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Knowledge, Attitude, and Practice of Using Helmets in Children amongst Parents to Prevent Head Injuries: A Cross-Sectional Study in Riyadh, Saudi Arabia

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Open Journal of Pediatrics 2024年第2期14卷 255-265页

作者： Turki Salah Aldeen Bukhari Abdullah Yahya Aldhban Anas Abdulrahman Alqasem Dona Jamal Al Hatlani Hareth Aldosaimani Hamad A. Al Madi khalid alqahtani Prince Sultan Military Medical City Riyadh Saudi Arabia Emergency Department Disaster Medicine and Emergency Preparedness Prince Sultan Military Medical City Riyadh Saudi Arabia Emergency Department Asir Central Hospital Abha Saudi Arabia

Objectives: The primary objective was to characterize the range of Knowledge, Attitude, and Practice (KAP) of Helmet use in children amongst parents to prevent head injuries and death. Methods: This is a cross-sectional study, done by online survey using a snowball sampling technique, the number of included responses were 386 parents (Male and female) living in Riyadh Aged 21 - 60 years old or above. Results: The study showed that there is a difference in Parents’ belief in the importance of helmet use while riding a Bicycle vs Motorcycle/Quad bike and that was affected by parents’ education level, almost all the people who answered the survey (76.7%) agree that it is important for their children to wear a helmet when riding both a Bicycle and a Motorcycle or Quadbike with a cumulative percentage of (93.8%). And almost all agreed on multiple approaches to help increase helmet use be it by forcing rental shops to give out helmets, forcing sellers to recommend the use of helmets, increasing awareness campaigns, and imposing fines for not wearing helmets. Conclusions: This study is the first to explore Family helmet use while riding Bicycles and Motorcycles/Quad bikes. Although Parent’s belief in the importance of helmet use for their children was high, it is clear that the level of practice is low. With that the risk of head injuries might be high, our findings suggest that safety interventions for increasing pediatric helmet use are needed to increase helmet use and reduce the risk of head injury and hospitalization.

关键词： Head Trauma Head Injury Helmet Bicycle Motorcycle Quad Bike KAP Knowledge Attitude Practice

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Awareness and Behaviour Related to Orthodontic Treatment among School Children in Aseer Region, Kingdom of Saudi Arabia

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Open Journal of Stomatology 2019年第4期9卷 87-94页

作者： M. Zakirulla Hussain Almubarak Sahar N. Fageeh Abeer A. Alghothimi Saleh khalid alqahtani Faris Mohammed alqahtani Fahad Thamer Alshahrani Department of Pediatric Dentistry and Orthodontic Sciences College of Dentistry King Khalid University Abha KSA Department of the Diagnostic Science and Oral Biology (DDS) College of Dentistry King Khalid University Abha KSA

Background: Awareness of malocclusion and the need to make corrections have increasingly become prevalent among the young population. In the period of adolescence, physical appearance is crucial in the construction of personal identity, including one’s relationship with one’s own body. Orthodontic treatment includes improved oral health and enhanced psychological wellbeing. Early orthodontic treatment for children will be crucial to improving oral health. The present study aims to assess the awareness towards orthodontic treatment among school children’s of Aseer region, Saudi Arabia. Materials and Methods: A total of 835 (450 boys and 385 girls) school children’s, of age group between 10 - 15 years were included in the study. A total of 16 schools in the all Aseer region were surveyed during January to May 2018. A pre-structured self-administered questionnaire consisting of 12 questions with multiple answers were given to the children after the clinical examination to assess their knowledge and attitude towards Orthodontic treatment. Statistical Analysis: The survey data was collected and organized into Microsoft Excel spreadsheets (Microsoft Inc., USA), and was statistically analyzed utilizing the Statistical Package for the Social Sciences version 20.0 software (IBM Inc., USA). The statistical test used here was the chi-square test and P values less than 0.05 were considered to be statistically significant (P Result: A total of 292 (65%) of males and 285 (74%) of females have heard of an orthodontist. 234 (52%) of males said that orthodontist would align their teeth. 203 (45%) and 250 (65%) of males and females respectively are aware that few teeth needed to be removed for aligning irregular teeth. Majority of the children are aware of taking braces treatment at an earlier age would improve facial appearance. 320 (83%) and 227 (59%) of female children aware of that irregular teeth can affect chewing ability and speech respectively. 261 (58%) of males knew that or

关键词： Orthodontic Treatment Malocclusion Children Oral Health Behaviour

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Integrating Transformer and Bidirectional Long Short-Term Memory for Intelligent Breast Cancer Detection from Histopathology Biopsy Images

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 443-458页

作者： Prasanalakshmi Balaji Omar alqahtani Sangita Babu Mousmi Ajay Chaurasia Shanmugapriya Prakasam Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61451Saudi Arabia College of Science and Arts in Rijal Alma King Khalid UniversityAbha61451Saudi Arabia Department of Information Technology Muffakham Jah College of Engineering and TechnologyHyderabad500034India Department of Computer Science and Business Systems Rajalakshmi Engineering CollegeThandalam602105India

Breast cancer is a significant threat to the global population,affecting not only women but also a threat to the entire *** recent advancements in digital pathology,Eosin and hematoxylin images provide enhanced clarity in examiningmicroscopic features of breast tissues based on their staining *** cancer detection facilitates the quickening of the therapeutic process,thereby increasing survival *** analysis made by medical professionals,especially pathologists,is time-consuming and challenging,and there arises a need for automated breast cancer detection *** upcoming artificial intelligence platforms,especially deep learning models,play an important role in image diagnosis and ***,the histopathology biopsy images are taken from standard data ***,the gathered images are given as input to the Multi-Scale Dilated Vision Transformer,where the essential features are ***,the features are subjected to the Bidirectional Long Short-Term Memory(Bi-LSTM)for classifying the breast cancer *** efficacy of the model is evaluated using divergent *** compared with other methods,the proposed work reveals that it offers impressive results for detection.

关键词： Bidirectional long short-term memory breast cancer detection feature extraction histopathology biopsy images multi-scale dilated vision transformer

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Contemporary Study for Detection of COVID-19 Using Machine Learning with Explainable AI

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Computers, Materials & Continua 2024年第7期80卷 1075-1104页

作者： Saad Akbar Humera Azam Sulaiman Sulmi Almutairi Omar alqahtani Habib Shah Aliya Aleryani Department of Computer Science University of KarachiKarachi75270Pakistan Department of Computing Faculty of Engineering Science and TechnologyHamdard UniversityKarachi75540Pakistan Department of Health Informatics College of Applied Medical SciencesQassim UniversityQassim51452Saudi Arabia Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia

The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic *** this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19,pneumonia,and normal conditions in chest X-ray images(CXIs)is proposed coupled with Explainable Artificial Intelligence(XAI).Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3,VGG16,and VGG19 that excel in the task of feature *** methodology is further enhanced by the inclusion of the t-SNE(t-Distributed Stochastic Neighbor Embedding)technique for visualizing the extracted image features and Contrast Limited Adaptive Histogram Equalization(CLAHE)to improve images before extraction of ***,an AttentionMechanism is utilized,which helps clarify how the modelmakes decisions,which builds trust in artificial intelligence(AI)*** evaluate the effectiveness of the proposed approach,both benchmark datasets and a private dataset obtained with permissions from Jinnah PostgraduateMedical Center(JPMC)in Karachi,Pakistan,are *** 12 experiments,VGG19 showcased remarkable performance in the hybrid dataset approach,achieving 100%accuracy in COVID-19 *** classification and 97%in distinguishing normal ***,across all classes,the approach achieved 98%accuracy,demonstrating its efficiency in detecting COVID-19 and differentiating it fromother chest disorders(Pneumonia and healthy)while also providing insights into the decision-making process of the models.

关键词： COVID-19 detection deep neural networks support vector machine CXIs InceptionV3 VGG16 VGG19 t-SNE embedding CLAHE attention mechanism XAI

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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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NPBMT: A Novel and Proficient Buffer Management Technique for Internet of Vehicle-Based DTNs

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Computers, Materials & Continua 2023年第10期77卷 1303-1323页

作者： Sikandar Khan khalid Saeed Muhammad Faran Majeed Salman A.alqahtani Khursheed Aurangzeb Muhammad Shahid Anwar Department of Computer Science Shaheed Benazir Bhutto University SheringalDir(U)Khyber Pakhtunkhwa18200Pakistan Department of Computer Science Kohsar University MurreePunjab47150Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of AI and Software Gachon UniversitySeongnam-si13120South Korea

Delay Tolerant Networks(DTNs)have the major problem of message delay in the network due to a lack of endto-end connectivity between the nodes,especially when the nodes are *** nodes in DTNs have limited buffer storage for storing delayed *** instantaneous sharing of data creates a low buffer/shortage ***,buffer congestion would occur and there would be no more space available in the buffer for the upcoming *** address this problem a buffer management policy is proposed named“A Novel and Proficient Buffer Management Technique(NPBMT)for the Internet of Vehicle-Based DTNs”.NPBMT combines appropriate-size messages with the lowest Time-to-Live(TTL)and then drops a combination of the appropriate messages to accommodate the newly arrived *** evaluate the performance of the proposed technique comparison is done with Drop Oldest(DOL),Size Aware Drop(SAD),and Drop Larges(DLA).The proposed technique is implemented in the Opportunistic Network Environment(ONE)*** shortest path mapbased movement model has been used as the movement path model for the nodes with the epidemic routing *** the simulation results,a significant change has been observed in the delivery probability as the proposed policy delivered 380 messages,DOL delivered 186 messages,SAD delivered 190 messages,and DLA delivered only 95 messages.A significant decrease has been observed in the overhead ratio,as the SAD overhead ratio is 324.37,DLA overhead ratio is 266.74,and DOL and NPBMT overhead ratios are 141.89 and 52.85,respectively,which reveals a significant reduction of overhead ratio in NPBMT as compared to existing *** network latency average of DOL is 7785.5,DLA is 5898.42,and SAD is 5789.43 whereas the NPBMT latency average is *** reveals that the proposed policy keeps the messages for a short time in the network,which reduces the overhead ratio.

关键词： Delay tolerant networks buffer management message drop policy ONE simulator NPBMT

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Intelligent Systems and Photovoltaic Cells Empowered Topologically by Sudoku Networks

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Computers, Materials & Continua 2023年第2期74卷 4221-4238页

作者： khalid Hamid Muhammad Waseem Iqbal MUsman Ashraf Akber Abid Gardezi Shafiq Ahmad Mejdal alqahtani Muhammad Shafiq Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot51310Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A graph invariant is a number that can be easily and uniquely calculated through a ***,part of mathematical graph invariants has been portrayed and utilized for relationship ***,no reliable appraisal has been embraced to pick,how much these invariants are associated with a network graph in interconnection networks of various fields of computer science,physics,and *** this paper,the study talks about sudoku networks will be networks of fractal nature having some applications in computer science like sudoku puzzle game,intelligent systems,Local area network(LAN)development and parallel processors interconnections,music composition creation,physics like power generation interconnections,Photovoltaic(PV)cells and chemistry,synthesis of chemical *** networks are generally utilized in disorder,fractals,recursive groupings,and complex *** outcomes are the normal speculations of currently accessible outcomes for specific classes of such kinds of networks of two unmistakable sorts with two invariants K-banhatti sombor(KBSO)invariants,Irregularity sombor(ISO)index,Contraharmonic-quadratic invariants(CQIs)and dharwad invariants with their reduced *** study solved the Sudoku network used in mentioned systems to improve the performance and find irregularities present in *** calculated outcomes can be utilized for the modeling,scalability,introduction of new architectures of sudoku puzzle games,intelligent systems,PV cells,interconnection networks,chemical compounds,and extremely huge scope in very large-scale integrated circuits(VLSI)of processors.

关键词： Sudoku dharwad KBSO indices CQIs network graph intelligent system photovoltaic cells

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Machine Learning Techniques for Intrusion Detection Systems in SDN-Recent Advances,Challenges and Future Directions

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 89-119页

作者： Gulshan Kumar Hamed alqahtani Shaheed Bhagat Singh State University Firozpur152024India King khalid University Abha61421Saudi Arabia

Software-Defined Networking(SDN)enables flexibility in developing security tools that can effectively and efficiently analyze and detect malicious network traffic for detecting *** Machine Learning(ML)techniques have attracted lots of attention from researchers and industry for developing intrusion detection systems(IDSs)considering logically centralized control and global view of the network provided by *** IDSs have developed using advances in machine learning and deep *** study presents a comprehensive review of recent work ofML-based IDS in context to *** presents a comprehensive study of the existing review papers in the *** is followed by introducing intrusion detection,ML techniques and their ***,we present a systematic study of recent works,discuss ongoing research challenges for effective implementation of ML-based intrusion detection in SDN,and promising future works in this field.

关键词： Controller intrusion detection intrusion detection system OpenFlow security software defined networking traffic analysis

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Deep Learning-Based Cancer Detection-Recent Developments,Trend and Challenges

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Computer Modeling in Engineering & Sciences 2022年第3期130卷 1271-1307页

作者： Gulshan Kumar Hamed alqahtani Shaheed Bhagat Singh State University FerozepurIndia King khalid University AbhaSaudi Arabia

Cancer is one of the most critical diseases that has caused several deaths in today’s *** most cases,doctors and practitioners are only able to diagnose cancer in its later *** the later stages,planning cancer treatment and increasing the patient’s survival rate becomes a very challenging ***,it becomes the need of the hour to detect cancer in the early stages for appropriate treatment and surgery *** and interpretation of medical images such as MRI and CT scans help doctors and practitioners diagnose many diseases,including cancer ***,manual interpretation of medical images is costly,time-consuming and ***,deep learning,a subset of artificial intelligence,is gaining increasing attention from practitioners in automatically analysing and interpreting medical images without their *** learning methods have reported extraordinary results in different fields due to their ability to automatically extract intrinsic features from images without any dependence on manually extracted *** study provides a comprehensive review of deep learning methods in cancer detection and diagnosis,mainly focusing on breast cancer,brain cancer,skin cancer,and prostate *** study describes various deep learningmodels and steps for applying deep learningmodels in detecting *** developments in cancer detection based on deep learning methods have been critically analysed and summarised to identify critical challenges in applying them for detecting cancer accurately in the early *** on the identified challenges,we provide a few promising future research directions for fellow researchers in the *** outcome of this study provides many clues for developing practical and accurate cancer detection systems for its early diagnosis and treatment planning.

关键词： Autoencoders(AEs) cancer detection convolutional neural networks(CNNs) deep learning generative adversarial models(GANs) machine learning

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Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

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Computers, Materials & Continua 2023年第3期74卷 5349-5367页

作者： khalid A.Alissa Mohammed Maray Areej A.Malibari Sana Alazwari Hamed alqahtani Mohamed K.Nour Marwa Obbaya Mohamed A.Shamseldin Mesfer Al Duhayyim SAUDI ARAMCO Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Mechanical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human *** the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital *** current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 *** suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image ***,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based *** proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover *** secret images,encrypted by signcryption technique,are embedded into cover ***,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax *** integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV *** proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct *** simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.

关键词： Unmanned Aerial Vehicles Artificial Intelligence emerging technologies Deep Learning Industry 4.0 image steganography

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