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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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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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A Novel Frequency Selective Sounding Scheme for TDD LTE-Advanced systems

A Novel Frequency Selective Sounding Scheme for TDD LTE-Adva...

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IEEE Global Communications Conference

作者： Shengjie Zhao Baolong Zhou Daqiang Zhang Key Lab of Embedded System and Service Computing Ministry of Education Tongji University

ISBN: (纸本)9781479935130

In this paper we propose a novel Frequency Selective SRS (FS-SRS) scheme to improve the quality of CSI. According to the CQIs (channel quality indications), which are periodically reported by each user, and the bandwidth requirement of each user, BSs dynamically schedule each user to send SRSs only on the requisite bandwidth with best CQIs instead of on full bandwidth or on specified sub-bandwidth as in the current LTE TDD systems. Simulation results show that the proposed FS-SRS scheme outperforms the current schemes in estimation accuracy for various frequency-selective and/or time-selective fading channels. In addition, the proposed FS-SRS scheme offers unique advantages over the current schemes. Firstly, it is robust to frequency selective channels. Secondly, it is hardly impacted by timing offset. Thirdly, it is adaptive to the change of the underlying scheduler. Fourthly, it can increase SRS capacity. Finally, it can be extended to multi-user MIMO (multiple-input multiple-output) systems, called extended FS-SRS scheme. Moreover, the proposed schemes are applicable to the uplink SRS design in LTE-Advanced systems.

关键词： Channel estimation error Frequency selective Long Term Evolution (LTE) Sounding Time division duplex (TDD)

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Top-n recommendation algorithms for cloud data

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2015年第1期43卷 54-61页

作者： Huang, Zhen-Hua Department of Computer and Technology Tongji University Shanghai200092 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China

Top-n recommendation technology has recently received a lot of attention in information service community. In this paper, we study the problem of top-n recommendation under the cloud data. Firstly, we propose a multilayer distributed storage architecture(MDSA)which can fit the need of top-n recommendation. Secondly, based on the consideration of reducing the cost of network transmission, we present the data encoding pattern which is based on the MDSA architecture. Lastly, we fast realize top-n recommendation using the map/reduce distributed programming model. For satisfying the realistic requirement, we further present three application variants of top-n recommendation. Massive experiments demonstrate that our approach is efficient and has high overall performance. ©, 2015, Chinese Institute of Electronics. All right reserved.

关键词： MapReduce

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A Prediction Based on Clustering and Personality Questionnaire Data for IGD Risk

A Prediction Based on Clustering and Personality Questionnai...

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International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery

作者： Xiaoliang Gong Kun Fang Yichu Hou Bozhong Long Zongling Di Lei Cao National Key Laboratory of Embedded System and Service Computing (Ministry of Education) Tongji University Shanghai China

ISBN: (纸本)9781509040940

With the development of the Internet, a lot of people trapped in the network, especially the adolescent depending on the network game and disturbing their normal life. 579 freshmen participated in this work who were collected the personality questionnaires in the first week they came in university and their grades points average (GPA) after half year. The questionnaires were including Self-Control (SCS), Barratt impulse Inventory (BIS) and Chinese Big Five Personality (CBF). This work used multi-clustering algorithms to construct the models of predicting for Internet game disorder (IGD) risk, including FCM, K-means, and Hierarchical for training model. This is the first try to predict the risk of IGD by personality traits. The results shown the questionnaire data were well separated by different clustering algorithms into three groups who were shared the analogous personality traits which has a relationship with the behavior of IGD. But compared to the GPA of each group, the efficiency of the prediction model seems not so satisfactory. There need more efforts to optimized the model in the future.

关键词： Personality questionnaire Data IGD Risk FCM K-means Hierarchical

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ST-ReP: Learning Predictive Representations Efficiently for Spatial-Temporal Forecasting

arXiv

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arXiv 2024年

作者： Zheng, Qi Yao, Zihao Zhang, Yaying The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China

Spatial-temporal forecasting is crucial and widely applicable in various domains such as traffic, energy, and climate. Benefiting from the abundance of unlabeled spatial-temporal data, self-supervised methods are increasingly adapted to learn spatial-temporal representations. However, it encounters three key challenges: 1) the difficulty in selecting reliable negative pairs due to the homogeneity of variables, hindering contrastive learning methods;2) overlooking spatial correlations across variables over time;3) limitations of efficiency and scalability in existing self-supervised learning methods. To tackle these, we propose a lightweight representation-learning model ST-ReP, integrating current value reconstruction and future value prediction into the pre-training framework for spatial-temporal forecasting. And we design a new spatial-temporal encoder to model fine-grained relationships. Moreover, multi-time scale analysis is incorporated into the self-supervised loss to enhance predictive capability. Experimental results across diverse domains demonstrate that the proposed model surpasses pre-training-based baselines, showcasing its ability to learn compact and semantically enriched representations while exhibiting superior scalability. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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Study and implementation of agent-based grid resource monitoring model

Study and implementation of agent-based grid resource monito...

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2nd International Conference on Information Science and Engineering, ICISE2010

作者： Ming, Liu Zhang, Junqi Wang, Yu Li, Jie Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

ISBN: (纸本)9781424480968

Grid is a promising infrastructure which enables scientists and engineers to access geographically distributed resources. Grid computing is a new technology which focuses on aggregating various kinds of resource (e.g., processor cycles, disk storage, and contents) into one computing platform. The realization of grid computing requires a resource agent to manage and monitor available resources. Based on study of past models, this paper presents a new agent-based resource monitoring model whose main feature is multi-layered monitoring architecture, which enhances the ability to monitor related resource efficiently. In the meantime, the new model has been implemented in the development of a resource monitoring module integrated within a academic grid project. © 2010 IEEE.

关键词： Grid computing

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A Remote Debugging system for OpenMP Parallel Program

A Remote Debugging System for OpenMP Parallel Program

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International Conference on Transportation, Mechanical, and Electrical Engineering

作者： Hua Chai Qinqin Shi The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

ISBN: (纸本)9781457717000

A remote debugging system for OpenMP parallel program is presented in this paper. The system consists of two parts, namely, an integrated debugging environment running on the clent-side and a background daemon running on the server-side. Information exchange between the two sides is accomplished through the socket-based network communication technology. The remote debugging function is realized by the automatic instrumentation technology at code level based on syntax tree. Instance tests show that the system can provide remote users with correctness checking, performance analysis and other debugging functions for OpenMP parallel programs. The user interface is simple and very easy to use.

关键词： Parallel Program OpenMP Remote Debugging Syntax Tree Instrumentation Technology

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Spatial-Temporal Interactive Dynamic Graph Convolution Network for Traffic Forecasting

arXiv

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arXiv 2022年

作者： Liu, Aoyu Zhang, Yaying The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China

Accurate traffic forecasting is essential for urban traffic control, route planning, and flow detection. Although many spatial-temporal methods are currently proposed, they are still deficient in synchronously capturing the spatial-temporal dependence of traffic data. In addition, most methods ignore the hidden dynamic associations that arise between the road network nodes as it evolves over time. We propose a neural network-based Spatial-Temporal Interactive Dynamic Graph Convolutional Network (STIDGCN) to address the above challenges for traffic forecasting. Specifically, we propose an interactive dynamic graph convolution structure which divides the traffic data by intervals and synchronously captures the divided traffic data‘s spatial-temporal dependence through an interactive learning strategy. The interactive learning strategy motivates STIDGCN effective for long-range forecasting. We also propose a dynamic graph convolution module through a novel dynamic graph generation method to capture the dynamically changing spatial correlations in the traffic network. Based on a priori knowledge and input data, the dynamic graph generation method can generate a dynamic graph structure, which allows exploring the unseen node connections in the road network and simulating the dynamic associations between nodes over time. Extensive experiments on four real-world traffic flow datasets demonstrate that STIDGCN outperforms the state-of-the-art baselines. Copyright © 2022, The Authors. All rights reserved.

关键词： Convolution

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Reliable Web services Selection Using a Heuristic Algorithm

Reliable Web Services Selection Using a Heuristic Algorithm

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The Ninth International Conference on Grid and Cloud computing(第九届网格与云计算国际学术会议 GCC 2010)

作者： Hongjie Shen Zhijun Ding Hongzhong Chen The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

Web services composition (WSC) is the key techniques in its application. Dynamically selecting reliable Web services (WSs) becomes crucial to users. In fact, most works regard a Web service (WS) as the basic unit and selection with end-to-end, and as more and more WSs become available, the WSs selection problem is a complex NP-hard optimization problem. So, in this paper, the WSs consist of the operations and the WSs selection problem is formalized as a finite state machine process and we proposed a backward algorithm to create the WSC tree (WSCT). Then, we proposed a heuristic algorithm to complete the selection of WSs based on the WSCT. The results of experiment show our proposed heuristic algorithm is effective.

关键词： Web services composition heuristic algorithm service selection reliability

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