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An Improved Evolutionary Algorithm for Data Mining and Knowledge Discovery

Computers, Materials & Continua 2022年第4期71卷 1233-1247页

作者： Mesfer Al Duhayyim Radwa Marzouk Fahd N.Al-Wesabi maram alrajhi Manar Ahmed Hamza Abu Sarwar Zamani 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 Mathematics Faculty of ScienceCairo UniversityGiza 12613Egypt Department of Computer Science Faculty of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems Faculty of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

Recent advancements in computer technologies for data processing,collection,and storage have offered several chances to improve the abilities in production,services,communication,and researches.Data mining(DM)is an interdisciplinary field commonly used to extract useful patterns from the data.At the same time,educational data mining(EDM)is a kind of DM concept,which finds use in educational sector.Recently,artificial intelligence(AI)techniques can be used for mining a large amount of data.At the same time,in DM,the feature selection process becomes necessary to generate subset of features and can be solved by the use of metaheuristic optimization algorithms.With this motivation,this paper presents an improved evolutionary algorithm based feature subsets election with neuro-fuzzy classification(IEAFSS-NFC)for data mining in the education sector.The presented IEAFSS-NFC model involves data pre-processing,feature selection,and classification.Besides,the Chaotic Whale Optimization Algorithm(CWOA)is used for the selection of the highly related feature subsets to accomplish improved classification results.Then,Neuro-Fuzzy Classification(NFC)technique is employed for the classification of education data.The IEAFSS-NFC model is tested against a benchmark Student Performance DataSet from the UCI repository.The simulation outcome has shown that the IEAFSS-NFC model is superior to other methods.

关键词： Educational data mining feature selection whale optimization classification

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Adherence to Advisory Committee on Immunization Practices in diabetes mellitus patients in Saudi Arabia:A multicenter retrospective study

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World Journal of Diabetes 2024年第3期15卷 440-454页

作者： Saleh Fahad Alqifari Aya K Esmail Dalal M Alarifi Ghalya Y Alsuliman maram M Alhati May R Mutlaq Mohammed Aldhaeefi Shaden A Alshuaibi Palanisamy Amirthalingam Abrar Abdallah Afaf S Wasel Heba R Hamad Shoroq Alamin Tasneem H Atia Tariq Alqahtani Department of Pharmacy Practice University of TabukTabuk 71491Saudi Arabia Department of Clinical Sciences Sulaiman Alrajhi UniversityQassim 52726Saudi Arabia Department of Family Medicine International Medical CenterJeddah 23214Saudi Arabia Clinical and Administrative Pharmacy Sciences College of PharmacyHoward UniversityWashingtonDC 20059United States Department of Pharmacology King Saud Bin Abdulaziz University for Health SciencesKing Abdullah International Medical Research CenterRiyadh 11481Saudi Arabia

BACKGROUND Patients with diabetes mellitus(DM)are predisposed to an increased risk of infection signifying the importance of vaccination to protect against its potentially severe complications.The Centers for Disease Control and Prevention/Advisory Committee on Immunization Practices(CDC/ACIP)issued immunization recommendations to protect this patient population.AIM To assess the adherence of patients with DM to the CDC/ACIP immunization recommendations in Saudi Arabia and to identify the factors associated with the vaccine adherence rate.METHODS An observational retrospective study conducted in 2023 was used to collect data on the vaccination records from 13 diabetes care centers in Saudi Arabia with 1000 eligible patients in phase I with data collected through chart review and 709 patients in phase II through online survey.RESULTS Among participants,10.01%(n=71)had never received any vaccine,while 85.89%(n=609)received at least one dose of the coronavirus disease 2019(COVID-19)vaccine,and 34.83%(n=247)had received the annual influenza vaccine.Only 2.96%(n=21),2.11%(n=15),and 1.12%(n=8)received herpes zoster,tetanus,diphtheria,and pertussis(Tdap),and human papillomavirus(HPV)vaccines,respectively.For patients with DM in Saudi Arabia,the rate of vaccination for annual influenza and COVID-19 vaccines was higher compared to other vaccinations such as herpes zoster,Tdap,pneumococcal,and HPV.Factors such as vaccine recommendations provided by family physicians or specialists,site of care,income level,DM-related hospitalization history,residency site,hemoglobin A1c(HbA1c)level,and health sector type can significantly influence the vaccination rate in patients with DM.Among non-vaccinated patients with DM,the most reported barriers were lack of knowledge and fear of side effects.This signifies the need for large-scale research in this area to identify additional factors that might facilitate adherence to CDC/ACIP vaccine recommendations in patients with DM.CONCLUSION In Saudi Arabia,patients with DM showed higher vacci

关键词： Diabetes mellitus Vaccine recommendation COVID-19 vaccine Influenza vaccine Pneumococcal vaccine Immunization Retrospective study

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Development of Non-ABO Red Blood Cell Alloantibodies in Patient Undergoing Allogeneic Haematopoietic Stem Cell Transplant

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Case Reports in Clinical Medicine 2024年第5期13卷 162-170页

作者： Ahmed Alsuhaibani Khalid Batarfi Ahmed Alharbi Haya Alwasel Abdullah Alenazi Abdulmohsen Alotaibi Jalal Hassan Rayyan Alotaibi Hajer Aziz Nourah Alharethi Sara Alobaidi maram Alonayzan Sanad Alharthi Majd Alanazi Sarah Alotaibi Ahmed Shareefi Bandar Alqahtani Department of Laboratory and Pathology King Abdulaziz Medical City of National Guard Riyadh Saudi Arabia

Alloantibodies that are non ABO Alloimmunization to protein antigens happens only after exposure, in contrast to ABO isohaemagglutinins, which are present naturally, even in the absence of prior exposure. It is recognized that while non-ABO RBC antibodies are less common than ABO antibodies, they generate essentially the same issues that lead to unfavorable clinical results. If non-ABO alloantibodies are identified early on, these issues related complications may be avoided This call for an in-depth understanding of the recipient and donor’s ABO-Rh grouping, antibody screening, and the phenotype of certain antigens. Equally important, the temporal association time between transplantation and hemolysis can help identify the underlying mechanism of hemolysis and direct appropriate management. Therefore, for that, it is crucial to identify the etiology of post-HSCT anemia for prevention and therapy, in addition to a thorough grasp of the mechanism of anemia in non-ABO-incompatible HSCT and the temporal link between HSCT and anemia. Finding the cause of post-HSCT anemia is essential for prevention and therapy, in addition to a thorough grasp of the mechanism of anemia in non-ABO-incompatible HSCT and the temporal link between HSCT and anemia. Therefore, for that, it is crucial to identify the etiology of post-HSCT anemia. In this case report review, we would like to highlight the vital role of transfusion medicine services and stem cell clinical teams in paying particular attention to the clinical significance of non-ABO alloantibodies involved to avoid causing overt hemolysis of incompatible donor RBCs or delayed erythropoiesis. Considering the fact that some of the Haematopoietic stem cell transplant centers do not give an attention to the other non-ABO RBC antigens.

关键词： Haematopoietic Stem Cell Transplant (HSCT) Non-ABO Red Blood Cell Antibodies Alloantibodies

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Intrusion Detection Systems in Internet of Things and Mobile Ad-Hoc Networks

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Computer Systems Science & Engineering 2022年第3期40卷 1199-1215页

作者： Vasaki Ponnusamy Mamoona Humayun NZJhanjhi Aun Yichiet maram Fahhad Almufareh Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKamparMalaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufSaudi Arabia School of Computer Science and Engineering(SCE) Taylor’s UniversitySelangorMalaysia

Internet of Things(IoT)devices work mainly in wireless mediums;requiring different Intrusion Detection System(IDS)kind of solutions to leverage 802.11 header information for intrusion detection.Wireless-specific traffic features with high information gain are primarily found in data link layers rather than application layers in wired networks.This survey investigates some of the complexities and challenges in deploying wireless IDS in terms of data collection methods,IDS techniques,IDS placement strategies,and traffic data analysis techniques.This paper’s main finding highlights the lack of available network traces for training modern machine-learning models against IoT specific intrusions.Specifically,the Knowledge Discovery in Databases(KDD)Cup dataset is reviewed to highlight the design challenges of wireless intrusion detection based on current data attributes and proposed several guidelines to future-proof following traffic capture methods in the wireless network(WN).The paper starts with a review of various intrusion detection techniques,data collection methods and placement methods.The main goal of this paper is to study the design challenges of deploying intrusion detection system in a wireless environment.Intrusion detection system deployment in a wireless environment is not as straightforward as in the wired network environment due to the architectural complexities.So this paper reviews the traditional wired intrusion detection deployment methods and discusses how these techniques could be adopted into the wireless environment and also highlights the design challenges in the wireless environment.The main wireless environments to look into would be Wireless Sensor Networks(WSN),Mobile Ad Hoc Networks(MANET)and IoT as this are the future trends and a lot of attacks have been targeted into these networks.So it is very crucial to design an IDS specifically to target on the wireless networks.

关键词： Internet of Things MANET intrusion detection systems wireless networks

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Security Threat and Vulnerability Assessment and Measurement in Secure Software Development

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Computers, Materials & Continua 2022年第6期71卷 5039-5059页

作者： Mamoona Humayun NZ Jhanjhi maram Fahhad Almufareh Muhammad Ibrahim Khalil Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufKSA School of Computer Science and Engineering(SCE) Taylor’s UniversitySelangorMalaysia Department of Computer Science Bahria UniversityIslamabadPakistan

Security is critical to the success of software,particularly in today’s fast-paced,technology-driven environment.It ensures that data,code,and services maintain their CIA(Confidentiality,Integrity,and Availability).This is only possible if security is taken into account at all stages of the SDLC(Software Development Life Cycle).Various approaches to software quality have been developed,such as CMMI(Capabilitymaturitymodel integration).However,there exists no explicit solution for incorporating security into all phases of SDLC.One of the major causes of pervasive vulnerabilities is a failure to prioritize security.Even the most proactive companies use the“patch and penetrate”strategy,inwhich security is accessed once the job is completed.Increased cost,time overrun,not integrating testing and input in SDLC,usage of third-party tools and components,and lack of knowledge are all reasons for not paying attention to the security angle during the SDLC,despite the fact that secure software development is essential for business continuity and survival in today’s ICT world.There is a need to implement best practices in SDLC to address security at all levels.To fill this gap,we have provided a detailed overview of secure software development practices while taking care of project costs and deadlines.We proposed a secure SDLC framework based on the identified practices,which integrates the best security practices in various SDLC phases.A mathematical model is used to validate the proposed framework.A case study and findings show that the proposed system aids in the integration of security best practices into the overall SDLC,resulting in more secure applications.

关键词： Security secure software development software development life cycle(SDLC) confidentiality integrity availability

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An Animated GIF Steganography Using Variable Block Partition Scheme

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Computer Systems Science & Engineering 2022年第12期43卷 897-914页

作者： maram Abdullah M.Alyahya Arshiya S.Ansari Mohammad Sajid Mohammadi Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia

The paper presents a novel Graphics Interchange Format (GIF) Steganography system. The algorithm uses an animated (GIF) file format video to applyon, a secured and variable image partition scheme for data embedding. The secretdata could be any character text, any image, an audio file, or a video file;that isconverted in the form of bits. The proposed method uses a variable partitionscheme structure for data embedding in the (GIF) file format video. The algorithmestimates the capacity of the cover (GIF) image frames to embed data bits. Ourmethod built variable partition blocks in an empty frame separately and incorporate it with randomly selected (GIF) frames. This way the (GIF) frame is dividedinto variable block same as in the empty frame. Then algorithm embeds secretdata on appropriate pixel of the (GIF) frame. Each selected partition block for dataembedding, can store a different number of data bits based on block size. Intruders could never come to know exact position of the secrete data in this stegoframe. All the (GIF) frames are rebuild to make animated stego (GIF) video.The performance of the proposed (GIF) algorithm has experimented andevaluated based on different input parameters, like Mean Square Error (MSE)and Peak Signal-to-Noise Ratio (PSNR) values. The results are compared withsome existing methods and found that our method has promising results.

关键词： (GIF)Steganography frame partition variable data insertion data encapsulation

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Patient Satisfaction with Primary Health Care Services in Riyadh City, Saudi Arabia

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International Journal of Clinical Medicine 2023年第8期11卷 366-376页

作者： maram Alqahtani Mona Alanazi Salem Alsuwaidan Family Medicine Academy King Saud Medical City Riyadh Saudi Arabia

Patient satisfaction is a crucial measure of healthcare quality and plays a vital role in ensuring effective healthcare systems. This study aims to assess the level of patient satisfaction with primary healthcare services in Riyadh, Saudi Arabia, identify social factors affecting satisfaction, and determine the reasons behind dissatisfaction and how to improve satisfaction. The study employed a cross-sectional observational design and included a random sample of 400 patients from primary healthcare centers in Riyadh. Data were collected using an electronic questionnaire and analyzed using SPSS software. The study found that patients were generally satisfied with the primary healthcare services provided in Riyadh, with high levels of satisfaction reported for booking appointments, triage services, and emergency care. However, some aspects of the healthcare experience, such as long waiting times and the physical design of healthcare centers, need improvement. These findings can be used to inform the development of policies and interventions aimed at enhancing healthcare quality in Saudi Arabia.

关键词： Patient Satisfaction Primary Healthcare Services PHC Healthcare Quality

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埃及重症监护护士临床领导力行为的调查研究

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International Journal of Nursing Sciences 2022年第3期9卷 357-363,I0004页

作者： Heba Mohamed Al Anwer Ashour maram Ahmed Banakhar Naglaa Abd Elaziz Elseesy Nursing Administration Department Faculty of NursingAlexandria UniversityAlexandriaEgypt Department of Public Health Nursing Faculty of NursingKing Abdulaziz UniversityJeddahSaudi Arabia

目的本研究旨在调查埃及医院重症监护护士的临床领导力行为现状,并比较私立和公立医院护士临床领导力水平的差异。方法2019年1—3月,在埃及1所公立教学医院和1所私立医院共选取365名具有护理学学士学位的重症监护护士进行横断面调查。... 详细信息

目的本研究旨在调查埃及医院重症监护护士的临床领导力行为现状,并比较私立和公立医院护士临床领导力水平的差异。方法2019年1—3月,在埃及1所公立教学医院和1所私立医院共选取365名具有护理学学士学位的重症监护护士进行横断面调查。采用社会人口学特征调查表和临床领导力行为问卷(the Clinical Leadership Behaviors Questionnaire,CLB-Q)收集数据,将各维度及总分的条目均分转换为百分制得分,以便进行比较和分析。结果结果显示,护士CLB-Q得分为(77.11±11.87)分,其中沟通维度得分最高(91.84±7.38)。私立医院重症监护护士的CLB-Q得分为(90.48±5.53)分,高于公立教学医院护士得分(68.29±4.21),差异有统计学意义(P<0.001)。有5~10年工作经验的护士在CLB-Q总分及自我认知、倡导和授权、决策、质量与安全、团队合作和临床卓越维度得分较其他组别护士得分高(P<0.01)。单身护士的CLB-Q总分及倡导和授权、决策、质量与安全以及临床卓越维度得分较已婚护士高(P<0.01)。结论护理管理者应促进重症监护护士加强临床实践,鼓励他们参加质量和安全方面的培训项目,以培养其临床领导力。公立医院的重症监护护士尤其需要全面提升临床领导力水平。

关键词：行为横断面研究重症监护病房领导力护士

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Deep Learning Based Sentiment Analysis of COVID-19 Tweets via Resampling and Label Analysis

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Computer Systems Science & Engineering 2023年第10期47卷 575-591页

作者： Mamoona Humayun Danish Javed Nz Jhanjhi maram Fahaad Almufareh Saleh Naif Almuayqil Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakah72311Saudi Arabia School of Computer Science SCSTaylor’s UniversitySubang Jaya47500SelangorMalaysia

Twitter has emerged as a platform that produces new data every day through its users which can be utilized for various purposes.People express their unique ideas and views onmultiple topics thus providing vast knowledge.Sentiment analysis is critical from the corporate and political perspectives as it can impact decision-making.Since the proliferation of COVID-19,it has become an important challenge to detect the sentiment of COVID-19-related tweets so that people’s opinions can be tracked.The purpose of this research is to detect the sentiment of people regarding this problem with limited data as it can be challenging considering the various textual characteristics that must be analyzed.Hence,this research presents a deep learning-based model that utilizes the positives of random minority oversampling combined with class label analysis to achieve the best results for sentiment analysis.This research specifically focuses on utilizing class label analysis to deal with the multiclass problem by combining the class labels with a similar overall sentiment.This can be particularly helpful when dealing with smaller datasets.Furthermore,our proposed model integrates various preprocessing steps with random minority oversampling and various deep learning algorithms including standard deep learning and bi-directional deep learning algorithms.This research explores several algorithms and their impact on sentiment analysis tasks and concludes that bidirectional neural networks do not provide any advantage over standard neural networks as standard Neural Networks provide slightly better results than their bidirectional counterparts.The experimental results validate that our model offers excellent results with a validation accuracy of 92.5%and an F1 measure of 0.92.

关键词： Bi-directional deep learning resampling random minority oversampling sentiment analysis class label analysis

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Exploring the factors influencing nurses' work motivation during the COVID-19 pandemic in King Faisal Hospital in Makkah al-Mukarramah, Saudi Arabia

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Nursing Communications 2022年第1期6卷 148-155页

作者： Albandre Alenezi Mari Almutairi Mohammed Saleh Alshmemri maram Taher Alghabbashi Hala Yehia Faculty of Nursing Umm Al-Qura UniversityMakkah 24382Saudi Arabia Ministry of health The Directorate of Health affairs in Northern ProvinceAr a r 91471Saudi Arabia

Background:At this time of severe budgetary constraints and worldwide nursing shortages,the nursing profession is already facing challenges in keeping its professionals motivated to work during the COVID-19 pandemic.This study explores the factors influencing nurses’work motivation during the COVID-19 pandemic in Saudi Arabia.Method s:A descriptive quantitative cross-sectional study was conducted at King Faisal Hospital in Makkah al-Mukarramah,Saudi Arabia.A convenience sample of 184 nurses participated in the study.An electronic self-administrative questionnaire in the English language was used to collect data.It comprises two parts:demographic data and the Multidimensional Work Motivation Scale(MWMS)using a 7-point Likert scale.Analysis of variance(ANOVA)and t-tests were utilized to identify the differences in MWMS scores among participants’characteristics.Results:The study found that the overall mean score for the MWMS scale accounted for M=81.32,SD=18.66,with the highest mean score reported for interjected regulation(M=20.19,SD=5.59).Moreover,the results revealed that 62%of the participants attained an average level on the overall MWMS.In addition,the ANOVA and t-test showed a significant overall effect of the duration of nurses’work experience,the unit of care,the number of working hours per week and salary on nurses’work motivation during COVID-19 at P<0.05.Conclusion:The study’s findings suggest that hospital administrators and nursing managers should pay careful attention to nurses’work motivation and related factors to increase nurses’quality performance,retention and satisfaction.

关键词： nurses work satisfaction motivation COVID-19 Saudi Arabia

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