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YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security

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Computers, Materials & Continua 2023年第12期77卷 3697-3722页

作者： Fares Alharbi Reem Alshahrani Mohammed Zakariah amjad aldweesh Abdulrahman Abdullah Alghamdi Department of Computer Science College of Computing and ITShaqra UniversityShaqra15526Saudi Arabia Department of Computer Science College of Computers and ITTaif UniversityP.O.Box 11099Taif21944Saudi Arabia College of Computer and Information Science King Saud UniversityRiyadhSaudi Arabia

Privacy and trust are significant issues in intelligent transportation systems(ITS).Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels,optical fiber,and blockchain *** Internet of Things(IoT)is a network of connected,interconnected *** issues occasionally arise due to the amount of data ***,they have been primarily addressed by blockchain and smart contract *** there are still security issues with smart contracts,primarily due to the complexity of writing the code,there are still many challenges to consider when designing blockchain designs for the IoT *** study uses traditional blockchain technology with the“You Only Look Once”(YOLO)object detection method to accurately locate and identify license *** YOLO and blockchain technologies used for intelligent vehicle license plate recognition are promising,they have received limited research ***-time object identification and recognition would be possible by combining a cutting-edge object detection technique with a regional convolutional neural network(RCNN)built with the tensor flow core open source *** method works reasonably well for identifying any license *** Automatic License Plate Recognition(ALPR)approach delivered outstanding results in various ***,with a recognition rate of 96.2%,our system(UFPR-ALPR)surpassed the previously used technology,consisting of 4500 frames and around 150 ***,a deep learning algorithm was trained to recognize images of license plate numbers using the UFPR-ALPR ***,the license plate’s characters were complicated for standard methods to identify because of the shifting lighting *** proposed model,however,produced beneficial outcomes.

关键词： Intelligent transportation system blockchain technology license plate recognition privacy YOLO deep learning technique ALPR

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Towards Generating a Practical SUNBURST Attack Dataset for Network Attack Detection

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Computer Systems Science & Engineering 2023年第11期47卷 2643-2669页

作者： Ehab AlMasri Mouhammd Alkasassbeh amjad aldweesh Princess Summaya University for Technology AmmanJordan College of Computing and IT Shaqra UniversityShaqraSaudi Arabia

Supply chain attacks,exemplified by the SUNBURST attack utilizing SolarWinds Orion updates,pose a growing cybersecurity threat to entities ***,the need for suitable datasets for detecting and anticipating SUNBURST attacks is a significant *** present a novel dataset collected using a unique network traffic data collection methodology to address this *** study aims to enhance intrusion detection and prevention systems by understanding SUNBURST attack *** construct realistic attack scenarios by combining relevant data and attack *** dataset is validated with the J48 machine learning algorithm,achieving an average F-Measure of 87.7%.Our significant contribution is the practical SUNBURST attack dataset,enabling better prevention and mitigation *** is a valuable resource for researchers and practitioners to enhance supply chain attack *** conclusion,our research provides a concise and focused SUNBURST attack dataset,facilitating improved intrusion detection and prevention systems.

关键词： SolarWinds orion software supply-chain-attack SUNBURSTattack solar gate UNC2452

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Deep Learning ResNet101 Deep Features of Portable Chest X-Ray Accurately Classify COVID-19 Lung Infection

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Computers, Materials & Continua 2023年第6期75卷 5213-5228页

作者： Sobia Nawaz Sidra Rasheed Wania Sami Lal Hussain amjad aldweesh Elsayed Tag eldin Umair Ahmad Salaria Mohammad Shahbaz Khan Basic Health Unit Sumra Lodhran59320Pakistan Basic Health Unit 20-G ChishtianBahawalnagar62300Pakistan Doctor’s Hospital Lahore54590Pakistan Department of Computer Science&IT Neelum CampusThe University of Azad Jammu and KashmirAthmuqam13230Azad KashmirPakistan Department of Computer Science&IT King Abdullah CampusThe University of Azad Jammu and KashmirMuzaffarabad13100Azad KashmirPakistan College of Computer science and information technology Shaqra UniversityShaqra15273Saudi Arabia Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Department of Electrical Engineering University of Azad Jammu and KashmirChehla CampusMuzaffarabad13100Azad KashmirPakistan Department of Electrical Engineering Mirpur University of Science&TechnologyMirpurMuzaffarabad10250Azad KashmirPakistan Children’s National Hospital 111 Michigan AVE NWWashingtonDC20854USA

This study is designed to develop Artificial Intelligence(AI)based analysis tool that could accurately detect COVID-19 lung infections based on portable chest x-rays(CXRs).The frontline physicians and radiologists suffer from grand challenges for COVID-19 pandemic due to the suboptimal image quality and the large volume of *** this study,AI-based analysis tools were developed that can precisely classify COVID-19 lung *** available datasets of COVID-19(N=1525),non-COVID-19 normal(N=1525),viral pneumonia(N=1342)and bacterial pneumonia(N=2521)from the Italian Society of Medical and Interventional Radiology(SIRM),Radiopaedia,The Cancer Imaging Archive(TCIA)and Kaggle repositories were taken.A multi-approach utilizing deep learning ResNet101 with and without hyperparameters optimization was ***,the fea-tures extracted from the average pooling layer of ResNet101 were used as input to machine learning(ML)algorithms,which twice trained the learning *** ResNet101 with optimized parameters yielded improved performance to default *** extracted features from ResNet101 are fed to the k-nearest neighbor(KNN)and support vector machine(SVM)yielded the highest 3-class classification performance of 99.86%and 99.46%,*** results indicate that the proposed approach can be bet-ter utilized for improving the accuracy and diagnostic efficiency of *** proposed deep learning model has the potential to improve further the efficiency of the healthcare systems for proper diagnosis and prognosis of COVID-19 lung infection.

关键词： COVID-19 deep learning(DL) lung infection convolutional neural network(CNN)

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Comprehensive Review and Analysis on Facial Emotion Recognition:Performance Insights into Deep and Traditional Learning with Current Updates and Challenges

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Computers, Materials & Continua 2025年第1期82卷 41-72页

作者： amjad Rehman Muhammad Mujahid Alex Elyassih Bayan AlGhofaily Saeed Ali Omer Bahaj Artificial Intelligence&Data Analytics Lab College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia MIS Department College of Business Administration Prince Sattam Bin Abdulaziz UniversityAlKharj11942Saudi Arabia

In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry *** demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial *** study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each *** immense achievement of deep learning has resulted in a growing use of its much architecture to enhance *** review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of *** following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics *** this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further *** information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.

关键词： Face emotion recognition deep learning hybrid learning CK+ facial images machine learning technological development

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Genome-wide association analysis reveals regulatory genes for the metabolite synthesis of 2-acetyl-1-pyrroline in aromatic coconut(Cocos nucifera L.)

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Journal of Genetics and Genomics 2025年第2期52卷 179-188页

作者： Hao Ding Xiang Lv Guangzhen Zhou Xiaomei Liu Xiwei Sun Jing Li amjad Iqbal Yaodong Yang Hainan Key Laboratory of Tropical Oil Crops Biology/Coconut Research Institute Chinese Academy of Tropical Agricultural SciencesWenchangHainan 571339China Hainan Coconut International Joint Research Center WenchangHainan 571339China Ministry of Education Key Laboratory for Ecology of Tropical Islands Key Laboratory of Tropical Animal and Plant Ecology of Hainan ProvinceCollege of Life SciencesHainan Normal UniversityHaikouHainan 570228China Department of Food Science&Technology Abdul Wali Khan University Mardan23200Pakistan

Coconut(Cocos nucifera L.)is a key tropical economic tree valued for its fruit flavor,particularly 2-acetyl-1-pyrroline(2AP),a vital aroma *** enhance high-aromatic coconut breeding efforts,it is essential to deeply understand the hereditary factors governing the production of *** this study,a genome-wide association analysis identifies 32 loci that exhibit significant associations with 2AP content based on single nucleotide polymorphism(SNP)variations from 168 aromatic coconut germplasm *** analysis then pinpoints 22 candidate genes near significant loci involved in 2AP *** encoded by these genes are involved in amino acid metabolism,glycolysis,and secondary *** these,Asparagine synthetase coding gene ASN1,Gamma-glutamylcysteine synthetase coding gene GSH1,and UbiA prenyltransferase coding gene UBIA are enriched in the linkage region constructed by significant locus Chr04_*** particular,the SNP mutation of CnASN1 leads to amino acid changes in the functional region of the coding protein,potentially resulting in differences in 2AP content among haplotype *** variations in related candidate genes,particularly the gene CnASN1,provides molecular markers closely associated with 2AP synthesis for coconut breeding and offers further insights into the metabolic mechanisms of 2AP.

关键词： Aromatic coconut 2AP SNP Genome-wideassociation study(GWAS) Haplotype analysis

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HybridEdge: A Lightweight and Secure Hybrid Communication Protocol for the Edge-Enabled Internet of Things

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Computers, Materials & Continua 2025年第2期82卷 3161-3178页

作者： amjad Khan Rahim Khan Fahad Alturise Tamim Alkhalifah Department of Computer Science Abdul Wali Khan UniversityMardan23200Pakistan Department of Cybersecurity College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Engineering College of ComputerQassim UniversityBuraydahSaudi Arabia

The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the critical issues, which is the prediction of fraudulent devices, i.e., adversaries, preferably as early as possible in the IoT. In this paper, a hybrid communication mechanism is presented where the Hidden Markov Model (HMM) predicts the legitimacy of the requesting device (both source and destination), and the Advanced Encryption Standard (AES) safeguards the reliability of the transmitted data over a shared communication medium, preferably through a secret shared key, i.e., , and timestamp information. A device becomes trusted if it has passed both evaluation levels, i.e., HMM and message decryption, within a stipulated time interval. The proposed hybrid, along with existing state-of-the-art approaches, has been simulated in the realistic environment of the IoT to verify the security measures. These evaluations were carried out in the presence of intruders capable of launching various attacks simultaneously, such as man-in-the-middle, device impersonations, and masquerading attacks. Moreover, the proposed approach has been proven to be more effective than existing state-of-the-art approaches due to its exceptional performance in communication, processing, and storage overheads, i.e., 13%, 19%, and 16%, respectively. Finally, the proposed hybrid approach is pruned against well-known security attacks

关键词： Internet of Things information security authentication hidden Markov model multimedia

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Novel Feature Extractor Framework in Conjunction with Supervised Three Class-XGBoost Algorithm for Osteosarcoma Detection from Whole Slide Medical Histopathology Images

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Computers, Materials & Continua 2025年第2期82卷 3337-3353页

作者： Tanzila Saba Muhammad Mujahid Shaha Al-Otaibi Noor Ayesha amjad Rehman Khan Artificial Intelligence&Data Analytics Lab College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Center of Excellence in Cyber Security(CYBEX) Prince Sultan UniversityRiyadh11586Saudi Arabia

Osteosarcomas are malignant neoplasms derived from undifferentiated osteogenic mesenchymal cells. It causes severe and permanent damage to human tissue and has a high mortality rate. The condition has the capacity to occur in any bone;however, it often impacts long bones like the arms and legs. Prompt identification and prompt intervention are essential for augmenting patient longevity. However, the intricate composition and erratic placement of osteosarcoma provide difficulties for clinicians in accurately determining the scope of the afflicted area. There is a pressing requirement for developing an algorithm that can automatically detect bone tumors with tremendous accuracy. Therefore, in this study, we proposed a novel feature extractor framework associated with a supervised three-class XGBoost algorithm for the detection of osteosarcoma in whole slide histopathology images. This method allows for quicker and more effective data analysis. The first step involves preprocessing the imbalanced histopathology dataset, followed by augmentation and balancing utilizing two techniques: SMOTE and ADASYN. Next, a unique feature extraction framework is used to extract features, which are then inputted into the supervised three-class XGBoost algorithm for classification into three categories: non-tumor, viable tumor, and non-viable tumor. The experimental findings indicate that the proposed model exhibits superior efficiency, accuracy, and a more lightweight design in comparison to other current models for osteosarcoma detection.

关键词： Medical image processing deep learning healthcare image classification histopathology

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Progress in twin roll casting of magnesium alloys: A review

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Journal of Magnesium and Alloys 2021年第2期9卷 362-391页

作者： amjad Javaid Frank Czerwinski CanmetMATERIALS Natural Resources CanadaHamiltonOntarioL8P 0A5Canada

Twin roll casting was commercialized for a strip production from ferrous and non-ferrous alloys in the 1950 s;however,its application to magnesium has proven difficult and still creates major *** report describes global efforts in expanding manufacturing capabilities of magnesium sheet through twin roll casting path,offering many benefits,including a reduction in number of processing steps and energy *** addition to hardware design,alloy transformation during processing,product microstructure and properties,examples of successful solutions along with present technology and knowledge limitations are discussed.A particular attention is paid to developments at Canmet MATERIALS,having the only in North America pilot scale twin roll casting facility,devoted to *** are described that aim at design of new magnesium alloys,which could take advantage of unique processing conditions during twin roll casting and contribute to the overall progress in magnesium sheet manufacturing.

关键词： Twin roll casting Magnesium alloys Solidification Magnesium sheet

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Numerical simulation of compression corner flows at Mach number 9

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Chinese Journal of Aeronautics 2020年第6期33卷 1611-1624页

作者： amjad APASHA Khalid AJUHANY Department of Aerospace Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia

A hypersonic vehicle encounters a wide range of conditions during its complete flight *** flight conditions may vary from low to high Mach numbers with varying angles of *** near-wall viscous dissipation associated with flows at combined high Mach and Reynolds numbers leads to significant wall heat transfer rates and shear *** shock wave/boundary-layer interaction results in a flow separation region,which commonly augments total pressure losses in the flow and lowers the efficiency of aerodynamic control surfaces such as fins installed on a *** standard turbulence models,when used to resolve such flows,result in incorrect separation bubble size for large separated ***,it results in an inaccurate aerodynamic load,such as the wall pressures,skin friction distribution,and heat transfer *** previous studies,the application of the shock-unsteadiness correction to the standard two-equation k-ωturbulence model improved the separation bubble size leading to an accurate pressure prediction and shock definition with the assumption of constant Prandtl *** the present work,the new shock-unsteadiness modification to the k-ωturbulence model is applied to the hypersonic compression corner *** new model with variable Prandtl number is based on the model parameter,which depends upon the local density *** computed wall pressures,heat flux and flow field are compared to the experimental data.A parametric study is carried out by varying compression deflection angles,free stream Reynolds number and wall temperatures to compute the flow field and wall data accurately,particularly in the shock boundary layer interaction *** new shockunsteadiness modified k-ωmodel with variable Prandtl number shows an accurate prediction of initial pressure rise location,pressure distribution in the plateau region and heat flux in comparison to the standard k-ωmodel.

关键词： Boundary layer Expansion fan Heat transfer Hypersonic flows Separation length Shock-unsteadiness model Shock wave Turbulence model Turbulent Prandtl number

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Solitons and quasi-Grammians of the generalized lattice Heisenberg magnet model

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Communications in Theoretical Physics 2023年第8期75卷 42-53页

作者： Zeeshan amjad Bushra Haider Department of Physics University of the PunjabQuaid-e-Azam CampusLahore-54590Pakistan

In this paper,we study the discrete Darboux and standard binary Darboux transformation for the generalized lattice Heisenberg magnet *** calculate the quasi-Grammian solutions by the iteration of standard binary Darboux ***,we derive the explicit matrix solutions for the binary Darboux matrix and then reduce them to the elementary Darboux matrix and plot the dynamics of solutions.

关键词： quasi-Grammian discrete integrable systems binary Darboux transformation

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