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A Deep Real-Time Fire Prediction Parallel D-CNN Model on UDOO BOLT V8

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Computers, Materials & Continua 2022年第12期73卷 6237-6252页

作者： amal h.alharbi hanan A.hosni Mahmoud Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

hazardous incidences have significant influences on human life,and fire is one of the foremost causes of such hazard in most *** prediction and classification model from a set of fire images can decrease the risk of losing human lives and *** promotion of fire emergency can be of great ***,construction of these prediction models is relevant and *** article proposes an operative fire prediction model that depends on a prediction unit embedded in the processor UDOO BOLT V8 hardware to predict fires in real time.A fire image database is improved to enhance the images quality prior to classify them as either fire or *** proposed deep learning-based Very Deep Convolutional Networks Visual Geometry Group(VGG-16)model(Parallel VGG-16)is an enhanced version of the VGG-16 model,by incorporating parallel convolution layers and a fusion module for better *** experimental results validate the performance of the Parallel VGG-16 which achieves an accuracy of 97%,compared to the compared state-of-the-art ***,we integrate the prediction module into a UDOO BOLT V8 computer,which precisely controlled the fire alarm so that it can cautious people from fire in real *** this paper we propose a complete fire prediction model using a camera and the UDOO BOLT V8 embedded *** experiments validate the effectiveness and applicability of the proposed fire model.

关键词： Fire prediction UDOO BOLT V8 deep learning

Computerized Detection of Limbal Stem Cell Deficiency from Digital Cornea Images

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Computer Systems Science & Engineering 2022年第2期40卷 805-821页

作者： hanan A.hosni Mahmoud Doaa S.Khafga amal h.alharbi Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11047KSA

Limbal Stem Cell Deficiency(LSCD)is an eye disease that can cause corneal opacity and *** its advanced stage it can lead to a degree of visual *** involves the changing in the semispherical shape of the cornea to a drooping shape to downwards *** is hard to be diagnosed at early *** color and texture of the cornea surface can provide significant information about the cornea affected by *** such as shape and texture are very crucial to differentiate normal from LSCD *** several medical approaches exist,most of them requires complicated procedure and medical ***,in this paper,we pursued the development of a LSCD detection technique(LDT)utilizing image processing *** diagnosis of LSCD is very crucial for physicians to arrange for effective *** the proposed technique,we developed a method for LSCD detection utilizing frontal eye images.A dataset of 280 eye images of frontal and lateral LSCD and normal patients were used in this ***,the cornea region of both frontal and lateral images is segmented,and the geometric features are extracted through the automated active contour model and the spline *** the texture features are extracted using the feature selection *** experimental results exhibited that the combined features of the geometric and texture will exhibit accuracy of 95.95%,sensitivity of 97.91% and specificity of 94.05% with the random forest classifier of n=*** a result,this research developed a Limbal stem cell deficiency detection system utilizing features’fusion using image processing techniques for frontal and lateral digital images of the eyes.

关键词： Feature extraction corneal opacity geometric features computerized detection image processing

Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security

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Intelligent Automation & Soft Computing 2023年第3期35卷 2773-2787页

作者： amal h.alharbi S.Karthick K.Venkatachalam Mohamed Abouhawwash Doaa Sami Khafaga Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Electrical Electronics and Communication Engineering GITAM School of TechnologyGITAM Deemed to be UniversityBengaluru CampusKarnataka560065India Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Department of Mathematics Faculty of ScienceMansoura UniversityMansoura 35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Recent security applications in mobile technologies and computer sys-tems use face recognition for high-end *** numerous security tech-niques,face recognition is considered a high-security *** fuse and carry out face identiﬁcation as an access authority into these ***,face identiﬁcation authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized *** the existing spooﬁng detection algorithm,there was some loss in the recreation of *** research proposes an unobtrusive technique to detect face spooﬁng attacks that apply a single frame of the sequenced set of frames to overcome the above-said *** research offers a novel Edge-Net autoencoder to select convoluted and dominant features of the input diffused ***,this pro-posed method is tested with the Cross-ethnicity Face Anti-spooﬁng(CASIA),Fetal alcohol spectrum disorders(FASD)*** database has three models of attacks:distorted photographs in printed form,photographs with removed eyes portion,and video *** images are taken with three different quality cameras:low,average,and high-quality real and spoofed *** extensive experimental study was performed with CASIA-FASD,3 Diagnostic Machine Aid-Digital(DMAD)dataset that proved higher results when compared to existing algorithms.

关键词： Image processing edge detection edge net auto-encoder face authentication digital security

Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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Computer Systems Science & Engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh amal h.alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WhO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

Exploring the Prevalence and Contributing Factors of Depression among Sickle Cell Anemia Patients in Saudi Arabia’s Jazan Region

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International Journal of Mental health Promotion 2024年第5期26卷 351-359页

作者： Abdullah A.alharbi Ahmad Y.Alqassim Mohammed A.Muaddi Najat h.Aldubayyan Rana I.Abuhadi Futon A.Akoor Sarah J.Mobarki Imtenan A.Oberi Ghaidaa h.alharbi Yara Ajeebi Adnan M.Alkhayat hafiz Malhan Mohammed Bakkar Anwar M.Makeen Family and Community Medicine Department Faculty of MedicineJazan UniversityJazan45142Saudi Arabia Laboratory Department King Fahd Central HospitalMinistry of HealthJazan45142Saudi Arabia Internal Medicine Department Prince Mohammad bin Nasser HospitalMinistry of HealthJazan45142Saudi Arabia hematology Department King AbdulAziz Medical City for National GuardRiyadh11426Saudi Arabia

Sickle Cell Anemia(SCA)is a prevalent genetic condition in Saudi Arabia,particularly in the Jazan *** study’s purpose was to assess the prevalence of de-pression among individuals with SCA in this area and to identify the factors associated with this *** study involved 391 adult participants,all patients in the hematology center of Prince Mohammed bin Nasser hospital(PMNh).Data was collected through an anonymous interview questionnaire–the Arabic version of the Patient health Questionnaire-9(PhQ-9)–between March–May *** questionnaire covered socio-demographic information and variables related to the participant’s SCA history,such as pain levels,frequency of pain,hospitalization duration,and frequency of blood *** variables underwent Chi-square and One-way ANOVA testing,followed by multivariate *** study found a 42%prevalence of depression among the SCA *** significantly linked with heightened depression levels included being widowed or divorced,experiencing frequent and severe pain,and longer duration of hospital *** educational level of at least a bachelor’s degree was also a significant *** study reveals a high prevalence of depression among SCA patients in the Jazan *** underscores the need for policymakers to educate both physicians and patients about the importance of mental health in SCA *** study also highlights the need for more research into the specific causes and effects of depressive symptoms in SCA patients to inform the creation of effective management plans.

关键词： Sickle cell anemia prevalence depression public health policy Jazan region Saudi Arabia

Exploring Multi-Task Learning for Forecasting Energy-Cost Resource Allocation in IoT-Cloud Systems

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Computers, Materials & Continua 2024年第6期79卷 4603-4620页

作者： Mohammad Aldossary hatem A.alharbi Nasir Ayub Department of Computer Engineering and Information College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Al-Dawasir11991Saudi Arabia Department of Computer Engineering College of Computer Science and EngineeringTaibah UniversityMadinah42353Saudi Arabia Department of Creative Technologies Air University IslamabadIslamabad44000Pakistan

Cloud computing has become increasingly popular due to its capacity to perform computations without relying on physical infrastructure,thereby revolutionizing computer ***,the rising energy consumption in cloud centers poses a significant challenge,especially with the escalating energy *** paper tackles this issue by introducing efficient solutions for data placement and node management,with a clear emphasis on the crucial role of the Internet of Things(IoT)throughout the research *** IoT assumes a pivotal role in this study by actively collecting real-time data from various sensors strategically positioned in and around data *** sensors continuously monitor vital parameters such as energy usage and temperature,thereby providing a comprehensive dataset for *** data generated by the IoT is seamlessly integrated into the hybrid TCN-GRU-NBeat(NGT)model,enabling a dynamic and accurate representation of the current state of the data center *** the incorporation of the Seagull Optimization Algorithm(SOA),the NGT model optimizes storage migration strategies based on the latest information provided by IoT *** model is trained using 80%of the available dataset and subsequently tested on the remaining 20%.The results demonstrate the effectiveness of the proposed approach,with a Mean Squared Error(MSE)of 5.33%and a Mean Absolute Error(MAE)of 2.83%,accurately estimating power prices and leading to an average reduction of 23.88%in power ***,the integration of IoT data significantly enhances the accuracy of the NGT model,outperforming benchmark algorithms such as DenseNet,Support Vector Machine(SVM),Decision Trees,and *** NGT model achieves an impressive accuracy rate of 97.9%,surpassing the rates of 87%,83%,80%,and 79%,respectively,for the benchmark *** findings underscore the effectiveness of the proposed method in optimizing energy efficiency and enhancing the predictive

关键词： Cloud computing energy efficiency data center optimization internet of things(IoT) hybrid models

Quaternionic Monge–Ampère Measure on Pluripolar Set

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Acta Mathematica Sinica,English Series 2024年第6期40卷 1431-1457页

作者： hichame amal Saïd ASSERDA Fadoua BOUKhARI Department of Mathematics Laboratory LaREAMIRegional Centre of Trades of Education and TrainingKenitraMorocco Ibn Tofail University Faculty of SciencesDepartment of MathematicsPO 242 KenitraMorroco

In this paper, we prove that in a hyperconvex domain Ω in h^(n), if a non-negative Borel measure is dominated by a quaternionic Monge–Ampère measure, then it is a quaternionic Monge–Ampère measure of a function i... 详细信息

关键词： Quaternion space Monge-Amp`ere operator plurisubharmonic function

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad hoc Networks Using Blockchain Based Smart Contracts

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 2005-2021页

作者： Abdulatif Alabdulatif Mada alharbi Abir Mchergui Tarek Moulahi Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Higher Institute of Management of GabesGabes UniversityGabes6029Tunisia Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Faculty of Science and Technology of Sidi Bouzid Kairouan UniversityKairouan3131Tunisia

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management *** advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer *** provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road ***,ITS suffers from routing issues at the network layer when utilising Vehicular Ad hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological *** may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS *** this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between ***-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed *** results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

关键词： Blockchain data privacy machine learning routing attacks smart contract VANET

Video Summarization Approach Based on Binary Robust Invariant Scalable Keypoints and Bisecting K-Means

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Computers, Materials & Continua 2024年第3期78卷 3565-3583页

作者： Sameh Zarif Eman Morad Khalid Amin Abdullah.alharbi Wail S.Elkilani Shouze Tang Department of Information Technology Faculty of Computers and InformationMenoufia UniversityMenoufia32511Egypt Department of Artificial Intelligence Faculty of Artificial IntelligenceEgyptian Russian UniversityBader11829Egypt Department of Computer Science Community CollegeKing Saud UniversityRiyadh11362Saudi Arabia College of Applied Computer Science King Saud UniversityAl-Muzahmiya19676Saudi Arabia School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

Due to the exponential growth of video data,aided by rapid advancements in multimedia *** became difficult for the user to obtain information from a large video *** process of providing an abstract of the entire video that includes the most representative frames is known as static video *** method resulted in rapid exploration,indexing,and retrieval of massive video *** propose a framework for static video summary based on a Binary Robust Invariant Scalable Keypoint(BRISK)and bisecting K-means clustering *** current method effectively recognizes relevant frames using BRISK by extracting keypoints and the descriptors from video *** video frames’BRISK features are clustered using a bisecting K-means,and the keyframe is determined by selecting the frame that is most near the cluster *** applying any clustering parameters,the appropriate clusters number is determined using the silhouette *** were carried out on a publicly available open video project(OVP)dataset that contained videos of different *** proposed method’s effectiveness is compared to existing methods using a variety of evaluation metrics,and the proposed method achieves a trade-off between computational cost and quality.

关键词： BRISK bisecting K-mean video summarization keyframe extraction shot detection