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Advances in Intelligent systems and computing 2013年 212卷 785-792页

作者： Liu, Jian-xin Du, Yu-yue Hong, Yong-fa Sun, Lin-lin College of Information Science Engineering Shandong University of Science and Technology Qingdao 266590 Shandong China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China College of Civil Engineering and Architecture SUST Qingdao 266590 Shandong China

ISBN: (纸本)9783642375019

According to the randomness of the vessel's arrival time and handling time, the establishment of a randomly-oriented environment container berths-crane allocation model, the optimizing goal is to minimize the average ship-waiting time. Taking into account the complexity of the model solution, this paper offers the design of an improved genetic algorithm to reduce the searching space, and according to the characteristics of the optimal solution. With testing example to verify that the model can simulate decision-making environment of berths-crane allocation problem and reflect the decision-maker's attitude toward risks and preferences. The algorithm can gain a stable and satisfactory solution within the operating time. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Genetic algorithms

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Predictive Resilience Assessment of Road Networks Based on Dynamic Multi-Granularity Graph Neural Network

SSRN

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SSRN 2024年

作者： Zang, Di Ding, Yongjie Zhao, Jiayi Tang, Keshuang Zhu, Hong Key Laboratory of Embedded System and Service Computing Ministry of Educaiton Department of Computer Science and Technology Tongji University No. 4800 Cao’an Road Shanghai China Key Laboratory of Road and Traffic Engineering Ministry of Education College of Transportation Engineering Tongji University No. 4800 Cao’an Road Shanghai China

Due to the influence of global climate anomalies, abnormal weather conditions such as heavy rainfall have become more frequent in recent years, posing a significant threat to the operation of transportation systems. An effective assessment of the resilience of the transportation system before and during heavy rain can alert the transportation department to take necessary emergency actions. However, existing methods for assessing the rainfall resilience of transportation networks mostly suffer from the following problems: 1) Simulation methods for modeling rainfall impacts lack realism;2) After-the-fact evaluations of resilience cannot offer advance warning prior to or during a heavy rain event. To address above problems, we present a novel resilience assessment methodology for evaluating the resilience of road networks in real-time during heavy rainfall scenarios. In this methodology, we propose the temporal decomposition-based dynamic multi-granularity graph neural network (TD2MG2NN) for long-term traffic speed forecasting, providing a perspective on the future evolution of traffic states for accurate resilience assessment. In addition, we construct a composite traffic resilience indicator, designed to comprehensively reflect changes in the spatial-temporal resilience of the transportation system during heavy rain. Experimental results on four publicly real datasets indicate that the prediction performance of TD2MG2NN outperforms state-of-the-art models. The assessment results for the transportation road network in California demonstrate that the comprehensive resilience indicator is superior to single functional resilience indicator and the real-time methodology for evaluating resilience can accurately depict and predict the operation of the road network system under heavy rainfall scenarios. © 2024, The Authors. All rights reserved.

关键词： Roads and streets

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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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SelectCast: Scalable Data Aggregation Scheme in Wireless Sensor Networks

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IEEE Transactions on Parallel and Distributed systems 2012年第10期23卷 1958-1969页

作者： Cheng Wang Changjun Jiang Shaojie Tang Xiang-Yang Li Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science and Engineering University of Tongji China Department of Computer Science Illinois Institute of Technology Chicago IL USA Department of Computer Science and Engineering Tsinghua National Laboratory for Information Science and Technology (TNLIST) University of Tongji China

In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density \lambda \in [1,n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called single-hop-length (SHL) scheme and multiple-hop-length (MHL) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MHL scheme, for a practically important set of symmetric functions called divisible perfectly compressible (DPC) functions, including the mean, max, and various kinds of indicator functions, etc., the data from \Theta (n) sensors can be aggregated to the sink at the throughput of a constant order \Theta (1), implying that, our MHL scheme is indeed scalable.

关键词： Throughput Wireless sensor networks Temperature measurement Protocols Lattices Temperature sensors

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Effcient poisoning attacks and defenses for unlabeled data in DDoS prediction of intelligent transportation systems

Security and Safety

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Security and Safety 2022年第1期1卷 145-165页

作者： Zhong Li Xianke Wu Changjun Jiang College of Information Science and Technology Donghua UniversityShanghai 201620China Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer ScienceTongji UniversityShanghai 201804China Shanghai Network Financial Security Collaborative Innovation Center Tongji UniversityShanghai 201804China

Nowadays,large numbers of smart sensors(e.g.,road-side cameras)which com-municate with nearby base stations could launch distributed denial of services(DDoS)attack storms in intelligent transportation *** attacks disable the services provided by base *** in this paper,considering the uneven communication traffic ows and privacy preserving,we give a hidden Markov model-based prediction model by utilizing the multi-step characteristic of DDoS with a federated learning framework to predict whether DDoS attacks will happen on base stations in the ***,in the federated learning,we need to consider the problem of poisoning attacks due to malicious *** poisoning attacks will lead to the intelligent transportation systems paralysis without security *** poisoning attacks mainly apply to the classi cation model with labeled *** this paper,we propose a reinforcement learning-based poisoningmethod speci cally for poisoning the prediction model with unlabeled ***,previous related defense strategies rely on validation datasets with labeled data in the ***,it is unrealistic since the local training datasets are not uploaded to the server due to privacy preserving,and our datasets are also ***,we give a validation dataset-free defense strategy based on Dempster-Shafer(D-S)evidence theory avoiding anomaly aggregation to obtain a robust global model for precise DDoS *** our experiments,we simulate 3000 points in combination with DARPA2000 dataset to carry out *** results indicate that our poisoning method can successfully poison the global prediction model with unlabeled data in a short ***,we compare our proposed defense algorithm with three popularly used defense *** results show that our defense method has a high accuracy rate of excluding poisoners and can obtain a high attack prediction probability.

关键词： Poisoning attacks Defenses Multi-step DDoS prediction Unlabeled data Intel-ligent transportation systems

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Polynomial-time hierarchy of computable reals

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Journal of Computational Information systems 2011年第4期7卷 1108-1115页

作者： Chen, Qingliang Su, Kaile Wu, Lijun Department of Computer Science Jinan University Guangzhou 510632 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of High Confidence Software Technologies Ministry of Education Peking University Beijing China Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia School of Computer Science and Engineering University of Electronic Science and Technology Chengdu 610054 China

In mathematics, various representations of real numbers have been investigated and all these representations are proved to be mathematically equivalent. Furthermore, it is known that all effective versions of these representations lead to the same class of "computable real numbers". However, when subrecursive (such as primitive recursive) is taken into account, these representations can lead to different notions of "computable real numbers". This paper will look into the polynomial-time version of the problem for computable real numbers under different representations. We will summarize the known results to exhibit the comprehensive hierarchy they form. Our goal is to clarify systematically how the polynomial-time computability depends on the representations of the real numbers. Copyright © 2011 Binary Information Press.

关键词： Polynomial approximation

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Information Security Evaluation by Information Flow Analysis Based on Stochastic Petri Nets

Information Security Evaluation by Information Flow Analysis...

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IEEE International Conference on systems, Man and Cybernetics

作者： Hanqian Tu Dongming Xiang Wang Lin Guanjun Liu Department of Computer Science and Technology Zhejiang Sci-Tech University Hangzhou China Department of Computer Science Key laboratory of Embedded System and Service Computing Ministry of Education Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University Shanghai China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The Petri-net-based information flow analysis offers an effective approach for detecting information leakage by the concept of non-interference. Although the related studies propose efficient solutions, they lack quantitative evaluation on information leakage. In this paper, we propose a novel method for quantitative evaluation of information security based on stochastic labeled Petri nets (SLPNs) and information flow analysis. Specifically, we introduce four different levels of security metrics, and provide a methodology for evaluating the information security. Furthermore, a case study is presented to show the feasibility of our method.

关键词： Measurement Petri nets Semantics Stochastic processes Information leakage Explosions Complexity theory Cybernetics Business

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A recent survey on controllable text generation: A causal perspective

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Fundamental Research 2024年

作者： Wang, Junli Zhang, Chenyang Zhang, Dongyu Tong, Haibo Yan, Chungang Jiang, Changjun Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education Shanghai 201804 China National (Province-Ministry Joint) Collaborative Innovation Center for Financial Network Security Tongji University Shanghai 201804 China

As an important subject of natural language generation, Controllable Text Generation (CTG) focuses on integrating additional constraints and controls while generating texts and has attracted a lot of attention. Existing controllable text generation approaches mainly capture the statistical association implied within training texts, but generated texts lack causality consideration. This paper intends to review recent CTG approaches from a causal perspective. Firstly, according to previous research on basic types of CTG models, it is discovered that their essence is to obtain the association, and then four kinds of challenges caused by absence of causality are introduced. Next, this paper reviews the improvements to address these challenges from four aspects, namely representation disentanglement, causal inference, knowledge enhancement and multi-aspect CTG respectively. Additionally, this paper inspects existing evaluations of CTG, especially evaluations for causality of CTG. Finally, this review discusses some future research directions for the causality improvement of CTG and makes a conclusion. © 2024

关键词： Causal inference Causality Controllable text generation Knowledge enhancement Representation disentanglement

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A distributed SVM ensemble for image classification and annotation

A distributed SVM ensemble for image classification and anno...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Nasullah Khalid Alham Maozhen Li Yang Liu Mahesh Ponraj Man Qi School of Engineering and Design Brunel University Uxbridge UK The Key Laboratory of Embedded Systems and Service Computing Ministry of Education University of Tongji China Department of Computing Canterbury Christ Church University Canterbury Kent UK

Combination of classifiers leads to a substantial reduction of classification errors in a wide range of applications. Among them SVM ensembles with bagging have shown better performance in classification than a single SVM. However, the training process of SVM ensembles is notably computationally intensive especially when the number of replicated training datasets is large. This paper presents MRESVM, a MapReduce based distributed SVM ensemble algorithm for image annotation which re-samples the training dataset based on bootstrapping and trains SVM on each dataset in parallel using a cluster of computers. MRESVM is evaluated in a experimental environment and the results show that the MRESVM algorithm reduces the training time significantly while achieves high level of accuracy in classifications.

关键词： Support vector machines Training Bagging Classification algorithms Accuracy Algorithm design and analysis Clustering algorithms

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Robust Adaptive Control of Nonlinear systems with Asymmetric Non-smooth Saturation

Robust Adaptive Control of Nonlinear Systems with Asymmetric...

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第28届中国控制与决策会议

作者： Xuehai Tu Junfeng Lai Kai Zhao Institute of Smart System and Renewable Energy School of AutomationChongqing University The Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing Universit

ISBN: (纸本)9781467397155

In this paper,the robust adaptive control is proposed for a class of parametric uncertain nonhnear system with asymmetric non-smooth input *** introducing a well-defined smooth function,a robust adaptive control algorithms are developed to deal with the problem of asymmetric non-smooth *** most of the existing control schemes for the uncertain nonhnear system,which requires an assumption that the control gain is an unknown constant,the developed controller only needs that the control gain is a bounded and unknown time-varying *** this work,the robust adaptive controller can guarantee global uniform boundedness of the closed-loop system signals as rigorously proved by Lyapunov analysis.A simulation results is presented to illustrate the effectiveness of the proposed adaptive control technique.

关键词： Robust Adaptive Control Asymmetric Non-Smooth Saturation Uniformly Bounded

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