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Numerical study of the effects of check dams on erosion and sedimentation in the Pachang River

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International Journal of Sediment Research 2013年第3期28卷 304-315页

作者： Hui-ming HSIEH Ching-ruey LUO Jinn-chuang YANG Rou-fei CHEN department of computer Science and multimedia Design Taiwan Shoufu University department of Civil Engineering National Chi-Nan University Dept.of Civil Engineering National Chiayio Tung University department of Geology Chinese Culture University

Scouring and deposition processes resulting from variable rainfall and typhoon occurrence in tropical climatic conditions induce significant changes in the riverbeds of *** the Pachang River of western Taiwan,severe damage occurs during typhoons due to large and sudden variations in discharge,erosion,sediment transport and *** order to simulate this process,the NETSTARS numerical modeling tool was used in the present *** influence of existing and planned check dam structures on flow control was also analyzed to determine their capacity to resist river erosion or to not be buried beneath *** only does the modeling tool allow calculation of the erosion-deposition behavior at the scale of the whole river,but it also provides local determination of the optimum location and characteristics such as foundation depth and lateral encroachment of future check *** results of a 10-year,long-term modeling simulation in terms of riverbed stability and scouring potential thus provide insights about unsafe future behavior at 4 *** numerical model provides a better general understanding and useful information for the optimal prevention of both the scouring damage and the burial related to sediment deposition with large changes in discharge and sediment transport.

关键词： NETSTARS model River bed erosion Check dam Pachang River

Robust visual tracking based on scale invariance and deep learning

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Frontiers of computer Science 2017年第2期11卷 230-242页

作者： Nan REN Junping DU Suguo ZHU Linghui LI Dan FAN JangMyung LEE Beijing Key Laboratory of Intelligent Telecommunication Software and multimedia School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 China department of Electronics Engineering Pusan National University Busan 46241 Korea

Visual tracking is a popular research area in com- puter vision, which is very difficult to actualize because of challenges such as changes in scale and illumination, rota- tion, fast motion, and occlusion. Consequently, the focus in this research area is to make tracking algorithms adapt to these changes, so as to implement stable and accurate vi- sual tracking. This paper proposes a visual tracking algorithm that integrates the scale invariance of SURF feature with deep learning to enhance the tracking robustness when the size of the object to be tracked changes significantly. Particle filter is used for motion estimation. The co^fidence of each parti- cle is computed via a deep neural network, and the result of particle filter is verified and corrected by mean shift because of its computational efficiency and insensitivity to external interference. Both qualitative and quantitative evaluations on challenging benchmark sequences demonstrate that the pro- posed tracking algorithm performs favorably against several state-of-the-art methods throughout the challenging factors in visual tracking, especially for scale variation.

关键词： visual tracking SURF mean shift particle filter neural network

An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

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Journal of Shanghai Jiaotong university(Science) 2018年第4期23卷 577-583页

作者： LI Shuoming CHEN Lei CHEN Shihong National Engineering Research Center for multimedia Software School of computer Science Wuhan UniversityWuhan 430072China

In order to realize high precision of environment parameters detection in irrigation applications,a sensor and sensor network(SSN) ontology based data fusion method is *** SSN sub-ontology for soilstate monitoring is revised,which includes the sensing devices hierarchies and measurement properties selection according to the detection feature *** for sensor data processing,a tuning data method by data pool filtering and clustering is adopted,as well as a useful data fusion method for multi-sensor *** testing results show that both the accuracy and efficiency of the proposed method are higher after related filtering and clustering process,which enables a thorough monitoring for intelligent irrigation systems and can be extended into environment monitoring and control applications.

关键词： sensor and sensor network(SSN) data fusion intelligent irrigation environment monitoring

Robust reconstruction of curved line structures in noisy point clouds

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Visual Informatics 2021年第3期5卷 1-14页

作者： Marcel Ritter Daniel Schiffner Matthias Harders Interactive graphics and Simulation Group Department of Computer ScienceUniversity of InnsbruckAustria Airborne Hydromapping GmbH InnsbruckAustria DIPF|Leibniz Institute for Research and Information Education FrankfurtGermany

Point-based geometry representations have become widely used in numerous contexts,ranging from particle-based simulations,over stereo image matching,to depth sensing via light detection and *** application focus is on the reconstruction of curved line structures in noisy 3D point cloud *** algorithms operating on such point clouds often rely on the notion of a local *** the latter,our approach employs multi-scale neighborhoods,for which weighted covariance measures of local points are *** line structures are reconstructed via vector field tracing,using a bidirectional piecewise streamline *** also introduce an automatic selection of optimal starting points via multi-scale geometric *** pipeline development and choice of parameters was driven by an extensive,automated initial analysis process on over a million prototype test *** behavior of our approach is controlled by several parameters—the majority being set automatically,leaving only three to be controlled by a *** an extensive,automated final evaluation,we cover over one hundred thousand parameter sets,including 3D test geometries with varying curvature,sharp corners,intersections,data holes,and systematically applied varying types of ***,we analyzed different choices for the point of reference in the co-variance computation;using a weighted mean performed best in most *** addition,we compared our method to current,publicly available line reconstruction *** to thirty times faster execution times were achieved in some cases,at comparable error ***,we also demonstrate an exemplary application on four real-world 3D light detection and ranging datasets,extracting power line cables.

关键词： Computational geometry Noisy point clouds Line reconstruction Automatic Adaptive control

Review Authorship Attribution in a Similarity Space

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Journal of computer Science & Technology 2015年第1期30卷 200-213页

作者：钱铁云刘兵李青司建锋 State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China department of computer Science University of Illinois at Chicago Chicago 60607 U.S.A. multimedia Software Engineering Research Centre and department of computer Science City University of Hong Kong Hong Kong China Data Analytics department Institute for Infocomm Research Singapore 138632 Singapore

Authorship attribution, also known as authorship classification, is the problem of identifying the authors （reviewers） of a set of documents （reviews）. The common approach is to build a classifier using supervised learning. This approach has several issues which hurts its applicability. First, supervised learning needs a large set of documents from each author to serve as the training data. This can be difficult in practice. For example, in the online review domain, most reviewers （authors） only write a few reviews, which are not enough to serve as the training data. Second, the learned classifier cannot be applied to authors whose documents have not been used in training. In this article, we propose a novel solution to deal with the two problems. The core idea is that instead of learning in the original document space, we transform it to a similarity space. In the similarity space, the learning is able to naturally tackle the issues. Our experiment results based on online reviews and reviewers show that the proposed method outperforms the state-of-the-art supervised and unsupervised baseline methods significantly.

关键词： authorship attribution supervised learning similarity space

Standardized Evaluation of Camera-based Driver State Monitoring Systems

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 716-732页

作者： Renran Tian Keyu Ruan Lingxi Li Jialiang Le Jeff Greenberg Saeed Barbat IEEE the Transportation Active Safety Institute (TASI) and also with the Department of Computer Information and Graphics TechnologyPurdue School of Engineering and Technology Indiana University-Purdue University Indianapolis (IUPUI) the Transportation Active Safety Institute(TASI) and also with the Department of Electrical and Computer EngineeringPurdue School of Engineering and Technology Indiana University-Purdue University Indianapolis (IUPUI) the Ford Research and Innovation Center

Driver state sensing technologies, such as vehicular systems, start to be widely considered by automotive manufacturers. To reduce the cost and minimize the intrusiveness towards driving, the majority of these systems rely on the in-cabin camera(s) and other optical sensors. With their great capabilities in detecting and intervening of driver distraction and inattention,these technologies may become key components in future vehicle safety and control systems. However, to the best of our knowledge,currently, there is no common standard available to objectively compare the performance of these technologies. Thus, it is imperative to develop one standardized process for evaluation *** this paper, we propose one systematic and standardized evaluation process after successfully addressing three difficulties:1) defining and selecting the important influential individual and environmental factors, 2) countering the effects of individual differences and randomness in driver behaviors, and 3) building a reliable in-vehicle driver head motion tracking tool to collect ground-truth motion data. We have collected data on a large scale on a commercial driver state-sensing platform. For each subject, 30 to 40 minutes of head motion data was collected and included variables, such as lighting conditions, head/face features,and camera locations. The collected data was analyzed based on a proposed performance measure. The results show that the developed process can efficiently evaluate an individual camerabased driver state sensing product, which builds a common base for comparing the performance of different systems.

关键词： Data analysis data collection driver state sensing human factors performance evaluation

LECF: recommendation via learnable edge collaborative filtering

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Science China(Information Sciences) 2022年第1期65卷 116-130页

作者： Shitao XIAO Yingxia SHAO Yawen LI Hongzhi YIN Yanyan SHEN Bin CUI School of computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing Key Lab of Intelligent Telecommunications Software and multimedia Beijing University of Posts and Telecommunications School of Information Technology and Electrical Engineering The University of Queensland department of computer Science and Engineering Shanghai Jiao Tong University department of computer Science and Technology Peking University National Engineering Laboratory for Big Data Analysis and Applications Peking University

The core of recommendation models is estimating the probability that a user will like an item based on historical interactions. Existing collaborative filtering(CF) algorithms compute the likelihood by utilizing simple relationships between objects, e.g., user-item, item-item, or user-user. They always rely on a single type of object-object relationship, ignoring other useful relationship information in data. In this paper, we model an interaction between user and item as an edge and propose a novel CF framework, called learnable edge collaborative filtering(LECF). LECF predicts the existence probability of an edge based on the connections among edges and is able to capture the complex relationship in data. Specifically, we first adopt the concept of line graph where each node represents an interaction edge; then calculate a weighted sum of similarity between the query edge and the observed edges(i.e., historical interactions) that are selected from the neighborhood of query edge in the line graph for a recommendation. In addition, we design an efficient propagation algorithm to speed up the training and inference of LECF. Extensive experiments on four public datasets demonstrate LECF can achieve better performance than the state-of-the-art methods.

关键词： collaborative filtering recommender system implicit feedback edge-edge similarity line graph

New Modified Controlled Bat Algorithm for Numerical Optimization Problem

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computers, Materials & Continua 2022年第2期70卷 2241-2259页

作者： Waqas Haider Bangyal Abdul Hameed Jamil Ahmad Kashif Nisar Muhammad Reazul Haque Ag.Asri Ag.Ibrahim Joel J.P.C.Rodrigues M.Adil Khan Danda B.Rawat Richard Etengu department of Computing and Technology Iqra University IslamabadPakistan computer Science Kohat University of Science and Technology(KUST)KohatPakistan Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu88400SabahMalaysia Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Federal University of Piauí(UFPI) Teresina-PLBrazil Instituto de Telecomunicacoes Covilh?6201-001Portugal department computer Science and Technology Chang’an UniversityXi’anChina department of Electrical Engineering and computer Science Howard UniversityWashingtonDCUSA

Bat algorithm(BA)is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization *** leverages the echolocation feature of bats produced by imitating the bats’searching *** faces premature convergence due to its local search *** of using the standard uniform walk,the Torus walk is viewed as a promising alternative to improve the local search *** this work,we proposed an improved variation of BA by applying torus walk to improve diversity and *** *** computerized Bat Algorithm(MCBA)approach has been examined for fifteen well-known benchmark test *** finding of our technique shows promising performance as compared to the standard PSO and standard *** proposed MCBA,BPA,Standard PSO,and Standard BA have been examined for well-known benchmark test problems and training of the artificial neural network(ANN).We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning(ML)repository of *** results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness,with more superiority compared to the traditional *** MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future.

关键词： Bat algorithm MCBA ANN ML Torus walk

An Object Oriented Model for Concurrent Systems

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Wuhan University Journal of Natural Sciences 1998年第2期3卷 152-156页

作者： Zhang Qian Chen Shihong(The Open Research Lab for multimedia Software under the State Education departmentThe National Engineering Technology Research Centre for multimedia Softwarecomputer Science & Technology Institution,Wuhan University,Wuhan 430072,China) Wuhan University The Open Research Lab for Multimedia Software under the State Education Department The National Engineering Technology Research Centre for Multimedia Software Computer Science &amp Technology Institution Wuhan China (GRID:grid.49470.3e) (ISNI:***)

It appears that extensibility and reusability of concurrent applications is far from trivial. Often the inheritance anomalies problems will arise. Basing on the composition-filters object model which is proposed by Aksit, we introduce the Generic Synchronization Policy (GSP) in the inheritance mechanism, produce a new kind of concurrent object-oriented computational model. After analyzing, we show that this new model can tackle the suffering from the inheritance anomalies.

关键词： object-oriented paradigm inheritance anomalies GSP ISVIS conflict