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Elevating Localization Accuracy inWireless Sensor Networks: A Refined DV-Hop Approach

Computers, Materials and Continua 2024年第1期81卷 1511-1528页

作者： Ejaz, Muhammad Aamer Bakar, Kamalrulnizam Abu Isnin, Ismail Fauzi Bin Isyaku, Babangida Eisa, Taiseer Abdalla Elfadil Abdelmaboud, Abdelzahir elnour, asma abbas hassan Department of Computer Science Faculty of Computing Universiti Technologi Malaysia Johor Bahru 81310 Malaysia Department of Computer Science Faculty of Computing and Information Technology Sule Lamido University P.M.B. 048 Kafin Hausa 741103 Nigeria Department of Information Systems-Girls Section King Khalid University Mahayil 62529 Saudi Arabia Humanities Research Center Sultan Qaboos University Muscat 123 Oman

Localization is crucial in wireless sensor networks for various applications, such as tracking objects in outdoor environments where GPS (Global Positioning System) or prior installed infrastructure is unavailable. However, traditional techniques involve many anchor nodes, increasing costs and reducing accuracy. Existing solutions do not address the selection of appropriate anchor nodes and selecting localized nodes as assistant anchor nodes for the localization process, which is a critical element in the localization process. Furthermore, an inaccurate average hop distance significantly affects localization accuracy. We propose an improved DV-Hop algorithm based on anchor sets (AS-IDV-Hop) to improve the localization accuracy. Through simulation analysis, we validated that the ASIDV- Hop proposed algorithm is more efficient in minimizing localization errors than existing studies. The ASIDV- Hop algorithm provides an efficient and cost-effective solution for localization inWireless Sensor Networks. By strategically selecting anchor and assistant anchor nodes and rectifying the average hop distance, AS-IDV-Hop demonstrated superior performance, achieving a mean accuracy of approximately 1.59, which represents about 25.44%, 38.28%, and 73.00% improvement over other algorithms, respectively. The estimated localization error is approximately 0.345, highlighting AS-IDV-Hop's effectiveness. This substantial reduction in localization error underscores the advantages of implementing AS-IDV-Hop, particularly in complex scenarios requiring precise node localization. © 2024 The Authors. Published by Tech Science Press.

关键词： Global positioning system

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Comparative Studies between Picard’s and Taylor’s Methods of Numerical Solutions of First Ordinary Order Differential Equations Arising from Real-Life Problems

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Journal of Applied Mathematics and Physics 2024年第3期12卷 877-896页

作者： Khalid Abd Elrazig Awad Alla elnour Department of Mathematics Preparatory Deanship Najran University Najran Kingdom of Saudi Arabia

To solve the first-order differential equation derived from the problem of a free-falling object and the problem arising from Newton’s law of cooling, the study compares the numerical solutions obtained from Picard’s and Taylor’s series methods. We have carried out a descriptive analysis using the MATLAB software. Picard’s and Taylor’s techniques for deriving numerical solutions are both strong mathematical instruments that behave similarly. All first-order differential equations in standard form that have a constant function on the right-hand side share this similarity. As a result, we can conclude that Taylor’s approach is simpler to use, more effective, and more accurate. We will contrast Rung Kutta and Taylor’s methods in more detail in the following section.

关键词： First-Order Differential Equations Picard Method Taylor Series Method Numerical Solutions Numerical Examples MATLAB Software

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Mental Health Consequences among Sudanese Due to the Armed Conflicts and Civil Unrest of 2023: One Year Later

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Journal of Biosciences and Medicines 2024年第4期12卷 21-37页

作者： Sahar Moawia Balla elnour Nahla Yousif Osman Mohammed Saeed Awadia Babiker Mohammed Osman Abeer Alawad hassan Eman Mohamed Nour Hamad Alneel Mustafa Rowa Abdelmonem Sidig Hamato Malaz Mohamed Khair Alsafi Mohamed Amna Alnaim Mohamed Ahmed Osman Awab Abdelbagi Mustafa Ahmed Jalal Abdelrasool hassan Eltaib Department of Family Medicine Health Gates Riyadh Saudi Arabia Family Medicine Department Ultracare Home Health Care Riyadh Saudi Arabia Psychiatic Department Erada Hospital and Mental Health Alkharj Saudi Arabia Family Medicine Department Ahmed Gasim Diabetic Center Portsudan Sudan QCHP Qatar Qatar Primary Care Najran Health Cluster Najran Saudi Arabia Emergency Department Best Care Hospital Khartoum Sudan Family Medicine Department Mouwasat Hospital Khobar Saudi Arabia

Aim: To investigate depression, anxiety, PTSD, and insomnia levels among Sudanese citizens after a year has passed since the start of Armed Forces conflict in Sudan. Methods: An online survey was distributed. It is composed of five parts, covering the following areas: 1) sociodemographic data;2) depression assessment;3) generalized anxiety disorder assessment;4) post-traumatic stress disorder assessment;and 5) insomnia assessment. Statistical Package for Social Sciences version 27 was used for data analysis;frequency and percentage were used to describe the qualitative variables. Spearman’s correlation analysis and Chi-square test were used for correlation and association analysis;a P-value equal to or less than 0.05 was considered statistically significant. Results: The study included 283 participants, primarily female (76.0%), with a mean age of 35.26 ± 6.96 years. The majority of participants were married (50.5%) and had a university level of education (50.2%). At the start of the war, 70.3% of participants were inside the war zones, and at the time of data collection, 73.5% were outside Sudan. The length of stay in the war zone ranged from 1 to 300 days, with a mean of 48.59 ± 70.284 days. Additionally, 63.3% of participants stated that they did not receive any form of mental health intervention, and the remaining did not provide an answer. There was a high prevalence of moderate-severe depression (50.5%), moderate anxiety (35.3%), PTSD (56.5%), and sub-threshold insomnia (53.4%) among the participants. Correlation analyses revealed associations between demographic factors such as sex, age, marital status, and education and mental health issues. Notably, female participants showed a higher prevalence of PTSD (53.0%) compared to male participants (67.6%). Conclusions: There is a substantial impact of war-related trauma on mental health, revealing a high prevalence of moderate-severe depression, moderate anxiety, PTSD, and sub-threshold insomnia among the particip

关键词： Sudan War Conflict Mental Health

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Artificial Intelligence-Based Fusion Model for Paddy Leaf Disease Detection and Classification

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Computers, Materials & Continua 2022年第7期72卷 1391-1407页

作者： Ahmed SAlmasoud Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Mesfer Al Duhayyim asma abbas hassan elnour Manar Ahmed Hamza Abdelwahed Motwakel Abu Sarwar Zamani Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Systems College of Science and ArtsKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAflaj16828Saudi Arabia Computer Science Department Community College-Girls SectionKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

In agriculture,rice plant disease diagnosis has become a challenging issue,and early identification of this disease can avoid huge loss incurred from less crop *** of the recently-developed computer vision and Deep Learning(DL)approaches can be commonly employed in designing effective models for rice plant disease detection and classification *** this motivation,the current research work devises an Efficient Deep Learning based FusionModel for Rice Plant Disease(EDLFM-RPD)detection and *** aim of the proposed EDLFM-RPD technique is to detect and classify different kinds of rice plant diseases in a proficient *** addition,EDLFM-RPD technique involves median filtering-based preprocessing and K-means segmentation to determine the infected *** study also used a fusion of handcrafted Gray Level Co-occurrence Matrix(GLCM)and Inception-based deep features to derive the ***,Salp Swarm Optimization with Fuzzy Support Vector Machine(FSVM)model is utilized for *** order to validate the enhanced outcomes of EDLFM-RPD technique,a series of simulations was *** results were assessed under different *** obtained values infer the improved performance of EDLFM-RPD technique over recent approaches and achieved a maximum accuracy of 96.170%.

关键词： Rice plant disease classification model artificial intelligence deep learning fusion model parameter optimization

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Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

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Computers, Materials & Continua 2023年第5期75卷 3239-3255页

作者： Majdy M.Eltahir Adil Yousif Fadwa Alrowais Mohamed K.Nour Radwa Marzouk Hatim Dafaalla asma abbas hassan elnour Amira Sayed A.Aziz Manar Ahmed Hamza Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Arts and Science Najran UniversitySharourahSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura 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 Applied SciencesKing Khalid UniversityMuhayil63772Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event *** is especially applicable in the case of elderly or disabled people who live self-reliantly in their *** sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during *** is one of the most important problems confronted by older people and people with movement *** previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled ***,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor ***,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s *** this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)*** presented IWODL-FDDP model aims to identify the fall events to assist disabled *** presented IWODLFDDP model applies an image filtering approach to pre-process the ***,the EfficientNet-B0 model is utilized to generate valuable feature vector ***,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall ***,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the *** experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.

关键词： Fall detection disabled people deep learning improved whale optimization assisted living

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Effect of Diabetes Self-Management Education on Glycaemic Control in Sudanese Adults with Type 2 Diabetes

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Journal of Biosciences and Medicines 2024年第3期12卷 316-327页

作者： Sahar Moawia Balla elnour Tayseer Abdelmotalib Ahmed Taha Haiam Abdalla Wadatalla Ziryab Zainelabdin Mohamed Elmahdi Marwah Isam Abdulmajeed Mohammedahmed Rowa Abdelmonem Sidig Hamadto Nahla Yousif Osman Mohammed Saeed Omnia Mubarak Saad Abdallah Sulafa Abdelbagi Mustafa Ahmed Hanady Abdelhameed Ahmed Mohamed Sarah Khalil Fathi Khalil Family Medicine Health Gates Primary Care Riyadh SAU Family Medicine Dhaman Health Assurance Hospitals Company Kuwait KWT Family Medicine First Health Cluster Riyadh SAU Emergency Department Sheikh Khalifa Medical City Abudahbi ARE Family Medicine University of Medical Sciences and Technology Khartoum SDN Family Medicine Sudan Medical Specialization Board-Sudan Khartoum SDN Family Medicine Ultra Care Home Care Company Riyadh SAU Medicine Department Health Gates Primary Care Riyadh SAU Family Medicine Mouwasat Hospital Madinah SAU

Research Background: The high prevalence of diabetes in Sudan, estimated at 16%, highlights the importance of effective health education in diabetes management. Diabetes self-management education has been identified as a crucial tool in enhancing the knowledge, attitudes, and abilities necessary for self-management among individuals with diabetes. Aim: To assess the impact of diabetes self-management education on medication adherence and glycemic control in Sudanese adults with type 2 diabetes before and 3 months after the DSME intervention. Method: The study was conducted in Sudan between September 2022 and March 2023, it was an interventional, one-group, pre- and post-test study that aimed to assess the impact of diabetes self-management education (DSME) on medication adherence and diabetes control in Sudanese adults with type 2 diabetes. The research was conducted in primary health care centers in six cities in Sudan and involved 244 participants. The data entry and statistical analysis were conducted using the Statistical Package for Social Sciences version 27.0. A paired t test was used for analysis. Results: The study included 244 participants, 67% of whom were males. The age mean ± SD was 48.6 ± 9.3 years, and 85.3% of participants were married. Age at onset of diabetes mean ± SD was 40.60 ± 7.81 years;44.6% had diabetes for less than 5 years;and 84.1% had a positive family history of diabetes mellitus. The levels of poor, low, and partial adherence to medication decreased by 8.2%, 4%, and 20.6%, respectively, after the intervention. The levels of good and high medication regime adherence increased by 13% and 19.8%, respectively;BMI decreased by 1.1 ± 0.73 kg/m2 (p = 0.005). The fasting blood sugar decreased by 69 ± 32.9 mg/dl (p = 0.049), and the glycated hemoglobin decreased by 1.21 ± 0.28% (p = 0.001). Conclusions: The findings of this study reinforce the importance of patient education in improving glycemic control and enhancing self-management

关键词： Sudan Adherence Intervention Education Self-Management Diabetes

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Prevalence of Spinal and Bony Structural Disorders in Saudi Adult Using MRI in Different Genders

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Open Journal of Medical Imaging 2022年第3期12卷 131-137页

作者： Hanan elnour Department of Radiological Sciences College of Applied Medical Sciences Taif University Taif Saudi Arabia

Background: Magnetic resonance imaging is the primary imaging modality for the evaluation of spinal cord and spinal column disorder. Aims: to assess the prevalence of bony structure and spinal disorders in the Saudi population and to find a correlation between patient age and gender. Material and Methods: A retrospective study was conducted using magnetic resonance imaging in Al-Taif city from November 2020 to February 2021 at King Abdul-Aziz Specialist Hospital and King Faisal Hospital in Taif City, Kingdom of Saudi Arabia, to assess the prevalence of bony structure and spinal disorders in the Saudi population. The data was collected after gaining ethical approval from the directorate of health affairs in Taif’s administration of research and studies, and then analyzed using SPSS version 25 to determine the frequency and percentage of disorder. To check if there was a significant difference between the two groups, the Pearson’s chi square test was utilized. Results: One hundred young adults underwent MR examination of the spine. The results show that the most common age group affected by spinal disorders is over 50 years (53%), the most common bony structural spinal disorders are straightening 59%, followed by lordosis (20%), and the most common disc disorders are disc bulges (15%), and the most common degenerative changes are spondylo-degenerative changes (21%), and there is no significant correlation between genders and MRI findings (p-value). Conclusion: The study found that straightening is the most prevalent MRI-diagnosed spine disorder, followed by degenerative illnesses and that there is no significant association between gender and the type of MRI-diagnosed spinal disorders.

关键词： MRI Spinal Disorders Gender

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Assessment of Image Quality Parameters for Computed Tomography in Sudan

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Open Journal of Radiology 2017年第1期7卷 75-84页

作者： Hanan elnour Hussein Ahmed hassan Ahmed Mustafa Hamid Osman Sultan Alamri Ali Yasen Alzaiem Alazhari University College of Radiological Science and Medical Imaging Khartoum Nort Sudan College of ALGHAD (Dammam) Girls AInfront of Tamimi dizziness or Arab Open University Dammam KSA Sudan University College of Medical Radiological Science Khartoum Sudan Taif University College of Applied Medical Science Taif KSA Taif University College of Medicine Taif KSA

X-ray-computed tomography (CT) has become one of the most important investigation procedures worldwide. The study aimed to assess image quality parameters, mainly noise, and radiation doses during abdominal examination. This study examined the diagnostic parameters (kilo voltage, tube current time product, slice thickness, and pitch) and their effects on image quality as well as the radiation doses received from computed tomography scanners using phantom. The study carried out in four CT centers in Sudan. The study applied prospective and experimental methods. The study demonstrated there was a linear correlation between diagnostic parameters and image noise. The reduction in milli-ampere second and peak kilo voltage increased the image noise. Moreover increasing the pitch led to an increase in the image noise, whereas increasing the slice thickness, reduced the image noise. There was also a linear relationship between kilo voltage and radiation dose at Elnileen diagnostic center characterized by an increase kilo voltages values which led to an increase in the radiation dose by 92% and a reduction in the image noise by 83%. However, at Antalya medical center, increasing in kilo voltage values led to an increase in the radiation dose by 35% and a reduction in the image noise by 26%. Also increasing in milli-ampere second values led to an increase in the radiation dose by 49% and a reduction in the image noise by 46% in a phantom compared with an increase in radiation dose by 82% and a reduction in the image noise by 51% in patients .The study found that an optimal protocol for adult abdominal scan at Antalya medical center was 4.22HU for image noise and 10.45 mGy for radiation dose when using 120 kVp, 300 mAs, 5 mm slice thickness and pitch of 0.8. At Elnileen diagnostic center, however, the optimal protocol was 5.4 HU for image noise and 5.4 mGy for radiation dose using 130 kVp, 50 mAs, 10 mm slice thickness and pitch of 2. In addition, the quality control tests for

关键词： CT Image Quality Patient Dose

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Drift DetectionMethod Using DistanceMeasures and Windowing Schemes for Sentiment Classification

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Computers, Materials & Continua 2023年第3期74卷 6001-6017页

作者： Idris Rabiu Naomie Salim Maged Nasser Aminu Da’u Taiseer Abdalla Elfadil Eisa Mhassen elnour Elneel Dalam School of Computing Univerti Teknologi MalaysiaJohor81310Malaysia UTM Big Data Centre Ibnu Sina Institute for Scientific and Industrial ResearchUniversiti Teknologi MalaysiaJohor81310Malaysia Ibrahim Badamasi Babangida University LapaiPMB 11Niger SteateNigeria UNITAR Graduate School UNITAR International UniversityTierra CrestJln SS6//3Petaling Jaya47301SelangorMalaysia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Mathematics-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online *** to changes in data distribution,commonly referred to as concept drift,mining this data stream is a challenging problem for *** majority of the existing drift detection techniques are based on classification errors,which have higher probabilities of false-positive or missed *** improve classification accuracy,there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data *** paper presents an adaptive unsupervised learning technique,an ensemble classifier based on drift detection for opinion mining and sentiment *** improve classification performance,this approach uses four different dissimilarity measures to determine the degree of concept drifts in the data *** a drift is detected,the proposed method builds and adds a new classifier to the *** add a new classifier,the total number of classifiers in the ensemble is first checked if the limit is exceeded before the classifier with the least weight is removed from the *** this end,a weighting mechanism is used to calculate the weight of each classifier,which decides the contribution of each classifier in the final classification *** experiments were conducted on real-world datasets and the resultswere evaluated on the false positive rate,miss detection rate,and accuracy *** proposed method is also compared with the state-of-the-art methods,which include DDM,EDDM,and PageHinkley with support vector machine(SVM)and Naive Bayes classifiers that are frequently used in concept drift detection *** all cases,the results show the efficiency of our proposed method.

关键词： Data streams sentiment analysis concept drift ensemble classification adaptive window

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Comparative study of the characterisation and extraction techniques of polyphenolic compounds from Acacia seyal gum

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Food Quality and Safety 2022年第1期6卷 24-33页

作者： Ahmed A.M.elnour Mohamed E.S.Mirghani Nassereldeen A.Kabbashi Khalid Hamid Musa Fahimeh Shahabipour Nureddin Ashammakhi Nour Hamid Abdurahman International Institute for Halal Research and Training International Islamic University MalaysiaKuala LumpurMalaysia Bioenvironmental Engineering Research Centre Biotechnology Engineering DepartmentKuliyah of EngineeringInternational Islamic University MalaysiaKuala LumpurMalaysia Institute of Gum Arabic&Desertification Studies University of KordofanElobiedSudan Department of Food Science and Human Nutrition College of Agriculture and Veterinary MedicineQassim UniversityBuraydahKingdom of SaudiArabia Skin Research Centre Shahid Beheshti University of Medical SciencesTehranIran Department of Bioengineering Henry Samueli School of EngineeringUniversity of CaliforniaLos AngelesCAUSA Department of Biomedical Engineering College of EngineeringMichigan State UniversityEast LansingMIUSA Centre of Excellence for Advanced Research in Fluid Flow University Malaysia PahangGambangMalaysia

Background Acacia seyal gum(ASG)is an abundant source of natural polyphenolic compounds(NPPCs)and antioxidant activity with numerous benefits and is often used in cancer *** type of extraction technique can significantly impact the yield and isolation of NPPCs from *** traditional use of maceration extraction reportedly yields fewer *** This study investigated five extraction techniques for NPPCs and ASG antioxidant activity,namely:homogenisation,shaking,ultrasonication,magneticstirring,*** and methods The evaluation of the antioxidant activity(AoA)of the extracted NPPCs from ASG used five assays,namely:total flavonoids content,Folin-Ciocalteu index,2,2-diphenyl-1-picrylhydrazyl radical scavenging activity,ferric reducing antioxidant power,and cupric *** To minimise the data set dimensionality requires principal component *** ultrasonic and maceration techniques were the best techniques to extract NPPCs and examine the AoA of ASG,with a high correlation between the NPPCs and ***,the maceration process was slow(12 h)compared to ultrasonication(1 h).Slow extraction can result in a decline of the NPPCs due to polyphenol oxidase-enzyme and impact *** These findings provide an essential guide for the choice of extraction techniques for the effective extraction of NPPCs from ASG and other plant materials.

关键词： Polyphenolic extraction gum Arabic comparison of techniques principal component analysis ultrasonication

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