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检索条件"机构=Key Laboratory of Embedded System and Service Computing"

共 631 条记录，以下是161-170 订阅

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HSim: A novel method on similarity computation by hybrid measure

HSim: A novel method on similarity computation by hybrid mea...

引用

International Conference on Information and Communication systems (ICICS)

作者： Qin Zhao Cheng Wang Changjun Jiang The Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

ISBN: (纸本)9781479973507

Link similarity is widely applied in measuring the similarity between objects, e.g., web pages, scientific papers and social networks. However, there are a lot of drawbacks in existing methods of measuring link similarity. In brief, these methods can not handle some semantic-similar content. Moreover, the computation of them are not accurate in some scenes. In this paper, we present a novel method of measuring link similarity called HSim. It introduces the semantic similarity to calculate the similarity between objects, and overcomes the drawback that existing methods ignore the semantic information of objects. We also develop a novel computation function to make the result of similarity more accurate.

关键词： Semantics Web pages Complexity theory Data mining Internet Ontologies

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Optimal stopping theory based fast coding tree unit decision for high efficiency video coding

Optimal stopping theory based fast coding tree unit decision...

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IEEE Visual Communications and Image Processing (VCIP)

作者： Xiuzhe Wu Hanli Wang Zhihua Wei Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

ISBN: (纸本)9781509053179

High Efficiency Video Coding (HEVC) is the most recent video coding standard aiming to further reduce the bitrate over 50% as compared to the state-of-the-art H.264/Advanced Video Coding under the same visual quality. In order to achieve this, a number of advanced coding techniques have been adopted in HEVC, including the quadtree structure of Coding Unit (CU), Prediction Unit (PU) and Transform Unit (TU), etc. However, these coding techniques lead to a tremendous increase in HEVC encoding computations. In order to reduce the HEVC encoding computational complexity, the optimal stopping theory is employed herein to design an efficient algorithm to optimize the decision making process when choosing the best coding parameters of CU, PU and TU. Extensive comparative experimental results are performed by the proposed algorithm and another two recent works, which demonstrate that the proposed algorithm is very efficient and better in reducing the HEVC encoding computations while keeping the video quality and compression efficiency almost intact.

关键词： Encoding Decision making Algorithm design and analysis Optimization High efficiency video coding Bit rate

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Modeling and Control of Urban Expressways with Emergency using Hybrid Petri Nets

Modeling and Control of Urban Expressways with Emergency usi...

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IEEE International Conference on systems, Man, and Cybernetics

作者： Yaying Zhang Yuefeng Fu Wei Qiang Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

ISBN: (纸本)9781509018987

The urban expressway system model based on hybrid petri nets is proposed. With the traffic detecting cameras and coils, the strategies of traffic signal lights and warning lights are enforced with the aim to prevent the large-scale congestion in emergencies (e.g. accidents). The simulation results verify the effectiveness of the proposed model and the warning light strategy is demonstrated to be suitable for traffic accidents and congestion in the accident-prone weaving sections in the urban expressways.

关键词： warning light strategy Hybrid petri nets urban expressway model emergency control

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Using estimation of distribution algorithm to coordinate decentralized learning automata for meta-task scheduling

Using estimation of distribution algorithm to coordinate dec...

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Congress on Evolutionary Computation

作者： Jie Li Junqi Zhang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Shanghai CN

Learning automaton (LA) is a reinforcement learning model that aims to determine the optimal action out of a set of actions. It is characterized by updating a selection probability vector through a sequence of repetitive feedback cycles interacting with an environment. Decentralized learning automata (DLAs) consists of many learning automata (LAs) that learn at the same time. Each LA independently selects an action based on its own selection probability vector. In order to provide an appropriate central coordination mechanism in DLAs, this paper proposes a novel decentralized coordination learning automaton (DCLA) using a new selection probability vector which is combined with the probability vectors derived from both LA and estimation of distribution algorithm (EDA). LA contributes to the own learning experience of each LA while EDA estimates the distribution of the whole swarm's promising individuals. Thus, decentralized LAs can be coordinated by EDA using the swarm's comprehensive knowledge. The proposed automaton is applied to solve the real problem of meta-task scheduling in heterogeneous computing system. Extensive experiments demonstrate a superiority of DCLA over other counterpart algorithms. The results show that the proposed DCLA provides an effective and efficient way to coordinate LAs for solving complicated problems.

关键词： Vectors Learning automata Sociology Statistics Processor scheduling Scheduling Estimation

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Meta-Heuristic Based Multipath Joint Routing and Scheduling of Time-Triggered Traffic for Time-Sensitive Networking in IIoT 2

Meta-Heuristic Based Multipath Joint Routing and Scheduling ...

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2nd International Conference on Green Communication, Network, and Internet of Things, CNIoT 2022

作者： Chen, Chen Li, Zhong The College of Information Science and Technology Donghua University Shanghai201620 China The Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science Tongji University Shanghai201804 China

ISBN: (纸本)9781510662940

Time-Sensitive networking (TSN) meets the needs of industrial internet of things (IIoT). It solves the challenges of deterministic transmission and reliable communication of time sensitive data streams. Traffic scheduling is the core mechanism of time-sensitive networks. Many excellent researches have explored and optimized the method of scheduling time-triggered streams in TSN. However, the existing time-triggered streams scheduling in TSN mostly separates routing and scheduling, which limits the scalability of scheduling. Many researches are based on fixed routing to schedule streams. Due to the interaction between scheduling and routing, the quality of fixed route solution is inferior to that of joint routing and scheduling. In this paper, we propose a meta-heuristic based multipath joint routing and scheduling method for time-triggered traffic in TSN, named MMRS. We set path selection as a variable and consider multipath routing for fault tolerance. At the same time, we establish the integer linear programming formulation and use meta-heuristic to obtain high-quality solutions. The evaluations show that compared with other excellent routing and scheduling methods, the runtime of 60 streams of MMRS method is reduced by 65.6%, and the schedulability is improved by 21% on average. The experiments verify that our proposed scheduling method can obtain high-quality solutions in an acceptable solution time. © 2023 SPIE.

关键词： Internet of things

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DSP Assembler Auto-Generation Technique and ToolChain Integration 21

DSP Assembler Auto-Generation Technique and ToolChain Integr...

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21st IEEE International Conference on Communication Technology, ICCT 2021

作者： Wang, Wanli Wu, Jun Ren, Haoqi Zhang, Zhifeng Tongji University Electronics and Information Engineering College Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Fudan University School of Computer Science Shanghai200438 China

ISBN: (纸本)9781665432061

To promote the application of DSP, a fast and accurate toolchain generation method must be realized. Unlike the traditional manual method, in this paper, we propose a toolchain generation algorithm based on the architecture description language, and migrate the toolchain to adapt to the specified processor architecture. The algorithm uses the DSP architecture description as input to generate intermediate expressions, then uses lexical analysis and syntax analysis tools to migrate the assembly toolchain. In addition, an integrated development environment is developed based on Eclipse, which creates a friendly human-computer interface. Experiments show that this toolchain generation algorithm runs fast and accurately, which solves problems of the development and application of the DSP toolchain, and creates favorable conditions for the promotion of DSP. © 2021 IEEE.

关键词： Syntactics

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A Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability 42

A Better Cardinality Estimator with Fewer Bits, Constant Upd...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Du, Yang Huang, He Sun, Yu-E Li, Kejian Zhang, Boyu Gao, Guoju Soochow University School of Computer Science and Technology Suzhou China Soochow University School of Rail Transportation Suzhou China Ministry of Education Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9798350334142

Cardinality estimation is a fundamental problem with diverse practical applications. HyperLogLog (HLL) has become a standard in practice because it offers good memory efficiency, constant update time, and mergeability. Some recent work achieved better memory efficiency, but typically at the cost of impractical update time or losing mergeability, making them incompatible with applications like network-wide traffic measurement. This work presents SpikeSketch, a better cardinality estimator that reduces memory usage of HLL by 37% without sacrificing other crucial metrics. We adopt a bucket-based data structure to promise constant update time, design a smoothed log4 ranking and a spike coding scheme to compress cardinality observables into buckets, and propose a lightweight mergeable lossy compression to balance memory usage, information loss, and mergeability. Then we derive an unbiased estimator for recovering cardinality from the lossy-compressed sketch. Theoretical and empirical results show that SpikeSketch can work as a drop-in replacement for HLL because it achieves a near-optimal MVP (memory-variance-product) of 4.08 (37% smaller than HLL) with constant update time and mergeability. Its memory efficiency even defeats ACPC and HLLL, the state-of-the-art lossless-compressed sketches using linear-time compression to reduce memory usage. © 2023 IEEE.

关键词： Efficiency

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The behavioral sign of account theft: Realizing online payment fraud alert 29

The behavioral sign of account theft: Realizing online payme...

引用

29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Wang, Cheng Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Shanghai Institute of Intelligent Science and Technology Tongji University China

ISBN: (纸本)9780999241165

As a matter of fact, it is usually taken for granted that the occurrence of unauthorized behaviors is necessary for the fraud detection in online payment services. However, we seek to break this stereotype in this work. We strive to design an ex-ante anti-fraud method that can work before unauthorized behaviors occur. The feasibility of our solution is supported by the cooperation of a characteristic and a finding in online payment fraud scenarios: The well-recognized characteristic is that online payment frauds are mostly caused by account compromise. Our finding is that account theft is indeed predictable based on users' high-risk behaviors, without relying on the behaviors of thieves. Accordingly, we propose an account risk prediction scheme to realize the ex-ante fraud detection. It takes in an account's historical transaction sequence, and outputs its risk score. The risk score is then used as an early evidence of whether a new transaction is fraudulent or not, before the occurrence of the new transaction. We examine our method on a real-world B2C transaction dataset from a commercial bank. Experimental results show that the ex-ante detection method can prevent more than 80% of the fraudulent transactions before they actually occur. When the proposed method is combined with an interim detection to form a real-time anti-fraud system, it can detect more than 94% of fraudulent transactions while maintaining a very low false alarm rate (less than 0.1%). © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Crime

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Two-dimensional color uncorrelated principal component analysis for feature extraction with application to face recognition

引用

2012 International Conference on service-Oriented computing, ICSOC 2012

作者： Zhao, Cairong Miao, Duoqian Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai 7201804 China Ministry of Education Nanjing 210094 China

ISBN: (纸本)9783319029603

This paper proposes a two-dimensional color uncorrelated principal component analysis algorithm(2DCUPCA) for unsupervised subspace learning directly from color face images. The 2DCUPCA can be used to explore uncorrelated properties among color-based features, which contain minimum redundancy and ensure linear independence among features. Furthermore, the proposed 2DCUPCA provided the theoretical foundations analysis and proved the uncorrelated property between color-based features in theory. This makes it sure that the extracted features directly from three color image matrices will be uncorrelated. Finally, experimental results on the AR and FRGC-2 color face databases show that 2DCUPCA achieves better recognition performance than other color face recognition methods. © Springer International Publishing 2013.

关键词： Principal component analysis

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Improved condition for controllability of strongly dependent strict minimal siphons in Petri nets

Improved condition for controllability of strongly dependent...

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International Conference on Networking, Sensing and Control

作者： Liu, Guanjun Jiang, Changjun Zhou, Mengchu Key Laboratory of the MoE for Embedded System and Service Computing Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

ISBN: (纸本)9781424495702

Li and Zhou propose an important concept for Petri nets: elementary siphons. They partition siphons into elementary and dependent ones. The controllability of the latter can be ensured by the former's proper control. They give a sufficient condition to decide whether a dependent siphon is controlled by its elementary ones in S3PR. However, this condition is so loose that in many cases the controllability of a dependent SMS cannot be determined although it is actually controlled. In this paper, we propose an improved condition to decide the controllability of strongly dependent SMS. © 2011 IEEE.

关键词： Controllability

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