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Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

Computers, Materials & Continua 2020年第1期62卷 123-136页

作者： Weijin Jiang Yang Wang Yirong Jiang Yuhui Xu Jiahui Chen Lina Tan Guo Liang Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Hunan University of Technology and BusinessChangsha410205China Institute of Big Data and Internet Innovation Hunan University of Technology and BusinessChangsha410205China School of Computer Science and Technology Wuhan University of TechnologyWuhan430073China Tonghua Normal University Tonghua134002China School of Bioinformatics University of MinnesotaTwin CitiesUSA

In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the *** at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is *** on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is *** isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the *** algorithm simulation and verification were carried out to prove its feasibility and effectiveness.

关键词： Cloud computing mobile agent system subjective trust objective trust dynamic trust management mobile Internet

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Adaptive Curriculum Learning for Semi-supervised Segmentation of 3D CT-Scans 28th

Adaptive Curriculum Learning for Semi-supervised Segmentati...

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28th International Conference on Neural Information Processing, ICONIP 2021

作者： Nartey, Obed Tettey Yang, Guowu Agyapong, Dorothy Araba Yakoba Wu, JinZhao Sarpong, Asare K. Frempong, Lady Nadia Big Data Research Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China The School of Computer Science and Electronic Information Guangxi University Nanning530004 China Biomedical Engineering Program Kwame Nkrumah University of Science and Technology Kumasi Ghana School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Medicine Department of Radiology and Imaging Sciences Emory University 1364 Clitton Rd. AtlantaGA30322 United States

ISBN: (纸本)9783030921842

Semi-supervised learning algorithms make use of both labelled training data and unlabelled data. However, the visual domain gap between these sets poses a challenge which prevents deep learning models from obtaining the results they have achieved most especially in the field of medical imaging. Recently, self-training with deep learning has become a powerful approach to leverage labelled training and unlabelled data. However, a challenge of generating noisy pseudo-labels and placing over-confident labelling belief on incorrect classes leads to deviation from the solution. To solve this challenge, the study investigates a curriculum-styled approach for deep semi-supervised segmentation which relaxes and treats pseudo-labels as continuous hidden variables by developing an adaptive pseudo-label generation strategy to jointly optimized the pseudo-label generation and selection process. A regularization scheme is further proposed to smoothen the probability outputs and sharpen the less represented pseudo-label regions. The proposed method was evaluated on three publicly available Computer Tomography (CT) scan benchmarks and extensive experiments on all modules have demonstrated the efficacy of the proposed method. © 2021, Springer Nature Switzerland AG.

关键词： Curricula

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Digital earth:yesterday,today,and tomorrow

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International Journal of Digital Earth 2023年第1期16卷 1022-1072页

作者： Alessandro Annoni Stefano Nativi ArzuÇöltekin Cheryl Desha Eugene Eremchenko Caroline M.Gevaert Gregory Giuliani Min Chen Luis Perez-Mora Joseph Strobl Stephanie Tumampos International Society for Digital Earth BeijingPeople’s Republic of China National Research Council RomeItaly University of Applied Sciences and Arts Northwestern Switzerland FHNW School of EngineeringInstitute of Interactive Technologies IITBrugg-WindischSwitzerland Nathan Campus Griffith UniversityCities Research InstituteBrisbaneAustralia Lomonosov Moscow State University MoscowRussia Department of Earth Observation Science University of TwenteTwenteThe Netherland Institute for Environmental Sciences/enviroSPACE University of GenevaGenevaSwitzerland Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjingPeople’s Republic of China Cities Research Institute Nathan CampusGriffith UniversityBrisbaneAustralia Department of Geoinformatics University of SalzburgSalzburgAustria Chair of Remote Sensing Technology Technical University of MunichMunichGermany Big Geospatial Data Management Technical University of MunichMunichGermany

The concept of Digital Earth(DE)was formalized by Al Gore in *** that time the technologies needed for its implementation were in an embryonic stage and the concept was quite *** then digital technologies have progressed significantly and their speed and pervasiveness have generated and are still causing the digital transformation of our *** creates new opportunities and challenges for the realization of DE.‘What is DE today?’,‘What could DE be in the future?’,and‘What is needed to make DE a reality?’.To answer these questions it is necessary to examine DE considering all the technological,scientific,social,and economic aspects,but also bearing in mind the principles that inspired its *** understanding the lessons learned from the past,it becomes possible to identify the remaining scientific and technological challenges,and the actions needed to achieve the ultimate goal of a‘Digital Earth for all’.This article reviews the evolution of the DE vision and its multiple definitions,illustrates what has been achieved so far,explains the impact of digital transformation,illustrates the new vision,and concludes with possible future scenarios and recommended actions to facilitate full DE implementation.

关键词： Digital Earth digital transformation sustainable development data governance and ethic citizen empowerment and industry engagement

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Deep learning-based multi-task prediction of response to neoadjuvant chemotherapy using multiscale whole slide images in breast cancer:A multicenter study

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Chinese Journal of Cancer Research 2025年第1期37卷 28-47页

作者： Qin Wang Feng Zhao Haicheng Zhang Tongpeng Chu Qi Wang Xipeng Pan Yuqian Chen Heng Zhou Tiantian Zheng Ziyin Li Fan Lin Haizhu Xie Heng Ma Lan Liu Lina Zhang Qin Li Weiwei Wang Yi Dai Ruijun Tang Jigang Wang Ping Yang Ning Mao School of Information and Electronic Engineering Shandong Technology and Business UniversityYantai 264005China Big Data and Artificial Intelligence Laboratory Yantai Yuhuangding Hospital of Qingdao UniversityYantai 264000China Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women’s Diseases Yantai Yuhuangding HospitalYantai 264000China Department of Radiology Yantai Yuhuangding Hospital of Qingdao UniversityYantai 264000China School of Computer Science and Technology Shandong Technology and Business UniversityYantai 264005China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin 541004China School of Medical Imaging Binzhou Medical UniversityYantai 264003China Department of Radiology Jiangxi Cancer Hospitalthe Second Affiliated Hospital of Nanchang Medical CollegeNanchang 330006China Department of Radiology the First Affiliated Hospital of China Medical UniversityShenyang 400042China Department of Radiology Weifang Hospital of Traditional Chinese MedicineWeifang 262600China Department of Medical Imaging Affiliated Hospital of Jining Medical UniversityJining 272029China Department of Radiology the Peking University Shenzhen HospitalShenzhen 518036China Department of Pathology Guilin Traditional Chinese Medicine HospitalGuilin 541002China Department of Pathology the Affiliated Hospital of Qingdao UniversityQingdao 266555China Department of Pathology Yantai Yuhuangding Hospital of Qingdao UniversityYantai 264000China

Objective:Early predicting response before neoadjuvant chemotherapy(NAC)is crucial for personalized treatment plans for locally advanced breast cancer *** aim to develop a multi-task model using multiscale whole slide images(WSIs)features to predict the response to breast cancer NAC more ***:This work collected 1,670 whole slide images for training and validation sets,internal testing sets,external testing sets,and prospective testing sets of the weakly-supervised deep learning-based multi-task model(DLMM)in predicting treatment response and pCR to *** approach models two-by-two feature interactions across scales by employing concatenate fusion of single-scale feature representations,and controls the expressiveness of each representation via a gating-based attention ***:In the retrospective analysis,DLMM exhibited excellent predictive performance for the prediction of treatment response,with area under the receiver operating characteristic curves(AUCs)of 0.869[95%confidence interval(95%CI):0.806−0.933]in the internal testing set and 0.841(95%CI:0.814−0.867)in the external testing *** the pCR prediction task,DLMM reached AUCs of 0.865(95%CI:0.763−0.964)in the internal testing and 0.821(95%CI:0.763−0.878)in the pooled external testing *** the prospective testing study,DLMM also demonstrated favorable predictive performance,with AUCs of 0.829(95%CI:0.754−0.903)and 0.821(95%CI:0.692−0.949)in treatment response and pCR prediction,*** significantly outperformed the baseline models in all testing sets(P<0.05).Heatmaps were employed to interpret the decision-making basis of the ***,it was discovered that high DLMM scores were associated with immune-related pathways and cells in the microenvironment during biological basis ***:The DLMM represents a valuable tool that aids clinicians in selecting personalized treatment strategies for breast cancer patients.

关键词： Artificial intelligence breast cancer digital pathology whole slide images

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High-spatial-resolution light field 3D perception based on unidirectional object motion

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Optics letters 2025年第11期50卷 3672-3675页

作者： Dongyang Wang Zhijun Zhang Jianpang Zhai Yan Kang Qingyang Wu College of Applied Sciences Shenzhen University Shenzhen 518060 China Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen 518060 China College of Big Data and Internet Shenzhen Technology University Shenzhen 518060 China MSI (Shenzhen) Technology Co. Ltd. Anbo Technology Park 2 2 Baolong 4th Road Shenzhen 518060 China College of New Materials and New Energies Shenzhen Technology University Shenzhen 518060 China College of Health Science and Environmental Engineering Shenzhen Technology University Shenzhen 518060 China

Light field cameras can capture comprehensive light information within a scene. Their core architecture incorporates a micro-lens array (MLA) positioned in front of the imaging sensor, mimicking the compound eye structure of insects. By processing the acquired data, these cameras enable the reconstruction of 3D spatial information. Despite their numerous advantages, light field cameras suffer from a critical drawback: low spatial resolution. To address this limitation, this study proposes a high-spatial-resolution light field imaging approach based on unidirectional object motion (UOMLF). A non-focused light field camera equipped with a hexagonally arranged MLA was developed as the foundation for a unidirectional object motion platform. Additionally, a 3D reconstruction algorithm tailored to high-resolution light field imaging was designed to complement this system. Experimental evaluations were conducted using the USAF resolution test chart and detector chip leads. Results demonstrate that the proposed method significantly enhances xy-plane resolution (approximately four times improvement) while maintaining -axis resolution. This high-spatial-resolution light field technique based on unidirectional object motion offers broad potential for applications in both industrial and scientific fields.

关键词： Imaging systems Optical imaging Plenoptic imaging Spatial resolution Systems design Three dimensional reconstruction

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Study of PSO Optimized BP Neural Network and Smith Predictor for MOCVD Temperature Control in 7nm 5G Chip Process 6th

Study of PSO Optimized BP Neural Network and Smith Predictor...

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6th International Conference on Advanced Intelligent Systems and Informatics, AISI 2020

作者： Chang, Kuo-Chi Zhou, Yu-Wen Wang, Hsiao-Chuan Lin, Yuh-Chung Chu, Kai-Chun Hsu, Tsui-Lien Pan, Jeng-Shyang School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan Department of Business Management Fujian University of Technology Fuzhou China Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Computer Science and Engineering Shandong University of Science and Technology Shandong China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9783030586683

The key industries of information technology in the semiconductor integrated circuit industry will have an important role after 2020, In the third generation of advanced semiconductor of 7nm 5G chips GaN is be used, MOCVD is a key technology for preparing high-quality communication semiconductor crystals. This study proposes PID controller of PSO and BP neural network algorithm to improve the control ability of MOCVD temperature. From the research results, it is found that the method proposed in this study adopts the PSO and BP neural network intelligent PID algorithm controller with Smith predictor, which has better dynamic performance, and the value from 150 to 500s is stable from 0 to 1 no vibration, any overshoot and short adjustment time, ideal control. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Controllers

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Unsupervised video summarization with a convolutional attentive adversarial network

arXiv

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arXiv 2021年

作者： Liang, Guoqiang Lv, Yanbing Li, Shucheng Zhang, Shizhou Zhang, Yanning National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi'an China

With the explosive growth of video data, video summarization, which attempts to seek the minimum subset of frames while still conveying the main story, has become one of the hottest topics. Nowadays, substantial achievements have been made by supervised learning techniques, especially after the emergence of deep learning. However, it is extremely expensive and difficult to collect human annotation for large-scale video datasets. To address this problem, we propose a convolutional attentive adversarial network (CAAN), whose key idea is to build a deep summarizer in an unsupervised way. Upon the generative adversarial network, our overall framework consists of a generator and a discriminator. The former predicts importance scores for all frames of a video while the latter tries to distinguish the score-weighted frame features from original frame features. Specifically, the generator employs a fully convolutional sequence network to extract global representation of a video, and an attention-based network to output normalized importance scores. To learn the parameters, our objective function is composed of three loss functions, which can guide the frame-level importance score prediction collaboratively. To validate this proposed method, we have conducted extensive experiments on two public benchmarks SumMe and TVSum. The results show the superiority of our proposed method against other state-of-the-art unsupervised approaches. Our method even outperforms some published supervised approaches. Copyright © 2021, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A benchmark for gait recognition under occlusion collected by multi-kinect SDAS

arXiv

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arXiv 2021年

作者： Li, Na Zhao, Xinbo National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University China

Human gait is one of important biometric characteristics for human identification at a distance. In practice, occlusion usually occurs and seriously affects accuracy of gait recognition. However, there is no available database to support in-depth research of this problem, and state-of-arts gait recognition methods have not paid enough attention to it, thus this paper focuses on gait recognition under occlusion. We collect a new gait recognition database called OG RGB+D database, which breaks through the limitation of other gait databases and includes multimodal gait data of various occlusions (self-occlusion, active occlusion, and passive occlusion) by our multiple synchronous Azure Kinect DK sensors data acquisition system (multi-Kinect SDAS) that can be also applied in security situations. Because Azure Kinect DK can simultaneously collect multimodal data to support different types of gait recognition algorithms, especially enables us to effectively obtain camera-centric multi-person 3D poses, and multi-view is better to deal with occlusion than single-view. In particular, the OG RGB+D database provides accurate silhouettes and the optimized human 3D joints data (OJ) by fusing data collected by multi-Kinects which are more accurate in human pose representation under occlusion. We also use the OJ data to train an advanced 3D multi-person pose estimation model to improve its accuracy of pose estimation under occlusion for universality. Besides, as human pose is less sensitive to occlusion than human appearance, we propose a novel gait recognition method SkeletonGait based on human dual skeleton model using a framework of siamese spatio-temporal graph convolutional networks (siamese ST-GCN). The evaluation results demonstrate that SkeletonGait has competitive performance compared with state-of-art gait recognition methods on OG RGB+D database and popular CAISA-B database. This database will be available at https://***/cvNXE/*** Codes 68T

关键词： Gait analysis

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The Adaptive Fault-tolerant Routing Based on an Improved Local Security Information Model of the Exchanged Hypercube

The Adaptive Fault-tolerant Routing Based on an Improved Loc...

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IEEE International Conference on big data and Cloud Computing (BdCloud)

作者： Yazhi Zhang Chuanwen Luo Guijuan Wang Li Zhang Mengjie Lv Jiguo Yu School of Computer Science and Technology Qilu University of Technology Jinan China School of Information Science and Technology Beijing Forestry University Beijing China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China College of Computer Nanjing University of Posts and Telecommunications Nanjing China Big Data Research Institute Qilu University of Technology (Shandong Academy of Sciences) Jinan China

With the increasing amount of computation in high-performance computing, the scale of interconnection networks is becoming larger and larger. It is inevitable that processors or links in the network become faulty. Therefore, it is very important for a processor to understand the security status of itself and neighbors, and then adaptively and reliably communicate. However, the existing security information models consider faulty processors or faulty links separately, and do not consider the situation where both processors and links fail simultaneously. The Exchanged Hypercube is an excellent interconnection network structure which achieves a balance between network functionality and hardware overhead while preserving many excellent properties of the Hypercube. In this paper, we propose an adaptive fault-tolerant routing algorithm of the Exchanged Hypercube based on an improved local security information model, which considers the faulty processors and faulty links simultaneously. This algorithm always can select suitable processors for routing based on the local security information and unsafe coefficients of processors, which greatly reduces the impact of the faulty of networks. The adaptive fault-tolerant routing algorithm of the Exchanged Hypercube network is not only suitable for regular networks but also for heterogeneous networks since the Exchanged Hypercube is a semi regular network. Sufficient experimental results show that the algorithm proposed in this paper has a lower packet loss rate, a higher success rate, and a shorter average path length.

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A Probability-Based All-Zero Block Early Termination Algorithm for QSHVC

A Probability-Based All-Zero Block Early Termination Algorit...

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IEEE International Conference on Image Processing

作者： Dayong Wang Xin Lu Frederic Dufaux Qianmin Wang Weisheng Li Bo Hang Ce Zhu Chongqing Key Laboratory on Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications School of Computer Science and Informatics De Montfort University CNRS CentraleSupélec Laboratoire des Signaux et systèmes Université Paris-Saclay School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Computer School Hubei University of Arts and Science School of Information and Communication Engineering University of Electronic Science and Technology of China

To seamlessly adapt to time-varying network bandwidths, Quality Scalable High-Efficiency Video Coding (QSHVC) is developed. However, its coding process is overwhelmingly complex, and this seriously limits its wide applications in realtime environments. Therefore, it is of great significance to study fast coding algorithms for QSHVC. In this paper, we propose a novel probability-based All-Zero Block (AZB) early termination algorithm for QSHVC. We observe that the generated residual coefficients follow the Laplace distribution if a CU is accurately predicted. Based on this observation, we derive the sum of squared differences-based AZB decision condition. Second, the probability of each coding mode and coding depth being chosen as the best ones are combined with AZBs to derive the probability-based early termination condition. The experimental results show that the proposed algorithm can improve the average coding speed by 74.95% with a 0.26% increase in BDBR.

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