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A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

Computer Systems Science & Engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud mohammed Al-Sarem Lhoussain Bahatti Faisal Saeed mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

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Vehicle Detection and Tracking in UAV Imagery via YOLOv3 and Kalman Filter

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Computers, Materials & Continua 2023年第7期76卷 1249-1265页

作者： Shuja Ali Ahmad Jalal mohammed Hamad Alatiyyah Khaled Alnowaiser Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-si15073Gyeonggi-doKorea

Unmanned aerial vehicles(UAVs)can be used to monitor traffic in a variety of settings,including security,traffic surveillance,and traffic *** academics have been drawn to this topic because of the challenges and the large variety of *** paper proposes a new and efficient vehicle detection and tracking system that is based on road extraction and identifying objects on *** is inspired by existing detection systems that comprise stationary data collectors such as induction loops and stationary cameras that have a limited field of view and are not *** goal of this study is to develop a method that first extracts the region of interest(ROI),then finds and tracks the items of *** suggested system is divided into six *** photos from the obtained dataset are appropriately georeferenced to their actual locations in the first phase,after which they are all *** ROI,or road and its objects,are retrieved using the GrabCut method in the second *** third phase entails data *** segmented images’noise is eliminated using Gaussian blur,after which the images are changed to grayscale and forwarded to the following stage for additional morphological *** YOLOv3 algorithm is used in the fourth step to find any automobiles in the *** that,the Kalman filter and centroid tracking are used to perform the tracking of the detected *** Lucas-Kanade method is then used to perform the trajectory analysis on the *** suggested model is put to the test and assessed using the Vehicle Aerial Imaging from Drone(VAID)*** detection and tracking,the model was able to attain accuracy levels of 96.7%and 91.6%,respectively.

关键词： Kalman filter georeferencing object detection object tracking YOLO

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Secure Communication Scheme based on A New Hyperchaotic System

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Computers, Materials & Continua 2022年第10期73卷 1019-1035页

作者： Khaled Benkouider Aceng Sambas Ibrahim mohammed Sulaiman Mustafa Mamat Kottakkaran Sooppy Nisar Non Destructive Testing Laboratory Automatic DepartmentJijel UniversityBP.9818000JijelAlgeria Department of Mechanical Engineering Universitas Muhammadiyah TasikmalayaTasikmalayaWest Java46196Indonesia School of Quantitative Sciences College of Art and SciencesUniversiti Utara MalaysiaSintok06010KedahMalaysia Faculty of Informatics and Computing Universiti Sultan Zainal AbidinBesut Campus22200Kuala BesutTerengganuMalaysia Department of Mathematics College of Arts and SciencesPrince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

This study introduces a new continuous time differential system,which contains ten terms with three quadratic *** new system can demonstrate hyperchaotic,chaotic,quasi-periodic,and periodic behaviors for its different parameter *** theoretical and numerical analysis are investigated to confirm the complex hyperchaotic behavior of our proposed model using many tools that include Kaplan-Yorke dimension,equilibrium points stability,bifurcation diagrams,and Lyapunov *** means of Multisim software,the authors also designed an electronic circuit to confirm our proposed systems’physical *** and Multisim simulation results excellently agree with each other,which validate the feasibility of our new ten terms hyperchaotic system and make it very desirable to use in different domains especially in chaotic-based ***,by employing the drive response synchronisation,we developed a secure communication strategy for the proposed *** from the proposed scheme show that the proposed approach was successful in completing the encryption and decryption procedure.

关键词： Hyperchaotic system synchronization circuit design secure communication system

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Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining

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Intelligent Automation & Soft Computing 2023年第6期36卷 3121-3137页

作者： Najm Alotaibi Badriyya B.Al-onazi Mohamed K.Nour Abdullah Mohamed Abdelwahed Motwakel Gouse Pasha mohammed Ishfaq Yaseen mohammed Rizwanullah Prince Saud AlFaisal Institute for Diplomatic Studies Riyadh13369Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16242Saudi Arabia

Opinion Mining(OM)studies in Arabic are limited though it is one of the most extensively-spoken languages *** the interest in OM studies in the Arabic language is growing among researchers,it needs a vast number of investigations due to the unique morphological principles of the *** OM studies experience multiple challenges owing to the poor existence of language sources and Arabic-specific linguistic *** comparative OM studies in the English language are wide and ***,comparative OM studies in the Arabic language are yet to be established and are still in a nascent *** unique features of the Arabic language make it essential to expand the studies regarding the Arabic *** contains unique featuressuchasdiacritics,elongation,*** study proposes a Political Optimizer with Probabilistic Neural Network-based Comparative Opinion Mining(POPNN-COM)model for the Arabic *** proposed POPNN-COM model aims to recognize comparative and non-comparative texts in Arabic in the context of social ***,the POPNN-COM model involves different levels of data pre-processing to transform the input data into a useful ***,the pre-processed data is fed into the PNN model for classification and recognition of the data under different class *** last,the PO algorithm is employed for fine-tuning the parameters involved in this model to achieve enhanced *** proposed POPNN-COM model was experimentally validated using two standard datasets,and the outcomes established the promising performance of the proposed POPNN-COM method over other recent approaches.

关键词： Comparative opinion mining Arabic text social media parameter tuning machine learning political optimizer

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Binary Archimedes Optimization Algorithm for Computing Dominant Metric Dimension Problem

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Intelligent Automation & Soft Computing 2023年第10期38卷 19-34页

作者： Basma Mohamed Linda Mohaisen mohammed Amin Mathematics and Computer Science Department Faculty of ScienceMenoufia UniversityShebin Elkom32511Egypt Faculty of Computer and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia

In this paper,we consider the NP-hard problem of finding the minimum dominant resolving set of graphs.A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B.A resolving set is dominating if every vertex of G that does not belong to B is a neighbor to some vertices in *** dominant metric dimension of G is the cardinality number of the minimum dominant resolving *** dominant metric dimension is computed by a binary version of the Archimedes optimization algorithm(BAOA).The objects of BAOA are binary encoded and used to represent which one of the vertices of the graph belongs to the dominant resolving *** feasibility is enforced by repairing objects such that an additional vertex generated from vertices of G is added to B and this repairing process is iterated until B becomes the dominant resolving *** is the first attempt to determine the dominant metric dimension problem *** proposed BAOA is compared to binary whale optimization(BWOA)and binary particle optimization(BPSO)*** results confirm the superiority of the BAOA for computing the dominant metric dimension.

关键词： Dominant metric dimension archimedes optimization algorithm binary optimization alternate snake graphs

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Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

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Computers, Materials & Continua 2022年第2期70卷 2319-2346页

作者： Buddhadeva Sahoo Sangram Keshari Routray Pravat Kumar Rout mohammed M.Alhaider Department of Electrical Engineering Siksha‘O’Anusandhan UniversityOdisha751030India Department of Electrical Electronics Engineering Siksha‘O’Anusandhan UniversityOdisha751030India College of Engineering atWadi Addawaser Prince Sattam bin Abdulaziz University11991Saudi Arabia

This paper presents a combined control and modulation technique to enhance the power quality(PQ)and power reliability(PR)of a hybrid energy system(HES)through a single-phase 11-level cascaded H-bridge inverter(11-CHBI).The controller and inverter specifically regulate the HES and meet the load *** track optimum power,a Modified Perturb and Observe(MP&O)technique is used for ***-capacitor(UCAP)based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell *** an improved PQ and PR,a two-way current control strategy such as the main controller(MC)and auxiliary controller(AC)is suggested for the 11-CHBI *** is used to regulate the active current component through the fuzzy controller(FC),and AC is used to regulate the dc-link voltage of CHBI through a neural network-based PI controller(ANN-PI).By tracking the reference signals fromMC and AC,a novel hybrid pulse widthmodulation(HPWM)technique is proposed for the 11-CHBI *** justify and analyze the MATLAB/Simulink software-based designed model,the robust controller performance is tested through numerous steady-state and dynamic state case studies.

关键词： Ultra-capacitor 11-level cascaded H-bridge inverter hybrid energy system modified perturb and observer neural network-based PI fuzzy controller

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Multiple Pedestrian Detection and Tracking in Night Vision Surveillance Systems

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Computers, Materials & Continua 2023年第5期75卷 3275-3289页

作者： Ali Raza Samia Allaoua Chelloug mohammed Hamad Alatiyyah Ahmad Jalal Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073Korea

Pedestrian detection and tracking are vital elements of today’s surveillance systems,which make daily life safe for ***,human detection and visualization have become essential inventions in the field of computer ***,developing a surveillance system with multiple object recognition and tracking,especially in low light and night-time,is still ***,we propose a novel system based on machine learning and image processing to provide an efficient surveillance system for pedestrian detection and tracking at *** particular,we propose a system that tackles a two-fold problem by detecting multiple pedestrians in infrared(IR)images using machine learning and tracking them using particle ***,a random forest classifier is adopted for image segmentation to identify pedestrians in an *** result of detection is investigated by particle filter to solve pedestrian *** the extensive experiment,our system shows 93%segmentation accuracy using a random forest algorithm that demonstrates high accuracy for background and roof ***,the system achieved a detection accuracy of 90%usingmultiple templatematching techniques and 81%accuracy for pedestrian ***,our system can identify that the detected object is a ***,our system provided the best results compared to the state-ofart systems,which proves the effectiveness of the techniques used for image segmentation,classification,and *** presented method is applicable for human detection/tracking,crowd analysis,and monitoring pedestrians in IR video surveillance.

关键词： Pedestrian detection machine learning segmentation tracking verification

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Lie symmetry analysis,explicit solutions,and conservation laws of the time-fractional Fisher equation in two-dimensional space

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Journal of Ocean Engineering and Science 2022年第4期7卷 345-352页

作者： Rawya Al-Deiakeh Omar Abu Arqub mohammed Al-Smadi Shaher Momani Department of Mathematics Faculty of ScienceThe University of JordanAmman 11942Jordan Department of Mathematics Faculty of ScienceAl Balqa Applied UniversitySalt 19117Jordan Nonlinear Analysis and Applied Mathematics(NAAM)Research Group Department of MathematicsFaculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Applied Science Ajloun CollegeAl-Balqa Applied UniversityAjloun 26816Jordan Nonlinear Dynamics Research Center(NDRC) Ajman UniversityAjmanUnited Arab Emirates Department of Mathematics and Sciences College of Humanities and SciencesAjman UniversityAjmanUnited Arab Emirates

In these analyses,we consider the time-fractional Fisher equation in two-dimensional *** the use of the Riemann-Liouville derivative approach,the well-known Lie point symmetries of the utilized equation are ***,we overturn the fractional fisher model to a fractional differential equation of nonlinear type by considering its Lie point *** diminutive equation’s derivative is in the Erdélyi-Kober sense,whilst we use the technique of the power series to conclude explicit solutions for the diminutive equations for the first *** conservation laws for the dominant equation are built using a novel conservation *** graphical countenances were utilized to award a visual performance of the obtained ***,some concluding remarks and future recommendations are utilized.

关键词： Fractional partial differential equation Time-fractional Fisher equation Lie point symmetry Explicit power series Conservation laws

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Coxiella burnetii,the causative agent of Q fever in Saudi Arabia:molecular detection from camel and other domestic livestock

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Asian Pacific Journal of Tropical Medicine 2014年第9期7卷 715-719页

作者： Osama B.mohammed Abdulrahman A.Jarelnabi Riyadh S.Aljumaah mohammed A.Alshaikh Amel O.Bakhiet Sawsan A.Omer abdulaziz N.Alagaili Mansour F.Hussein KSU Mammals Research Chair Department of ZoologyCollege of ScienceKing Saudi University Department of Animal Production College of Food & Agricultural SciencesKing Saudi University College of Veterinary Medicine Sudan University of Science and Technology Department of Zoology College of ScienceKing Saud UniversityUniversity Centre for Women StudentsRiyadh 11495Saudi Arabia Saudi Wildlife Authority Riyadh 11575Saudi Arabia

Objective:To detect Coxiella burnetii(***)DNA in clinical specimens from camel,goats,cattle and sheep in the Kingdom of Saudi ***:A total of 367 clinical samples including blood,milk,faeces and urine were collected from different livestock and subjected to PCR amplification using primers which amplify transposon-like region and transposase ***:Positive amplification from both regions was obtained from camel,goats and cattle but not from sheep.A percentage of 10.8%samples yielded positive PCR amplification from both blood and milk,where 15 of 139 blood and 16 of 148 milk samples were *** and urine showed higher percentages of positive samples reaching 40.8%and 23.8%***:The preferred route of shedding in camel appeared to be the faeces followed by urine,while that of goats appeared to be the faeces and that of the cattle appeared to be the milk.

关键词： Coxiella burnetii Camel PCR Saudi Arabia Zoonotic disease

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Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System

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Computers, Materials & Continua 2023年第2期74卷 2889-2903页

作者： Mahmoud Ragab mohammed W.Al-Rabia Sami Saeed Binyamin Ahmed A.Aldarmahi Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Medical Microbiology and Parasitology Faculty of MedicineKing Abdulaziz UniversityJeddah 21589Saudi Arabia Health Promotion Center King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer and Information Technology Department The Applied CollegeKing Abdulaziz UniversityJeddah 21589Saudi Arabia Basic Science Department College of Science and Health ProfessionsKing Saud Bin Abdulaziz University for Health SciencesJeddah 21423Saudi Arabia King Abdullah International Medical Research Center Ministry of National Guard-Health AffairsJeddah 21423Saudi Arabia

With the increasing and rapid growth rate of COVID-19 cases,the healthcare scheme of several developed countries have reached the point of *** important and critical steps in fighting against COVID-19 is powerful screening of diseased patients,in such a way that positive patient can be treated and isolated.A chest radiology image-based diagnosis scheme might have several benefits over traditional *** accomplishment of artificial intelligence(AI)based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition *** study develops an Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19Monitoring System(IFFA-DTLMS).The proposed IFFADTLMSmodelmajorly aims at identifying and categorizing the occurrence of COVID19 on chest *** attain this,the presented IFFA-DTLMS model primarily applies densely connected networks(DenseNet121)model to generate a collection of feature *** addition,the firefly algorithm(FFA)is applied for the hyper parameter optimization of DenseNet121 ***,autoencoder-long short term memory(AE-LSTM)model is exploited for the classification and identification of *** ensuring the enhanced performance of the IFFA-DTLMS model,a wide-ranging experiments were performed and the results are reviewed under distinctive *** experimental value reports the betterment of IFFA-DTLMS model over recent approaches.

关键词： COVID-19 artificial intelligence intelligent systems deep learning decision making

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