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A Particle swarm Optimization Based Deep Learning Model for Vehicle Classification

Computer systems science & Engineering 2022年第1期40卷 223-235页

作者： Adi Alhudhaif Ammar saeed Talha Imran Muhammad Kamran ahmed s.alghamdi ahmed O.Aseeri shtwai Alsubai Department of Computer science College of Computer Engineering and Sciences in Al-KharjPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Computer science COMSATS University IslamabadWah Cantt47010Pakistan University of Jeddah College of Computer Science and Engineering Department of CybersecurityJeddah21959Saudi Arabia

Image classification is a core field in the research area of image proces-sing and computer vision in which vehicle classification is a critical *** purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and applications such as security,traffic analysis,and self-driving and autonomous *** recent revolution in the field of machine learning and artificial intelligence has provided an immense amount of support for image processing related problems and has overtaken the conventional,and handcrafted means of solving image analysis *** this paper,a combina-tion of pre-trained CNN GoogleNet and a nature-inspired problem optimization scheme,particle swarm optimization(PsO),was employed for autonomous vehi-cle *** model was trained on a vehicle image dataset obtained from Kaggle that has been suitably *** trained model was classified using several classifiers;however,the Cubic sVM(CsVM)classifier was found to out-perform the others in both time consumption and accuracy(94.8%).The results obtained from empirical evaluations and statistical tests reveal that the model itself has shown to outperform the other related models not only in terms of accu-racy(94.8%)but also in terms of training time(82.7 s)and speed prediction(380 obs/sec).

关键词： Vehicle classification intelligent transport system deep learning constrained machine learning particle swarm optimization CNN GoogleNet

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A Novel Database Watermarking Technique Using Blockchain as Trusted Third Party

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Computers, Materials & Continua 2022年第1期70卷 1585-1601页

作者： ahmed s.alghamdi surayya Naz Ammar saeed Eesa Al solami Muhammad Kamran Mohammed saeed Alkatheiri Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahKSA Abdul Wali Khan University MardanPakistan Department of Computer science COMSATS University IslamabadWah CampusWah CanttPakistan

With widespread use of relational database in various real-life applications,maintaining integrity and providing copyright protection is gaining keen interest of the *** this purpose,watermarking has been used for quite a long *** requires the role of trusted third party and a mechanism to extract digital signatures(watermark)to prove the ownership of the data under *** is often inefficient as lots of processing is ***,certain malicious attacks,like additive attacks,can give rise to a situation when more than one parties can claim the ownership of the same data by inserting and detecting their own set of watermarks from the same *** solve this problem,we propose to use blockchain technology—as trusted third party—along with watermarking for providing a means of rights protection of relational *** blockchain for writing the copyright information alongside watermarking helps to secure the watermark as changing the blockchain is very *** way,we combined the resilience of our watermarking scheme and the strength of blockchain technology—for protecting the digital rights information from alteration—to design and implement a robust scheme for digital right protection of relational ***,we also discuss how the proposed scheme can also be used for version *** proposed technique works with nonnumeric features of relational database and does not target only selected tuple or portion(subset)from the database for watermark embedding unlike most of the existing techniques;as a result,the chances of subset selection containing no watermark decrease *** proposed technique employs zerowatermarking approach and hence no intentional error(watermark)is added to the original *** results of the experiments proved the effectiveness of the proposed scheme.

关键词： Watermarking blockchain digital copyright protection relational databases security

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An Automated Real-Time Face Mask Detection system Using Transfer Learning with Faster-RCNN in the Era of the COVID-19 Pandemic

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Computers, Materials & Continua 2022年第5期71卷 4151-4166页

作者： Maha Farouk s.sabir Irfan Mehmood Wafaa Adnan Alsaggaf Enas Fawai Khairullah samar Alhuraiji ahmed s.alghamdi ahmed A.Abd El-Latif Department of Information systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversitySaudi Arabia Centre for Visual Computing Faculty of Engineering and InformaticsUniversity of BradfordBradfordU.K Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahP.O.Box 23713Saudi Arabia Department of Computer science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of Mathematics and Computer science Faculty of ScienceMenoufia University32511Egypt

Today,due to the pandemic of COVID-19 the entire world is facing a serious health *** to the World Health Organization(WHO),people in public places should wear a face mask to control the rapid transmission of *** governmental bodies of different countries imposed that wearing a face mask is compulsory in public ***,it is very difficult to manually monitor people in overcrowded *** research focuses on providing a solution to enforce one of the important preventative measures of COVID-19 in public places,by presenting an automated system that automatically localizes masked and unmasked human faces within an image or video of an area which assist in this outbreak of *** paper demonstrates a transfer learning approach with the Faster-RCNN model to detect faces that are masked or *** proposed framework is built by fine-tuning the state-of-the-art deep learning model,Faster-RCNN,and has been validated on a publicly available dataset named Face Mask Dataset(FMD)and achieving the highest average precision(AP)of 81%and highest average Recall(AR)of 84%.This shows the strong robustness and capabilities of the Faster-RCNN model to detect individuals with masked and un-masked ***,this work applies to real-time and can be implemented in any public service area.

关键词： COIVD-19 deep learning faster-RCNN object detection transfer learning face mask

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Vascular endothelial growth factor:a double-edged sword in the development of white matter lesions

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Neural Regeneration Research 2025年第1期20卷 191-192页

作者： Narek Manukjan Daniel Fulton Zubair ahmed WMatthijs Blankesteijn sébastien Foulquier Department of Pharmacology and Toxicology Maastricht UniversityMaastrichtThe Netherlands CARIM-school for Cardiovascular Diseases Maastricht UniversityMaastrichtThe Netherlands Neuroscience and Ophthalmology Institute of Inflammation and AgeingUniversity of BirminghamEdgbastonBirminghamUK Centre for Trauma sciences Research University of BirminghamEdgbastonBirminghamUK MHeNs-school for Mental Health and Neuroscience Maastricht UniversityMaastrichtThe Netherlands Department of Neurology Maastricht University Medical CenterMaastrichtThe Netherlands

As the population ages,the burden of age-related diseases becomes ***,over 55 million people suffer from dementia worldwide,with Alzheimer’s disease being the most common ***,it is becoming clearer that underlying vascular pathology such as cerebral small vessel disease(csVD)may be a more detrimental cause for dementia(Cuadrado-Godia et al.,2018).It is estimated that 10%-30%of the elderly population and 35%-90%of all dementia patients exhibit signs of *** term csVD refers to pathology affecting the small vessels of the brain,which can lead to lacunar cerebral infarcts,enlarged perivascular spaces,and cortical hemorrhages(Cuadrado-Godia et al.,2018).CsVD is often associated with cognitive decline,gait problems,and dementia(Cuadrado-Godia et al.,2018).

关键词： pathology becoming white

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stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

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Computer Modeling in Engineering & sciences 2023年第12期137卷 2163-2192页

作者： Ali s.alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PsO),and salp swarm algorithm(ssA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： stochastic energy hub scheduling energy profit uncertainty Hong’s two-point estimate method improved artificial rabbits optimization

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Nanosecond pulse and dual-wavelength Q-switched 1.5 μm fiber laser using MAX phase Cr2TiAlC2 saturable absorber

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Optoelectronics Letters 2025年第1期21卷 7-12页

作者： ahmed shakir AL-HITI Hiba HAssAN Department of Electrical Engineering Faculty of Engineering University of Anbar Department of Laser and Optoelectronics Engineering University of Technology-Iraq

We demonstrated a new type of MAX phase material, chromium titanium aluminum carbide（Cr2TiAlC2） polymer film, to generate a passively Q-switched erbium-doped fiber laser（EDFL）. The film thickness was measured to be around 45 μm, which was fabricated using the embedding method with polyvinyl alcohol（PVA） polymer as hoster. The saturable absorber（sA） film demonstrates a dual-wavelength passively Q-switched EDFL which operates at 1 531 nm and 1 560.19 nm, respectively. The Q-switching pulse duration could be varied from 2.46 μs to 770 ns, while the repetition rate varied from 92.76 kHz to 106.6 kHz with an increasing input pumping range from 154 mW to 300 mW. The maximum output power and pulse energy of 15.05 mW and 141.18 nJ were obtained at the maximum input power of 300 mW, respectively.

关键词： saturable absorbers

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An Intelligent Cluster Verification Model Using WsN to Avoid Close Proximity and Control Outbreak of Pandemic in a Massive Crowd

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Computer Modeling in Engineering & sciences 2022年第11期133卷 327-350页

作者： Naeem ahmed Nawaz Norah saleh alghamdi Hanen Karamti Mohammad Ayoub Khan Department of Computer science Umm Al-Qura UniversityMakkah Al-Mukarmah24381Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

Assemblage at public places for religious or sports events has become an integral part of our *** gatherings pose a challenge at places where fast crowd verification with social distancing(sD)is required,especially during a ***,verification of crowds is carried out in the form of a queue that increases waiting time resulting in congestion,stampede,and the spread of *** article proposes a cluster verification model(CVM)using a wireless sensor network(WsN),single cluster approach(sCA),and split cluster approach(spCA)to solve the aforementioned problem for pandemic *** show that sD,cluster approaches,and verification by WsN can overcome the management issues by optimizing the cluster size and verification ***,our proposed method minimizes the chances of spreading diseases and stampedes in large events such as a *** consider the assembly points in the annual pilgrimage to Makkah Al-Mukarmah and Umrah for verification using Contiki/Cooja *** compute results such as verified cluster members(CMs)to define cluster size,success rate to determine the best success rate,and verification time to determine the optimal verification time for various *** validate ourmodel by comparing the results of each approach with the existing *** results showthat the spCAwith sD is the best approach with a 96% success rate and optimization of verification time as compared to sCA with sD and the existing model.

关键词： Cluster verification model wireless sensor network social distancing crowd single approach split approach

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Automated Grading of Breast Cancer Histopathology Images Using Multilayered Autoencoder

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Computers, Materials & Continua 2022年第5期71卷 3407-3423页

作者： shakra Mehak M.Usman Ashraf Rabia Zafar ahmed M.alghamdi ahmed s.Alfakeeh Fawaz Alassery Habib Hamam Muhammad shafiq Knowledge Unit of system and Technology University of Management&TechnologySialkot Campus51310Pakistan Department of Computer science University of Management and TechnologySialkot Campus51310Pakistan Faculty of Computing and Technology University of Engineering&TechnologyNarowal51610Pakistan College of Computer science and Engineering University of Jeddah21493Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Breast cancer(BC)is the most widely recognized cancer in women *** 2018,627,000 women had died of breast cancer(World Health Organization Report 2018).To diagnose BC,the evaluation of tumours is achieved by analysis of histological *** present,the Nottingham Bloom Richardson framework is the least expensive approach used to grade BC *** contemplate three elements,*** count,*** formation,and *** atypia,which is a laborious process that witness’s variations in expert’s ***,some algorithms have been proposed for the detection of mitotic cells,but nuclear atypia in breast cancer histopathology has not received much *** atypia analysis is performed not only to grade BC but also to provide critical information in the discrimination of normal breast,non-invasive breast(usual ductal hyperplasia,atypical ductal hyperplasia)and pre-invasive breast(ductal carcinoma in situ)and invasive breast *** proposed a deep-stacked multi-layer autoencoder ensemble with a softmax layer for the feature extraction and classification *** classification results show the value of the multilayer autoencoder model in the evaluation of nuclear *** proposed method has indicated promising results,making them more fit in breast cancer grading.

关键词： Breast cancer nuclear atypia autoencoder

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Hybrid Color Texture Features Classification Through ANN for Melanoma

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Intelligent Automation & soft Computing 2023年第2期35卷 2205-2218页

作者： saleem Mustafa Arfan Jaffar Muhammad Waseem Iqbal Asma Abubakar Abdullah s.Alshahrani ahmed alghamdi Faculty of Computer science&Information Technology Superior UniversityLahore54600Pakistan Department of software Engineering Superior UniversityLahore54600Pakistan Department of Computer science&Artificial Intelligence College of Computer Science&EngineeringUniversity of Jeddah21493Saudi Arabia Department of software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia

Melanoma is of the lethal and rare types of skin *** is curable at an initial stage and the patient can survive *** is very difﬁcult to screen all skin lesion patients due to costly *** are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders,pigment networks,and the color of *** challenges are required an automated system to classify the clinical features of melanoma and non-melanoma *** trained clinicians can overcome the issues such as low contrast,lesions varying in size,color,and the existence of several objects like hair,reﬂections,air bubbles,and oils on almost all *** contour is one of the suitable methods with some drawbacks for the segmentation of irre-gular *** entropy and morphology-based automated mask selection is pro-posed for the active contour *** proposed method can improve the overall segmentation along with the boundary of melanoma *** this study,features have been extracted to perform the classiﬁcation on different texture scales like Gray level co-occurrence matrix(GLCM)and Local binary pattern(LBP).When four different moments pull out in six different color spaces like HsV,Lin RGB,YIQ,YCbCr,XYZ,and CIE L*a*b then global information from different colors channels have been ***,hybrid fused texture features;such as local,color feature as global,shape features,and Artiﬁcial neural network(ANN)as classiﬁers have been proposed for the categorization of the malignant and *** had been carried out on datasets Dermis,DermQuest,and *** results of our advanced method showed super-iority and contrast with the existing state-of-the-art techniques.

关键词： Gray level co-occurrence matrix local binary pattern artiﬁcial neural networks support vector machines color skin cancer dermoscopic

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Automatic Detection of Weapons in surveillance Cameras Using Efficient-Net

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Computers, Materials & Continua 2022年第9期72卷 4615-4630页

作者： Erssa Arif syed Khuram shahzad Muhammad Waseem Iqbal Muhammad Arfan Jaffar Abdullah s.Alshahrani ahmed alghamdi Department of Computer science Superior UniversityLahore54000Pakistan Department of Informatics&systems University of Management&TechnologyLahore54000Pakistan Department of software Engineering Superior UniversityLahore54000Pakistan Faculty of Computer science&Information Technology Superior UniversityLahore54000Pakistan Department of Computer science&Artificial Intelligence College of Computer Science&EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia

The conventional Close circuit television(CCTV)cameras-based surveillance and control systems require human resource *** all the criminal activities take place using weapons mostly a handheld gun,revolver,pistol,swords ***,automatic weapons detection is a vital requirement now a *** current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–*** time datasets,from local surveillance department’s test sessions are used for model training and *** consist of local environment images and videos from different type and resolution cameras that minimize the *** research also contributes in the making of Efficient-Net that is experimented and results in a positive *** results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research ***-Net algorithm gives better results than existing *** using Efficient-Net algorithms the accuracy achieved 98.12%when epochs increase as compared to other algorithms.

关键词： Detection algorithms machine learning machine vision video surveillance

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