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Modeling and monitoring of online shopping business processes based on system behavior patterns

Journal of Computational Information systems 2013年第12期9卷 4691-4698页

作者： Yu, Wangyang Yan, Chungang Ding, Zhijun Zhong, Junzhu Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Lab. of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China

Online shopping integrating third-party payment platforms (TPPs) has rapidly developed recently. The integration leads to new security problems derived from complex interactions among Application Programming Interfaces (APIs), and the detection of such defects in application-level is costly and difficult. To deal with these security issues at the online stages, this paper presents a framework of modeling and monitoring online shopping business processes from the point of legal behavior patterns. We present Online Shopping Net (OSN) to model the normal business process, and make it as the legal behavior pattern used to monitor system behaviors. Then, a monitor based on OSN is constructed. The system behaviors beyond the legal behavior pattern would be alarmed and blocked. It is a novel attempt to guarantee the security of online shopping from the point of behaviors and online monitoring. Using the active defense tactics, we can effectively prevent the illegal behaviors of the users at application-level instead of constantly fixing bugs of applications. As a case study, we simulate an e-commerce site and a TPP, and the monitor can effectively prevent the malicious behaviors appearing recently. © 2013 by Binary Information Press.

关键词： Application programming interfaces (API)

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Low-rate non-intrusive appliance load monitoring based on graph signal processing

Low-rate non-intrusive appliance load monitoring based on gr...

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2019 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2019

作者： Zhang, Bing Zhao, Shengjie Shi, Qingjiang Zhang, Rongqing Tongji University Key Laboratory of Embedded System and Service Computing of Ministry of Education Shanghai China Tongji University Sch. of Software Eng. the Key Lab. of Embedded System and Service Computing of Ministry of Education Shanghai China Tongji University School of Software Engineering Shanghai China

ISBN: (纸本)9781728159287

Thanks to the large-scale smart meters deployments around the world, non-intrusive appliance load monitoring (NILM) is receiving popularity. It aims to disaggregate the total electricity load of a home into individual appliances without resorting to any specific appliance power monitors. NILM is worthy of broad attention owing to its facilitation in energy savings. This paper regards NILM as a classification task and proposes a two-step method based on graph signal processing (GSP). In the first step, a smoothest solution is obtained by minimizing the regularization term. In the second step, gradient projection method, which uses the obtained minimizer as a start point, is adopted to optimize the while objective function, where NILM is regarded as a constrained nonlinear programming problem. The experiment results based on the open-access data set REDD clearly demonstrate that the proposed GSP-based method achieves improved performance compared with other state-of-the-art low-rate NILM approaches. © 2019 IEEE.

关键词： Signal processing

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Design and implementation of communication module in passive ultrasonic sensor networks

Design and implementation of communication module in passive...

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2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010

作者： Han, Lina Zhao, Rui Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Third Research Institute of The Ministry of Public Security Shanghai China

ISBN: (纸本)9781424479566

Passive sensor networks can achieve accurate detection of target under complex environment. In order to adapt to different communication demands of sensor networks in different environments, this paper designed and implemented a wireless and wired mixed communication module, that is, a communication system combined short-distance wireless communication based on radio frequency technology with broadband cable communication. Simulation results show that our system can achieve the desired requirements in different circumstances. © 2010 IEEE.

关键词： Ultrasonic applications

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Analysis and Design of Ironless Axial Flux Permanent Magnet Synchronous Motor 10

Analysis and Design of Ironless Axial Flux Permanent Magnet ...

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10th International Conference on Intelligent Human-Machine systems and Cybernetics, IHMSC 2018

作者： Zhang, Yufeng Liu, Na Guo, Shan Tong, Jun Zhou, Qixun Xi'an University of Science and Technology Xi'an China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781538658369

In this paper, a single stator twin external rotors ironless AFPMSM for robot applications is studied. The design method of the motor is proposed. The magnetic circuit calculation and the main motor size equations are obtained. To solve the problem of low air-gap flux density in the ironless disk-type PMSM, the armature windings adopts the single-layer concentrated windings, which effectively reduces the air-gap length, increasing the motor power density, and they are initially verified with 3D-FEA. Finally, the mechanical structure of the motor is designed, a prototype is built and experiments are performed. The results show that the back-EMF error is within 2%, the air-gap flux density can reach 0.75T, and the motor has good acceleration performance, which verifies the rationality and feasibility of the design. © 2018 IEEE.

关键词： Permanent magnets

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An Initialization Method based on The Core Clusters for Locality-weight Fuzzy C-Means Clustering 4th

An Initialization Method based on The Core Clusters for Loca...

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2013 IEEE 4th International Conference on Software Engineering and service Science

作者： Lei Gu The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University School of Computer Science and Technology Nanjing University of Posts and Telecommunication

ISBN: (纸本)9781467349970

The Locality-weight fuzzy c-means clustering method has been presented *** this approach can improve the clustering accuracies,it often gains the unstable clustering results because some random samples are employed for the initial *** this paper,an initialization method based on the core clusters is used for the locality-weight fuzzy c-means *** core clusters can be formed by constructing the σ-neighborhood graph and their centers are regarded as the initial centers of the locality-weight fuzzy c-means *** investigate the effectiveness of our approach,several experiments are done on three *** results show that our proposed method can improve the clustering performance compared to the previous locality-weight fuzzy c-means clustering.

关键词： the initialization clustering methods core clusters locality-weight fuzzy c-means neighborhood graph

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A hierarchical clustering strategy of processing class imbalance and its application in fraud detection 21

A hierarchical clustering strategy of processing class imbal...

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21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and systems, HPCC/SmartCity/DSS 2019

作者： Zhang, Youjun Liu, Guanjun Zheng, Lutao Yan, Chungang Key Laboratory of the Ministry of Education for Embedded System and Service Computing Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University Shanghai China

ISBN: (纸本)9781728120584

With the Internet and mobile communications becoming an indispensable part of people's daily lives, online transactions have become one of the most common payment methods. However, transaction fraud incidents also occur frequently, causing a larger number of economic losses. Therefore, transaction fraud detection is significant. The methods of machine learning are often used to detect fraudulent transactions from a larger amount of transaction data. However, the class imbalance problem reduces the performance of these methods. There are mainly four factors causing this problem: imbalanced class distribution, sample size, class separability and within-class concept. The existing improvement strategies for class imbalance mainly focus on the first factor but omit other three ones. This paper considers the four factors to propose a comprehensive model called clustering tree. Constructing a clustering tree includes two steps: 1) we first select a clustering algorithm considering the class separability;and then 2) we use this clustering algorithm to construct a tree that can be used to determine if an incoming transaction is illegal. The root node of this tree contains all samples, and we consider both the imbalanced class distribution and the within-class concept when samples are hierarchically divided into sub-nodes during the constructing process. We compare the proposed method with five state-of-the-art ones on two real transaction datasets, and the experimental results show that our method works better. © 2019 IEEE.

关键词： Clustering algorithms

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Method on the fault detection and diagnosis for the railway turnout based on the current curve of switch machine

Method on the fault detection and diagnosis for the railway ...

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2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013

作者： Mo, Xue Mei Fang, Yu Yang, Yun Guo The Key Laboratory of Embedded System and Service Computing Ministry of Education China Shanghai Railway Telecommunication Equipment Ltd Co. Shanghai China

ISBN: (纸本)9783037858905

This paper proposes a method of the fault detection and diagnosis for the railway turnout based on the current curve of switch machine. Exact curve matching fault detection method and SVM-based fault diagnosis method are adopted in the paper. Based on envelope and morpheme match algorithm, exact curve matching method is used to match the detected current curve with the reference curve so as to predict whether the curve would have fault or not. Moreover, the SVM-based fault diagnosis method is used to make sure that the fault conditions could be diagnosed intelligently. Finally, the experimental results show that the proposed method can accurately identify the turnout fault status in the conversion process, and the accuracy rate in the diagnosis of the fault location is above 98%, which verify the effectiveness of the method in the fault detection and diagnosis. © (2013) Trans Tech Publications, Switzerland.

关键词： Fault detection

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Adaptive Granulation for Efficient Classification on Noise Labeled Images 9

Adaptive Granulation for Efficient Classification on Noise L...

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9th IEEE International Conference on Computational Intelligence and Applications, ICCIA 2024

作者： Cai, Kecan Zhang, Hongyun Miao, Duoqian Tongji University Department of Computer Science and Technology Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (纸本)9798350352214

Current semi-supervised learning-based sample selection methods for noisy label image classification typically utilize all clean and noisy samples for model training. However, not all noisy samples contribute positively to model training. This paper introduces a novel semi-supervised image data granulation method that employs adaptively generated granular noisy sample subsets in place of the original noisy samples to enhance classification efficiency. The granular data generated retain the essential features of the original data, thereby improving efficiency without compromising classification accuracy. The quality of the granular data is assessed using coverage and specificity criteria, standard metrics for evaluating information granules. The proposed method consists of three main components: (i)selecting clean and noisy samples through network co-training, (ii)calculating granular noisy sample subsets by adaptive granulation, and (iii)optimizing the network model using a semi-supervised strategy. Experimental results on benchmark datasets with varying noise rates demonstrate that our method significantly improves the efficiency of noisy label image classification while maintaining accuracy. © 2024 IEEE.

关键词： Self-supervised learning

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Multi‐granularity re‐ranking for visible‐infrared person re‐identification

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 770-779页

作者： Yadi Wang Hongyun Zhang Duoqian Miao Witold Pedrycz Department of Computer Science and Technology Tongji UniversityShanghaiChina Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghaiChina Department of Electrical and Computer Engineering University of AlbertaEdmontonAlbertaCanada System Research Institute Polish Academy of SciencesWarsawPoland

Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more challenging than single‐modality ReID because,in addition to difficulties in pedestrian posture,camera shoot-ing angle and background change,there are also difficulties in the cross‐modality *** works only involve coarse‐grained global features in the re‐ranking calculation,which cannot effectively use fine‐grained ***,fine‐grained features are particularly important due to the lack of information in cross‐modality re‐*** this end,the Q‐center Multi‐granularity K‐reciprocal Re‐ranking Algorithm(termed QCMR)is proposed,including a Q‐nearest neighbour centre encoder(termed QNC)and a Multi‐granularity K‐reciprocal Encoder(termed MGK)for a more comprehensive feature *** converts the probe‐corresponding modality features into gallery corresponding modality features through modality transfer to narrow the modality *** takes a coarse‐grained mutual nearest neighbour as the dominant and combines a fine‐grained nearest neighbour as a supplement for similarity *** experiments on two widely used VI‐ReID benchmarks,SYSU‐MM01 and RegDB have shown that our method achieves state‐of‐the‐art ***,the mAP of SYSU‐MM01 is increased by 5.9%in all‐search mode.

关键词： computer vision recognition

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Particle swarm optimization based on pairwise comparisons 9th

Particle swarm optimization based on pairwise comparisons

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9th International Conference on Swarm Intelligence, ICSI 2018

作者： Zhang, JunQi Chen, JianQing Zhu, XiXun Wang, ChunHui Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (纸本)9783319938141

Particle swarm optimization (PSO) is a widely-adopted optimization algorithm which is based on particles’ fitness evaluations and their swarm intelligence. However, it is difficult to obtain the exact fitness evaluation value and is only able to compare particles in a pairwise manner in many real applications such as dose selection, tournament, crowdsourcing and recommendation. Such ordinal preferences from pairwise comparisons instead of exact fitness evaluations lead the traditional PSO to fail. This paper proposes a particle swarm optimization based on pairwise comparisons. Experiments show that the proposed method enables the traditional PSO to work well by using only ordinal preferences from pairwise comparisons. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Swarm intelligence

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