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Using stereo vision to construct 3-D surface models

IEEE Potentials 2012年第2期31卷 31-37页

作者： Xu, Weifeng Deng, Lin Zheng, Qing Frezza, Stephen Keystone Software Development Institute United States Department of Software Engineering Gannon University Erie PA United States George Mason University United States Electrical and Computer Engineering Department Gannon University United States

Surface model reconstruction from stereo vision is appealing to the rehabilitation industry, including the rehabilitation treatment equipment manufacturers. This article presents a systematic approach for constructing editable three-dimensional (3-D) surface models from stereo cameras and employ this approach to develop a commercializable system for automatically building custom-contoured seats. © 2006 IEEE.

关键词： Stereo vision

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Assessing Diagnosis Approaches for Wireless Sensor Networks:Concepts and Analysis

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Journal of Computer Science & Technology 2014年第5期29卷 887-900页

作者：李瑞刘克彬李向阳何源惠维王志赵季中万猛 Institute of Software Engineering Xidian University School of Electronic and Information Engineering Xi’an Jiaotong University School of Software Tsinghua University Tsinghua National Laboratory for Information Science and Technology Tsinghua University Department of Computer Science Illinois Institute of Technology Chicago IL 60616 U.S.A. Center for Science and Technology Development Ministry of Education

Diagnosis is of great importance to wireless sensor networks due to the nature of error prone sensor nodes and unreliable wireless links. The state-of-the-art diagnostic tools focus on certain types of faults, and their performances are highly correlated with the networks they work with. The network administrators feel difficult in measuring the effectiveness of their diagnosis approaches and choosing appropriate tools so as to meet the reliability demand. In this work, we introduce the D-vector to characterize the property of a diagnosis approach. The D-vector has five dimensions, namely the degree of coupling, the granularity, the overhead, the tool reliability and the network reliability, quantifying and evaluating the effectiveness of current diagnostic tools in certain applications. We employ a skyline query algorithm to find out the most effective diagnosis approaches, i.e., skyline points（SPs）, from five dimensions of all potential D-vectors. The selected skyline D-vector points can further guide the design of various diagnosis approaches. In our trace-driven simulations, we design and select tailored diagnostic tools for GreenOrbs, achieving high performance with relatively low overhead.

关键词： diagnosis approach analysis and measurement wireless sensor network

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A probabilistic framework of preference discovery from folksonomy corpus

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Frontiers of Computer Science 2017年第6期11卷 1075-1084页

作者： Xiaohui GUO Chunming HU Richong ZHANG Jinpeng HUAI State Key Lab of Software Development Environment Beihang University Beijing 100191 China Institute of Advanced Computing Technology School of Computer Science and Engineering Beihang University Beijing 100191 China

The increasing availability of folksonomy data makes them vital for user profiling approaches to precisely detect user preferences and better understand user interests, so as to render some personalized recommendation or re- trieval results. This paper presents a rigorous probabilis- tic framework to discover user preference from folkson- omy data. Furthermore, we incorporate three models into the framework with the corresponding inference methods, expectation-maximization or Gibbs sampling algorithms. The user preference is expressed through topical conditional distributions. Moreover, to demonstrate the versatility of our framework, a recommendation method is introduced to show the possible usage of our framework and evaluate the applica- bility of the engaged models. The experimental results show that, with the help of the proposed framework, the user pref- erence can be effectively discovered.

关键词： preference discovery tagging folksonomy so-cial annotation

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Verification of initialization sequences for sequential circuits by using dependency matrixes 6

Verification of initialization sequences for sequential circ...

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6th International Conference on Electrical and Control Technologies, ECT 2011

作者： Morkunas, Kęstutis Šeinauskas, Rimantas Software Engineering Department Information Technology Development Institute Kaunas University of Technology Lithuania

ISBN: (纸本)9781634398008

This article suggests and approach to verification of initializing sequences for sequential circuits. Binary method might be considered as providing optimistic results, as ternary - pessimistic ones. This article also explains the difference between these two methods, the differences in results and why this is happening. Using ternary approach might prove useful if validation results for both methods differ greatly. Binary method appears to be more accurate at finding initializing sequences, because of reduction to states space after each of input patterns is used. This is not the case when using ternary logic testing under Verilog. To improve overall reliability of experiment results, dependency matrixes are introduced and used to gain valuable knowledge about the circuit working conditions.

关键词： Sequential circuits

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Research on Quality Model and Measurement for Microservices 3

Research on Quality Model and Measurement for Microservices

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3rd International Workshop on Experience with SQuaRE Series and Its Future Direction, IWESQ 2021

作者： Yu, Jinchuan Ge, Jianxin Sun, Jixin Software Engineering Institute Shanghai Key Laboratory of Computer Software Testing & Evaluation Shanghai Development Center of Computer Software Technology Shanghai China

In recent years, microservice architecture (MSA) has become popular. Emerging from the agile community, MSA implies a number of small, independently deployable microservices. They are characterized by low coupling, high cohesion, low complexity, and are more flexible and convenient in application, saving resource ***, there is limited research on quality models for MSA. Although MSA is a special form of service-oriented architecture, there are still some differences between the two that are hard to ignore, such as decentralization, smaller service size and encouraging technical heterogeneity. Therefore, it is difficult to directly apply the traditional quality model research of service-oriented architecture to MSA. Based on the above considerations, this paper proposes a quality model for MSA, which reflects the quality characteristics of microservices through 16 measures for each of the Functional Suitability, Flexibility, Interactivity, Performance Efficiency, Reliability and Security. At the same time, to address the shortage of theoretical validation of current research, this paper uses static analysis and dynamic analysis to validate the proposed measures and prove the rationality of its theory. © 2021 for this paper by its authors

关键词： Static analysis

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Survey on Testing of Autonomous Driving Systems 3

Survey on Testing of Autonomous Driving Systems

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3rd International Workshop on Experience with SQuaRE Series and Its Future Direction, IWESQ 2021

作者： Chen, Wenjie Ma, Zeyu Wang, Chao Chen, Mingang Cai, Lizhi Software Engineering Institute Shanghai Key Laboratory of Computer Software Testing & Evaluation Shanghai Development Center of Computer Software Technology Shanghai China

Before autonomous driving vehicles are commercialized, they need to undergo a series of rigorous tests. This paper first proposes the general process of autonomous driving system testing, and then summarizes the research progress of autonomous driving vehicle testing from the model, simulation, network, and vehicle levels, and analyzes the characteristics of various testing technologies. Finally, this paper gives suggestions on the development of autonomous driving testing technology. © 2021 for this paper by its authors

关键词： Autonomous vehicles

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H2-MARL: Multi-Agent Reinforcement Learning for Pareto Optimality in Hospital Capacity Strain and Human Mobility during Epidemic

arXiv

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arXiv 2025年

作者： Luo, Xueting Deng, Hao Yang, Jihong Shen, Yao Guo, Huanhuan Sun, Zhiyuan Liu, Mingqing Wei, Jiming Zhao, Shengjie School of Computer Science and Technology Tongji University Shanghai201804 China China Land Surveying and Planning Institute Beijing100035 China College of Architecture and Urban Planning Tongji University Shanghai200092 China Chongqing Institute of Planning and Natural Resources Investigation and Monitoring Chongqing401121 China Li-Fi Research and Development Centre University of Cambridge CambridgeCB3 0FA United Kingdom Guangdong Urban-rural Planning and Design Research Institute Technology Group Co. Ltd. Guangzhou510290 China Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of Education Shanghai201804 China

The necessity of achieving an effective balance between minimizing the losses associated with restricting human mobility and ensuring hospital capacity has gained significant attention in the aftermath of COVID-19. Reinforcement learning (RL)-based strategies for human mobility management have recently advanced in addressing the dynamic evolution of cities and epidemics;however, they still face challenges in achieving coordinated control at the township level and adapting to cities of varying scales. To address the above issues, we propose a multi-agent RL approach that achieves Pareto optimality in managing hospital capacity and human mobility (H2-MARL), applicable across cities of different scales. We first develop a township-level infection model with online-updatable parameters to simulate disease transmission and construct a city-wide dynamic spatiotemporal epidemic simulator. On this basis, H2-MARL is designed to treat each division as an agent, with a trade-off dual-objective reward function formulated and an experience replay buffer enriched with expert knowledge built. To evaluate the effectiveness of the model, we construct a township-level human mobility dataset containing over one billion records from four representative cities of varying scales. Extensive experiments demonstrate that H2-MARL has the optimal dual-objective trade-off capability, which can minimize hospital capacity strain while minimizing human mobility restriction loss. Meanwhile, the applicability of the proposed model to epidemic control in cities of varying scales is verified, which showcases its feasibility and versatility in practical applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

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A Secure Mutual Authentication Protocol Based on Visual Cryptography Technique for IoT-Cloud

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Chinese Journal of Electronics 2024年第1期33卷 43-57页

作者： Brou Bernard Ehui Chen CHEN Shirui WANG Hua GUO Jianwei LIU School of Cyber Sciences and Technology Beihang University State Key Laboratory of Software Development Environment Beihang University Sino-French Engineering School Beihang University Beihang Hangzhou Innovation Institute Yuhang

Because of the increasing number of threats in the IoT cloud, an advanced security mechanism is needed to guard data against hacking or attacks. A user authentication mechanism is also required to authenticate the user accessing the cloud services. The conventional cryptographic algorithms used to provide security mechanisms in cloud networks are often vulnerable to various cyber-attacks and inefficient against new attacks. Therefore,developing new solutions based on different mechanisms from traditional cryptography methods is required to protect data and users' privacy from attacks. Different from the conventional cryptography method, we suggest a secure mutual authentication protocol based on the visual cryptography technique in this paper. We use visual cryptography to encrypt and decrypt the secret images. The mutual authentication is based on two secret images and *** user requests the ticket from the authentication server(AS) to obtain the permission for accessing the cloud services. Three shared secret keys are used for encrypting and decrypting the authentication process. We analyze the protocol using the Barrows-Abadi-Needham(BAN)-logic method and the results show that the protocol is robust and can protect the user against various attacks. Also, it can provide a secure mutual authentication mechanism.

关键词： Internet of things Visual cryptography Security Mutual authentication IoT-cloud

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Weight-based sparse coding for multi-shot person re-identification

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Science China(Information Sciences) 2015年第10期58卷 38-52页

作者： ZHENG YanWei SHENG Hao ZHANG BeiChen ZHANG Jun XIONG Zhang State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang University Shenzhen Key Laboratory of Data Vitalization Research Institute in ShenzhenBeihang University Department of Electrical Engineering and Computer Science University of Wisconsin-Milwaukee

Person re-identification(Re-ID) is the problem of matching a person from different cameras based on appearance. It has interesting algorithm challenges and extensive practical applications. This paper presents a weight-based sparse coding approach for person re-identification. First, three hypotheses are introduced to achieve a linear combination of images based on sparse coding. Then, we convert the person re-identification problem into an optimization problem with sparse constraints. To reduce the influence of abnormal residuals caused by occlusion and body variation, a weight-based sparse coding approach is proposed to achieve the optimal weights by the ordering statistics of square residuals iteratively. Experiments on various public datasets for different multi-shot modalities have shown good performance of the proposed approach compared with other state-of-the-art ones(more than 42% and 34% at rank-1 on CAVIAR4 REID and i-LIDS, respectively).

关键词： smart city person re-identification video surveillance multi-shot weight-based sparse coding

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Application of sparse S transform network with knowledge distillation in seismic attenuation delineation

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Petroleum Science 2024年第4期21卷 2345-2355页

作者： Nai-Hao Liu Yu-Xin Zhang Yang Yang Rong-Chang Liu Jing-Huai Gao Nan Zhang School of Information and Communications Engineering Xi'an Jiaotong UniversityXi'an710049ShaanxiChina School of Software Engineering Xi'an Jiaotong UniversityXi'an710049ShaanxiChina PetroChina Research Institute of Petroleum Exploration and Development(RIPED) CNPCBeijing100083China Research Institute of Exploration and Development Yumen Oilfield CompanyCNPCJiuquan735019GansuChina

Time-frequency analysis is a successfully used tool for analyzing the local features of seismic ***,it suffers from several inevitable limitations,such as the restricted time-frequency resolution,the difficulty in selecting parameters,and the low computational *** by deep learning,we suggest a deep learning-based workflow for seismic time-frequency *** sparse S transform network(SSTNet)is first built to map the relationship between synthetic traces and sparse S transform spectra,which can be easily pre-trained by using synthetic traces and training ***,we introduce knowledge distillation(KD)based transfer learning to re-train SSTNet by using a field data set without training labels,which is named the sparse S transform network with knowledge distillation(KD-SSTNet).In this way,we can effectively calculate the sparse time-frequency spectra of field data and avoid the use of field training *** test the availability of the suggested KD-SSTNet,we apply it to field data to estimate seismic attenuation for reservoir characterization and make detailed comparisons with the traditional time-frequency analysis methods.

关键词： S transform Deep learning Knowledge distillation Transfer learning Seismic attenuation delineation

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