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

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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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Multi-sensor based perception network for vehicle driving assistance

Multi-sensor based perception network for vehicle driving as...

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2009 2nd International Congress on Image and Signal Processing, CISP'09

作者： Jun, Han Fuqiang, Liu Zhipeng, Li Shanshan, Zhang Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China Tongji University China College of Electronics and Information Engineering Tongji China

ISBN: (纸本)9781424441310

In this paper, a multi-sensor based perception network for vehicle driving assistance is described. The network could reconstruct the 3D real world from the data obtained by the sensors, recognize dangerous occasions in advance and give the driver a suggestion or warning to prevent from the accident. Vehicle driving assistance is a research area which requires high accuracy and precision. The purpose of this perception network is to make up for the weakness of one sensor by means of the advantages of other sensors in the network. We will discuss the details of our adopted solutions, and present some real experimental results. ©2009 IEEE.

关键词： Vehicles

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Optimized image recognition based sewing pattern file auto-generating method for intelligent industrial equipments

Optimized image recognition based sewing pattern file auto-g...

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2012 IEEE/ACIS 11th International Conference on computer and Information Science, ICIS 2012

作者： Su, Erfeng Zhang, Kailong Zhou, Xingshe School of Computer Northwestern Polytechnical University Xi'an China Shaanxi Key Laboratory of Embedded System Technology Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9780769546940

The development of embedded system (ES) promotes the trend that the numerical-control equipment becomes more networked and intelligent. ES is the kernal of network and intelligence, yet the image data with contained information is the key point to realize high antomatization and intelligence of ES. The overall automatization level of industrial equipment becomes higher than before. However, in some basic industries, such as the sewing industry, the automatization is backward. This paper analyzes the working mechanism of current pattern-designing software and concludes that the system input is complicated, and the usability and automatization is low. To deal with the problem, the paper proposes a sewing pattern generating method based on optimized image recognition. This method is data-driven, which includes image calibration, edge detecting and curve fitting to simplify the system input. A new algorithm is designed to transfer the system input from vectors to scalars, or to accept both of them, which improves the system's scalability and usability. Corresponding software is developed and the results show that it is more reliable, and it can satisfy the industrial requirements in an acceptable degree. © 2012 IEEE.

关键词： Curve fitting

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BMSAD: Behavior Feature and Multi-Scenario -Based Sybil Attack Detection Method in Vehicular Networks 3

BMSAD: Behavior Feature and Multi-Scenario -Based Sybil Atta...

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3rd International Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022

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

ISBN: (数字)9781510662971

ISBN: (纸本)9781510662964

Vehicular networks improve traffic safety and efficiency by wireless communications among vehicles and infrastructures. However, security has always been a challenge to vehicular networks, which may cause severe harm to the intelligent transportation systems. Sybil attack is considered as a serious security threat to vehicular networks since the attacker can disseminate false messages with multiple forged identities. In this paper, we designed a behavior feature and multi-scenario-based Sybil attack detection method, named BMSAD in vehicular networks. In BMSAD, we propose solutions for two scenarios: normal traffic and traffic congestion. A node is allowed to verify the authenticity of another node by estimating their geographic distance based on received signal strength, and compare them to its claimed localizations. Then we design long- and short-term pattern to analyze the similarity of vehicles' behavior features and trajectory for Sybil nodes detection, which act as the second line of defense in normal traffic scenario. At last, the Sybil nodes of the traffic congestion scenario are detected by logical inference based on kinematics theory. And experiment results demonstrate that the proposed scheme achieves high detection rate and low false positive rate. © 2023 SPIE.

关键词： Traffic congestion

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A 3rd order opamp-based tunable low-pass filter design for data demodulator of a 5.8 GHz ETC RF receiver

A 3rd order opamp-based tunable low-pass filter design for d...

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International Conference on computer, Informatics, Cybernetics and Applications 2011, CICA 2011

作者： Li, Yan Yu, Hang Lin, Shengyue Jiang, Lai Wei, Rongchen Ji, Zhen Shenzhen City Key Laboratory of Embedded System Design College of Computer Science and Software Engineering Shenzhen University Shenzhen Guangdong 518060 China

ISBN: (纸本)9789400718388

Electronic tolling collection (ETC) will be applied in the construction of the new national highway network in China and the Chinese standard has been released. A 5.8 GHz receiver satisfied the standard is one of the key components in the ETC system. In this work, a 3rd order low-pass filter was designed in a 0.18 μm CMOS process for the data demodulation block of the receiver. An operational amplifier was firstly realized and then a tunable low pass filter was designed based on the amplifier. Detailed simulation results are presented and the main design issues were discussed. © 2012 Springer Science+Business Media B.V.

关键词： Operational amplifiers

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Incremental sensor node deployment for low cost and highly available WSNs

Incremental sensor node deployment for low cost and highly a...

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International Conference on Mobile Ad-hoc and Sensor Networks

作者： Al-Omari, Safwan Shi, Weisong Jordan University of Science and Technology Jordan Key Laboratory of Embedded System and Service Computing Tongji University China Wayne State University United States

ISBN: (纸本)9780769543154

We attack the sensor network deployment problem. We define the deployment problem as the problem of deciding how many sensor nodes should be deployed in the sensor field over how many phases during its lifetime. We target the optimal deployment strategy that meets user-defined availability requirement with minimum total cost taking into consideration node failures and changing field trip to sensor node cost ratio. We model WSN availability and total cost as functions of the deployment plan, then, we formalize the deployment problem as a 2D optimization problem. Our modeling enables us to explore cost-benefit tradeoffs, we believe, this is a solid step toward bringing cost as an explicit dimension in the design space of WSN protocols. We compare the performance of the optimized solution (denoted as pro-active) to more ad-hoc solutions: on-demand) and at-front. The former strategy schedules future deployments only on demand. The latter strategy deploys all nodes at front with no later field trips. Using extensive simulations, we show that proactive outperforms at-front and on-demand in terms of total cost per availability unit in all application scenarios. For example, using pro-active costs $7 compared to $40 and $280 per total uptime in case of on-demand and at-front, respectively. © 2010 IEEE.

关键词： Sensor nodes

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Inertial estimator learning automata

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IEICE Transactions on Fundamentals of Electronics, Communications and computer Sciences 2012年第6期E95-A卷 1041-1048页

作者： Zhang, Junqi Ni, Lina Xie, Chen Gao, Shangce Tang, Zheng Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Tongji University Shanghai 200092 China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China Department of Intellectual Information Systems Engineering University of Toyama Toyama-shi 930-8555 Japan

This paper presents an inertial estimator learning automata scheme by which both the short-term and long-term perspectives of the environment can be incorporated in the stochastic estimator-the long term information crystallized in terms of the running reward-probability estimates, and the short term information used by considering whether the most recent response was a reward or a penalty. Thus, when the shortterm perspective is considered, the stochastic estimator becomes pertinent in the context of the estimator algorithms. The proposed automata employ an inertial weight estimator as the short-term perspective to achieve a rapid and accurate convergence when operating in stationary random environments. According to the proposed inertial estimator scheme, the estimates of the reward probabilities of actions are affected by the last response from environment. In this way, actions that have gotten the positive response from environment in the short time, have the opportunity to be estimated as "optimal", to increase their choice probability and consequently, to be selected. The estimates become more reliable and consequently, the automaton rapidly and accurately converges to the optimal action. The asymptotic behavior of the proposed scheme is analyzed and it is proved to be Ε-optimal in every stationary random environment. Extensive simulation results indicate that the proposed algorithm converges faster than the traditional stochastic-estimator-based SERI scheme, and the deterministicestimator- based DGPA and DPRI schemes when operating in stationary random environments. Copyright © 2012 The Institute of Electronics, Information and Communication Engineers.

关键词： Probability

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