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Ontological Model for Cohesive Smart Health Services Management

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Computers, Materials & Continua 2023年第2期74卷 3679-3695页

作者： Muhammad Raza Naqvi Muhammad Waseem Iqbal Syed Khuram Shahzad M.Usman Ashraf Khalid Alsubhi hani moaiteq aljahdali Le Laboratoire Génie de Production de l’École Nationale d’Ingénieurs de Tarbes(LGP-INP-ENIT) Universitéde ToulouseCEDEXTarbes65016France Department of Software Engineering Superior UniversityLahore53700Pakistan Department of Informatics&Systems University of Management&TechnologyLahore54000Pakistan Department of Computer Science University of Management and TechnologySialkot51310Pakistan Department of Computer Science King Abdul-Aziz UniversityJeddah21577Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21577Saudi Arabia

Health care has become an essential social-economic concern for all stakeholders(e.g.,patients,doctors,hospitals etc.),health needs,private care and the elderly class of *** massive increase in the usage of health care Internet of things(IoT)applications has great technological evolvement in human *** are various smart health care services like remote patient monitoring,diagnostic,disease-specific remote treatments and *** applications are available in a split fashion and provide solutions for variant diseases,medical resources and remote service *** main objective of this research is to provide a management platform where all these services work as a single unit to facilitate the *** ontological model of integrated healthcare services is proposed by getting requirements from various existing healthcare *** were 26 smart health care services and 26 smart health care services to classify the knowledge-based ontological *** proposed ontological model is derived from different classes,relationships,and constraints to integrate health care *** model is developed using Protégébased on each interrelated/correlated health care service having different *** querying SPARQL protocol and RDF query language(SPARQL)were used for knowledge *** Pellet Reasoner is used to check the validity and relations coherency of the proposed ontology *** to other smart health care services integration systems,the proposed ontological model provides more cohesiveness.

关键词： Ontology internet of things smart health services integration

Optimization of Interactive Videos Empowered the Experience of Learning Management System

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Computer Systems Science & Engineering 2023年第7期46卷 1021-1038页

作者： Muhammad Akram Muhammad Waseem Iqbal M.Usman Ashraf Erssa Arif Khalid Alsubhi hani moaiteq aljahdali Department of Computer Science Superior University Lahore54000Pakistan Department of Software Engineering Superior University Lahore54000Pakistan Department of Computer Science GC Women University SialkotPakistan Department of Computer Science King Abdulaziz UniversityJeddahSaudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia

The Learning management system(LMS)is now being used for uploading educational content in both distance and blended *** platform has two types of users:the educators who upload the content,and the students who have to access the *** students,usually rely on text notes or books and video tutorials while their exams are conducted with formal *** assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive *** aim is to design an interactive LMS and examination video-based interface to cater the issues of educators and *** is designed according to Human-computer interaction(HCI)principles to make the interactive User interface(UI)through User experience(UX).The interactive lectures in the form of annotated videos increase user engagement and improve the self-study context of users involved in *** interface design defines how the design will interact with users and how the interface exchanges *** findings show that interactive videos for LMS allow the users to have a more personalized learning experience by engaging in the educational *** result shows a highly personalized learning experience due to the interactive video and quiz within the video.

关键词： User interface user experience learning management system linear nonlinear video interactive video visual design

A Novel Deep Learning Based Healthcare Model for COVID-19 Pandemic Stress Analysis

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Computers, Materials & Continua 2022年第9期72卷 6029-6044页

作者： Ankur Dumka Parag Verma Rajesh Singh Anil Kumar Bisht Divya Anand hani moaiteq aljahdali Irene Delgado Noya Silvia Aparicio Obregon Computer Science and Engineering Women Institute of TechnologyUttarakhand-248007India Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Research and Innovation Uttranchal UniversityDehradunUttrakhand248007India Department of Computer Science&IT MJP Rohilkhand UniversityBareilly236006UPIndia Computer Science and Engineering Lovely Professional UniversityPunjab144411India Higher Polytechnic School Universidad Europea del Atlántico39011SantanderSpain Faculty of Computing and Information Technology King Abdulaziz University37848JeddahSaudi Arabia Universidad Internacional Iberoamericana CampecheMexico Universidade Internacional do Cuanza Bairro Kaluanda EN 250CuitoBié.Angola

Coronavirus(COVID-19)has impacted nearly every person across the globe either in terms of losses of life or as of *** current coronavirus(COVID-19)pandemic is a rare/special situation where people can express their feelings on Internet-based social *** media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their *** research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 *** research is based on the logic expressed by people in this perspective and emotions for the suffering of COVID-19 and *** this research,we have used a Long Short-Term Memory(LSTM)network model with Convolutional Neural Network using Keras python deep-learning library to determine whether social media platform users are depressed in terms of positive,negative,or neutral emotional out bust based on their Twitter *** results showed that the model has 88.14%accuracy(representation of the correct prediction over the test dataset)after 10 epochs which most tweets showed had neutral *** evaluation shows interesting results in positive(1),negative(–1),and neutral(0)emotions through different visualization.

关键词： COVID-19 lockdown stress analysis depression analysis sentiment analysis social media COVID-19 twitter dataset coronavirus

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

Heating-Cooling Monitoring and Power Consumption Forecasting Using LSTM for Energy-Efficient Smart Management of Buildings: A Computational Intelligence Solution for Smart Homes

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Tsinghua Science and Technology 2024年第1期29卷 143-157页

作者： Omid Akbarzadeh Sahand Hamzehei hani Attar Ayman Amer Nazanin Fasihihour Mohammad R.Khosravi Ahmed A.Solyman Department of Electronics and Telecommunications Politecnico di TorinoTurin 10129Italy Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 262799China Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNisantası UniversityIstanbul 25370The Republic of Turkiye

Energy management in smart homes is one of the most critical problems for the Quality of Life(QoL)and preserving energy *** of the relevant issues in this subject is environmental contamination,which threatens the world's *** computing-enabled Artificial Intelligence(Al)algorithms can provide impactful solutions to this *** research proposes using one of the Recurrent Neural Network(RNN)algorithms known as Long Short-Term Memory(LSTM)to comprehend how it is feasible to perform the cloud/fog/edge-enabled prediction of the building's *** parameters of power electricity,power heating,power cooling,and total power in an office/home in cold-climate cities are considered as our features in the *** on the collected data,we evaluate the LSTM approach for forecasting parameters for the next year to predict energy consumption and online monitoring of the model's performance under various *** implementing the Al predictive algorithm,several existing tools are *** results have been generated through simulations,and we find them promisingforfutureapplications.

关键词： design-builder Besos smart cities smart building neural network Long Short-Term Memory(LSTM)

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1807-1830页

作者： Aadel M.Alatwi Abualkasim Bakeer Sherif A.Zaid Ibrahem E.Atawi hani Albalawi Ahmed M.Kassem Electrical Engineering Department Faculty of EngineeringUniversity of TabukTabuk47913Saudi Arabia Industrial Innovation and Robotic Center(IIRC) University of TabukTabuk47731Saudi Arabia Department of Electrical Engineering Faculty of EngineeringAswan UniversityAswan81542Egypt Renewable Energy and Environmental Technology Centre University of TabukTabuk47913Saudi Arabia Electrical Engineering Department Faculty of EngineeringSohag UniversitySohag82524Egypt

An autonomous microgrid that runs on renewable energy sources is presented in this *** has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage ***,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult ***-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and *** suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum *** suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid *** optimal FOPI+iFOPI controller manages the voltage and frequency of the *** behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed *** simulations were used to evaluate the recommended system’s *** results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and *** addition,the required load demand was accurately ***,the microgrid functioned incredibly well despite SMES and varying wind *** obtained under identical conditions were compared with and without the best FOPI+iFOPI *** utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

关键词： Fractional-order proportional integral(FOPI) intelligent controller renewable energy resources superconducting magnetic energy storage optimization

Formation Mechanisms of Some Features in Siliceous Upper Cretaceous-Lower Tertiary Beds of Jordan-Undulations, Geodes, Boudinages

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Open Journal of Geology 2024年第4期14卷 569-577页

作者： Elias Salameh hani Khoury Department of Geology University of Jordan Amman Jordan

Geode, boudinage, and undulation structures are widely distributed in the siliceous beds of the Upper Cretaceous/Tertiary rocks in Jordan. Their formation was attributed to tectonic forces, syngenetic processes, organic disintegration processes, subaquatic gliding, compaction and settlement, and meteoritic impacts. In this work, the structural features in the siliceous beds of Jordan are attributed to an interplay of load and directed pressures, and mineralogical transformation processes (opal-A to opal-CT to quartz), governed by pH changes. Tectonic directed pressure was acting in an ESE-WSW direction and is common in the silicified limestone of Upper Cretaceous.

关键词： Undulations Geodes Boudinages Opal-A Porcelanite Chert Transformations pH Changes Stress Fields Jordan

High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

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Tsinghua Science and Technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster