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2nd International Conference on Signal Processing and Machine Learning, SPML 2019

作者： Zhang, Enwei Zhou, Hongtu Ding, Yongchao Zhao, Junqiao Ye, Chen Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University School of Electronics and Information Engineering Shanghai China

ISBN: (纸本)9781450372213

Obstacle avoiding is one of the most complex tasks for autonomous driving systems, which was also ignored by many cutting-edge end-to-end learning-based methods. The difficulties stem from the integrated process of detection and interpretation of environment and obstacles and generation of proper behaviors. We make the use of CARLA, a simulator for autonomous driving research, and collect massive human drivers' reactions to obstacles on road subjecting to given driving commands, i.e. follow, go straight, turn left and turn right for about 6 hours. A behavior-Cloning neural network architecture is proposed with the modified loss that enlarge the effects of errors for steer, which indicates the benefit to high an accuracy. We found the data augmentation of the image is crucial to the training of the proposed network. And a reasonable limit allows avoiding unexpected stop. The experiments demonstrate 3 obstacle avoidance cases: for the same type as the training dataset, other automobile and two-wheeled vehicles. Finally, the CARLA benchmark is also tested. © 2019 Association for computing Machinery.

关键词： Autonomous vehicles

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Behavior-aware Trustworthiness Study of Networked Software

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International Journal of Computational Intelligence systems 2010年第5期3卷 542-552页

作者： Fang, Xianwen Jiang, Changjun Fan, Xiaoqin Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Lab of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China

The essence characteristics of software trustworthiness are software execution effect and behavior can be anticipated, which is an important index of software quality. Under the open and dynamic environments, some uncertainty factors cause the behavior of software to be uncontrolled, uncertainty and unpredictable. Behavior-aware networked software trustworthiness research methods are proposed in the paper. Firstly, we propose the analysis methods of the consistency between the inferred specification models with component specification model. Then, for analyzing the component interaction behavior, the behavior relativity analyzing method is presented based on Petri net. Finally, aimed to the outer factors, we analyze the behavioral congruence between theoretical composite models with dynamic behavior model based on running logs. Theoretical analysis and the example analysis indicated that this method is benefit to analyze the trustworthiness of networked software. © 2010, the authors.

关键词： consistency networked software Petri net software behavior trustworthiness

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On complementary effect of blended behavioral analysis for identity theft detection in mobile social networks 1

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13th International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2017

作者： Wang, Cheng Luo, Jing Yang, Bo Jiang, Changjun Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science and Technology Tongji University Shanghai China

ISBN: (数字)9789811088902

ISBN: (纸本)9789811088896

User behavioral analysis is expected to act as a promising technique for identity theft detection in the Internet. The performance of this paradigm extremely depends on a good individual-level user behavioral model. Such a good model for a specific behavior is often hard to obtain due to the insufficiency of data for this behavior. The insufficiency of specific data is mainly led by the prevalent sparsity of users’ collectable behavioral footprints. This work aims to address whether it is feasible to effectively detect identify thefts by jointly using multiple unreliable behavioral models from sparse individual-level records. We focus on this issue in mobile social networks (MSNs) with multiple dimensions of collectable but sparse data of user behavior, i.e., making check-ins, posing tips and forming friendships. Based on these sparse data, we build user spatial distribution model, user post interest model and user social preference model, respectively. Here, as the arguments, we validate that there is indeed a complementary effect in multi-dimensional blended behavioral analysis for identity theft detection in MSNs. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Social networking (online)

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Fuzzy H∞ Filtering for Nonlinear Networked systems with Multiple Stochastic Time-Varying Delays, Packet Dropouts and Sensor Saturation 34

Fuzzy H∞ Filtering for Nonlinear Networked Systems with Mul...

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第三十四届中国控制会议

作者： XU Xiaoli YAN Huaicheng ZHANG Hao SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education School of information Science and Engineering East China University of Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (纸本)9781467374439

This paper investigates the problem of H∞ filter design for a class of nonlinear networked system based on T-S fuzzy model. Multiple stochastic time-varying delays and some incomplete information are considered simultaneously. Incomplete information includes randomly occurring sensor saturation and packet dropouts. Stochastic time-varying delays are depicted as a sequence of stochastic and independent variables, which take values on 0 and 1. Two sets of Bernoulli distributed white noises are introduced to describe randomly occurring sensor saturation and packet dropouts. system conservatism is reduced due to introduce an approach of piecewise quadratic Lyapunov function. By solving a set of linear matrix inequalities(LMIs), the filter parameters are obtained. Finally, a simulation example is provided to illustrate the effectiveness of the proposed filter design approach.

关键词： H ∞ filtering,multiple time-varying delays,randomly occurring sensor saturation,packet dropouts,piecewise quadratic Lyapunov function

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Block diagonal precoding based power allocation for coordinated multi-point transmission

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Journal of Communications 2011年第7期6卷 524-528页

作者： Han, Jing Wang, Ping Liu, Fuqiang Zhu, Yin Broadband Wireless Communications and Multimedia Laboratory Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China

This paper studies power allocation in coordinated multi-point (CoMP) transmission of 3GPP LTE-Advanced system with remote radio units(RRUs) power constraints. We apply block diagonal (BD) precoding to downlink transmission, and assume perfect knowledge of downlink channels and transmit messages at each transmit point. We propose a modified water-filling power (MWF) allocation algorithm in order to maximize the downlink sum capacity, at the same time the low complexity is achieved. The interior-point method is also used to solve the optimization problem. Simulations show that interior-point method converges after only a few iterative steps and the system capacity is near-optimal. As for complexity and power efficiency, MWF achieves a good compromise. © 2011 ACADEMY PUBLISHER.

关键词： Iterative methods

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A service selection method based on web service clusters

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Journal of Applied Sciences 2013年第24期13卷 5734-5738页

作者： Liu, Wei Du, Yu-Yue Yan, Chun College of Information Science and Engineering Shandong University of Science and Technology 266590 Qingdao China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University 200092 Shanghai China

service selection is an essential issue in service discovery based on Web service clusters. The ratio of trust value to price is introduced to select the most suitable service in a cluster. The method of computing the initial trust, the direct trust and the recommendation trust are, respectively presented and the overall trust is derived based on them. The proposed method keeps the balance between the price and service quality. © 2013 Asian Network for Scientific Information.

关键词： Web services

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Adaptive social network construction using Gaussian mixture model

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Information Technology Journal 2011年第12期10卷 2252-2259页

作者： Guo, Xin Xiang, Yang Chen, Qian Wei, Wei Department of Computer Science and Technology School of Electronic and Information Engineering Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

A Social network graph shows social interactions and relationships between individuals in a specific social environment, which is very helpful for analyzing social relationships, activities, structures, etc. The author quantized the strengths of social objects' relationships in social environment using an improved vector space model. Gaussian mixture model was employed to set the threshold for identifying social relationships adaptively and divide social subgroups automatically. According to the threshold, social network graph would be constructed based on performance measures. It is concluded that hidden social relationships can be discovered effectively by using this approach which is very flexible and adaptive for dynamic information feedback mechanism. © 2011 Asian Network for Scientific Information.

关键词： Gaussian distribution

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Probabilistic bootstrap-based evolutionary algorithm for three-objective wind farm turbine position optimization

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Swarm and Evolutionary Computation 2025年 96卷

作者： Chen Zhang Haotian Li Xiuxian Li Jiujun Cheng Zhenyu Lei Shangce Gao Faculty of Engineering University of Toyama Toyama-shi 930-8555 Japan College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China Ministry of Education Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

Amid the worsening energy crisis, wind farm layout optimization (WFLO) to increase power generation, reduce costs, and mitigate potential environmental impacts is of great significance. This paper formulates three-objective wind farm layout optimization (TWFLO) which is rarely considered, aiming to effectively utilize existing information to optimize power output, land usage, and costs. We propose a new algorithm (MOEA/D-P) based on probability distributions to guide turbine placement and improve the performance of a Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D). This algorithm addresses the issue of neglecting valuable information during layout optimization. Additionally, we make improvements to the traditional land-use function to avoid situations where non-convex layouts result in an area calculation of zero. The MOEA/D-P is tested on six different initial layouts and compared with five algorithms under two wind conditions. Results are evaluated using inverted generational distance, hypervolume, and scatter plot distributions. The impact of initial probability distribution on algorithm performance is discussed under four simple wind conditions. The results show that MOEA/D-P outperforms the other five algorithms in terms of performance.

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A Novel Mutual Information based Ant Colony Classifier 5

A Novel Mutual Information based Ant Colony Classifier

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2017 International Conference on Progress in Informatics and computing(PIC)

作者： Hang Yu Xiaoxiao Qian Yang Yu Jiujun Cheng Ying Yu Shangce Gao College of Computer Science and Technology Taizhou University Faculty of Engineering University of Toyama Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

ISBN: (纸本)9781538619797;9781538619780

By constructing a list of IF-THEN rules, the traditional ant colony optimization(ACO) has been successfully applied on data classification with not only a promising accuracy but also a user comprehensibility. However, as the collected data to be classified usually contain large volumes and redundant features, it is challenging to further improve the classification accuracy and meanwhile reduce the computational time for *** paper proposes a novel hybrid mutual information based ant colony algorithm(mrAM+) for classification. First, a maximum relevance minimum redundancy feature selection method is used to select the most informative and discriminative attributes in a dataset. Then, we use the enhanced ACO classifier(i.e., AM+)to perform the classification. Experimental results show that the proposed mrAM+ outperforms other seven state-of-art related classification algorithms in terms of accuracy and the size of model.

关键词： ant colony optimization mutual information classification data mining feature selection

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Performance analysis for large scale parallel microscopic traffic simulation system

Performance analysis for large scale parallel microscopic tr...

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International Symposium on Advances in Computer and Sensor Networks and systems, 2008

作者： Fei, Yin Dongliang, Zhang Department of Computer Science and Technology Tongji University The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai 201804 China

ISBN: (纸本)9781427629807

In this paper, we present the parallel implementation of the traffic microsimulation PMTS (Parallel Microscopic Traffic Simulation) focusing on the performance issues. The parallelization of PMTS is domain decomposition, which means that each processor of the PC cluster is responsible for a different geographical area of the simulation region. We describe the transportation network graph partition and information exchange between domains. We demonstrate the time cost mathematics models for PMTS: the vehicle generation, vehicle position calculation, and vehicle information exchange between domains. The workload balance is obtained by adjusting the boundary lines according to the relative load of adjacent subnetworks. All these works have been proved to be effective when PMTS put into use and the experiment results are also provided which match our analysis.

关键词： Vehicles

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