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International Conference on systems and Informatics (ICSAI)

作者： Xiwei Liu Ping Li Yuan Xu Ying Liu Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781479954599

Quasi-synchronization is an important type of synchronization because of the parameter mismatches in the real world, so we will investigate it for a delayed network, which is master-slave coupled. By applying the aperiodically and nonlinearly intermittent control on the network, and assuming the time delay is varying, we will present some useful criteria for exponential quasi-synchronization. The main difference of this paper with previous works is that the intermittent mode is aperiodic while that in previous works is periodic. Finally, simulations are also given to show its validity.

关键词： Synchronization Mathematical model Delay effects Numerical models Observers Equations Educational institutions

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Feedback-based Coarse Time-Granularity POI Recommendation and Itinerary Planning

Feedback-based Coarse Time-Granularity POI Recommendation an...

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Chinese Automation Congress (CAC)

作者： Jie Zong Zhijun Ding The Key Laboratory of Embedded System and Service Computing Ministry of Education TONGJI University Shanghai China

ISBN: (纸本)9781665426480

For tourists, planning their own travel itinerary to a strange city is really challenging. Although there are many researches on Point of Interests (POIs) recommendation and itinerary planning, two problems occur in currently proposed recommendation algorithms. First, the time granularity of the algorithms is too fine. POI recommendation should be considered within a more coarse-grained time factor. For example, a visitor wouldn’t like to visit a water park in winter, although he appears to love such places. However, seldom researches have taken this into consideration. Second, most of the algorithms build their models based on the tourists’ trajectory, which means, they did not consider users’ feedback. In fact, quite a number of tourists do not like their travel experience and give negative feedbacks after their visits. In this situation, we shouldn’t recommend similar POIs to this user because he may not like such kind of scenic spots at all. To address these two problems, this paper proposes an algorithm called Feedback-based Coarse Time-Granularity POI Recommendation, which can extract information from comments and distinguish tourists’ attitudes towards the POIs they have visited. At the same time, the coarse-grained time factor is considered while making recommendations. In addition, an itinerary planning algorithm is proposed. Experiments show that our algorithm can reach SOTA.

关键词： Negative feedback Automation Urban areas Planning Trajectory Time factors Data mining

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Edge-weight-Based link prediction in heterogeneous graph

Edge-weight-Based link prediction in heterogeneous graph

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IEEE International Conference on Networking, Sensing and Control

作者： Jie Zong Zhijun Ding The key laboratory of embedded system and service computing ministry of education TONGJI University Shanghai China

ISBN: (纸本)9781665472449

Link prediction is to predict whether there is a link between two nodes in the graph, it is a very important application and plays a great role in various industries. In recent years, with the development of graph neural network technology, many algorithms make effort to study the expression of each node from the original graph data and use them to infer new links. However, most of the existing algorithms have a common problem when facing heterogeneous graphs, which is, they do not consider the weight of edges in graphs. Instead, they put all their energies into computing node features. Although a few algorithms such as RGCN are trying to take the influence of different link types into account while extracting node features, these implicit feature extractions do not start from the global information, but just calculate independently for each node. In other words, in these algorithms, even the same type of links will be abstracted into different features on different nodes. This is obviously inconsistent with reality. On the same map, the feature of the same link should be relatively fixed and should not be changed just because of different positions. In addition, when the current graph neural network algorithm is applied to link prediction, the link type to be predicted must be specified in advance, which makes the algorithm extremely inflexible. In order to solve these problems, we propose an edge weight calculation algorithm that extracts the edge feature from the whole graph. We also propose the edge-weight-based link prediction algorithm. By introducing edge weight into the MLP, there is no need to specify the target link type at the beginning of model training. It improves both the performance and efficiency of the link prediction model. Experiments on two datasets show that this edge-weight-based link prediction algorithm performs better than current algorithms and reaches SOTA.

关键词： Training Industries Semantics Predictive models Prediction algorithms Feature extraction Graph neural networks

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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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The preference relation and its application in the information system

The preference relation and its application in the informati...

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IEEE International Conference on Computer Science and Automation Engineering (CSAE)

作者： Zhao Mingqing Key Laboratory of Embedded System and Service Computing Ministry of Education University of Tongji Shanghai China

In order to strengthen the traditional information system's capacity of describing practical problems, preference relation is introduced into information system and the concepts of preference information system, preference decision table, and information utility function are offered in this paper. In addition, the existence theorem of information utility function and several applications of information utility function in knowledge acquisition are provided.

关键词： Information systems Knowledge acquisition Economics Clustering methods Transforms Information science Approximation methods

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Quality assessment for color images with tucker decomposition

Quality assessment for color images with tucker decompositio...

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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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Implicit cooperative caching based on information popularity for vehicular networks 12

Implicit cooperative caching based on information popularity...

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12th Workshop on Challenged Networks, CHANTS 2017

作者： Li, Yuhong Wang, Ji Lindgren, Anders Su, Xiang Riekki, Jukka State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China RISE SICS Sweden Luleå University of Technology Sweden Centre for Ubiquitous Computing University of Oulu Finland

ISBN: (纸本)9781450351447

Information-centric networking (ICN) technology is becoming a popular research topic in vehicular networks due to the connectionless and lightweight characteristics of this networking paradigm. Caching plays an essential role in information-centric networks, but current caching techniques for ICN are not ideal for the dynamic and wireless vehicular networks. This paper presents a caching approach for ICN-based vehicular networks that takes into account both the dynamicity of vehicular networks and the popularity of the information being distributed. We introduce an interval metric for selective caching. With this metric and estimates of information popularity and vehicle density, cooperative caching can be realized without exchanging cache management information among the vehicular nodes. Simulation results show that the proposed approach can increase the storage space utilization and has low data response time for vehicular networks. © 2017 Association for computing Machinery.

关键词： Digital storage

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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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Analysis for one-place unbounded Petri nets based on modified reachability trees

Analysis for one-place unbounded Petri nets based on modifie...

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IEEE International Conference on Networking, Sensing and Control

作者： Yu Wang Zhi Jun Ding Key Laboratory of Embedded System and Service Computing Ministry of Education University of Tongji Shanghai China Key Laboratory of Embedded ystem nd Service Computing Ministry of Education University of Tongji Shanghai China

Analysis approaches of reachability decision is fundamental to Petri nets theory; however, the relevant research work in the past cannot always guarantee the correctness of analysis conclusions. This paper firstly reveals the root cause of wrong conclusions, which are drawn in analysis for deadlock of Petri nets based on modified reachability trees (MRT), and then proposes the rectified calculation of the next-state function and some corresponding definitions, which guarantee MRT's usefulness and correctness in analyzing reachability and deadlock of one-place unbounded Petri nets. Finally, a necessary and sufficient condition of MRT's reachability and the theoretical proof are presented. Examples are given to illustrate the method.

关键词： Petri nets system recovery Firing laboratories Educational institutions Analytical models Mathematical model

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