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IEEE International Geoscience and Remote Sensing Symposium

作者： Qi Lv Yong Dou Xin Niu Jiaqing Xu Baoliang Li National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology

ISBN: (纸本)9781479953141

Urban land use and land cover (LULC) classification is one of the core applications in Geographic Information System (GIS). In this paper, a novel classification approach based on Deep Belief Network (DBN) for detailed urban mapping is proposed. Deep Belief Network (DBN) is a widely investigated and deployed deep learning model. By applying the DBN model, effective spatio-temporal mapping features can be automatically extracted to improve the classification performance. Six-date RADARSAT-2 Polarimetric SAR (PolSAR) data over the Great Toronto Area were used for evaluation. Experimental results showed that the proposed method can outperform SVM and contextual approaches using adaptive MRF.

关键词： Land cover classification Deep learning Restricted Boltzmann Machines (RBMs) Deep Belief Network (DBN) PolSAR

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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： He Yi-Bai Chen Shu-Ming 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：重离子实验放大效应单事件双极寄生 PMOS 验证瞬态

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Low-trimming-power design of on-chip optical networks

Low-trimming-power design of on-chip optical networks

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Photonic Networks and Devices, 2014

作者： Zhang, Luo Kefie, Wang Zhengbin, Pang Weixia, Xu School of Computer Science National University of Defense Technology Changsha 410073 China National Laboratory for Parallel and Distribution Processing National University of Defense Technology Changsha 410073 China

The trimming power of on-chip optical networks consisted by 105 microrings is simulated. The total trimming power is no larger than 14W from 20°C to 100°C, if the distribution of these rings is optimized. &#... 详细信息

ISBN: (纸本)9781557527370

关键词： Fiber optic networks

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Who should review this pull-request: Reviewer recommendation to expedite crowd collaboration 21

Who should review this pull-request: Reviewer recommendation...

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21st Asia-Pacific Software Engineering Conference, APSEC 2014

作者： Yu, Yue Wang, Huaimin Yin, Gang Ling, Charles X. National Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha410073 China Department of Computer Science University of Western Ontario LondonONN6A 5B7 Canada

ISBN: (纸本)9781479974252

Github facilitates the pull-request mechanism as an outstanding social coding paradigm by integrating with social media. The review process of pull-requests is a typical crowdsourcing job which needs to solicit opinions of the community. Recommending appropriate reviewers can reduce the time between the submission of a pull-request and the actual review of it. In this paper, we firstly extend the traditional Machine Learning (ML) based approach of bug triaging to reviewer recommendation. Furthermore, we analyze social relations between contributors and reviewers, and propose a novel approach to recommend highly relevant reviewers by mining comment networks (CN) of given projects. Finally, we demonstrate the effectiveness of these two approaches with quantitative evaluations. The results show that CN-based approach achieves a significant improvement over the ML-based approach, and on average it reaches a precision of 78% and 67% for top-1 and top-2 recommendation respectively, and a recall of 77% for top-10 recommendation. © 2014 IEEE.

关键词： Learning systems

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Hierarchical categorization of open source software by online profiles

Hierarchical categorization of open source software by onlin...

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作者： Wang, Tao Wang, Huaimin Yin, Gang Yang, Cheng Li, Xiang Zou, Peng Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China Department of Computer Science University of Western Ontario London ON N6A 5B7 Canada Academy of Equipment Beijing 100000 China

The large amounts of freely available open source software over the Internet are fundamentally changing the traditional paradigms of software development. Efficient categorization of the massive projects for retrieving relevant software is of vital importance for Internet-based software development such as solution searching, best practices learning and so on. Many previous works have been conducted on software categorization by mining source code or byte code, but were verified on only relatively small collections of projects with coarse-grained categories or clusters. However, Internet-based software development requires finer-grained, more scalable and language-independent categorization approaches. In this paper, we propose a novel approach to hierarchically categorize software projects based on their online profiles. We design a SVMbased categorization framework and adopt a weighted combination strategy to aggregate different types of profile attributes from multiple repositories. Different basic classification algorithms and feature selection techniques are employed and compared. Extensive experiments are carried out on more than 21,000 projects across five repositories. The results show that our approach achieves significant improvements by using weighted combination. Compared to the previous work, our approach presents competitive results with more finer-grained and multi-layered category hierarchy with more than 120 categories. Unlike approaches that use source code or byte code, our approach is more effective for large-scale and languageindependent software categorization. In addition, experiments suggest that hierarchical categorization combined with general keyword-based searching improves the retrieval efficiency and accuracy. Copyright © 2014 The Institute of Electronics, Information and Communication Engineers.

关键词： Open source software

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Delayed Switch:Cloud Service Upgrade with Low Availability and Capacity Loss

Delayed Switch:Cloud Service Upgrade with Low Availability a...

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2014 IEEE 5th International Conference on Software Engineering and Service science

作者： Xue Ouyang Bo Ding Huaimin Wang Parallel and Distributed Laboratory School of Computer Science National University of Defense Technology

Cloud services must upgrade continuously in order to maintain ***,a large body of empirical evidence suggests that,upgrade procedures used in practice are failure-prone and often cause planned or unplanned *** this paper,we first define what is cloud service online upgrade,and then we analyze the shortcomings of current mainstream cloud service online upgrade *** particular,the mixed version problem along with rolling upgrade and the capacity loss problem brought by split mode upgrade have been *** that,we propose a solution called Delayed Switch,which can conduct cloud service upgrade with lower loss of availability and capacity in contrast with existing *** prove the performance of delayed switch in theory and develop a prototype system applying this *** by conducting experiments with a typical e-commerce service named Rubis,we validate the effectiveness and efficiency of our approach.

关键词： cloud service availability on-line upgrade mixed version problem split mode upgrade

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AUModel:A Conceptual model for Adaptive Software

AUModel:A Conceptual model for Adaptive Software

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2014 IEEE 5th International Conference on Software Engineering and Service science

作者： Hui Liu Bo Ding Dianxi Shi Huaimin Wang National Key Laboratory for Parallel and Distributed Processing College of Computer ScienceNational University of Defense Technology

Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive software,which takes adaptability as an inherent feature and can act as the foundation of the engineering *** introducing AUModel,the reuse of software adaptation infrastructure as well as the separation of adaptation concerns are enabled,which can facilitate both the development and maintenance of adaptive *** paper also presents our initial attempts to realize this model,including a middleware prototype to support this model and an application to validate its effectiveness.

关键词： pervasive computing adaptive software middleware

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IWFR: Exploiting full-duplex in wireless relay networks

IWFR: Exploiting full-duplex in wireless relay networks

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International Conference on Information science and technology (ICIST)

作者： Yong Lu Shaohe Lv Xiaodong Wang Xingming Zhou National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan China

Traditional wireless relay networks have large end-to-end time delay and low throughput because of the limit that it can't receive and forward at the same time. In this paper, we proposed IWFR: Immediate Wireless Full-Duplex Relay which exploits the advantages of full-duplex to shorten the end-to-end time delay and improve the throughput. At the same time, we designed a new implicit acknowledgement mechanism, which can eliminate the ACK overheads and evidently improve the throughput of the relay. To implement IWFR, we also modified the full-duplex node architecture to make it support for immediate relay. Simulation shows that IWFR shortens the end-to-end time delay by 60% on average and improves the throughput to 240% of the original relay.

关键词： Wireless communication Throughput Delay effects Wireless sensor networks Interference Relay networks (telecommunications)

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DKNNS:Scalable and accurate distributed K nearest neighbor search for latency-sensitive applications

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science China(Information sciences) 2013年第3期56卷 123-139页

作者： FU YongQuan WANG YiJie National Key Laboratory for Parallel and Distributed Processing School of Computer ScienceNational University of Defense Technology

To reduce the access latencies of end hosts,latency-sensitive applications need to choose suitably close service machines to answer the access requests from end *** K nearest neighbor search locates K service machines closest to end hosts,which can efficiently optimize the access latencies for end *** work has weakness in terms of the accuracy and *** to the scalable and accurate K nearest neighbor search problem,we propose a distributed K nearest neighbor search method called DKNNS in this *** machines are organized into a locality-aware multilevel *** first locates a service machine that starts the search process based on a farthest neighbor search scheme,then discovers K nearest service machines based on a backtracking approach within the proximity region containing the target in the latency *** analysis,simulation results and deployment experiments on the PlanetLab show that,DKNNS can determine K approximately optimal service machines,with modest completion time and query ***,DKNNS is also quite stable that can be used for reducing frequent searches by caching found nearest neighbors.

关键词： latency sensitive network applications K nearest neighbor search network coordinate

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Soft-Constrained Nonnegative Matrix Factorization via Normalization

Soft-Constrained Nonnegative Matrix Factorization via Normal...

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International Joint Conference on Neural Networks

作者： Long Lan Naiyang Guan Xiang Zhang Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Semi-supervised clustering aims at boosting the clustering performance on unlabeled samples by using labels from a few labeled samples. Constrained NMF (CNMF) is one of the most significant semi-supervised clustering methods, and it factorizes the whole dataset by NMF and constrains those labeled samples from the same class to have identical encodings. In this paper, we propose a novel soft-constrained NMF (SCNMF) method by softening the hard constraint in CNMF. Particularly, SCNMF factorizes the whole dataset into two lower-dimensional factor matrices by using multiplicative update rule (MUR). To utilize the labels of labeled samples, SCNMF iteratively normalizes both factor matrices after updating them with MURs to make encodings of labeled samples close to their label vectors. It is therefore reasonable to believe that encodings of unlabeled samples are also close to their corresponding label vectors. Such strategy significantly boosts the clustering performance even when the labeled samples are rather limited, e.g., each class owns only a single labeled sample. Since the normalization procedure never increases the computational complexity of MUR, SCNMF is quite efficient and effective in practices. Experimental results on face image datasets illustrate both efficiency and effectiveness of SCNMF compared with both NMF and CNMF.

关键词： Matrix decomposition Encoding Vectors Clustering methods Clustering algorithms Time complexity Face

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