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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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Fast mode decision based on optimal stopping theory for multiview video coding

Fast mode decision based on optimal stopping theory for mult...

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19th International Conference on Advances in Multimedia Modeling, MMM 2013

作者： Wang, Hanli Heng, Yue Zhao, Tiesong Xiao, Bo Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada

ISBN: (纸本)9783642357275

Optimal stopping theory is developed to achieve a good trade-off between decision performance and decision efforts such as the consumed decision time. In this paper, the optimal stopping theory is applied to fast mode decision for multiview video coding in order to reduce the tremendous encoding computational complexity, with the benefit of theoretical decision-making expectation and predictable decision performance. The characteristics of encoding modes in multiview video coding are studied to derive an optimal stopping theory-based model to early terminate mode decision and thus a fast mode decision algorithm is designed. Extensive experimental results demonstrate that the proposed algorithm can save a great amount of encoding time for multiview video coding and meanwhile keep the compression performance more or less intact. © Springer-Verlag 2013.

关键词： Decision making

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Asymptotic signal bandwidth of impulse radio UWB communication networks

Asymptotic signal bandwidth of impulse radio UWB communicati...

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54th Annual IEEE Global Telecommunications Conference: "Energizing Global Communications", GLOBECOM 2011

作者： Xu, Juan College of Electronics and Information Engineering Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781424492688

The asymptotic signal bandwidth of various kinds of large-scale asynchronous Time Hopping Impulse Radio Ultra-Wide Band (TH-IR UWB) communication networks such that multiple access interference can be negligible with respect to output noise with high probability is derived. The asynchronous TH-IR UWB communication networks consist of n nodes distributed in a cube (three-dimension) or on a square (two-dimension) according to a Poisson point process. The theoretic results indicate that the obtained asymptotic bandwidth of IR-UWB signal is in proportion to the number of nodes, and that the asymptotic bandwidth of IR-UWB signal of dense network is much more than that of extended network. The results also reveal that the asymptotic bandwidth of three-dimensional network is less than that of two-dimensional network assuming that the number of nodes in the networks and the distance loss exponent are the same. As the bandwidth of IR-UWB signal satisfies the obtained theoretic bandwidth, the expression of probability of error of multi-node network is simplified to that of single node network. © 2011 IEEE.

关键词： Bandwidth

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A fault prediction method based on modified Genetic Algorithm using BP neural network algorithm

A fault prediction method based on modified Genetic Algorith...

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2016 IEEE International Conference on systems, Man, and Cybernetics, SMC 2016

作者： Liu, Qing Feng, Zhang Liu, Min Shen, Weiming School of Electronic and Information Engineering Tongji University Shanghai201804 China Key Laboratory of Embedded System and Service Computing Tongji University Shanghai201804 China

ISBN: (纸本)9781509018970

In order to improve fault forecasting model accuracy of back propagation neural network (BPNN), an improved prediction method of optimized BPNN based on Multilevel Genetic Algorithm (MGA) was proposed. We design new chromosome with multilevel structure, improve the encoding mode, fitness function and genetic operator. Which can optimizes the initial values of weights, thresholds and the structure of BPNN synchronously. Enhancing the ability of nonlinear learning and generalization of BPNN. Case study of continuous casting equipment verified that the proposed model with higher prediction accuracy is better than classical BPNN and GA-BPNN prediction method for fault prediction. © 2016 IEEE.

关键词： Chromosomes

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Deep Learning-based Mortality Prediction of COVID-19 Patients with Cardiovascular Disease 9

Deep Learning-based Mortality Prediction of COVID-19 Patient...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Zheng, Huilin Liang, Yingyi Zhang, Daming Shi, Kai Dong, Luxi Xie, Xiaolan Guilin University of Technology Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin University of Technology College of Computer Science and Engineering Guilin China

ISBN: (纸本)9798350391367

Coronavirus disease 2019 (COVID-19) is one of the most dangerous diseases in recorded human history due to its high contagiousness and rapid dissemination. Moreover, people who already have medical issues like cardiovascular disease (CVD) have a higher risk of getting seriously ill. Therefore, this study proposes a deep learning-based prediction model for the mortality of COVID-19 patients with CVD. The research substances are introduced as follows. First, we obtain the original dataset from the Kaggle website provided by the Mexican government, and extract our experimental data. After that, we develop a deep learning-based prediction model for the mortality of COVID-19 patients with CVD while applying a 5-fold cross-validation approach for the model training and validation. Finally, we evaluate the performance of the proposed model and also compare it with many common machine learning models. In our experimental results, the proposed model achieved higher performance than all of the other models. It facilitates decision-making and provides an accurate mortality prediction for COVID-19 patients with CVD. © 2024 IEEE.

关键词： COVID-19

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Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

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computers, Materials & Continua 2024年第1期78卷 1227-1252页

作者： Yongwang Yuan Xiangwei Liu Ke Lu School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan232001China School of Economics and Management Anhui University of Science and TechnologyHuainan232001China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji UniversityShanghai201804China

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral *** present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process ***,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data ***,the first layer BERT network learns the correlations between different category attribute ***,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted ***,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual ***,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

关键词： Business process prediction monitoring deep learning attention mechanism BERT multi-perspective

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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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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Tu, Hanqian Xiang, Dongming Lin, Wang Liu, Guanjun Zhejiang Sci-Tech University Department of Computer Science and Technology Hangzhou310018 China Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science Shanghai201804 China

ISBN: (纸本)9781665410205

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. © 2024 IEEE.

关键词： Information leakage

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An ultrasound system for tumor detection in soft tissues using low transient pulse

An ultrasound system for tumor detection in soft tissues usi...

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2011 7th IEEE International Conference on Automation Science and Engineering, CASE 2011

作者： Ratnakar, Ashish R. Zhou, MengChu Dept. of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102-1982 United States MoE Key Laboratory of Embedded System and Service Computing Tongji University Shanghai 200092 China

ISBN: (纸本)9781457717307

This work presents a method to detect the size and location of tumor in soft tissues using ultrasound. Quantitative ultrasound is utilized to allow an ultrasound signal to be sent from a transmitter to multiple receivers. This received signal is analyzed for echogenic and echolucent tumors to differentiate between the two along with non-tumor sample and also studied for the delay to determine the size/location of the tumor. The proposed system utilizes Low Transient Pulse (LTP) technique and is implemented using Field Programmable Gate Array (FPGA) and Digital Signal Processor (DSP) technologies. In this co-design architecture, DSP carries out the analysis of received demodulated signal at a lower speed while FPGA runs at a higher one to generate LTP signal and demodulate bandpass ultrasonic signal. This work elaborates the implementation of Quadrature Amplitude Modulation (QAM) receiver on FPGA for the received signal from an ultrasound detector. LTP is applied to the tumor samples through the transmitter and the received signal at an ultrasonic receiver is passed through QAM to obtain different maxima that are then further used to compute the location and the size of the tumor using DSP. This dual platform co-design demonstrates a good application of a FPGA/DSP platform for the LTP generation and received signal processing. © 2011 IEEE.

关键词： Tumors

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Personalized web retrieval based on rough-fuzzy method

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Journal of Computational Information systems 2007年第3期3卷 1067-1074页

作者： Duan, Qiguo Miao, Duoqian Zhang, Hongyun Zheng, Ji Key Laboratory of 'Embedded System and Service Computing' Department of Computer Science and Technology Tongji University Shanghai 201804 China

A novel approach of rough-fuzzy hybridization is proposed for efficient personalized Web retrieval. Variable precision rough set model is used to discover user preference. Fuzzy sets are incorporated to take care of the real-valued weights in each document vector. Discerning keywords are identified to refine a query for more focused representation. To further filter out irrelevant documents for the user, retrieved results are re-ranked according to rough similarity measures. Experiments compared with traditional search engine are presented and experimental results indicate the performance of document retrieval is greatly improved.

关键词： Search engines

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Synchronization of delayed complex-valued networks via aperiodically intermittent pinning control

Synchronization of delayed complex-valued networks via aperi...

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International Conference on Information and Automation (ICIA)

作者： Xiwei Liu Department of Computer Science and Technology The Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781467391054

In this paper, the synchronization problem for linearly coupled complex networks is investigated, which is denoted by ordinary differential equations with complex-values. The coupling topology can be asymmetric, and the time delay also exists in the network model. By pinning some external aperiodically intermittent control on the network nodes, we will prove that under some conditions, the complete synchronization will be finally realized exponentially. Moreover, applying the adaptive technique on the coupling strength, we will also present an adaptive rule, whose validity is rigorously proved. Finally, some numerical simulations will be given to illustrate the correctness of these obtained results.

关键词： Synchronization Delay effects Couplings Adaptation models Mathematical model Complex networks Delays

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