检索结果-内蒙古大学图书馆

Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images

computers, Materials & Continua 2022年第11期73卷 4193-4210页

作者： Nagwan Abdel Samee El-Sayed M.El-Kenawy Ghada Atteia Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Noha E.El-Attar Tarek Gaber Adam Slowik Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura 35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura 35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityEgypt School of Science Engineeringand EnvironmentUniversity of SalfordUK Faculty of Computers and Informatics Suez Canal UniversityIsmailia41522Egypt Koszalin University of Technology Poland Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

As corona virus disease(COVID-19)is still an ongoing global outbreak,countries around the world continue to take precautions and measures to control the spread of the *** of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals,a rapid,reliable,and automatic detection of COVID-19 is in extreme need to curb the number of *** analyzing the COVID-19 chest X-ray images,a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm *** lung region was segmented from the original chest X-ray images and augmented using various transformation ***,the augmented images were fed into the VGG19 deep network for feature *** the other hand,a feature selection method is proposed to select the most significant features that can boost the classification ***,the selected features were input into an optimized neural network for *** neural network is optimized using the proposed hybrid *** experimental results showed that the proposed method achieved 99.88%accuracy,outperforming the existing COVID-19 detection *** addition,a deep statistical analysis is performed to study the performance and stability of the proposed *** results confirm the effectiveness and superiority of the proposed approach.

关键词： Covid-19 feature selection dipper throated optimization particle swarm optimization deep learning

来源：评论

学校读者我要写书评

暂无评论

Integrating a Digital Twin Concept in the Zero Emission Sea Transporter (ZEST) Project for Sustainable Maritime Transport Using Stonefish Simulator

Integrating a Digital Twin Concept in the Zero Emission Sea ...

引用

OCEANS

作者： Michele Grimaldi Carlo Cernicchiaro George Rossides Angelos Ktoris Elias Yfantis Ioannis Kyriakides Computer Vision and Robotics Institute University of Girona Girona Spain School of Engineering & Physical Sciences Heriot-Watt University Marine Robotics Innovation Centre Cyprus Marine and Maritime Institute Larnaca Cyprus Computational Cognition Lab Open University of Cyprus Nicosia Cyprus Marine & Offshore Science Technology & Engineering Centre Cyprus Marine and Maritime Institute Larnaca Cyprus Department of Engineering University of Nicosia Nicosia Cyprus Marine Technology Division Cyprus Marine and Maritime Institute Larnaca Cyprus

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

In response to stringent emission reduction targets imposed by the International Maritime Organization (IMO) and the European Green Deal's Fit for 55 legislation package, the maritime industry has shifted its focus towards decarbonization. While significant attention has been placed on vessels exceeding 5,000 gross tons (GT), emissions from coastal and short sea shipping, amounting to approximately 13% of global shipping transportation and 15% within the European Union (EU), have not received adequate consideration. This abstract introduces the Zero Emission Sea Transporter (ZEST) project, designed to address this issue by developing a zero-emissions multi-purpose catamaran for short sea routes, shown in Figure 1.

关键词： Visualization Scalability Europe Sea measurements Seaports Low carbon economy Digital twins

来源：评论

学校读者我要写书评

暂无评论

Multiple Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Multiple Redundant Weighted Clustered Scheme with Dynamic We...

引用

IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Grace Khayat Constandinos X Mavromoustakis Jordi Mongay Batalla Andreas Pitsillides Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Warsaw University of Technology Warsaw Poland Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor)

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay.

关键词： Measurement Conferences Computational modeling Redundancy Clustering algorithms Autonomous aerial vehicles Routing Routing protocols Delays Vehicle dynamics

来源：评论

学校读者我要写书评

暂无评论

Hybrid-RIS Empowered UAV-Aided ISAC Systems 100

Hybrid-RIS Empowered UAV-Aided ISAC Systems

引用

100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Saikia, Prajwalita Jee, Anand Singh, Keshav Tsiftsis, Theodoros A. Boulogeorgos, Alexandros-Apostolos A. National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi110016 India University of Thessaly Department of Informatics & Telecommunications Lamia35100 Greece University of Western Macedonia Department of Electrical and Computer Engineering Kozani50131 Greece

ISBN: (纸本)9798331517786

In this paper, we consider a novel hybrid reconfigurable intelligent surface (HRIS) consisting of active as well as passive reflecting elements mounted on unmanned aerial vehicle (UAV). The aim is to improve air-to-ground communication by assisting multiple users, while detecting several moving targets. We formulate an optimization model that account for statistical channel estimation errors (SCEEs) to concurrently fine-tune both active and passive phase-shift matrices, UAV trajectory and transmit beamformer for integrated sensing and communication (ISAC), while aiming to maximize the overall achievable sum-rate. Subsequently, we introduce an alternating optimization algorithm that employs a repetitive method to address the combinatorial nonconvex optimization problem and ultimately yielding a solution that is nearly optimal. Using Monte Carlo simulations, we showcase the superiority of the suggested approach in comparison to baseline schemes. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Optimized Price Prediction of Cryptocurrencies using Deep Learning on High-Volume Time Series Data

Optimized Price Prediction of Cryptocurrencies using Deep Le...

引用

International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Gerasimos Vonitsanos Andreas Kanavos Foteini Grivokostopoulou Spyros Sioutas Computer Engineering and Informatics Department University of Patras Patras Greece Department of Informatics Ionian University Corfu Greece Computer Technology Institute and Press “Diophantus“ Patras Greece

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

Statistical models, enhanced by deep learning techniques, have become pivotal in various predictive tasks, including financial forecasting. This paper addresses the challenge of predicting cryptocurrency prices, utilizing a dataset comprising various cryptocurrencies treated as time series. We employ several deep neural network architectures-including Multilayer Perceptrons (MLP), Recurrent Neural Networks (RNN), Long Short-Term Memory networks (LSTM), and Bidirectional LSTM networks-to forecast future prices. Our methodology involves a detailed analysis of cryptocurrency time series to inform the design of these networks. The performance of each model is rigorously compared, highlighting their predictive capabilities in the context of cryptocurrency markets. This study not only contributes to the empirical literature by applying advanced neural networks to high-volume financial data but also provides a comparative analysis that may guide future applications of deep learning in economic forecasting.

关键词： Deep learning Biological system modeling Time series analysis Predictive models Multilayer perceptrons Economic forecasting Big Data applications Cryptocurrency Context modeling

来源：评论

学校读者我要写书评

暂无评论

Voice signal analysis techniques for cognitive decline (stress) assessment

Voice signal analysis techniques for cognitive decline (stre...

引用

International Conference on engineering Systems 2020, ICES 2020

作者： Loizou, C.P. Christodoulides, P. Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Faculty of Engineering and Technology Cyprus University of Technology Limassol Cyprus

Speech signals may provide important information for measuring and modelling human behaviour, especially for assessing mental health as well as estimating the emotional state of a person. Speaker's physiological and/or physical state may be thus identified by detecting the cognitive decline (CD) or stress levels using signal analysis of voice. This preliminary study presents a survey on methods introduced for CD and stress voice detection in humans. It is shown that increase in signal's fundamental frequency (f0) as well as its frequency formants, are the most common effects of CD and stress. Additional voice parameters could be used to identify normal from CD and normal from stressed voice as well as the cognitive state of the elderly. The present study poses the initiation of a project for the development of a mobile application for the automated voice detection and analysis on the fly, which will aid in the detection of early signs of CD and stress. Further investigation with application on a large number of voice samples is required for validating the methods. © Published under licence by IOP Publishing Ltd.

关键词： Signal analysis

来源：评论

学校读者我要写书评

暂无评论

A New Handover Management Model for Two-Tier 5G Mobile Networks

引用

computers, Materials & Continua 2022年第6期71卷 5491-5509页

作者： Mohammad Arifin Rahman Khan Mohammed Golam Kaosar Mohammad Shorfuzzaman Kire Jakimoski Department of Computer Science and Engineering Bangladesh UniversityDhaka1207Bangladesh Discipline of IT Media and CommunicationsMurdoch UniversityPerthWA6150Australia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Faculty of Informatics AUE-FON UniversitySkopjeRepublic of North Macedonia

There has been an exponential rise in mobile data traffic in recent times due to the increasing popularity of portable devices like tablets,smartphones,and *** rapid rise in the use of these portable devices has put extreme stress on the network service providers while forcing telecommunication engineers to look for innovative solutions to meet the increased *** solution to the problem is the emergence of fifth-generation(5G)wireless communication,which can address the challenges by offering very broad wireless area capacity and potential cut-power *** application of small cells is the fundamental mechanism for the *** use of small cells can enhance the facility for higher capacity and ***,it must be noted that small cells deployment will lead to frequent handovers of mobile *** the importance of small cells in 5G,this paper aims to examine a new resource management scheme that can work to minimize the rate of handovers formobile phones through careful resources allocation in a two-tier ***,the resource management problem has been formulated as an optimization issue thatwe aim to overcome through an optimal *** find a solution to the existing problem of frequent handovers,a heuristic approach has been *** solution is then evaluated and validated through simulation and testing,during which the performance was noted to improve by 12%in the context of handover ***,this model has been observed to be more efficient as compared to the existing model.

关键词： Two-tier mobile networks small cell densification management of mobility handover cost average throughput power consumption

来源：评论

学校读者我要写书评

暂无评论

Sensors, Signals, and Imaging informatics: Best contributions from 2023

引用

Yearbook of Medical informatics 2025年第1期33卷 277-279页

作者： Rittner, Leticia Baumgartner, Christian Deserno, Thomas M. Medical Imaging Computing Lab (MICLab) School of Electrical and Computer Engineering University of Campinas Brazil Institute of Health Care Engineering with European Testing Center of Medical Devices Graz University of Technology Austria Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School Braunschweig Germany

OBJECTIVES: To identify and highlight research papers that represent the advances and trends in the field of sensors, signals, and imaging informatics in 2023. METHOD: We performed a bibliographic search on Scopus and PubMed databases using Medical Sub-ject Heading (MeSH) terms combined with keywords. Our aim was to build specific queries for sen-sors, signals, and imaging informatics. We disregarded journals that returned less than three papers on the query and then evaluated titles and abstracts of the papers using a 3-point Likert scale, ranging from 1 (do not include) to 3 (should be included). Only the papers with a total score of 8 or more were re-evaluated again, this time considering the full text, and the top 14 papers with the highest scores were then reviewed by external reviewers and editors of the International Medical informatics Association (IMIA) Yearbook. RESULTS: Among the 643 returned papers published in 2023 in the various areas of sensors, signals, and imaging informatics (SSII), we selected 58 papers with at least 8 Likert points (in total). After a comprehensive evaluation, we identified 14 papers as the best contributions and sent them to eight external reviewers. The full review process resulted in a selection of the four best papers, which were then approved by consensus by the IMIA Yearbook Editorial Board. Although the imaging informatics sub-search returned all of these four papers, one is about sensorless freehand 3D ultrasound recon-struction (representing sensors), and another deals with video-based pulse rate estimation (representing signals). CONCLUSIONS: Sensors, signals, and imaging informatics is a dynamic field of intensive research. The four best papers in 2023 represent advanced approaches focusing on DL-based image processing, analysis, and indicate a shift in the research field from sensor technology development to biosignal and image analysis. The Author(s). This is an open access article published by Thieme under the terms

关键词： Biomedical informatics Deep learning Imaging informatics International Medical informatics Association Yearbook Machine learning Personalized medicine Sensor informatics Signal in-formatics

来源：评论

学校读者我要写书评

暂无评论

Handover Management through Reconfigurable Intelligent Surfaces for VLC under Blockage Conditions

arXiv

引用

arXiv 2024年

作者： Palitharathna, Kapila W.S. Vegni, Anna Maria Diamantoulakis, Panagiotis D. Suraweera, Himal A. Krikidis, Ioannis Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Department of Industrial Electronic and Mechanical Engineering Roma Tre University Rome Italy Department of Applied Informatics University of Macedonia Thessaloniki Greece Department of Electrical and Electronic Engineering University of Peradeniya Peradeniya Sri Lanka

In this paper, we consider an indoor visible light communication (VLC) system with multiple "white" light emitting diodes serving to form overlapping wireless communication cells. In order to maintain seamless connectivity to mobile users, a handover procedure should be implemented. In particular, practical conditions such as blockages due to obstacles inside the room environment and the mobility of users can affect direct VLC connectivity. The use of reconfigurable intelligent surfaces (RISs) in optical wireless systems allows to exploit non-direct connectivity links, thus providing efficient communication links. In this paper, we present a proactive handover mechanism that exploits the presence of a RIS, in order to redirect the communication links in case of blockages. The proposed approach has been implemented both in hard and soft modes and assessed in terms of achievable data rate and handover latency for a user walking in a given reference room at different user speeds and blockage conditions. Our presented results and comparisons with conventional handover methods (i.e., without RIS) are helpful in showing the superiority of the presented algorithm. © 2024, CC BY.

关键词： Visible light communication

来源：评论

学校读者我要写书评

暂无评论

On the Integration of IoT and Cloud Computing for Ultra-Reliable Spectrum Allocation in e-Health 29

On the Integration of IoT and Cloud Computing for Ultra-Reli...

引用

29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Batalla, Jordi Mongay Markakis, Evangelos Bourdena, Athina Mastorakis, George University of Nicosia Department of Computer Science Nicosia Cyprus Hellenic Mediterranean University Crete Heraklion Greece Warsaw University of Technology and Octawave S.A. Warsaw Poland Hellenic Mediterranean University Department of Electrical and Computer Engineering Crete Heraklion Greece Hellenic Mediterranean University Department of Business Administration and Tourism Crete Heraklion Greece Hellenic Mediterranean University Department of Management Science and Technology Crete Agios Nikolaos Greece

ISBN: (纸本)9798350377644

Integrating cloud computing, IoT, and computational intelligence is crucial in e-health to ensure ultra-reliable communication, which is essential for health monitoring and telemedicine. This paper explores the complex spectrum requirements for ultra-reliable communication in next-generation networks, which are vital for seamless e-health applications. It introduces multi-operator network sharing as a solution to the growing spectrum demands, allowing devices to connect with base stations from multiple providers, thus improving connectivity and reliability. Through detailed analysis, we de-rive closed-form equations using meta-distributions to evaluate spectrum needs under different sharing setups, highlighting the balance between spectrum use and reliability, particularly in e-health scenarios. Findings indicate that multi-operator network sharing and multi-connectivity strategies significantly reduce spectrum requirements for e-health services, leading to more effective and reliable healthcare delivery. The fusion of next-generation technology with IoT and cloud computing marks a significant step towards advanced e-health applications, promising high-quality, accessible, and continuous healthcare services. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：