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Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

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Computers, Materials & Continua 2024年第8期80卷 2917-2939页

作者： Islam Zada mohammed naif alatawi Syed Muhammad Saqlain Abdullah Alshahrani Adel Alshamran Kanwal Imran Hessa Alfraihi Department of Software Engineering International Islamic UniversityIslamabad25000Pakistan Information Technology Department Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science University of PeshawarPeshawar25121Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention *** machine learning classifiers have emerged as promising tools for malware ***,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware *** this gap can provide valuable insights for enhancing cybersecurity *** numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware *** the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security *** study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows *** objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows *** the accuracy,efficiency,and suitability of each classifier for real-world malware detection *** the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and *** recommendations for selecting the most effective classifier for Windows malware detection based on empirical *** study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and *** data analysis involves understanding the dataset’s characteristics and identifying preprocessing *** preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for *** training utilizes various

关键词： Security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors Stochastic Gradient Descent Classifier Decision Tree

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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi naif Al Mudawi mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2795-2823页

作者： naif Alotaibi A.S.Al-Moisheer Ibrahim Elbatal mohammed Elgarhy Ehab M.Almetwally Department of Mathematics and Statistics Faculty of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Mathematics College of ScienceJouf UniversityP.O.Box 848Sakaka72351Saudi Arabia Mathematics and Computer Science Department Faculty of ScienceBeni-Suef UniversityBeni-Suef62521Egypt Department of Basic Sciences Higher Institute of Administrative SciencesBelbeisEgypt Faculty of Business Administration Delta University for Science and TechnologyGamasa11152Egypt

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(SGLE)*** SGLE distribution utilizes the sine transformation to enhance its *** updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability *** suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique *** model includes many well-known lifespan distributions as separate *** suggested model is accompanied with a range of statistical *** model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored *** order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing *** relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

关键词： Sine G family generalized linear failure rate progressively censored data moments maximum likelihood estimation Bayesian estimation simulation

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Preimplantation genetic testing for embryos predisposed to hereditary cancer:Possibilities and challenges

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Cancer Pathogenesis and Therapy 2024年第1期2卷 1-14页

作者： mohammed H.Albujja Maher Al-Ghedan Lakshmidevi Dakshnamoorthy Josep Pla Victori Department of Forensic Sciences Naif Arab University for Security SciencesRiyadh 11452Saudi Arabia Genetics Laboratory Thuriah Medical CenterRiyadh 11523Saudi Arabia Department of Genetic Counselling VI-RMA GlobalValencia 46004Spain

Preimplantation genetic testing(PGT),which was developed as an alternative to prenatal genetic testing,allows couples to avoid pregnancies with abnormal chromosomes and the subsequent termination of the affected *** used for early onset monogenic conditions,PGT is now used to prevent various types of inherited cancer conditions based on the development of PGT technology,assisted reproductive techniques(ARTs),and in vitro fertilization(IVF).This review provides insights into the potential benefits and challenges associated with the application of PGT for hereditary cancer and provides an overview of the existing literature on this test,with a particular focus on the current challenges related to laws,ethics,counseling,and ***,this review predicts the future potential applications of this *** PGT may be utilized to predict and prevent hereditary cancer,each case should be comprehensively *** motives of couples must be assessed to prevent the misuse of this technique for eugenic purposes,and non-pathogenic phenotypes must be carefully *** cases that require this technology should also be carefully considered based on legal and ethical *** may be the preferred treatment for hereditary cancer cases;however,such cases require careful case-by-case ***,this study concludes that multidisciplinary counseling and support for patients and their families are essential to ensure that PGT is a viable option that meets all legal and ethical concerns.

关键词： Preimplantation genetic testing Hereditary cancer Late-onset diseases Ethics Legal restrictions

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Forecasting Mental Stress Using Machine Learning Algorithms

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Computers, Materials & Continua 2022年第9期72卷 4945-4966页

作者： Elias Hossain Abdulwahab Alazeb naif Almudawi Sultan Almakdi mohammed Alshehri M.Gazi Golam Faruque Wahidur Rahman Department of Software Engineering Daffodil UniversityDhakaBangladesh Collage of Computer Science and Information System University of NajranNajranSaudi Arabia Department of Computer Science and Engineering Khwaja Yunus Ali UniversitySirajganj 6751Bangladesh

Depression is a crippling affliction and affects millions of individuals around the *** general,the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts,which results in lower costs and improved patient ***,this strategy can necessitate a lot of buy-in from a large number of people,as well as additional training and logistical ***,utilizing the machine learning algorithms,patients with depression based on information generally present in a medical file were analyzed and *** methodology of this proposed study is divided into six parts:Proposed Research Architecture(PRA),Data Pre-processing Approach(DPA),Research Hypothesis Testing(RHT),Concentrated Algorithm Pipeline(CAP),Loss Optimization Stratagem(LOS),and Model Deployment Architecture(MDA).The Null Hypothesis and Alternative Hypothesis are applied to test the *** addition,Ensemble Learning Approach(ELA)and Frequent Model Retraining(FMR)have been utilized for optimizing the loss ***,the Features Importance Interpretation is also delineated in this *** forecasts could help individuals connect with expert mental health specialists more quickly and *** to the findings,71%of people with depression and 80%of those who do not have depression can be appropriately *** study obtained 91%and 92%accuracy through the Random Forest(RF)and Extra Tree *** after applying the Receiver operating characteristic(ROC)curve,79%accuracy was found on top of RF,81%found on Extra Tree,and 82%recorded for the eXtreme Gradient Boosting(XGBoost)***,several factors are identified in terms of predicting depression through statistical data *** the additional effort is needed to develop a more accurate model,this model can be adjustable in the healthcare sector for diagnosing depression.

关键词： Depression analysis mental health machine learning model deployment XGBoost ROC-AUC

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A Novel Human Interaction Framework Using Quadratic Discriminant Analysis with HMM

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Computers, Materials & Continua 2023年第11期77卷 1557-1573页

作者： Tanvir Fatima Naik Bukht naif Al Mudawi Saud S.Alotaibi Abdulwahab Alazeb mohammed Alonazi Aisha Ahmed AlArfaj Ahmad Jalal Jaekwang Kim Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Information Systems Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Convergence Program for Social Innovation Sungkyunkwan UniversitySuwon03063Korea

Human-human interaction recognition is crucial in computer vision fields like surveillance,human-computer interaction,and social *** enhances systems’ability to interpret and respond to human behavior *** research focuses on recognizing human interaction behaviors using a static image,which is challenging due to the complexity of diverse *** overall purpose of this study is to develop a robust and accurate system for human interaction *** research presents a novel image-based human interaction recognition method using a Hidden Markov Model(HMM).The technique employs hue,saturation,and intensity(HSI)color transformation to enhance colors in video frames,making them more vibrant and visually appealing,especially in low-contrast or washed-out *** filters reduce noise and smooth imperfections followed by silhouette extraction using a statistical *** extraction uses the features from Accelerated Segment Test(FAST),Oriented FAST,and Rotated BRIEF(ORB)*** application of Quadratic Discriminant Analysis(QDA)for feature fusion and discrimination enables high-dimensional data to be effectively analyzed,thus further enhancing the classification *** ensures that the final features loaded into the HMM classifier accurately represent the relevant human *** impressive accuracy rates of 93%and 94.6%achieved in the BIT-Interaction and UT-Interaction datasets respectively,highlight the success and reliability of the proposed *** proposed approach addresses challenges in various domains by focusing on frame improvement,silhouette and feature extraction,feature fusion,and HMM *** enhances data quality,accuracy,adaptability,reliability,and reduction of errors.

关键词： Human interaction recognition HMM classification quadratic discriminant analysis dimensionality reduction

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Factors Influencing Patients to Decide to Discharge Themselves against Medical Advice at Tertiary Hospitals: A Cross-Sectional Study

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International Journal of Clinical Medicine 2023年第3期14卷 163-174页

作者： Malak Alsharif Aeshah alatawi Abdulhadi M. Alqahtani mohammed Alufi Faisal Alghamdi Emergency Medicine Ministry of Health Riyadh Saudi Arabia Emergency Medicine King Fahd Medical City Riyadh Saudi Arabia Clinical Research Department Research Centre King Fahd Medical City Riyadh Saudi Arabia Imam Mohammad Ibn Saud Islamic University Riyadh Saudi Arabia Pediatric Emergency King Fahd Medical City Riyadh Saudi Arabia

Background: Discharged against medical advice (DAMA) is defined as any instance when a patient wants to leave the hospital against the managing physician’s decision. This study aimed to identify factors that influence patients to decide to be DAMA. Methods: A descriptive, cross-sectional study. The study was conducted in the emergency department (ED) of King Fahad Medical City (KFMC)-Saudi Arabia-Riyadh city. A questionnaire in both Arabic and English was distributed to all participants to fill in either English or Arabic. Results: Between 1 March and 30 April 2021, 510 responses were collected. Most of the study participants (31.4%) were over the age of 54. Our findings showed that 12.5% of our participants had taken discharge against medical advice in the past. Results Regarding Factors That Influence Patients to Decide on DAMA Showed: Regarding Inappropriate behavior and disrespect of the physician or staff to the patient and his relatives, 262 (51.4%) participants, 85 (16.7%) participants, and 163 (32%) participants agreed, neutral, and disagreed, respectively. Regarding the Lack of physicians’ and nurses’ attention to the patient and his relatives (emotionally), our result showed that 278 (54.5%) participants, 95 (18.6%) participants, and 137 (26.9%) participants agreed, neutral, and disagree, respectively. Regarding failure to inform the patient or his relatives of his condition, it showed that 257 (50.4%) participants, 95 (18.6%) participants, and 158 (31%) participants agreed, neutral, and disagreed, respectively. Regarding feeling better from DAMA, our result showed 226 (44.3%) participants, 119 (23.3%) participants, and 165 (32.4%) participants agreed, neutral, and disagreed, respectively. Regarding patients’ or their relative’s tiredness of hospital stay, the result showed that 166 (32.5%) participants, 104 (20.4%) participants, and 240 (47.1%) participants agreed, neutral, and disagreed, respectively. Conclusion: The long wait time to be seen by a physic

关键词： Against Medical Advice DAMA Discharge Factor Saudi Arabia

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Digital Transformation of Medical Maintenance at PSAFHM

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Open Journal of Applied Sciences 2023年第10期13卷 1844-1854页

作者： Ahmed Abdulaziz Alburaidi mohammed naif Albarakati Ahmed Khalid Sabr mohammed Fadhy Alharbi Abdulaziz Khalaf Alkhathami Nesreen Ayman Kurdi Department of Biomedical Engineering Prince Sultan Armed Forces Hospital Medina Saudi Arabia

In this research, the researchers addressed the issue of digital transformation and its impact on the development of medical maintenance, and this topic is very important in the field of medical engineering. The researchers chose the military Hospital in Medina as his study location. The study aimed to identify and address the main challenges facing the digital transformation of medical maintenance at the Military Hospital in Medina. It seeks to analyze the current state of digitalization in medical maintenance operations, identify areas requiring improvement, and propose effective strategies to overcome obstacles. The study will evaluate the impact of digital transformation on efficiency, cost-effectiveness, patient care, and overall operational performance. At the end of the research, the researchers reached several results, including that introducing digital systems and technologies into medical maintenance can increase efficiency in various aspects, such as scheduling equipment maintenance, inventory management, and resource allocation. Researchers may find evidence of reduced downtime, streamlined workflow, and optimized use of resources. In addition, digital transformation initiatives in medical maintenance may focus on ensuring the safety and reliability of medical equipment. Research can reveal improvements in equipment reliability, decreased equipment failure rates, and improved patient safety outcomes. The researchers also recommended developing a comprehensive strategy for digital transformation: Based on the research results, it is recommended to develop a well-defined strategy that defines the hospital’s vision, goals, and roadmap for the digital transformation of medical maintenance. This strategy should consider factors such as technology selection, resource allocation, timeline, and change management. Invest in a solid digital infrastructure: To support the digital transformation of medical maintenance, the hospital must invest in a reliable and secu

关键词： Digital Transformation Medical Maintenance Malfunctions

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The Impact of the FreeStyle Libre^TM Flash Glucose Monitoring System on Glycemic Control in Patients with Diabetes;Observational Multicenter 15-Months Study

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International Journal of Clinical Medicine 2022年第8期13卷 391-404页

作者： Saud Alsifri Abdulkarim Almalki Samar Alsifri naif Alsifri mohammed Moatism Sahar Alsifri Emad R. Issak Endocrinology & Diabetes Department Alhada Armed Forces Hospital Taif Saudi Arabia Medicine Department King Fahad Armed Forces Hospital Jeddah Saudi Arabia Medicine Department East Jeddah Hospital Jeddah Saudi Arabia King Abdulaziz University Hospital Jeddah Saudi Arabia Medicine Department Asalam Center Cairo Egypt

Objectives: The study was to determine the impact of using the FreeStyle LibreTM flash glucose monitoring system on glycemic control and the rate of events due to diabetes in people with diabetes from different types and age groups. Methods: a retrospective cohort chart review study was carried out at three centers in the Taif region in the Kingdom of Saudi Arabia: The study was approved by an accredited centralized institutional review board. Paper or electronic medical records were included for individuals of any age with diabetes (type 1, type 2, gestational diabetes) managed with diet, insulin therapy, or/and oral antihyperglycemic medication and/or non-insulin injection therapy. The primary outcome measure was the laboratory HbA1c level as well as reduction. Secondary outcome measures were frequency of severe hypoglycemia, admission to hospital or ER visit related to diabetes complications, and severe hyperglycemia (DKA or HHS). Results: Data was analyzed from 1695 patients. The average HbA1c before using the flash glucose monitoring system was 9.60% ± 1.44% and 3 months HbA1c after using the FreeStyle LibreTM flash glucose monitoring system was 8.70% + 1.45% for a difference of -0.90% ([95% CI -0.92: -0.88];p 65 years, (p-values Conclusion: The benefits of using the FreeStyle LibreTM flash glucose monitoring system are self-evident in reducing HbA1c and events due to hyperglycemia or hypoglycemia.

关键词： FreeStyle LibreTM Flash Glucose Monitoring System Diabetes HbA1C Hypoglycemia Diabetic Ketoacidosis Hyperglycemic Hyperosmolar State

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Aquatic Ecosystem and Biodiversity: A Review

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Open Journal of Ecology 2019年第1期9卷 1-13页

作者： Sufia Irfan Aishah mohammed Motir alatawi Biology Department Faculty of Science College of Science University of Tabuk Tabuk KSA

Aquatic ecosystems support a substantial source of the earth’s biological diversity. They are an essential reservoir and share an enormous proportion of earth’s biological productivity. Both aquatic resources and its biodiversity are interrelated to each other and they perform a myriad of functions and are valuable and essential for the sustainability of biotic communities. Aquatic biodiversity in both freshwater and marine environments are under continuous decline because of overexploitation of species, introduced exotic plant or animal, pollution sources from cities, industries and agricultural zones, loss and changes in ecological niche. Their conservation and management in the form of bio reserve points and bioregional management and worldwide monitoring are needed for the protection of the aquatic biodiversity. This review is presenting information on biodiversity in aquatic habitats and their resources, in marine and fresh water ecosystems, their importance conservation and restoration mechanisms.

关键词： Aquatic Ecosystem Biodiversity Conservation Restoration

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