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A new cloud-based method for composition of healthcare services using deep reinforcement learning and Kalman filtering

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computers in Biology and Medicine 2024年 172卷 108152-108152页

作者： Zhong, Chongzhou Darbandi, Mehdi Nassr, Mohammad Latifian, Ahmad Hosseinzadeh, Mehdi Jafari Navimipour, Nima School of Public Health & Management Wenzhou Medical University Zhejiang Wenzhou325035 China Pôle Universitaire Léonard de Vinci Paris France Communication Technology Engineering Department Tartous University Syria Department of Mathematics and Natural Sciences Gulf University for Science and Technology Mishref Campus Kuwait Department of Management Faculty of Economics and Administrative Sciences Ferdowsi University of Mashhad Iran Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Computer Engineering Faculty of Engineering and Natural Sciences Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Douliou Yunlin64002 Taiwan

Healthcare has significantly contributed to the well-being of individuals around the globe;nevertheless, further benefits could be derived from a more streamlined healthcare system without incurring additional costs. Recently, the main attributes of cloud computing, such as on-demand service, high scalability, and virtualization, have brought many benefits across many areas, especially in medical services. It is considered an important element in healthcare services, enhancing the performance and efficacy of the services. The current state of the healthcare industry requires the supply of healthcare products and services, increasing its viability for everyone involved. Developing new approaches for discovering and selecting healthcare services in the cloud has become more critical due to the rising popularity of these kinds of services. As a result of the diverse array of healthcare services, service composition enables the execution of intricate operations by integrating multiple services' functionalities into a single procedure. However, many methods in this field encounter several issues, such as high energy consumption, cost, and response time. This article introduces a novel layered method for selecting and evaluating healthcare services to find optimal service selection and composition solutions based on Deep Reinforcement Learning (Deep RL), Kalman filtering, and repeated training, addressing the aforementioned issues. The results revealed that the proposed method has achieved acceptable results in terms of availability, reliability, energy consumption, and response time when compared to other methods. © 2024 Elsevier Ltd

关键词： Cloud computing

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Multi-modal Multi-kernel Graph Learning for Autism Prediction and Biomarker Discovery

arXiv

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arXiv 2023年

作者： Liu, Jin Mao, Junbin Lin, Hanhe Kuang, Hulin Pan, Shirui Wu, Xusheng Xie, Shan Liu, Fei Pan, Yi Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of software Xinjiang University Wulumuqi830000 China Hunan Province Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China School of Science and Engineering University of Dundee DundeeDD1 4HN United Kingdom School of Information and Communication Technology Griffith University Gold CoastQLD4215 Australia Shenzhen Health Development Research and Data Management Center Shenzhen518109 China

Graph learning-based multi-modal integration and classification is one of the most challenging tasks for disease prediction. To effectively offset the negative impact among modalities in the process of multi-modal integration and heterogeneous information extractions from graphs, we propose a novel method called Multi-modal Multi-Kernel Graph Learning (MMKGL). To solve the problem of negative impact among modalities, we propose a multi-modal graph embedding module to construct a multi-modal graph. Different from conventional methods that manually construct static graphs for all modalities, each modality generates a separate graph by adaptive learning, where a function graph and a supervision graph are introduced for optimization during the multi-graph fusion embedding process. We then propose a multi-kernel graph learning module to extract heterogeneous information from the multi-modal graph. The information in the multi-modal graph at different levels is aggregated by convolutional kernels with different receptive field sizes, followed by generating a cross-kernel discovery tensor for disease prediction. Our method is evaluated on the benchmark Autism Brain Imaging Data Exchange (ABIDE) dataset and outperforms the state-of-the-art methods. In addition, discriminative brain regions associated with autism are identified by our model, providing guidance for the study of autism pathology. The source code will be available at https://***/yutian0315/MMKGL. © 2023, CC BY-NC-ND.

关键词： Graph embeddings

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Design and Fabrication of a Low-Loss Microstrip Lowpass-Bandpass Diplexer for WiMAX Applications

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China communications 2020年第6期17卷 109-120页

作者： Leila Nouri Salah Yahya Abbas Rezaei Institute of Research and Development Duy Tan UniversityDa Nang 550000Vietnam Faculty of Electrical–Electronic Engineering Duy Tan UniversityDa Nang 550000Vietnam Department of Communication and Computer Engineering Cihan University-ErbilErbilKurdistan RegionIraq Department of Software Engineering Faculty of EngineeringKoya UniversityKoya KOY45Kurdistan RegionIraq Department of Electrical Engineering Kermanshah University of TechnologyKermanshahIran

This work presents a compact lowpass-bandpass microstrip diplexer with a novel *** consists of a lowpass filter integrated with a bandpass filter via a simple compact *** proposed bandpass filter consists of four rectangular patch cells and some thin *** step impedance structures,with a radial cell,are applied to achieve a lowpass frequency *** lowpass channel of the introduced diplexer has 2.64 GHz cut-off frequency,whereas,the bandpass channel center frequency is 3.73 GHz for WiMAX applications and covers the frequencies3.31 GHz to 4 *** addition to having novel structures,both filters have other advantages in terms of high return loss,low insertion loss and high *** presented microstrip diplexer has the compact size of 29 mm×13.8 mm×0.762 mm,calculated at 2.64 *** obtained insertion losses are 0.20 dB(for the first channel)and 0.25 dB(for the second channel),which make the proposed diplexer suitable for energy *** stopband properties of both bandpass and lowpass filters are improved by creating several transmission *** comparison results show that the lowest insertion losses,the minimum gap between channels,good return losses,and good isolation are obtained.

关键词： compact diplexer lowpass-bandpass low-loss microstrip selectivity

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

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International Conference on Smart communications and Networking (SmartNets)

作者： Jessé Da Costa Rocha Marcela Alves de Souza Evelin Helena Silva Cardoso Nandamudi Vijaykumar Jasmine Priscyla Leite de Araújo Renato Lisboa Francês Graduate Program in Electrical Engineering Institute of Technology Federal University of Pará (UFPA) Belém Pará Brazil Information and Communication Technology Center Federal University of the South and Southeast of Para (Unifesspa) Marabá Pará Brazil Department of Computer Science Federal Rural University of the Amazon (UFRA) Capitão Poço Pará Brazil Coordination of Applied Research and Technological Development National Institute for Space Research (INPE) São Paulo Brazil

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics.

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Spiral-Phased Laguerre-Gaussian Modes Generation in SWDM over Few Mode Fiber based on Electrical Equalization 2

Spiral-Phased Laguerre-Gaussian Modes Generation in SWDM ove...

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2nd Joint International Conference on Emerging Computing Technology and Sports, JICETS 2019

作者： Ghazi, Alaan Fareed, Alaa Masunda, Tendai Aljunid, S.A. Idrus, Syed Zulkarnain Syed Amphawan, Angela Al-Dawoodi, Aras Rashidi, C.B.M. Fadhel, Ibrahim Eskandar Ibrahim School of Human Development and Techno-communication Universiti Malaysia Perlis Malaysia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Computer Technical Engineering Alkitab University Iraq School of Computing Universiti Utara Malaysia Malaysia Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA United States Computer Science Department College of Computer Science and Information Technology Kirkuk University Iraq Department of Computer and Information Systems National Institute of Administrative Science Yemen

Space division multiplexing, in conjunction with wavelength division multiplexing, is a powerful mechanism that increases spatial channels significantly in a single optical fiber. Spiral Phased-Laguerre-Gaussian (SP-LG) modes indicate that they effectively reduce mode coupling, thereby increasing the channel response and performance positively. However, mode-coupling influence optical fiber system leads to inter-symbol interference (ISI) between the channels and reduces both capacity and distance. In this paper, we apply the SP-LG modes in a space wavelength division multiplexing over a few-mode fiber system. The results demonstrate significant improvements in reducing channels effects and ISI. The performance evaluations are based on the bit-error-rate (BER), eye diagram and spectrum analyzer. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Spectrum analyzers

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Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

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computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP DDoS attack

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Metaverse for Industry 5.0 in NextG communications: Potential Applications and Future Challenges

arXiv

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arXiv 2023年

作者： Prabadevi, B. Deepa, N. Victor, Nancy Gadekallu, Thippa Reddy Maddikunta, Praveen Kumar Reddy Yenduri, Gokul Wang, Wei Pham, Quoc Viet Huynh-The, Thien Liyanage, Madhusanka The School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India The Department of Computer Science School of Engineering and Technology Pondicherry University Karaikal Campus Puducherry Union Territory Karaikal609605 India The Zhongda Group Haiyan County Zhejiang Province Jiaxing City314312 China The Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon The College of Information Science and Engineering Jiaxing University Jiaxing314001 China The Division of Research and development Lovely Professional University Phagwara India The School of Medical Technology Beijing Institute of Technology Beijing China Department of Engineering Shenzhen MSU-BIT University Shenzhen China The School of Computer Science and Statistics Trinity College Dublin The University of Dublin DublinD02PN40 Ireland Department of Computer and Communication Engineering Ho Chi Minh City University of Technology and Education Viet Nam The School of Computer Science UCD Ireland

With the advent of new technologies and endeavors for automation in almost all day-to-day activities, the recent discussions on the metaverse life have a greater expectation. Furthermore, we are in the era of the fifth industrial revolution, where machines and humans collaborate to maximize productivity with the effective utilization of human intelligence and other resources. Hence, Industry 5.0 in the metaverse may have tremendous technological integration for a more immersive experience and enhanced *** technological amalgamations are suitable for the present environment and entirely different from the previous perception of virtual technologies. This work presents a comprehensive review of the applications of the metaverse in Industry 5.0 (so-called industrial metaverse). In particular, we first provide a preliminary to the metaverse and industry 5.0 and discuss key enabling technologies of the industrial metaverse, including virtual and augmented reality, 3D modeling, artificial intelligence, edge computing, digital twin, blockchain, and 6G communication networks. This work then explores diverse metaverse applications in Industry 5.0 vertical domains like Society 5.0, agriculture, supply chain management, healthcare, education, and transportation. A number of research projects are presented to showcase the conceptualization and implementation of the industrial metaverse. Furthermore, various challenges in realizing the industrial metaverse, feasible solutions, and future directions for further research have been presented. © 2023, CC BY.

关键词： Virtual reality

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Analysis of the different locomotive wireless multi-traction synchronous control systems for heavy-haul combined trains and their performance

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Transportation Safety and Environment 2020年第3期2卷 202-215页

作者： Wei Li Chunyang Chen Hui Li KaiWang Liang Xie Wenlu Zhang School of Traffic&Transportation Engineering Central South UniversityChangsha 410075HunanChina Signal&Communication Research Institute China Academy of Railway SciencesBeijing 100081China School of Computer Science and Engineering Central South UniversityChangsha 410075HunanChina Shuohuang Railway Development Co. Ltd.Suning 062350HebeiChina

This paper looks at the heavy-haul combined train composed of different types of locomotives and its distributed power control system with a combination of 800 MHz and TD-LTE wireless *** analyses some key characteristic parameters that affect the synchronism and communication of the differential wireless multi-traction synchronous control systems for heavy-haul combined *** the same time,in order to reduce the latency of instruction and information transfer between different types of locomotives,improve the time-limit certainty of wireless transmission and optimize the control quality of multi-traction control systems for heavy-haul combined trains,a synchronism optimization strategy based on the Markov decision process on the basis of Petri networkconstruction is *** experiments and tests are carried out to verify the effectiveness of the synchronism optimization of the control system,which provides a guarantee for improving the differential wireless multi-traction synchronous control system for combined trains and optimizing train control.

关键词： heavy-haul train mixed-traction locomotive wireless multi-traction control locomotive synchronism running Markov decision process

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Intelligent Multi-Modal Sensing-communication Integration: Synesthesia of Machines

arXiv

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arXiv 2023年

作者： Cheng, Xiang Zhang, Haotian Zhang, Jianan Gao, Shijian Li, Sijiang Huang, Ziwei Bai, Lu Yang, Zonghui Zheng, Xinhu Yang, Liuqing The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China The Samsung Semiconductor Samsung SoC Research and Development Lab San DiegoCA92121 United States Shandong University Jinan250100 China Guangzhou510000 China Guangzhou510000 China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

In the era of sixth-generation (6G) wireless communications, integrated sensing and communications (ISAC) is recognized as a promising solution to upgrade the physical system by endowing wireless communications with sensing capability. Existing ISAC is mainly oriented to static scenarios with radio-frequency (RF) sensors being the primary participants, thus lacking a comprehensive environment feature characterization and facing a severe performance bottleneck in dynamic environments. To date, extensive surveys on ISAC have been conducted but are limited to summarizing RF-based radar sensing. Currently, some research efforts have been devoted to exploring multi-modal sensing-communication integration but still lack a comprehensive review. To fill the gap, we embark on an initial endeavor with the goal of establishing a unified framework of intelligent multi-modal sensing-communication integration by generalizing the concept of ISAC and providing a comprehensive review under this framework. Inspired by the human synesthesia, the so-termed Synesthesia of Machines (SoM) gives the clearest cognition of such an intelligent integration and details its paradigm for the first time. We commence by justifying the necessity and potential of the new paradigm. Subsequently, we offer a rigorous definition of SoM and zoom into the detailed paradigm, which is summarized as three operational modes realizing the integration. To facilitate SoM research, we overview the prerequisite of SoM research, that is, mixed multi-modal (MMM) datasets, and introduce our work. Built upon the MMM datasets, we introduce the mapping relationships between multi-modal sensing and communications, and discuss how channel modeling can be customized to support the exploration of such relationships. Afterward, aiming at giving a comprehensive survey on the current research status of multi-modal sensing-communication integration, we cover the technological review on SoM-enhance-based and SoM-concert-based app

关键词： Beamforming

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Deep Learning in Medical Imaging and Drug Design

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Journal of Human Physiology 2020年第2期2卷 32-37页

作者： Surayya Ado Bala Shri Ojha Kant Adamu Garba Department of Computer Science and Engineering Sharda UniversityIndia Research and Technology Development Center Sharda UniversityIndia School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang212013China

Over the last decade,deep learning(DL)methods have been extremely successful and widely used in almost every *** are now focusing on the convergence of medical imaging and drug design using deep learning to revolutionize medical diagnostic and improvement in the monitoring from response to *** a new machine learning paradigm that focuses on learning with deep hierarchical models of *** imaging has transformed healthcare science,it was thought of as a diagnostic tool for disease,but now it is also used in drug *** in medical imaging technology have enabled scientists to detect events at the cellular *** role of medical imaging in drug design includes identification of likely responders,detection,diagnosis,evaluation,therapy monitoring,and follow-up.A qualitative medical image is transformed into a quantitative biomarker or surrogate endpoint useful in drug design *** this,a parameter needs to be identified that characterizes the disease baseline and its subsequent response to *** result is a quantifiable improvement in healthcare quality in most therapeutic areas,resulting in improvements in quality and life *** paper provides an overview of recent studies on applying the deep learning method in medical imaging and drug *** briefly discuss the fields related to the history of deep learning,medical imaging,and drug design.

关键词： Deep learning Medical imaging Drugs design Cheminformatics

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