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2015 6th IEEE International Conference on Software Engineering and Service Science(ICSESS 2015)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing School of Computer National University of Defense Technology

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in Stack Overflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in Stack Overflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Software ranking Open Source Crowd Wisdom Open Source Community

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Robust Weighted Supervised Sparse Coding for Image Classification

Robust Weighted Supervised Sparse Coding for Image Classific...

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2015 IEEE 16th International Conference on Communication Technology(ICCT 2015)

作者： Xiang Zhang Naiyang Guan Zhigang Luo College of Computer National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Sparse coding has shown its great potential in learning image feature representation. Recent developed methods such as group sparse coding prefer discovering the group relationships among examples and have achieved the state-of-the-art results in image classification. However, they suffer from poor robustness shortcomings in practice. This paper proposes a robust weighted supervised sparse coding method(RWSSC) to address this ***, RWSSC distinguishes different classes' contributions to the sparse coding by a novel weighting strategy meanwhile removes the out liers by imposing1 l-regularization over the noisy entries. Benefitting from these strategies, RWSSC can effectively boost performance of sparse coding in image ***, we developed the block coordinate descent algorithm to optimize it, and proved its *** results of image classification on two popular datasets show that RWSSC outperforms the representative sparse coding methods in quantities.

关键词： Sparse coding Supervised learning Image classification

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Virtual Frame Aggregation: Clustered Channel Access in Wireless Networks

Virtual Frame Aggregation: Clustered Channel Access in Wirel...

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IEEE International Conference on Communications

作者： Xuan Dong Shaohe Lv Chunsheng Zhu Rukhsana Ruby Xiaodong Wang Xingming Zhou Victor C. M. Leung National Laboratory of Parallel and Distributed Processing National University of Defense Technology Department of Electrical and Computer Engineering The University of British Columbia

ISBN: (纸本)9781467364300

Coordination among users is inevitable in wireless communication for efficient medium access. Even though the data rate of individual user increases significantly, the performance of wireless network does not grow up accordingly due to the high MAC coordination overhead. In this paper, we present VFA, namely virtual frame aggregation, to achieve high coordination efficiency by amortizing the overhead over multiple transmissions. VFA provides a novel way to construct a winner cluster and allow the winners to transmit without interruption. Specifically, in a multicarrier network, every contending node chooses a subcarrier and the nodes are ordered by the index of the chosen subcarrier. When there are some subcarriers chosen by two or more nodes, an additional slot is exploited to reorder the collided nodes. Finally, all ordered nodes form a cluster and the transmissions are issued sequentially and uninterruptedly. Simulation results show that usually two slots are enough to construct a sufficiently large winner cluster. Moreover, VFA achieves a notable throughput gain over IEEE 802.11 as high as 120% with better fairness under various scenarios.

关键词： Wireless communication Antennas Wires

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Comparison of heavy-ion induced SEU for D- and TMR-flip-flop designs in 65-nm bulk CMOS technology

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Science China(Information Sciences) 2014年第10期57卷 223-229页

作者： HE YiBai CHEN ShuMing School of Computer Science National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

Heavy ion experiments were performed on D flip-flop(DFF) and TMR flip-flop(TMRFF) fabricated in a 65-nm bulk CMOS process. The experiment results show that TMRFF has about 92% decrease in SEU crosssection compared to the standard DFF design in static test mode. In dynamic test mode, TMRFF shows much stronger frequency dependency than the DFF design, which reduces its advantage over DFF at higher operation frequency. At 160 MHz, the TMRFF is only 3.2× harder than the standard DFF. Such small improvement in the SEU performance of the TMR design may warrant reconsideration for its use in hardening design.

关键词： SEU flip-flop TMR heavy-ion frequency

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Classification of Tiangong-1 hyperspectral remote sensing image via contextual sparse coding

Classification of Tiangong-1 hyperspectral remote sensing im...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qi Lv Yong Dou Xin Niu Jiaqing Xu Jinbo Xu School of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9781467372220

The hyperspectral remote sensing is one of the frontier techniques in the remote sensing research fields. Applying the sparse coding model to the hyperspectral remote sensing image processing is a hot topic in hyperspectral information processing. To improve the accuracy of hyperspectral image classification, we propose a classification method based on the spatial-spectral join-t contextual sparse coding. Firstly, a dictionary is obtained by training using samples selected from the ground-truth reference data. Then, the sparse coefficients of each pixel are calculated based on the learned dictionary. Afterward, the sparse coefficients are input to the classifier and the final classification result is obtained. The visible and near-infrared hyperspectral remote sensing image collected by Tiangong-1 in Chaoyang District of Beijing is used to evaluate the performance of the proposed approach. Experimental results show that the proposed method yields the best classification performance with the overall accuracy of 95.74% and the Kappa coefficient of 0.9476 in comparison with other classification methods.

关键词： Hyperspectral image Remote sensing Sparse coding Sparse coding Classification Methods remote sensing hyperspectral remote sensing hyperspectral imagery Image classification

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Experimental verification of the parasitic bipolar amplification effect in PMOS single event transients

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Chinese Physics B 2014年第7期23卷 775-779页

作者：何益百陈书明 College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

The contribution of parasitic bipolar amplification to SETs is experimentally verified using two P-hit target chains in the normal layout and in the special layout. For PMOSs in the normal layout, the single-event charge collection is composed of diffusion, drift, and the parasitic bipolar effect, while for PMOSs in the special layout, the parasitic bipolar junction transistor cannot turn on. Heavy ion experimental results show that PMOSs without parasitic bipolar amplification have a 21.4% decrease in the average SET pulse width and roughly a 40.2% reduction in the SET cross-section.

关键词： single event effect single event transient parasitic bipolar amplification heavy ion experiments

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OpenMP-Based Monte Carlo Dose Calculation for Radiotherapy Treatment Planning on the Intel MIC Architecture

OpenMP-Based Monte Carlo Dose Calculation for Radiotherapy T...

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Qinglin Wang Jie Liu Peizhen Xie Chunye Gong Yuan Li Zuocheng Xing School of Computer Science National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

Monte Carlo (MC) simulation plays an important part in dose calculation for radiotherapy treatment planning. Since the accuracy of MC simulation relies on the number of simulated particles histories, it's very time-consuming. The Intel Many Integrated Core (MIC) architecture, which consists of more than 50 cores and supports many parallel programming models, provides an efficient alternative for accelerating MC dose calculation. This paper implements the OpenMP-based MC Dose Planning Method (DPM) for radiotherapy treatment problems on the Intel MIC architecture. The implementation has been verified on the target MIC coprocessor including 57 cores. The results demonstrate that the OpenMP-based DPM implementation exhibits very accurate results and achieves the maximum speedup of 10.53 times in comparison to the original DPM one on a Xeon E5-2670 CPU. Additionally, speedup and efficiency of the implementation running on the different number of cores in MIC are also reported.

关键词： Microwave integrated circuits Instruction sets computer architecture Photonics Computational modeling History Interpolation

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Robust weighted supervised sparse coding for image classification

Robust weighted supervised sparse coding for image classific...

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International Conference on Communication Technology (ICCT)

作者： Xiang Zhang Naiyang Guan Zhigang Luo College of Computer National University of Defense Technology Changsha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467370066

Sparse coding has shown its great potential in learning image feature representation. Recent developed methods such as group sparse coding prefer discovering the group relationships among examples and have achieved the state-of-the-art results in image classification. However, they suffer from poor robustness shortcomings in practice. This paper proposes a robust weighted supervised sparse coding method (RWSSC) to address this deficiency. Particularly, RWSSC distinguishes different classes' contributions to the sparse coding by a novel weighting strategy meanwhile removes the out liers by imposing l1-regularization over the noisy entries. Benefitting from these strategies, RWSSC can effectively boost performance of sparse coding in image classification. Besides, we developed the block coordinate descent algorithm to optimize it, and proved its convergence. Experimental results of image classification on two popular datasets show that RWSSC outperforms the representative sparse coding methods in quantities.

关键词： Support vector machines Robustness Classification algorithms Dictionaries Manganese

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Running mechanism and implementation technique of self-adaptive software in open environment

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Jisuanji Xuebao/Chinese Journal of computers 2015年第9期38卷 1893-1906页

作者： Mao, Xin-Jun Dong, Meng-Gao Qi, Zhi-Chang Yin, Jun-Wen Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha410073 China Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China Laboratory of Science and Technology on Integrated Logistic Support National University of Defense Technology Changsha410073 China

Due to the uncertainty and unpredictability of environment changes, it is a great challenge to develop self-adaptive systems in open environment. First, it is difficult for developers to clearly predict various environment changes and precisely define self-adaptation requirements at design-time. Second, many of self-adaptation decisions should be made by system at run-time. In order to deal with the problems, the paper presents an approach that is based on software agent technology and organization metaphor to support the development and running of such systems. Our approach enables developer to describe self-adaptive systems and investigate self-adaptation according to the high-level organization abstractions. A self-adaptation mechanism called role dynamic binding is designed and on-line self-adaptation is achieved by introducing enforcement learning. The paper details the on-line self-adaptation decision algorithm that integrates dynamic binding mechanism with enforcement learning together. Especially, a general-purpose and systematics software engineering solution to developing such system is provided, including self-adaptive software model, implementation framework, structured process and supporting software environment SADE+. A case is studied to illustrate our approach and validate its effectiveness. ©, 2015, Jisuanji Xuebao/Chinese Journal of computers. All right reserved.

关键词： Dynamics

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An Online/Offline HIBS Scheme for Privacy Protection of People-centric Sensing

An Online/Offline HIBS Scheme for Privacy Protection of Peop...

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International Conference on Industrial Informatics, Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII)

作者： Peixin Chen Xiaofeng Wang Jinshu Su College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467383134

People-Centric Sensing (PCS), which collects information closely related to human activity and interactions in societies, is stepping into a flourishing time. Along with its great benefits, PCS poses new security challenges such as data integrity, participant privacy. Hierarchical Identity-Based Signature (HIBS) scheme can efficiently provide high integrity messaging, secure communication and privacy protection to PCS. However, the low computation efficiency primarily hinders the PCS adoption of HIBS scheme. In this paper, we propose an online/offline HIBS (HIBOOS) scheme for securing PCS. By splitting the signing phase into online and offline procedures, our scheme achieves high signing efficiency.

关键词： Games Sensors Privacy Public key Generators Wireless sensor networks

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