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IEEE International Conference on Image Processing

作者： Cheng, Cheng Wang, Hanli Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

As an extension of the singular value decomposition based approaches, a novel metric based on Tucker decomposition for color image quality assessment is proposed in this paper. It extracts both the spacial and chromatic information of a color image with Tucker decomposition. As compared to most of the other existing quality metrics for color images, the key advantage of the proposed metric is that it treats the color image as a whole entity instead of an assembly of three independent visual channels, and thus the interrelation among the different visual channels is well involved. Experimental results on the LIVE Database Release 2 demonstrate that the proposed metric can generally achieve similar or better performance than other metrics.

关键词： Tensile stress Measurement Image color analysis Color Matrix decomposition Image quality Vectors

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An Efficient and Scalable Algorithm for the Traveling Salesman Problem

An Efficient and Scalable Algorithm for the Traveling Salesm...

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2014 IEEE 5th International Conference on Software Engineering and service Science

作者： Chen Ye Zhongcheng Yang Tianxing Yan Key Laboratory on Embedded System and Service Computing College of Electronics and Information EngineeringTongji University

This paper presents a genetic algorithm based on dynamic programming for solving large-scale instance of the Traveling Salesman Problem(TSP) to ***,an improved dynamic programming algorithm is described to deal with large-scale data,and then it is used as crossover and mutation operator in the genetic *** results show that this novel method with good stability can solve TSP with very-large-scale,effectively reduce the error rate,and improve the solution precision while keeping computational complexity relatively low.

关键词： traveling salesman problem genetic algorithm dynamic programming optimization

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An Adaptive Heterogeneous Credit Card Fraud Detection Model Based on Deep Reinforcement Training Subset Selection

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4026-4041页

作者： Zhu, Kun Zhang, Nana Ding, Weiping Jiang, Changjun the Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Collaborative Innovation Center for Financial Network Security Tongji University Shanghai201804 China the School of Computer Science and Technology Donghua University Shanghai201620 China the School of Information Science and Technology Nantong University Nantong226019 China

Heterogeneous fraud detection is an important means of credit card security assurance, which can utilize historical transaction records in a source and target domain to build an effective fraud detection model. Nevertheless, large feature distribution differences between source and target transaction instances and the complex intrinsic structure hidden behind transaction data make it difficult for existing credit card fraud detection (CCFD) models to capture and transfer the most informative feature representations and seriously hinder detection performance. In this work, we propose a novel adaptive heterogeneous CCFD model named adaptive heterogeneous credit card fraud detection model based on deep reinforcement training subset selection (RTAHC) based on deep reinforcement training subset selection, which mainly contains two components: selection distribution generator (SDG) and transaction fraud detector (TFD, including feature extractor with an attention mechanism and classifier). The SDG can generate the selection probability distribution vector via the reinforcement reward mechanism, and then transaction instances in the source domain relevant to the target domain are selected. The feature extractor with an attention mechanism can learn the abstract deep semantic feature representations of selected source transaction instances and the target domain. The joint training of SDG and TFD can provide more real-time and accurate transaction feature representations to reduce the distribution discrepancy between the two domains. We verify the detection performance of RTAHC across a large real-world credit card transaction dataset and four public datasets. Experimental results demonstrate that the RTAHC model can exhibit competitive CCFD performance. Impact Statement—With the rise of artificial intelligence (AI)generated models, credit card fraud has become increasingly rampant, which also causes tens of billions of U.S. dollars in credit card losses worldwide every year

关键词： Hidden Markov models

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Mining World Indicators for Analyzing and Modeling the Development of Countries

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ACM/IMS Transactions on Data Science 2021年第4期2卷 1–27页

作者： Huang, Hong Chi, Mingyuan Song, Yu Jin, Hai The National Engineering Research Center for Big Data Technology and System Key Laboratory of Service Computing Technology and System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

The world indicators released by the World Bank or other organizations usually give the basic public knowledge about the world. However, separate and static index lacks the complex interplay among different indicators and thus cannot help us have an overall understanding of the world. To this end, we study the world indicators from a different angle. Firstly, we discover that there exist correlations between indicators either from a static view or from a dynamic view. Moreover, taking the trade and diplomatic relationships into consideration, we construct a multi-relational network to depict the interactions between different countries, and propose a Multiple Relations to Vector (MR2vec) model to study world indicators from a network perspective. The experimental results show the changes of world indicators are predictable with the proposed model, and our proposed MR2vec has wide adaptability in predicting multi-relation networks. © 2022 Copyright held by the owner/author(s).

关键词： Data mining

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Reader activation scheduling in multi-reader RFID systems: A study of general case

Reader activation scheduling in multi-reader RFID systems: A...

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25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011

作者： Tang, Shaojie Wang, Cheng Li, Xiang-Yang Jiang, Changjun Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (纸本)9780769543857

Radio frequency identification (RFID) is a technology where a reader device can "sense" the presence of a close by object by reading a tag device attached to the object. To guarantee the coverage quality, multiple RFID readers can be deployed in the given region. In this paper, we consider the problem of activation schedule for readers in a multi-reader environment. In particular, we try to design a schedule for readers to maximize the number of served tags per time-slot while avoiding various interferences. We first develop a centralized algorithm under the assumption that different readers may have different interference and interrogation radius. Next, we propose a novel algorithm which does not need any location information of the readers. Finally, we extend the previous algorithm in distributed manner in order to suit the case where no central entity exists. We conduct extensive simulations to study the performances of our proposed algorithm. And our evaluation results corroborate our theoretical analysis. © 2011 IEEE.

关键词： Graph theory

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KNOB particle swarm optimizer 1

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1st International Conference on Advances in Swarm Intelligence, ICSI 2010

作者： Zhang, Junqi Liu, Kun Tan, Ying Key Laboratory of Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai 200092 China Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

ISBN: (数字)9783642134951

ISBN: (纸本)3642134947

It is not trivial to tune the swarm behavior just by parameter setting because of the randomness, complexity and dynamic involved in particle swarm optimizer (PSO). Hundreds of variants in the literature of last decade, brought various mechanism or ideas, sometimes also from outside of the traditional metaheuristics field, to tune the swarm behavior. While, in the same time, additional parameters have to be afforded. This paper proposes a new mechanism, named KNOB, to directly tune the swarm behavior through parameter setting of PSO. KNOB is defined as the first principal component of the statistical probability sequence of exploration and exploitation allocation along the search process. The using of the KNOB to tune PSO by parameter setting is realized through a statistical mapping, between the parameter set and the KNOB, learned by a radial basis function neural network (RBFNN) simulation model. In this way, KNOB provides an easy way to tune PSO directly by its parameter setting. A simple application of KNOB to promote is presented to verify the mechanism of KNOB. © 2010 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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Monitor-based Liveness-enforcing Petri Net Supervisors for Flexible Manufacturing systems 33

Monitor-based Liveness-enforcing Petri Net Supervisors for F...

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第三十三届中国控制会议

作者： YOU Dan WANG Shouguang ZHOU MengChu WU Wenhui School of Information & Electronic Engineering Zhejiang Gongshang University IEEE State Key Laboratory for Manufacturing Systems Engineering Xi’ an Jiaotong University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102USA

ISBN: (纸本)9781479947249

Deadlocks are a rather undesirable phenomenon in flexible manufacturing systems(FMSs).This work,by adding monitors,develops a deadlock prevention policy for FMSs that can be modeled by a class of Petri nets called-S3 PR ***,an algorithm is given to reduce an S3 PR via *** on it,-resources in-S3 PRs are classified into A--resources and ***,for an-S3 PR with only B--resources,it is proved that a maximally permissive liveness-enforcing supervisor can be designed by M-controlling all the emptied strict minimal siphons(SMSs).For an-S3 PR containing A--resources,a liveness-enforcing supervisor can be designed by iteratively reducing the net via A--resources and adding the corresponding ***,a comprehensive deadlock prevention algorithm for-S3 PRs is *** FMS example is used to illustrate its application.

关键词： Flexible manufacturing system(FMS),Petri nets,deadlock prevention policy,supervisory control

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A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

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IEEE/CAA Journal of Automatica Sinica 2018年第5期5卷 934-945页

作者： Liang Qi Mengchu Zhou Wenjing Luan IEEE Department of Computer Scicnce and Technology Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Tongji UniversityShanghai 201804China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102USA Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghai Electronic Transactions and Information Service Collaborative Innovation CenterDepartment of Com-puter ScienceTongji UniversityShanghai 201804China

Advanced information and communication technolo-gies can be used to facilitate traffic incident *** an incident is detected and blocks a road link,in order to reduce the incident-induced traffic congestion,a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this ***-dependent shortest path algorithms are used to generate a subnetwork where vehicles should receive such information.A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well *** results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles,operation time interval of the proposed strategy,traffic density in the traffic network,and the scope of the area where traffic incident information is *** results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.

关键词： Cell transmission model(CTM) intelligent transportation systems(ITS) traffic incident management(TIM) urban traffic congestion

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Single camera 3D lane detection and tracking based on EKF for urban intelligent vehicle

Single camera 3D lane detection and tracking based on EKF fo...

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IEEE International Conference on Vehicular Electronics and Safety, ICVES 2006

作者： Min, Tian Fuqiang, Liu Zhencheng, Hu IEEE Key Laboratory of Embedded System and Service Computing Ministry of Education China Electronic and Information Engineering Department Tongji University Shanghai 201804 China Department of Computer Science Kumamoto University Kumamoto 860-8555 Japan

ISBN: (纸本)1424407591

Road boundary detection and tracking is an important and integral function in advanced driver-assistance system. This paper proposes an algorithm, which can follow multi-kinds of lane, straight and curved, quickly and robustly. The algorithm uses several masks to extract blobs of road markings, combining with KNN function to remove the disturbance. Further more, road is modeled as a 3D surface, and some important parameters of current lane are provided on real-time by tracking based on Extended Kalman Filter (EKF). The results of experiments, which have been done in urban road, show that the algorithm is adapted to many road conditions. Even in a complex driving environment, it also has a good performance. © 2006 IEEE.

关键词： Extended Kalman filters

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Moving object detection through efficient detection and clustering of reliable singular points

Advances in Intelligent and Soft Computing

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Advances in Intelligent and Soft computing 2011年 104卷 381-385页

作者： Cui, Jianzhu Wang, Ping Li, Zhipeng Li, Jing Li, Yan Key Laboratory of Embedded System and Service Computing Supported by Ministry of Education Tongji University Cao'an Highway Shanghai 4800 China

ISBN: (纸本)9783642237768

This paper presents a method to detect vehicles from a moving camera. The detection component involves a cascade of modules. First, motion estimation of singular points in video sequences is used to detect moving vehicle. Finding the image points is the selection of singular points. We impose restrictions about the gradient magnitude and the cornerness. A sparse motion vector field outlines the image motion. We obtain excellent results in real sequences in China. At last, vehicles are detected by clustering of singular points. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Motion estimation

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