检索结果-南通市图书馆

Exploring the Self-Perceived Needs for Family Members Having Adult Critically Ill Loved Person: Descriptive Study

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Health 2014年第21期6卷 3005-3012页

作者： Suhair H. Al Ghabeesh Hana abu-Snieneh Luay abu-Shahror Firas abu-Sneineh Mohammad Alhawamdeh Faculty of Nursing Al-Zaytoonah University Amman Jordan Faculty of Nursing University of Jordan Amman Jordan College of Nursing University of Dammam Dammam KSA Critical Care Department Prince Mohammed Bin Abdul Aziz Hospital Alryad KSA

The aim of this study was to explore the self-perceived needs for adult family members having critically ill patient, measure to how extent the needs are met and identify who meet the needs. The study took place in critical care units of the largest governmental hospital in Jordan. The study adopted a descriptive cross-sectional design. The Arabic translation of Critical Care Family Need Inventory was used to investigate the needs of convenient samples of 60 adult family members having critically ill patients. Findings revealed that 16 out of 45 need items on the CCFNI were rated as very important in >90% of the sample. The participants ranked need for assurance, information and proximity as the highest;need for support and comfort as the lowest. Families in this study viewed nurses as the most important source to meet their needs. A holistic approach of nursing management requires that nurses assess family needs using valid and reliable tools and develop intervention strategies to meet the identified needs.

关键词： Family Needs Critical Care Family Need Inventory (CCFNI) Critical Ill Patients

Deep Learning Enabled Computer Aided Diagnosis Model for Lung Cancer using Biomedical CT Images

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第10期73卷 1437-1448页

作者： Mohammad Alamgeer Hanan Abdullah Mengash Radwa Marzouk Mohamed K Nour Anwer Mustafa Hilal Abdelwahed Motwakel abu Sarwar Zamani Mohammed Rizwanullah Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Early detection of lung cancer can help for improving the survival rate of the *** imaging tools such as computed tomography(CT)image was utilized to the proper identification and positioning of lung *** recently developed deep learning(DL)models can be employed for the effectual identification and classification of *** article introduces novel deep learning enabled CAD technique for lung cancer using biomedical CT image,named DLCADLC-BCT *** proposed DLCADLC-BCT technique intends for detecting and classifying lung cancer using CT *** proposed DLCADLC-BCT technique initially uses gray level co-occurrence matrix(GLCM)model for feature ***,long short term memory(LSTM)model was applied for classifying the existence of lung cancer in the CT ***,moth swarm optimization(MSO)algorithm is employed to optimally choose the hyperparameters of the LSTM model such as learning rate,batch size,and epoch *** demonstrating the improved classifier results of the DLCADLC-BCT approach,a set of simulations were executed on benchmark dataset and the outcomes exhibited the supremacy of the DLCADLC-BCT technique over the recent approaches.

关键词： Biomedical images lung cancer deep learning machine learning metaheuristics hyperparameter tuning

Intelligent Cybersecurity Classification Using Chaos Game Optimization with Deep Learning Model

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第4期45卷 971-983页

作者： Eatedal Alabdulkreem Saud S.Alotaibi Mohammad Alamgeer Radwa Marzouk Anwer Mustafa Hilal Abdelwahed Motwakel abu Sarwar Zamani Mohammed Rizwanullah Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science and Bioinformatics Singhania UniversityPacheri BariJhnujhunuRajasthanIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Cyberattack detection has become an important research domain owing to increasing number of cybercrimes in recent *** Machine Learning(ML)and Deep Learning(DL)classification models are useful in effective identification and classification of *** addition,the involvement of hyper parameters in DL models has a significantly influence upon the overall performance of the classification *** this background,the current study develops Intelligent Cybersecurity Classification using Chaos Game Optimization with Deep Learning(ICC-CGODL)*** goal of the proposed ICC-CGODL model is to recognize and categorize different kinds of attacks made upon ***,ICC-CGODL model primarily performs min-max normalization process to normalize the data into uniform *** addition,Bidirectional Gated Recurrent Unit(BiGRU)model is utilized for detection and classification of ***,CGO algorithm is also exploited to adjust the hyper parameters involved in BiGRU model which is the novelty of current work.A wide-range of simulation analysis was conducted on benchmark dataset and the results obtained confirmed the significant performance of ICC-CGODL technique than the recent approaches.

关键词： Deep learning chaos game optimization cybersecurity chaos game optimization cyberattack

Artificial Fish Swarm Optimization with Deep Learning Enabled Opinion Mining Approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第4期45卷 737-751页

作者： Saud S.Alotaibi Eatedal Alabdulkreem Sami Althahabi Manar Ahmed Hamza Mohammed Rizwanullah abu Sarwar Zamani Abdelwahed Motwakel Radwa Marzouk Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt

Sentiment analysis or opinion mining(OM)concepts become familiar due to advances in networking technologies and social ***,massive amount of text has been generated over Internet daily which makes the pattern recognition and decision making process *** OM find useful in business sectors to improve the quality of the product as well as services,machine learning(ML)and deep learning(DL)models can be considered into ***,the hyperparameters involved in the DL models necessitate proper adjustment process to boost the classification ***,in this paper,a new Artificial Fish Swarm Optimization with Bidirectional Long Short Term Memory(AFSO-BLSTM)model has been developed for OM *** major intention of the AFSO-BLSTM model is to effectively mine the opinions present in the textual *** addition,the AFSO-BLSTM model undergoes pre-processing and TF-IFD based feature extraction ***,BLSTM model is employed for the effectual detection and classification of ***,the AFSO algorithm is utilized for effective hyperparameter adjustment process of the BLSTM model,shows the novelty of the work.A complete simulation study of the AFSO-BLSTM model is validated using benchmark dataset and the obtained experimental values revealed the high potential of the AFSO-BLSTM model on mining opinions.

关键词： Sentiment analysis opinion mining natural language processing artificial fish swarm algorithm deep learning

Automated Deep Learning Driven Crop Classification on Hyperspectral Remote Sensing Images

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第2期74卷 3167-3181页

作者： Mesfer Al Duhayyim Hadeel Alsolai Siwar Ben Haj Hassine Jaber SAlzahrani Ahmed SSalama Abdelwahed Motwakel Ishfaq Yaseen abu Sarwar Zamani Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Hyperspectral remote sensing/imaging spectroscopy is a novel approach to reaching a spectrum from all the places of a huge array of spatial places so that several spectral wavelengths are utilized for making coherent *** remote sensing contains acquisition of digital images from several narrow,contiguous spectral bands throughout the visible,Thermal Infrared(TIR),Near Infrared(NIR),and Mid-Infrared(MIR)regions of the electromagnetic *** order to the application of agricultural regions,remote sensing approaches are studied and executed to their benefit of continuous and ***,hyperspectral images(HSI)are considered the precise for agriculture as they can offer chemical and physical data on *** this motivation,this article presents a novel Hurricane Optimization Algorithm with Deep Transfer Learning Driven Crop Classification(HOADTL-CC)model onHyperspectralRemote Sensing *** presentedHOADTL-CC model focuses on the identification and categorization of crops on hyperspectral remote sensing *** accomplish this,the presentedHOADTL-CC model involves the design ofHOAwith capsule network(CapsNet)model for generating a set of useful feature ***,Elman neural network(ENN)model is applied to allot proper class labels into the input ***,glowworm swarm optimization(GSO)algorithm is exploited to fine tune the ENNparameters involved in this *** experimental result scrutiny of the HOADTL-CC method can be tested with the help of benchmark dataset and the results are assessed under distinct *** comparative studies stated the enhanced performance of the HOADTL-CC model over recent approaches with maximum accuracy of 99.51%.

关键词： Hyperspectral images remote sensing deep learning hurricane optimization algorithm crop classification parameter tuning

Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations:A concept demonstration study

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2018年第1期3卷 373-384页

作者： Houssein H.Ayoub Susanne F.Awad Laith J.abu-Raddad Department of Mathematics Statisticsand PhysicsQatar UniversityDohaQatar Infectious Disease Epidemiology Group Weill Cornell Medicine-QatarCornell UniversityQatar Foundation-Education CityDohaQatar Department of Healthcare Policy and Research Weill Cornell MedicineCornell UniversityNew YorkUSA College of Health and Life Sciences Hamad Bin Khalifa UniversityDohaQatar

Introduction:HIV epidemics in hard-to-reach high-risk subpopulations are often discovered years after epidemic emergence in settings with poor surveillance *** hypothesis-generation modeling,we aimed to investigate and demonstrate the concept of using routine HIV testing data to identify and characterize hidden epidemics in high-risk *** also compared this approach to surveillance based on AIDS case ***:A deterministic mathematical model was developed to simulate an emerging HIV epidemic in a high-risk subpopulation.A stochastic Monte Carlo simulation was implemented on the total population to simulate the sampling process of generating routine HIV testing *** measures were estimated on the simulated epidemic and on the generated testing *** analyses were conducted on the ***:In the simulated epidemic,HIV prevalence saturated at 32%in the high-risk subpopulation and at 0.33%in the total *** epidemic started its emergingepidemic phase 28 years after infection introduction,and saturated 67 years after infection *** the simulated HIV testing sample,a significant time trend in prevalence was identified,and the generated metrics of epidemic emergence and saturation were similar to those of the simulated *** epidemic was identified 4.0(95%CI 3.4e4.6)years after epidemic emergence using routine HIV testing,but 29.7(95%CI 15.8 e52.1)years after emergence using AIDS case *** the sensitivity analyses,none of the sampling biases affected the conclusion of an emerging epidemic,but some affected the estimated epidemic growth ***:Routine HIV testing data provides a tool to identify and characterize hidden and emerging epidemics in high-risk *** approach can be specially useful in resource-limited settings,and can be applied alone,or along with other complementary data,to provide a meaningful characterization of emer

关键词： HIV High-risk subpopulation Surveillance Mathematical modeling Monte Carlo simulations Epidemiology Sexually transmitted infection

Powering Mobile Networks with Optimal Green Energy for Sustainable Development

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第10期69卷 661-677页

作者： Mohammed H.Alsharif Mahmoud A.Albreem abu Jahid Kannadasan Raju Peerapong Uthansakul Jamel Nebhen Venkatesan Chandrasekaran Ayman A.Aly Department of Electrical Engineering College of Electronics and Information EngineeringSejong UniversityGwangjin-guSeoul05006Korea Department of Electronics and Communications Engineering A’Sharqiyah UniversityIbra400Oman Department of Electrical and Computer Engineering University of OttawaOttawaK1N 6N5ONCanada Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India School of Telecommunication Engineering Suranaree University of TechnologyNakhon RatchasimaThailand Prince Sattam bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia

Green wireless networking is an emerging area for many societies,especially academia and industry,in light of economic and ecological *** wireless infrastructures exploiting green power sources can enhance sustainability due to the adverse effects of conventional power sources and atmospheric ***,the specific power supply requirements for a base station(BS),such as cost effectiveness,efficiency,sustainability,and reliability,can be met by utilizing technological advances in renewable *** drivers and motivators are involved in the deployment of renewable energy technologies and the transition toward green *** energy is free,clean,and abundant in most locations throughout the *** this work,a sustainable optimal stand-alone solarpowered model envisioning green cellular BSs for urban locations in Oman is *** model can extend 24 h uninterrupted power supply support to a cellular BS that fully utilizes an integrated storage *** system analysis is conducted using a hybrid optimization model for electric renewables(HOMER)based on actual prevailing conditions of the regions and their technical *** results showed can be achieved operational expenditure savings up to 16%.These outcomes provide a huge benefit to the cellular operators of Oman economically,technically,and ecologically.

关键词： wireless networks green wireless networks green communications sustainability OPEX

Preparation of epoxy resin/rare earth doped aluminate nanocomposite toward photoluminescent and superhydrophobic transparent woods

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Rare Earths 2023年第3期41卷 397-405,I0003页

作者： Mehrez E.El-Naggar Sami Ullah S.wageh M.A.abu-Saied Tawfik A.Khattab Dalal Alhashmialameer Manal Abou Taleb E.A.Matter Institute of Textile Research and Technology National Research CenterDokkiCairo16221Egypt Research Center for Advanced Materials Science(RCAMS) King Khalid UniversityP.O.Box 9004Abha61413Saudi Arabia Department of Chemistry College of ScienceKing Khalid UniversityP.O.Box 9004Abha61413Saudi Arabia Department of Physics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589Saudi Arabia Polymeric Materials Research Department Advanced Technology and New Materials Research InstituteCity of Scientific Research and Technological Applications(SRTACITY)New Borg El-Arab CityAlexandria21934Saudi Arabia Department of Chemistry College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Chemistry College of Science and HumanitiesPrince Sattam Bin Abdulaziz UniversityAl-kharj11942Saudi Arabia Department of Polymer Chemistry National Center for Radiation Research and Technology(NCRRT)Egyptian Atomic Energy AuthorityNasr CityP.O.Box 7551Cairo11762Egypt Department of Chemistry Faculty of ScienceDamanhour University22111 DamanhourEgypt

A translucent wooden substrate with long-lasting phosphorescence,high photostability and durability,tough surface,ultraviolet protection,high optical transmittance,and superhydrophobicity was *** long-lasting phosphorescent wooden substrate is able to continue emitting light for extended time ***-modified wood(LMw)was immobilized with a solution of epoxy resin(ER)and rare-earth doped aluminate(REDA)phosphor nanoparticles(NPs).For an improved dispersion of pigment,REDA was synthesized in a nanoscale particle size,and characterized by transmission electron microscopy(TEM)to indicate a particle size of 8-14 *** crystal structure of REDA nanoparticles was also proved by X-ray diffraction(XRD).For an improved production of long-persistent phosphorescent colo rless woods,REDA must be well-dispersed in MAA without *** and emissio n,as well as decay and lifetime spectra were *** morphologies of the wooden substrates with different ratios of REDA were investigated by scanning electron microscopy(SEM),X-ray fluorescence(XRF)analysis,Fourier transform infrared spectra(FT-IR),elemental mapping,and energy-dispersion Xray(EDXA).The phosphorescent woods show changes in color from colorless to green under ultraviolet(UV)irradiation,and to yellowish-green in the dark,as proved by the colorimetric parameters of the CIE Lab *** afterglow wood samples display an absorbance band at 365 nm and two phosphorescent bands at 431 and 520 *** UV shielding,photostability,and hydrophobicity were *** increasing REDA ratio,both static contact and slide angles are found to improve in the ranges of147.6°-163.6°and 9°-14°,*** long-lasting photoluminescence is optimized at a REDA ratio of 8%.The present strategy shows a large-scale production approach of multiple functional woods for many potential applications,such as smart glow in the dark windows and safety signs.

关键词： Translucent wood Rare-earth doped aluminate Superhydrophobic Long-lasting light emission Ultraviolet protection

Intelligent Machine Learning Based EEG Signal Classification Model

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第4期71卷 1821-1835页

作者： Mesfer Al Duhayyim Haya Mesfer Alshahrani Fahd N.Al-wesabi Mohammed Abdullah Al-Hagery Anwer Mustafa Hilal abu Sarwar Zaman Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

In recent years,Brain-Computer Interface(BCI)system gained much popularity since it aims at establishing the communication between human brain and *** systems are applied in several research areas such as neuro-rehabilitation,robots,exoeskeletons,***(EEG)is a technique commonly applied in capturing brain *** is incorporated in BCI systems since it has attractive features such as noninvasive nature,high time-resolution output,mobility and *** classification process is highly essential in decision making process and it incorporates different processes namely,feature extraction,feature selection,and *** this motivation,the current research paper presents an Intelligent Optimal Fuzzy Support Vector Machine-based EEC recognition(IOFSVM-EEG)model for BCI *** Component Analysis(ICA)technique is applied onto the proposed IOFSVM-EEG model to remove the artefacts that exist in EEG signal and to retain the meaningful EEG ***,Common Spatial Pattern(CSP)-based feature extraction technique is utilized to derive a helpful set of feature vectors from the preprocessed EEG ***,OFSVM method is applied in the classification of EEG signals,in which the parameters involved in FSVM are optimally tuned using Grasshopper Optimization Algorithm(GOA).In order to validate the enhanced EEG recognition outcomes of the proposed IOFSVM-EEG model,an extensive set of experiments was *** outcomes were examined under distinct *** experimental results highlighted the enhanced performance of the presented IOFSVM-EEG model over other state-of-the-art methods.

关键词： Brain computer interface EEG recognition human computer interface machine learning parameter tuning FSVM