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On complementary effect of blended behavioral analysis for identity theft detection in mobile social networks 1

引用

13th International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2017

作者： Wang, Cheng Luo, Jing Yang, Bo Jiang, Changjun Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science and Technology Tongji University Shanghai China

ISBN: (数字)9789811088902

ISBN: (纸本)9789811088896

User behavioral analysis is expected to act as a promising technique for identity theft detection in the Internet. The performance of this paradigm extremely depends on a good individual-level user behavioral model. Such a good model for a specific behavior is often hard to obtain due to the insufficiency of data for this behavior. The insufficiency of specific data is mainly led by the prevalent sparsity of users’ collectable behavioral footprints. This work aims to address whether it is feasible to effectively detect identify thefts by jointly using multiple unreliable behavioral models from sparse individual-level records. We focus on this issue in mobile social networks (MSNs) with multiple dimensions of collectable but sparse data of user behavior, i.e., making check-ins, posing tips and forming friendships. Based on these sparse data, we build user spatial distribution model, user post interest model and user social preference model, respectively. Here, as the arguments, we validate that there is indeed a complementary effect in multi-dimensional blended behavioral analysis for identity theft detection in MSNs. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Social networking (online)

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Transport complexity of data dissemination in large-scale online social networks 19

Transport complexity of data dissemination in large-scale on...

引用

2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： Wang, Cheng Zhu, Hangyu Wang, Chaodong Zhao, Qin Zhang, Bo Key Laboratory of Embedded Systems Service Computing Ministry of Education Tongji University Shanghai China East China Branch China Academy of Information and Communications Technology Shanghai China Department of Computer Science Shanghai Normal University Tongji University Shanghai China

ISBN: (纸本)9781450371582

In this paper, we aim to measure the transport difficulty of data dissemination in online social networks (OSNs). We focus on a usual type of interest-driven social sessions in OSNs, called Social-InterestCast, under which users autonomously determine whether to view the content from their followees depending on their interest. We define the fundamental limit of transport load as a new metric, called transport complexity, i.e., the minimally required transport load for an OSN in a given carrier network. We derive the transport complexity for Social-InterestCast sessions in a large-scale OSN in the carrier network with optimal communication architecture. The results can act as the common lower bounds on transport load for Social-InterestCast in any carrier networks. To the best of our knowledge, this is the first work to measure the transport difficulty for data dissemination in OSNs by modeling session patterns with the interest-driven characteristics. © 2019 Association for computing Machinery.

关键词： Social networking (online)

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Joint Transmit Power and Trajectory Optimization for Two-Way Multi-Hop UAV Relaying Networks

Joint Transmit Power and Trajectory Optimization for Two-Way...

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IEEE International Conference on Communications Workshops, ICC

作者： Bing Li Shengjie Zhao Rongqing Zhang Hao Zhang Hanli Wang Liuqing Yang School of Software Engineering Tongji University Shanghai China National Mobile Communications Research Laboratory Southeast University China Ministry of Education Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China School of Electronic and Information Engineer Tongji University Shanghai China Department of Electrical & Computer Engineering Colorado State University CO USA

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

Unmanned aerial vehicle (UAV) has been regarded as a promising means to supplement ground communications. As flying relays, UAVs can be rapidly and flexibly deployed to assist data transmissions in many practical scenarios. In this paper, we investigate a two-way multi-hop UAV relaying network, where there are two ground users as sources and multiple UAVs as relays to help the two ground sources exchange information. We first provide an efficient two-way multi-hop UAV relaying pattern, which can achieve a data rate of 2/4 data packets per time slot with decode-and-forward (DF) protocol. Then, we further formulate a joint transmit power and trajectory optimization problem for the UAVs in this two-way multi-hop relaying scenario. The formulated problem is non-convex which makes it difficult to solve directly, hence we propose an iterative algorithm to obtain an approximate optimal solution. Numerical results demonstrate that our proposed network achieves significant throughput gains.

关键词： Relays Protocols Throughput Trajectory optimization Data communication

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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 ...

引用

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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Random Occlusion Recovery with Noise Channel for Person Re-identification 16th

Random Occlusion Recovery with Noise Channel for Person Re-i...

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16th International Conference on Intelligent computing, ICIC 2020

作者： Zhang, Kun Wu, Di Yuan, Changan Qin, Xiao Wu, Hongjie Zhao, Xingming Zhang, Lijun Du, Yuchuan Wang, Hanli Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Tongji University Shanghai China Guangxi Academy of Science Nanning530025 China School of Computer and Information Engineering Nanning Normal University Nanning530299 China School of Computer Science and Technology Soochow University Suzhou215006 China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China Fudan University Shanghai200433 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai China Collaborative Innovation Center of Intelligent New Energy Vehicle and School of Automotive Studies Tongji University Shanghai201804 China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Department of Transportation Engineering Tongji University Shanghai201804 China Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing and Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

ISBN: (纸本)9783030607982

Person re-identification, as the basic task of a multi-camera surveillance system, plays an important role in a variety of surveillance applications. However, the current mainstream person re-identification model based on deep learning requires a lot of labeled data, which takes a lot of time and manpower. In this study, we proposed a person re-identification method based on random occlusion recovery with noise channel. We add random occlusion blocks to the original image, use the GAN model for repair, and use the repaired image to expand the original training set. After that, the generated image is adjusted through the noise channel. Finally, we use the enhanced data set to train the baseline model. Our model achieves the state-of-the-art on Market-1501 dataset, proving that the method is effective. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Particle swarm optimization based on pairwise comparisons 9th

Particle swarm optimization based on pairwise comparisons

引用

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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Application of SIRUS in credit card fraud detection 1

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7th International Conference on Computational Data and Social Networks, CSoNet 2018

作者： Zhang, Yuwei Liu, Guanjun Luan, Wenjing Yan, Chungang Jiang, Changjun Department of Computer Science and Technology Tongji University Shanghai201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China

ISBN: (数字)9783030046484

ISBN: (纸本)9783030046477

Credit card fraud problem is very common in recent years. It not only causes economic loss to people, but also causes trust crisis to enterprises. Due to the imbalance of data, fraud detection has always been tricky. In our previous work, we proposed a method of dealing with the class imbalance problem based on stacking ensemble learning and inverse random undersampling method (SIRUS). First, the inverse random undersampling method is used to generate multiple data subsets from the original data set. Then we use the stacking ensemble learning method for each data subset to train several different learners (also called first-level learners), and then the results generated by each first-level learner are taken as features to train a meta learner. We apply SIRUS to detect the credit card fraud in this paper. Our dataset comes from a financial company in China. A variety of measurements such as recall, precision, accuracy, F-measure, and G-mean to illustrate the effectiveness of our method in fraud detection. © Springer Nature Switzerland AG 2018.

关键词： Learning systems

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Toward the First SDN Programming Capacity Theorem on Realizing High-Level Programs on Low-Level Datapaths

Toward the First SDN Programming Capacity Theorem on Realizi...

引用

2018 IEEE Conference on Computer Communications, INFOCOM 2018

作者： Leet, Christopher Wang, Xin Richard Yang, Y. Aspnes, James Department of Computer Science Yale University United States Department of Computer Science Tongji University China Key Laboratory of Embedded System and Service Computing Ministry of Education China

ISBN: (纸本)9781538641286

High-Ievel programming and programmable data paths are two key capabilities of software-defined networking (SDN). A fundamental problem linking these two capabilities is whether a given high-level SDN program can be realized onto a given low-level SDN datapath structure. Considering all high-level programs that can be realized onto a given datapath as the programming capacity of the datapath, we refer to this problem as the SDN data path programming capacity problem. In this paper, we conduct the first study on the SDN datapath programming capacity problem, in the general setting of high-level, datapath oblivious, algorithmic SDN programs and state-of-art multi-table SDN data path pipelines. In particular, considering datapath-oblivious SDN programs as computations and datapath pipelines as computation capabilities, we introduce a novel framework called SDN characterization junctions, to map both SDN programs and datapaths into a unifying space, deriving the first rigorous result on SDN datapath programming capacity. We not only prove our results but also conduct realistic evaluations to demonstrate the tightness of our analysis. © 2018 IEEE.

关键词： Computation theory

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On Theoretical Optimization of the Sensing Matrix for Sparse-Dictionary Signal Recovery

On Theoretical Optimization of the Sensing Matrix for Sparse...

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IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Jianchen Zhu Shengjie Zhao Xu Ma Gonzalo R. Arce Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai CHN School of Optics and Photonics Beijing Institute of Technology Beijing CHN Department of Electrical and Computer Engineering University of Delaware Newark Delaware USA

Compressive Sensing (CS) is a new paradigm for the efficient acquisition of signals that have sparse representation in a certain domain. Traditionally, CS has provided numerous methods for signal recovery over an orthonormal basis. However, modern applications have sparked the emergence of related methods for signals not sparse in an orthonormal basis but in some arbitrary, perhaps highly overcomplete, dictionary, particularly due to their potential to generate different kinds of sparse representation of signals. Here, we first propose the Signal space Subspace Pursuit (SSSP) algorithm, and then we derive a low bound on the number of measurements required. The algorithm has low computational complexity and provides high recovery accuracy.

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A Microfluidic Spherical Helix Module Using Liquid Metal and Additive Manufacturing for Drug Delivery Applications

A Microfluidic Spherical Helix Module Using Liquid Metal and...

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Microwave, MTT-S International Symposium

作者： Yangyang Guan Shicong Wang Manos M. Tentzeris Yuanan Liu Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and Telecommunications China Key Laboratory of Embedded System and Service Computing of the Ministry of Education Tongji University China Agile Technologies for High-performance Electromagnetic Novel Applications Georgia Institute of Technology USA

In this paper, a spherical helix module based on 3D printing and microfluidic technologies was fabricated, tested and applied to drug delivery applications. A liquid metal alloy is introduced to enhance the sensitivity of the complex and drug-/liquid-reconfigurable helix topology. Moreover, the influence of the dimensions of the hemisphere inscribed by the helical turns on the resonant frequency of the structure is researched. The microfluidic channels with 1 mm radius are shaped in the form of double semispherical helix using a Form-2 3D printer. To fulfill effectively the liquid metal (LM) injection, movement and recycle for reuse, a syringe pump is integrated to flexibly control the flow of the fluid. Besides, the proof-of-concept prototype achieves excellent radiation gain and impedance matching. The realized sensitivity is 0.96 mL/GHz and 0.33 mL/GHz corresponding with the frequency shift from 2.28 to 2.01 GHz and 2.01 to 1.65 GHz.

关键词： Resonant frequency Monitoring Microfluidics Liquids Drugs Mathematical model Three-dimensional printing

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