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1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

作者： Tian, Daxin Kang, Lu Zheng, Kunxian Duan, Xuting Rong, Hui Guo, Peng Wang, Wenyang Zhang, Haijun Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University XueYuan Road No.37 Beijing100191 China China Automotive Technology and Research Center Automotive Engineering Research Institute East Xianfeng Road No.68 Tianjin300300 China School of Computer and Communication Engineering University of Science and Technology Beijing XueYuan Road No.30 Beijing100083 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University XueYuan Road No.37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Si Pai Lou. 2 Nanjing210096 China Key Lab of Urban ITS Technology Optimization and Integration The Ministry of Public Security of China Hefei230088 China

ISBN: (纸本)9783319728223

Fatigue driving might affect the traffic safety when the vehicles are on the cruising state in highway. Trying to solve this problem, this paper uses the movement pattern of the fish to the vehicles fleet, and develops a model of vehicle group with realistic restrictions based on the existed fish algorithms, the mobile behavioral model and cluster behavior model, and then demonstrates the feasibility of applying the fish behavior to the cooperative movement of vehicle groups through analyzing the trajectory, velocity and spacing of vehicles. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Vehicles

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REFF: REliable and Fast Forwarding in Vehicular Ad-hoc Network 1st

REFF: REliable and Fast Forwarding in Vehicular Ad-hoc Netwo...

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1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

作者： Tian, Daxin Dai, Ziyi Zheng, Kunxian Zhou, Jianshan Duan, Xuting Guo, Peng Rong, Hui Wang, Wenyang Zhang, Haijun Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University XueYuan Road No. 37 Beijing100191 China China Automotive Technology and Research Center Automotive Engineering Research Institute East Xianfeng Road No. 68 Tianjin300300 China School of Computer and Communication Engineering University of Science and Technology Beijing XueYuan Road No. 30 Beijing100083 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University XueYuan Road No. 37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Si Pai Lou. 2 Nanjing210096 China Key Lab of Urban ITS Technology Optimization and Integration The Ministry of Public Security of China Hefei230088 China

ISBN: (纸本)9783319728223

Vehicular Ad-Hoc Network (VANET) has emerged as an increasingly dominant technology for future connected vehicle and vehicular networks, where the focus of the development of VANET lies in the standardization of message transmission and dissemination via multi-hop broadcasting. However, the current communication protocols concerning VANET face many challenges, including data flooding and collision, transmission delay and other problems. Most of the challenges are closely related to next-hop selection. Therefore, this paper proposes a new routing protocol named REliable and Fast Forwarding (REFF) to optimize the selection of nodes in VANET. In this protocol, node filtering and node evaluation are two main steps. Distance between previous node and candidate node, relative velocity between previous node and candidate nodes, included angle between direction of target node’s velocity and candidate node’s velocity and transmission power of candidate node are adopted as indexes to help select a specific node as the next hop using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). By using this technique, the number of candidates as next-hop is largely reduced, avoiding the data flooding and resulting transmission relay. In addition, simulations based on experiments are done to verify the feasibility. The results show that message achieves a faster and more reliable transmission using REFF. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Vehicular ad hoc networks

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The packing problem of uncertain multicasts

The packing problem of uncertain multicasts

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作者： Ren, Bangbang Guo, Deke Xie, Junjie Li, Wenxin Yuan, Bo Liu, Yunfei Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China School of Computer Science and Technology Dalian University of Technology Dalian China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin China

Multicast performs better than unicast in delivering the same content from a fixed single source to a set of destinations. Many efforts have been made to optimize such kind of deterministic multicast, such as minimizing the transmission cost of each multicast session. In practice, it is not necessary that the source of each multicast session has to be in a specific location, as long as certain constraints are satisfied. Accordingly, applications usually meet a novel multicast with uncertain sources, ie, uncertain multicast. That is, multiple nodes have the responsibility to act as the root node of a multicast session. Prior proposals have addressed an uncertain multicast by constructing the minimum cost forest. However, it is still unknown how to efficiently share the network resources, when a set of uncertain multicast occupies the network simultaneously. To tackle such a challenging issue, we present the packing problem of uncertain multicasts (MPU) to minimize the total transmission cost, under the constraint of link capacity. We prove that the MPU problem is NP-hard. An intrinsic solution is constructing the minimum cost forest for each uncertain multicast individually. This method, however, is inefficient and may be infeasible because of the constraint of link capacity. Thus, we design 2 dedicated greedy methods, named priority-based and adjusting congested link, to approximate the optimal solution. The comprehensive results indicate that both of our 2 methods can find a feasible solution for the MPU problem. Moreover, given a set of uncertain multicasts, the adjusting congested link method can generate a desired transmission structure for each uncertain multicast and achieve the least total cost when packing them. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Routing algorithms

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Low-resolution face recognition in the wild via selective knowledge distillation

arXiv

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arXiv 2018年

作者： Ge, Shiming Zhao, Shengwei Li, Chenyu Li, Jia Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security at University of Chinese Academy of Sciences China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible solution is compressing a complex face model to achieve higher speed and lower memory at the cost of minimal performance drop. Inspired by that, this paper proposes a learning approach to recognize low-resolution faces via selective knowledge distillation. In this approach, a two-stream convolutional neural network (CNN) is first initialized to recognize high-resolution faces and resolution-degraded faces with a teacher stream and a student stream, respectively. The teacher stream is represented by a complex CNN for high-accuracy recognition, and the student stream is represented by a much simpler CNN for low-complexity recognition. To avoid significant performance drop at the student stream, we then selectively distil the most informative facial features from the teacher stream by solving a sparse graph optimization problem, which are then used to regularize the fine-tuning process of the student stream. In this way, the student stream is actually trained by simultaneously handling two tasks with limited computational resources: approximating the most informative facial cues via feature regression, and recovering the missing facial cues via low-resolution face classification. Experimental results show that the student stream performs impressively in recognizing low-resolution faces and costs only 0.15MB memory and runs at 418 faces per second on CPU and 9, 433 faces per second on GPU. Copyright © 2018, The Authors. All rights reserved.

关键词： Students

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A Multilayer Framework for Online Metric Learning

arXiv

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arXiv 2018年

作者： Li, Wenbin Liu, Yanfang Huo, Jing Shi, Yinghuan Gao, Yang Wang, Lei Luo, Jiebo The State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China The College of Mathematics and Information Engineering Longyan University 364012 China The State Key Laboratory for Novel Software Technology National Institute of Healthcare Data Science Nanjing University Nanjing210023 China The School of Computing and Information Technology University of Wollongong Australia The Department of Computer Science University of Rochester RochesterNY14611 United States

Online metric learning has been widely applied in classification and retrieval. It can automatically learn a suitable metric from data by restricting similar instances to be separated from dissimilar instances with a given margin. However, the existing online metric learning algorithms have limited performance in real-world classifications, especially when data distributions are complex. To this end, this paper proposes a multilayer framework for online metric learning to capture the nonlinear similarities among instances. Different from the traditional online metric learning, which can only learn one metric space, the proposed Multi-Layer Online Metric Learning (MLOML) takes an online metric learning algorithm as a metric layer and learns multiple hierarchical metric spaces, where each metric layer follows a nonlinear layers for the complicated data distribution. Moreover, the forward propagation (FP) strategy and backward propagation (BP) strategy are employed to train the hierarchical metric layers. To build a metric layer of the proposed MLOML, a new Mahalanobis-based Online Metric Learning (MOML) algorithm is presented based on the passive-aggressive strategy and one-pass triplet construction strategy. Furthermore, in a progressively and nonlinearly learning way, MLOML has a stronger learning ability than traditional online metric learning in the case of limited available training data. To make the learning process more explainable and theoretically guaranteed, theoretical analysis is provided. The proposed MLOML enjoys several nice properties, indeed learns a metric progressively, and performs better on the benchmark datasets. Extensive experiments with different settings have been conducted to verify these properties of the proposed MLOML. Copyright © 2018, The Authors. All rights reserved.

关键词： Multilayers

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A fine-grained perspective on the robustness of global cargo ship transportation networks

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Journal of Geographical Sciences 2018年第7期28卷 881-899页

作者：彭澎程诗奋陈金海廖梦迪吴琳刘希亮陆锋 State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS University of Chinese Academy of Sciences Navigation Aids Technology Research Center of Jimei University National & Local Joint Engineering Research Center for Marine Navigation Aids Services College of Geomatics Shandong University of Science and Technology Institute of Computing Technology CAS Fujian Collaborative Innovation Center for Big Data Applications in Governments Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application

The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transportation network based on the most recent Automatic Identification System（AIS） data available. First, we subdivide three typical cargo ship transportation networks（i.e., oil tanker, container ship and bulk carrier） from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, including random attack and three intentional attacks（i.e., degree-based attack, betweenness-based attack and flux-based attack） to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1） compared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation; 2） different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3） small-scale intentional attacks may have significant influence on the integrity of the container network but a minor impact on the bulk carrier and oil tanker transportation networks. These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation ***： The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current resear

关键词： complex network fine-grained cargo ship transportation network robustness automatic identification system

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A local algorithm and its percolation analysis of bipartite z-matching problem

arXiv

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arXiv 2018年

作者： Zhao, Jin-Hua School of Data Science and Engineering South China Normal University Shanwei516600 China Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China

A z-matching on a bipartite graph is a set of edges, among which each vertex of two types of the graph is adjacent to at most 1 and at most z (≥ 1) edges, respectively. The z-matching problem concerns finding z-matchings with the maximum size. Our approach to this combinatorial optimization problem is twofold. From an algorithmic perspective, we adopt a local algorithm as a linear approximate solver to find z-matchings on any graph instance, whose basic component is a generalized greedy leaf removal procedure in graph theory. From a theoretical perspective, on uncorrelated random bipartite graphs, we develop a mean-field theory for percolation phenomenon underlying the local algorithm, leading to an analytical estimation of z-matching sizes on random graphs. Our analytical theory corrects the prediction by belief propagation algorithm at zero-temperature limit in (Kreačić and Bianconi 2019 EPL 126 028001). Besides, our theoretical framework extends a core percolation analysis of k-XORSAT problems to a general context of uncorrelated random hypergraphs with arbitrary degree distributions of factor and variable nodes. Copyright © 2018, The Authors. All rights reserved.

关键词： Graph theory

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Intelligent Question and Answering System Based on SVM and Cosine Similarity

Intelligent Question and Answering System Based on SVM and C...

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2017 International Conference on Mathematics, Modelling and Simulation Technologies and Applications（MMSTA 2017)

作者： Wan-li SONG Wei-wei CHEN Ming-zhu ZHANG Key Laboratory of Trusted Cloud Computing and Big Data Analysis School of Information EngineeringNanjing Xiao Zhuang University

It is a tough task for teachers to answer all questions from students effectively and *** this paper,we design and implements an intelligent question answering system using Natural Language Processing,template classification,support vector *** system also calculates the similarity between the question and answer pairs by cosine similarity algorithm,and returns the most similar *** the user is not satisfied with the answer,the system will write the question into the public section to fall back on other *** answer will be evaluated and added to the QA base if it is passed with the corresponding *** that the questions and answers in the QA base continue to *** use the QA base of a network forum as the basic library to carry out the *** implementation and experimental results indicate that the proposed approach is achievable.

关键词： Intelligent system Question classification Question similarity Cosine similarity

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Towards merging collaborating processes for artifact lifecycle synthesis 17

Towards merging collaborating processes for artifact lifecyc...

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2017 Australasian Computer Science Week Multiconference, ACSW 2017

作者： Kunchala, Jyothi Yu, Jian Yongchareon, Sira Han, Yanbo School of Engineering Computer and Mathematical Sciences Auckland University of Technology Auckland1142 New Zealand Research Centre for Cloud Computing Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data North China University of Technology Beijing100144 China

ISBN: (纸本)9781450347686

Research on transforming traditional activity-centric processes into the newly emerged artifact-centric processes has gained an increasing interest in recent years. This transformation lead to the emergence of several approaches to transforming standalone activity-centric business processes, while neglecting the inter-organizational processes consisting of multiple collaborating processes having message flows among them. In this paper, we propose an approach for transforming activity-centric collaborating processes into the artifact-centric processes. The proposed approach consists of two phases: the first phase is to merge the collaborating processes into an integrated process and the second phase is to synthesize the artifact lifecycles from the resulting integrated process. The feasibility of this approach has been studied with an inter-organizational e-business process scenario. © 2017 ACM.

关键词： Merging

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Investigating different syntactic context types and context representations for learning word embeddings

Investigating different syntactic context types and context ...

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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Li, Bofang Liu, Tao Zhao, Zhe Tang, Buzhou Drozd, Aleksandr Rogers, Anna Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shenzhen Graduate School Harbin Institute of Technology China Global Scientific Information and Computing Center Tokyo Institute of Technology China Department of Computer Science University of Massachusetts Lowell United States

ISBN: (纸本)9781945626838

The number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open question what is the best definition of context. We provide a systematical investigation of 4 different syntactic context types and context representations for learning word embeddings. Comprehensive experiments are conducted to evaluate their effectiveness on 6 extrinsic and intrinsic tasks. We hope that this paper, along with the published code, would be helpful for choosing the best context type and representation for a given task. © 2017 Association for Computational Linguistics.

关键词： Embeddings

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