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Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images

Computers, Materials & Continua 2024年第7期80卷 139-161页

作者： Roseline Oluwaseun Ogundokun Joseph Bamidele Awotunde Hakeem Babalola Akande Cheng-Chi Lee Agbotiname Lucky Imoize Department of Multimedia Engineering Kaunas University of TechnologyKaunas44249Lithuania Department of Computer Science Landmark UniversityOmu Aran251103Nigeria Department of Computer Science Faculty of Information and Communication SciencesUniversity of IlorinIlorin240003Nigeria Department of Telecommunication Science University of IlorinIlorin230003Nigeria Department of Library and information Science Fu Jen Catholic UniversityNew Taipei City24205TaiwanChina Department of Computer Science and information Engineering Fintech and Blockchain Research CenterAsia UniversityTaichung City41354TaiwanChina Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and information Technology Institute of Digital CommunicationRuhr UniversityBochum44801Germany

Mobile technology is developing *** phone technologies have been integrated into the healthcare industry to help medical ***,computer vision models focus on image detection and classification ***2 is a computer vision model that performs well on mobile devices,but it requires cloud services to process biometric image information and provide predictions to *** leads to increased *** biometrics image datasets on mobile devices will make the prediction faster,but mobiles are resource-restricted devices in terms of storage,power,and computational ***,a model that is small in size,efficient,and has good prediction quality for biometrics image classification problems is *** pre-trained CNN(PCNN)MobileNetV2 architecture combined with a Support Vector Machine(SVM)compacts the model representation and reduces the computational cost and memory *** proposed novel approach combines quantized pre-trained CNN(PCNN)MobileNetV2 architecture with a Support Vector Machine(SVM)to represent models efficiently with low computational cost and *** contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches,showing the superiority of deep features from MobileNetV2 and SVM classification models,comparing traditional methods,exploring six ocular diseases and normal classification with 20,111 images postdata augmentation,and reducing the number of trainable *** model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration(AMD),one of the most common eye illnesses,Cataract,Diabetes,Glaucoma,Hypertension,andMyopia with one class *** the experiment outcomes,it is observed that the suggested MobileNetV2-SVM model size is *** testing accuracy for MobileNetV2-SVM,InceptionV3,and MobileNetV2 is 90.11%,86.88%,a

关键词： Retinal images ocular disorder deep transfer learning disease identification mobile device

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A survey on semantic communications:technologies,solutions,applications and challenges

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digital communications and Networks 2024年第3期10卷 528-545页

作者： Yating Liu Xiaojie Wang Zhaolong Ning MengChu Zhou Lei Guo Behrouz Jedari School of communication and information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Baotou Vocational&Technical College Baotou 014035China School of information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102USA Nokia Finland

Semantic communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity *** the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for *** this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are ***,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are *** of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are ***,some challenges and future research directions are presented to provide guidance for further research of SC.

关键词： Semantic communication Semantic coding Semantic extraction Semantic communication framework Semantic communication applications

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QoE oriented intelligent online learning evaluation technology in B5G scenario

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digital communications and Networks 2024年第1期10卷 7-15页

作者： Mingzi Chen Xin Wei Peizhong Xie Zhe Zhang School of communications and information Engineering Nanjing University of Posts and TelecommunicationsNanjing210003China Key Lab of Broadband Wireless communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing210003China institute of Higher Education Nanjing University of Posts and TelecommunicationsNanjing210003China

Students'demand for online learning has exploded during the post-COvID-19 pandemic ***,due to their poor learning experience,students'dropout rate and learning performance of online learning are not always *** technical advantages of Beyond Fifth Generation(B5G)can guarantee a good multimedia Quality of Experience(QoE).As a special case of multimedia services,online learning takes into account both the usability of the service and the cognitive development of the *** that affect the Quality of Online Learning Experience(OL-QoE)become more *** get over this dilemma,we propose a systematic scheme by integrating big data,Machine Learning(ML)technologies,and educational psychology ***,we first formulate a general definition of OL-QoE by data analysis and experimental *** formula considers both the subjective and objective factors(i.e.,video watching ratio and test scores)that most affect ***,we induce an extended layer to the classic Broad Learning System(BLS)to construct an Extended Broad Learning System(EBLS)for the students'OL-QoE *** the extended layer can increase the width of the BLS model and reduce the redundant nodes of BLS,the proposed EBLS can achieve a trade-off between the prediction accuracy and computation ***,we provide a series of early intervention suggestions for different types of students according to their predicted OL-QoE *** timely interventions,their OL-QoE and learning performance can be *** results verify the effectiveness oftheproposed scheme.

关键词： B5G Online learning Quality of experience

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Blockchain Meets Generative Behavior Steganography:A Novel Covert communication Framework for Secure IoT Edge Computing

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Chinese Journal of Electronics 2024年第4期33卷 886-898页

作者： Yuanlong CAO Junjie LI Kailin CHAO Jianmao XIAO Gang LEI School of Computer information Engineering Jiangxi Normal University Jiangxi Blockchain Data Security and Governance Engineering research Center Jiangxi Normal University School of Software Jiangxi Normal University

The rapid development of Internet of things(Io T) and edge computing technologies has brought forth numerous possibilities for the intelligent and digital future. The frequent communication and interaction between devices inevitably generate a large amount of sensitive information. Deploying a blockchain network to store sensitive data is crucial for ensuring privacy and security. The openness and synchronicity of blockchain networks give rise to challenges such as transaction privacy and storage capacity issues, significantly impeding their development in the context of edge computing and Io T. This paper proposes a reliable fog computing service solution based on a blockchain fog architecture. This paper stores data files in the inter planetary file system(IPFS) and encrypts the file hash values used for retrieving data files with stream cipher encryption. It employs a steganographic transmission technique leveraging Alpha Zero's Gomoku algorithm to discretely transmit the stream cipher key across the blockchain network without a carrier, thus achieving dual encryption. This approach aims to mitigate the storage burden on the blockchain network while ensuring the security of transaction data. Experimental results demonstrate that the model enhances the transmission capacity of confidential information from kilobytes(KB) to megabytes(MB) and exhibits high levels of covert and security features.

关键词： Steganography Ciphers Privacy Data privacy Blockchains Encryption Internet of Things

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UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 430-445页

作者： Jiawen Kang Junlong Chen Minrui Xu Zehui Xiong Yutao Jiao Luchao Han Dusit Niyato Yongju Tong Shengli Xie IEEE School of Automation Guangdong University of TechnologyGuangzhou 510006China 111 Center for Intelligent Batch Manufacturing based on IoT Technology Guangzhou 510006China Key Laboratory of Intelligent information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Pillar of information Systems Technology and Design Singapore University of Technology and DesignSingaporeSingapore College of communication Engineering Army Engineering University of PLANanjing 210007China National Natural Science Foundation of China Beijing 100085China Key Laboratory of Intelligent Detection and IoT in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong Key Laboratory of IoT information Technology Guangzhou 510006China

Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach

关键词： Avatar blockchain metaverses multi-agent deep reinforcement learning transformer UAVs

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Key technologies for wireless network digital twin towards smart railways

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High-Speed Railway 2024年第1期2卷 1-10页

作者： Ke Guan Xinghai Guo Danping He Philipp Svoboda Marion Berbineau Stephen Wang Bo Ai Zhangdui Zhong Markus Rupp State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China School of Electronic and information Engineering Beijing Jiaotong UniversityBeijing 100044China Christian Doppler Laboratory for digital Twin Assisted AI for Sustainable Radio Access Networks Institute of TelecommunicationsTU WienVienna 1040Austria UniversitéGustave Eiffel COSYSLEOSTVilleneuve d′Ascq 59650France VIAVI Marconi Labs VIAVI SolutionsStevenage SG12ANUK institute of Telecommunications TU WienVienna 1040Austria

An emerging railway technology called smart railway promises to deliver higher transportation efficiency,enhanced comfort in services,and greater *** smart railway is expected to integrate fifth-generation mobile communication(5G),Artificial Intelligence(AI),and other technologies,which poses new problems in the construction,operation and maintenance of railway wireless *** digital Twins(DTs),which have recently emerged as a new paradigm for the design of wireless networks,can address these problems and enable the whole lifecycle management of railway wireless ***,there are still many scientific issues and challenges for railway-oriented wireless *** key technologies to solve these problems are introduced and described,including characterization of materials'physical-EM properties,autonomous reconstruction of Three-dimensional(3D)environment model,AI-empowered environmental cognition,Ray-Tracing(RT),model-based and AIbased RT acceleration,and generation of multi-spectra sensing ***,this paper presents our research results for each key technology and describes the wireless network planning and optimization system based on highperformance RT developed by our *** paper outlines the framework for realizing the wireless DT of smart railways,providing the direction for future research.

关键词： digital twin Smart railways Ray tracing Channel characterization

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Security Analysis in Smart Agriculture: Insights from a Cyber-Physical System Application

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Computers, Materials & Continua 2024年第6期79卷 4781-4803页

作者： Ahmed Redha Mahlous College of Computer and information Sciences Prince Sultan UniversityRiyadh11586Saudia Arabia

Smart agriculture modifies traditional farming practices,and offers innovative approaches to boost production and sustainability by leveraging contemporary *** today’s world where technology is everything,these technologies are utilized to streamline regular tasks and procedures in agriculture,one of the largest and most significant industries in every *** research paper stands out from existing literature on smart agriculture security by providing a comprehensive analysis and examination of security issues within smart agriculture *** into three main sections-security analysis,system architecture and design and risk assessment of Cyber-Physical Systems(CPS)applications-the study delves into various elements crucial for smart farming,such as data sources,infrastructure components,communication protocols,and the roles of different stakeholders such as farmers,agricultural scientists and researchers,technology providers,government agencies,consumers and many *** contrast to earlier research,this work analyzes the resilience of smart agriculture systems using approaches such as threat modeling,penetration testing,and vulnerability *** discoveries highlight the concerns connected to unsecured communication protocols,possible threats from malevolent actors,and vulnerabilities in IoT ***,the study suggests enhancements for CPS applications,such as strong access controls,intrusion detection systems,and encryption *** addition,risk assessment techniques are applied to prioritize mitigation tactics and detect potential hazards,addressing issues like data breaches,system outages,and automated farming process *** research sets itself apart even more by presenting a prototype CPS application that makes use of a digital temperature *** application was first created using a Tinkercad simulator and then using actual hardware with Arduino *** CPS application’s defenses against p

关键词： Smart agriculture cyber-physical system IoT security temperature sensor threats vulnerabilities

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Hyper 360—Towards a Unified Tool Set Supporting Next Generation VR Film and TV Productions

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Journal of Software Engineering and Applications 2019年第5期12卷 127-148页

作者： Barnabas Takacs Zsuzsanna Vincze Hannes Fassold Antonis Karakottas Nikolaos Zioulis Dimitrios Zarpalas Petros Daras Drukka Kft/PanoCAST BudapestHungary joanneum research digital—institute for information and communication technologies GrazAustria Centre for research&Technology Hellas(CERTH)—information technologies institute(ITI) ThessalonikiGreece

We describe four fundamental challenges that complex real-life Virtual Reality (VR) productions are facing today (such as multi-camera management, quality control, automatic annotation with cinematography and 360˚?depth estimation) and describe an integrated solution, called Hyper 360, to address them. We demonstrate our solution and its evaluation in the context of practical productions and present related results.

关键词： Deep Learning Tensor Flow YoloV3 360°Video Virtual Reality Free Viewpoint Video Quality Control Automatic Cinematography Multi-Camera Systems

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Defensive deception framework against reconnaissance attacks in the cloud with deep reinforcement learning

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Science China(information Sciences) 2022年第7期65卷 67-85页

作者： Huanruo LI Yunfei GUO Shumin HUO Hongchao HU Penghao SUN Department of Computer Science Information Engineering University Department of communication technologies Academy of Military Science

Implementing defensive deception in the cloud is promising to proactively counter reconnaissance attack. This technique presents decoys to camouflage cloud assets and distracts attack resource. However,the major challenge is to develop an effective deception strategy to orchestrate digital decoys. To address this issue, we propose a deep reinforcement learning(DRL)-based defensive deception framework. First,we formulate a utility function, which mathematically models underlying threats associated with common vulnerabilities among virtual machines in the cloud. Then, we customize training interfaces and the neural networks for a DRL agent. The reward function reflects the effectiveness of asset concealment and the waste of attack resources, referring to a comprehensive defense goal. Finally, the well-trained DRL agent generates the optimal defense strategy. It specifies a more granular deception strategy than existing proposals. Simulation results show that the proposed framework leads to a 7.87% average advantage in realizing the comprehensive defense goal. Moreover, it can stably improve the concealment degree of cloud assets up to 20.58%, and increase the attack cost up to 40.40%. This study shows that it is promising to improve cloud security with deception defense and artificial intelligence techniques.

关键词： cyber deception defense Cyber Deception Defense artificial intelligence Artificial Intelligence Cloud Security cloud security Reconnaissance Attack reconnaissance attack Deep Reinforcement Learning deep reinforcement learning deception strategy Deception Strategy

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Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China

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Journal of Forestry research 2016年第6期27卷 1407-1410页

作者： Chengbo Wang Yanyou Qiao Honggan Wu Yuanfei Chang Muyao Shi institute of Remote Sensing and digital Earth Chinese Academy of Sciences research institute of Forest Resource information Techniques Chinese Academy of Forestry

Recent advances in information and communication technologies, such as mobile Internet and smart- phones, have created new paradigms for participatory environment monitoring. The ubiquitous mobile phones with capabilities such as a global positioning system, camera, and network access, offer opportunities to estab- lish distributed monitoring networks that can perform a wide range of measurements for a landscape. This study examined the potential of mobile phone-based community monitoring of fall webworm （Hyphantria cunea Drury）. We built a prototype of a participatory fall webworm monitoring System based on mobile devices that stream- lined data collection, transmission, and visualization. We also assessed the accuracy and reliability of the data collected by the local community. The system performance was evaluated at the Ziya commune of Tianjin municipality in northern China, where fall webworm infestation has occurred. The local community provided data with accuracy comparable to expert measurements （Willmott＇s index of agreement 〉0.85）. Measurements by the local community effectively complemented remote sensing images in both temporal and spatial resolution.

关键词： Forest pest monitoring Mobile phone Community monitoring Hyphantria cunea Drury Field survey

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