCE COLLECTION BASED APPROACH

DETECTING THE RUN TIME ATTACKS IN THE CLOUD WITH AN EVIDENCE...

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2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Jie lin Chuanyi Liu Zhichun Ning Binxing Fang School of Computer Science Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service(BUPT) Ministry of Education School of Software Engineering Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing University of Posts and Telecommunications

As the impacts of security threats are amplified and spread quickly in the cloud,especially with the attribute of large-scale *** of researches focus on monitoring the network ***,these methods don't check how the attack happened and what damage the attack caused for the virtual *** paper presents a logging method to analyze the potential attacks out of VM and a prototype was *** experimental results show that this method can detect the real world attacks effectively and the performance overhead is acceptable.

关键词： Virtual machine Cloud Security Control

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Matrix Classifier On Dynamic Functional Connectivity For Mci Identification

Matrix Classifier On Dynamic Functional Connectivity For Mci...

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IEEE International Conference on Image Processing

作者： Lei Zhou Liang Zhang Xiao Bai Jun Zhou School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing State Key Laboratory of Software Development Environment Beihang University Beijing School of Information and Communication Technology Griffith University Nathan

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

One of the most popular method for Alzheimer's disease (AD) diagnosis is exploring the Brain functional connectivity (FC) from resting-state functional magnetic resonance imaging (RS-fMRI). To early prevent AD, it is crucial to distinguish AD and and its preclinical stage, mild cognitive impairment (MCI) and early MCI (eMCI). In many existing works, dynamic functional connectivity (dFC) which contains rich spatiotemporal information has been exploited for the MCI and eMCI identification. However, most of these dFC based methods only consider the correlation between discrete brain status while ignore the valuable spatiotemporal information contained in dFC. To overcome this limitation, we propose a matrix classifier based method on the dFC signal for MCI and eMCI identification. Specifically, we first represent the dFC correlations by matrix features which contain rich spatiotemporal information and then learn the support matrix machines (SMM) to classify AD and its preclinical stage. Experiments on 600 real people data provide by the Alzheimer's Disease Neuroimaging Initiative (ADNI) demonstrate that our proposed matrix classifier based method outperforms other FC and dFC based methods for both normal controls (NC)/MCI identification and NC/eMCI identification.

关键词： Feature extraction Correlation Dementia Microsoft Windows Spatiotemporal phenomena Training

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Multi-Layer Visual Perception for No-Reference Image Quality Assessment

Multi-Layer Visual Perception for No-Reference Image Quality...

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IEEE International Conference on Electronic Information and communication Technology (ICEICT)

作者： Junwei Qi Yingzhen Wang Qingchun Wang Yingsong Li College of Computer Science and Technology Harbin Engineering University Harbin China College of Information and Communication Engineering Harbin Engineering University Harbin China Shanghai Yanding Information Technology Co. Ltd. Shanghai China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China

In this work, we propose a no-reference image quality evaluation approach, aiming to solve the problem that the traditional convolutional neural network is insufficient to express the global information of the image. Therefore, in order to make the captured image features have the coherence of global context information, we combine a Transformer structure widely used in NLP (natural language processing) with the traditional CNN to realize the attention mechanism in the human visual perception characteristics. Firstly, the self-attention mechanism of Transformer is used to learn the global representation of the image from the multi-layer features extracted from different levels of CNN. Additionally, to forecast the ultimate image quality score, the global and local attributes are combined. Finally, the proposed algorithm is evaluated on three public datasets commonly used in CSIQ [1], TID2013 [2] and LIVE [3]. Compared with eight traditional no-reference image quality evaluation algorithms and five methods based on deep learning, the proposed algorithm achieves competitive results.

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Speaker recognition with mel scale-based wavelet packet decomposition and AR-volterra model

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ICIC Express Letters, Part B: Applications 2016年第10期7卷 2087-2094页

作者： Yang, Shuying Guo, Jijn Jiang, Jiaojiao School of Computer and Communication Engineering Tianjin University of Technology No. 391 Binshui Xidao Xiqing District Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology No. 391 Binshui Xidao Xiqing District Tianjin300384 China

In order to improve the rate of speaker recognition, this paper proposes a new scheme with Mel scale-based Wavelet Packet Decomposition and AR-Volterra model. First, the speech signal is decomposed by wavelet packet of Mel scale, and calculate energy spectrum of the sub-band signals. The sub-bands of low energy are discarded according to weighting the proportion ofenergy for all-bands. Second, chaos ofsub-band signals are determined by the largest Lyapunov exponent. Ifsub-band is chaotic, Volterra adaptive model will be used to extract features. Otherwise, the autoregressive model will be used to extract features. Third, linear and nonlinear characteristic parameters will be used to speaker recognition. Hidden Markov model is used to recognize speaker. The experimental results show the extracted features have been obviously improved. © 2016 ICIC International.

关键词： Hidden Markov models

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