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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer Graphics, EG 2019

作者： Li, Wenhui Liu, Anan Nie, Weizhi Song, Dan Li, Yuqian Wang, Weijie Xiang, Shu Zhou, Heyu Bui, Ngoc-Minh Cen, Yunchi Chen, Zenian Chung-Nguyen, Huy-Hoang Diep, Gia-Han Do, Trong-Le Doubrovski, Eugeni L. Duong, Anh-Duc Geraedts, Jo M.P. Guo, Haobin Hoang, Trung-Hieu Li, Yichen Liu, Xing Liu, Zishun Luu, Duc-Tuan Ma, Yunsheng Nguyen, Vinh-Tiep Nie, Jie Ren, Tongwei Tran, Mai-Khiem Tran-Nguyen, Son-Thanh Tran, Minh-Triet Vu-Le, The-Anh Wang, Charlie C.L. Wang, Shijie Wu, Gangshan Yang, Caifei Yuan, Meng Zhai, Hao Zhang, Ao Zhang, Fan Zhao, Sicheng Shool of Electrical and Information Engineering Tianjin University China University of Science VNU-HCM Viet Nam State Key Laboratory of Virtual Reality Technology and System Beihang University China Delft University of Technology Netherlands University of Information Technology VNU-HCM Viet Nam Nanjing University China SuoAo Technology Center SAEE University of Science and Technology Beijing China Chinese University of Hong Kong Hong Kong School of Software Dalian University of Technology China Department of Electrical Engineering and Computer Sciences University of California Berkeley United States Ocean University of China China

ISBN: (纸本)9783038680772

Monocular image based 3D object retrieval is a novel and challenging research topic in the field of 3D object retrieval. Given a RGB image captured in real world, it aims to search for relevant 3D objects from a dataset. To advance this promising research, we organize this SHREC track and build the first monocular image based 3D object retrieval benchmark by collecting 2D images from ImageNet and 3D objects from popular 3D datasets such as NTU, PSB, ModelNet40 and ShapeNet. The benchmark contains classified 21,000 2D images and 7,690 3D objects of 21 categories. This track attracted 9 groups from 4 countries and the submission of 20 runs. To have a comprehensive comparison, 7 commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. The evaluation results show that the supervised cross domain learning get the superior retrieval performance (Best NN is 97.4 %) by bridging the domain gap with label information. However, there is still a big challenge for unsupervised cross domain learning (Best NN is 61.2%), which is more practical for the real application. Although we provided both view images and OBJ file for each 3D model, all the participants use the view images to represent the 3D model. One of the interesting work in the future is directly using the 3D information and 2D RGB information to solve the task of monocular Image based 3D model retrieval. © 2019 The Author(s)

关键词： 3D modeling

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A Novel Identity Authentication for FPGA Based IP Designs

A Novel Identity Authentication for FPGA Based IP Designs

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Yin Huang Wei Liang Jing Long Jianbo Xu Kuan-Ching Li College of Computer Science and Engineering Hunan University of Science and Technology Xiangtan Hunan China Shool of Opto-Electronic and Communication Engineering Xiamen University of Technology Xiamen China College of Computer Science and Electronic Engineering Hunan University Changsha Hunan China School of Computer Science Hubei University of Education Wuhan China

With the rapid development of Internet-of-Things (IoT), hardware security becomes an important issue. Once a chip is attacked, the authentication always faces serious credibility crisis. In this work, a Hausdorff distance model-based scheme is proposed to authenticate circuit identity under IoT environment. Firstly, the structure of FPGA is analyzed and the positions of LUTs are abstracted into a collection of reconfigurable nodes. The depth-first searching algorithm is used to determine the unused LUT resources for inserting the copyright information. The Hausdorff distance matching function is utilized to reorder the random positions. These positions will be further mapped to satisfy specific constraints of the optimal watermark positions. As the identity of circuit requires real-time authentication, virtual positions are mapped to initial key file. Once decrypted, the identity can be authenticated by the mapping relationship of Hausdorff distance function. Lastly, we conduct a series of experiments to evaluate the ability of the proposed scheme against illegal attacks, such as removal attacks. Experiments show that, the proposed scheme has good randomness and secrecy. Besides, the resource overhead during authentication is encouraging.

关键词： IP networks Authentication Table lookup Integrated circuit modeling Field programmable gate arrays Hardware

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Scalable Hash Ripple Join on Spark

Scalable Hash Ripple Join on Spark

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Hao Liu Jiang Xiao Fengchao Peng The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Services Computing Technology and System Lab Cluster and Grid Computing Lab Shool of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (纸本)9781538632086

Hash Ripple join is an online aggregation algorithm that can rapidly give good approximate join results increases with the progress of the join operation and converges to the real result when the join finishes. Luo et al. proposed a parallel hash ripple join (PHRJ) that runs in a distributed setting. However, the PHRJ has two drawbacks when handling large-scale data: 1) PHRJ updates approximate results in fine grain which induces extra communication cost in a distributed environment 2) When data is out of memory, PHRJ cannot provide unbiased approximate result. In this thesis, a scalable hash ripple join is proposed that 1) runs on a distributed framework that can process distributed data in coarse-grain to speed up the join performance; 2) continuously gives unbiased and consistent approximate join results even in the presence of memory overflow; and 3) has good scalability handling growing amount of data. We have implemented a prototype of the scalable hash ripple join (SHRJ) algorithm on Spark. Experiment results show that SHRJ can give good approximate join result while taking less than 10% of the time of Spark's own join operator.

关键词： Sparks Distributed databases Approximation algorithms Clustering algorithms Indexes Standards computer science

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Integrative computing method for the prediction of zinc-binding sites in proteins

Integrative computing method for the prediction of zinc-bind...

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International Joint Conference on Neural Networks (IJCNN)

作者： Hui Li Dechang Pi Yinghong Liang Chuanming Chen Yongzhi Liu College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Shool of Software Engineering Jinling Institute of Technology Nanjing Jiangsu China

ISBN: (纸本)9781509061839

A large number of metalloproteins contained in Protein Data Bank, taking metal ions as cofactors, have important biological functions. As the second most abundant bound trace metal elements in organism, zinc ion plays an important regulatory role in the biological growth and development, disease control, DNA synthesis. So, research on the area of zinc-binding protein sites has an important significance. Because of the availability of protein sequence information, a series of predictive tools based on sequence for zinc-binding sites in proteins have been developed. But presently, there is little research on the integration of these tools. Based on this, an integrative predictor termed meta-zincPrediction is presented in the paper to combine the predictive tools. The linear regression method is used in the integrated approach to combine the scores of different prediction tools, the parameters are adjusted and optimized until to the optimal. Tested on the non-redundant Zhao_dataset, AURPC value of meta-zincPrediction reached nearly 0.9, an increase of 2% -9% than other three predictors, and other performance indexes were also improved mostly. Moreover, the prediction ability of meta-zincPrediction was better than other three predictors, regardless of zinc-binding sites for all four types of residues, or zinc-binding sites for a single type of residues. Our method can not only be applied to large-scale identification of zinc-binding sites based on sequence information, but also be useful for the inference of protein function.

关键词： Proteins Tools Ions Metals Linear regression Machine learning algorithms Predictive models

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A Three-Stage Defect Prediction Model for Cross-Project Defect Prediction

A Three-Stage Defect Prediction Model for Cross-Project Defe...

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International Conference on Dependable Systems and Their Applications (DSA)

作者： Song Huang Yaning Wu Haijin Ji Chengzu Bai PLA Military Training Software Testing and Evaluation Centre Nanjing Jiangsu Province China Shool of Computer Science and Technology Huaiyin Normal University Huaian Jiangsu Province China Cornmand Information Institute Army Engineering University of PLA Nanjing Jiangsu Province China Institute of Meteorology & Oceanography National University of Defense Technology Changsha China

Aiming at dealing with the problems of the data deficiency, data high dimensionality in software defect prediction (SDP), this paper proposes a novel three-stage defect prediction model. First we introduced the information flow algorithm (IFA) to do the causality analysis to choose the most representative feature subset. Then we utilized the nearest neighbor method in similarity measuring between the local dataset and the cross-project data, to construct a homogenous training dataset. Last we proposed a new Bayes classifier, which evolves the Naïve Bayes classifier with the vibration of string based diffusion function (VSDF).

关键词： Predictive models Data models Training Software Data preprocessing Computational modeling Software engineering

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Analysis of image stitching error based on scale invariant feature transform and random sample consensus 12

Analysis of image stitching error based on scale invariant f...

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12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015

作者： Shuang, Dou Cai, Hua Yang, Yong Tailin, Han Xue, Menghan School of Computer Engineering Changchun University of Science and Technology Changchun China College of Electronic and Information Engineer Changchun University of Science and Technology Changchun China Electronic Engineering Shool Beijing University of Posts and Telecommunications Changchun China

ISBN: (纸本)9781467376822

This article introduced the process of image stitching based on SIFT and RANSAC. It was pointed out that the reliability calculation of the RANSAC algorithm is based on an idealized assumption which does not hold. The false assumption will lead to the instability of image stitching results, especially in multi-map or panorama situations. To solve the problem, this paper presents a strategy to limit the range of randomly points selecting. Experiments show that the strategy can effectively reduce the effect caused by random errors, and obtain more stable image stitching result. © 2015 IEEE.

关键词： Random errors

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Analysis of image stitching error based on scale invariant feature transform and random sample consensus

Analysis of image stitching error based on scale invariant f...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Dou Shuang Hua Cai Yong Yang Han Tailin Menghan Xue School of Computer Engineering Changchun University of Science and Technology Changchun China College of electronic and information engineer Changchun University of Science and Technology Changchun China Electronic Engineering Shool Beijing University of Posts and Telecommunications Changchun China

ISBN: (纸本)9781467376839

关键词： Reliability Algorithm design and analysis Mathematical model Transforms computers Error analysis Search problems

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Association Rules Mining with Multiple Constraints

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Procedia Engineering 2011年 15卷 1678-1683页

作者： Li Guang-yuan Cao Dan-yang Guo Jian-wei School of Computer and Communication Engineering University of Science&Technology Beijing Beijing China Shool of Computer and Information Engineering Guangxi Teachers Education University Nanning China

Association rules mining(ARM) is an important task in the field of data mining, mining frequent itemsets is a key step of many algorithms for ARM. In a very large dataset, rules generated may be very large, but some of them are useless to the users, to improve the effectiveness and efficiency of mining tasks, constraint-based mining enables users to concentrate on mining their interested association rules instead of the complete set of association rules. Most of previously proposed methods are mainly deal with a single constraint. In this paper, we present an algorithm for mining association rules with multiple constraints, the proposed algorithm simultaneously copes with two different kinds of constraints, it consists of three phases, first, the frequent 1-itemset are generated, second, we exploit the properties of the given constraints to prune search space or save constraint checking in the conditional databases. Third, for each itemset possible to satisfy the constraint, we generate its conditional database and perform the three phases in the conditional database recursively. Experimental results show that the proposed method outperform the revised FP-growth algorithm.

关键词： Data mining Association rules mining Constraints-based mining

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An optimal path selection algorithm for knowledge learning amongst multiple curricula within computer supported collaborative learning

An optimal path selection algorithm for knowledge learning a...

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2011 International Conference on computer science and Service System, CSSS 2011

作者： Tan, Wenan Zhu, Guosheng Jiang, Chuanqun Du, Yi Shool of Compute Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China School of Computer and Information Shanghai Second Polytechnic University Shanghai China

ISBN: (纸本)9781424497638

As the never-ending development of current knowledge science and computer technology, learning knowledge of multiple curricula or even inter-discipline attracts attention more and more widely in computer supported collaborative learning. So, there exist some reasonable knowledge learning sequences of related curricula. Although there are some researchers focusing on the shortest path selection, they still discuss about the single curriculum. In this study, an optimal path selection algorithm for knowledge learning amongst multiple curricula has been developed for improving the efficiency of computer supported collaborative learning. At the same time, an illustrated example is discussed for explanation. © 2011 IEEE.

关键词： Curricula

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Capture, recognition, and visualization of human semantic interactions in meetings

Capture, recognition, and visualization of human semantic in...

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8th IEEE International Conference on Pervasive Computing and Communications, PerCom 2010

作者： Yu, Zhiwen Yu, Zhiyong Aoyama, Hideki Ozeki, Motoyuki Nakamura, Yuichi Shool of Computer Science Northwestern Polytechnical University China Academic Center for Computing and Media Studies Kyoto University Japan Graduate School of Science and Technology Kyoto Institute of Technology Japan

ISBN: (纸本)9781424453290

Human interaction is one of the most important characteristics of group social dynamics in meetings. In this paper, we propose an approach for capture, recognition, and visualization of human interactions. Unlike physical interactions (e.g., turn-taking and addressing), the human interactions considered here are incorporated with semantics, i.e., user intention or attitude toward a topic. We adopt a collaborative approach for capturing interactions by employing multiple sensors, such as video cameras, microphones, and motion sensors. A multimodal method is proposed for interaction recognition based on a variety of contexts, including head gestures, attention from others, speech tone, speaking time, interaction occasion (spontaneous or reactive), and information about the previous interaction. A support vector machines (SVM) classifier is used to classify human interaction based on these features. A graphical user interface called MMBrowser is presented for interaction visualization. Experimental results have shown the effectiveness of our approach. ©2009 IEEE.

关键词： Video cameras

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