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A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

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Computers, Materials & Continua 2023年第12期77卷 3969-3992页

作者： Naeem Ullah Javed Ali Khan sultan Almakdi mohammed s.alshehri Mimonah Al Qathrady Eman Abdullah Aldakheel Doaa sami Khafaga Department of software Engineering University of Engineering and TechnologyTaxila4400Pakistan Department of Computer science Faculty of PhysicsEngineeringand Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Departments of Information systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tomato leaf diseases significantly impact crop production,necessitating early detection for sustainable *** Learning(DL)has recently shown excellent results in identifying and classifying tomato leaf ***,current DL methods often require substantial computational resources,hindering their application on resource-constrained *** propose the Deep Tomato Detection Network(DTomatoDNet),a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome *** Convn kernels used in the proposed(DTomatoDNet)framework is 1×1,which reduces the number of parameters and helps in more detailed and descriptive feature extraction for *** proposed DTomatoDNet model is trained from scratch to determine the classification success rate.10,000 tomato leaf images(1000 images per class)from the publicly accessible dataset,covering one healthy category and nine disease categories,are utilized in training the proposed DTomatoDNet *** specifically,we classified tomato leaf images into Target spot(Ts),Early Blight(EB),Late Blight(LB),Bacterial spot(Bs),Leaf Mold(LM),Tomato Yellow Leaf Curl Virus(YLCV),septoria Leaf spot(sLs),spider Mites(sM),Tomato Mosaic Virus(MV),and Tomato Healthy(H).The proposed DTomatoDNet approach obtains a classification accuracy of 99.34%,demonstrating excellent accuracy in differentiating between tomato *** model could be used on mobile platforms because it is lightweight and designed with fewer *** farmers can utilize the proposed DTomatoDNet methodology to detect disease more quickly and easily once it has been integrated into mobile platforms by developing a mobile application.

关键词： CNN deep learning DTomatoDNet tomato leaf disease classification smart agriculture

sACNN-IDs: A self-attention convolutional neural network for intrusion detection in industrial internet of things

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1398-1411页

作者： Mimonah Al Qathrady safi Ullah mohammed s.alshehri Jawad Ahmad sultan Almakdi samar M.Alqhtani Muazzam A.Khan Baraq Ghaleb Department of Information systems College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Computer science Quaid-i-Azam UniversityIslamabadPakistan Department of Computer science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia school of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghUK ICEsCO Chair Big Data Analytics and Edge Computing Quaid-i-Azam UniversityIslamabadPakistan

Industrial Internet of Things(IIoT)is a pervasive network of interlinked smart devices that provide a variety of intelligent computing services in industrial *** IIoT nodes operate confidential data(such as medical,transportation,military,etc.)which are reachable targets for hostile intruders due to their openness and varied *** Detection systems(IDs)based on Machine Learning(ML)and Deep Learning(DL)techniques have got significant ***,existing ML and DL-based IDs still face a number of obstacles that must be *** instance,the existing DL approaches necessitate a substantial quantity of data for effective performance,which is not feasible to run on low-power and low-memory *** and fewer data potentially lead to low performance on existing *** paper proposes a self-attention convolutional neural network(sACNN)architecture for the detection of malicious activity in IIoT networks and an appropriate feature extraction method to extract the most significant *** proposed architecture has a self-attention layer to calculate the input attention and convolutional neural network(CNN)layers to process the assigned attention features for *** performance evaluation of the proposed sACNN architecture has been done with the Edge-IIoTset and X-IIoTID *** datasets encompassed the behaviours of contemporary IIoT communication protocols,the operations of state-of-the-art devices,various attack types,and diverse attack scenarios.

关键词： convolutional neural network deep learning industrial internet of things intrusion detection self-attention

Generic Attribute scoring for Information Decay in Threat Information sharing Platform

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Computers, Materials & Continua 2021年第4期67卷 917-931页

作者： mohammed alshehri Department of Information Technology Majmaah UniversityMajmaah11952Saudi Arabia

Cyber Threat Intelligence(CTI)has gained massive attention to collect hidden knowledge for a better understanding of the various cyber-attacks and eventually paving the way for predicting the future of such *** information exchange and collaborative sharing through different platforms have a significant contribution towards a global *** CTI and the information exchange can help a lot in focusing and prioritizing on the use of the large volume of complex information among different organizations,there exists a great challenge ineffective processing of large count of different Indicators of Threat(IoT)which appear regularly,and that can be solved only through a collaborative *** approach and intelligence sharing have become the mandatory element in the entire world of processing the *** order to covet the complete needs of having a definite standard of information exchange,various initiatives have been taken in means of threat information sharing platforms like MIsP and formats such as *** paper proposes a scoring model to address information decay,which is shared within *** scoring model is implemented,taking the use case of detecting the Threat Indicators in a phishing data *** proposed method calculates the rate of decay of an attribute through which the early entries are removed.

关键词： Information interchange cyber threat intelligence indicators of threats threat intelligence sharing platform

steam Methane Reforming(sMR)Combined with ship Based Carbon Capture(sBCC)for an Efficient Blue Hydrogen Production on Board Liquefied Natural Gas(LNG)Carriers

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Fluid Dynamics & Materials Processing 2025年第1期21卷 71-85页

作者： Ikram Belmehdi Boumedienne Beladjine Mohamed Djermouni Amina sabeur mohammed El Ganaoui Laboratoire des sciences et Ingénierie Maritimes Facultéde Génie MécaniqueUniversitédes Sciences et de la Technologie d’Oran Mohammed BoudiafOran31000Algérie Laboratoire LERMAB IUT Henri Poincaréde Longwy Universitéde LorraineCosnes et RomainLongwy54400France

The objective of this study is to propose an optimal plant design for blue hydrogen production aboard a liquefiednatural gas(LNG)*** investigation focuses on integrating two distinct processes—steam methanereforming(sMR)and ship-based carbon capture(sBCC).The first refers to the common practice used to obtainhydrogen from methane(often derived from natural gas),where steam reacts with methane to produce hydrogenand carbon dioxide(CO_(2)).The second refers to capturing the CO_(2) generated during the sMR process on *** capturing and storing the carbon emissions,the process significantly reduces its environmental impact,making the hydrogen production“blue,”as opposed to“grey”(which involves CO_(2) emissions without capture).For the sMR process,the analysis reveals that increasing the reformer temperature enhances both the processperformance and CO_(2) ***,a higher steam-to-carbon(s/c)ratio reduces hydrogen yield,therebydecreasing thermal *** study also shows that preheating the air and boil-off gas(BOG)before theyenter the combustion chamber boosts overall efficiency and curtails CO_(2) *** the sBCC process,puremonoethanolamine(MEA)is employed to capture the CO_(2) generated by the exhaust gases from the sMR *** results indicate that with a 90%CO_(2) capture rate,the associated heat consumption amounts to 4.6 MJ perkilogram of CO_(2) *** combined approach offers a viable pathway to produce blue hydrogen on LNGcarriers while significantly reducing the carbon footprint.

关键词： Carbon dioxide(CO_(2))emissions blue hydrogen boil-off gas(BOG) steam methane reforming(sMR) ship-based carbon capture(sBCC)

Optimizing BERT for Bengali Emotion Classification: Evaluating Knowledge Distillation, Pruning, and Quantization

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Computer Modeling in Engineering & sciences 2025年第2期142卷 1637-1666页

作者： Md Hasibur Rahman mohammed Arif Uddin Zinnat Fowzia Ria Rashedur M.Rahman Department of Electrical and Computer Engineering North South UniversityDhaka1229Bangladesh

The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text ***,BERT’s size and computational demands limit its practicality,especially in resource-constrained *** research compresses the BERT base model for Bengali emotion classification through knowledge distillation(KD),pruning,and quantization *** Bengali being the sixth most spoken language globally,NLP research in this area is *** approach addresses this gap by creating an efficient BERT-based model for Bengali *** have explored 20 combinations for KD,quantization,and pruning,resulting in improved speedup,fewer parameters,and reduced memory *** best results demonstrate significant improvements in both speed and *** instance,in the case of mBERT,we achieved a 3.87×speedup and 4×compression ratio with a combination of Distil+Prune+Quant that reduced parameters from 178 to 46 M,while the memory size decreased from 711 to 178 *** results offer scalable solutions for NLP tasks in various languages and advance the field of model compression,making these models suitable for real-world applications in resource-limited environments.

关键词： Bengali NLP black-box distillation emotion classification model compression post-training quantization unstructured pruning

Iron-promoted zirconia-alumina supported Ni catalyst for highly efficient and cost-effective hydrogen production via dry reforming of methane

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Journal of Environmental sciences 2025年第2期148卷 274-282页

作者： Ahmed s.Al-Fatesh Naitik Patel Vijay Kumar srivastava Ahmed I.Osman David W.Rooney Anis H.Fakeeha Ahmed E.Abasaeed mohammed F.Alotibi Rawesh Kumar Chemical Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh 11421Saudi Arabia Department of Chemistry Indus UniversityAhmedabadGujarat 382115India school of Chemistry and Chemical Engineering Queen’s University BelfastBelfast BT95AGNorthern IrelandUK Institute of Refining and Petrochemicals Technologies King Abdulaziz City for Science and Technology(KACST)P.O.Box 6086Riyadh 11442Kingdom of Saudi Arabia

Developing cost-effective and high-performance catalyst systems for dry reforming of methane(DRM)is crucial for producing hydrogen(H_(2))***,we investigate using iron(Fe)as a promoter and major alumina support in Ni-based catalysts to improve their DRM *** addition of iron as a promotor was found to add reducible iron species along with reducible NiO species,enhance the basicity and induce the deposition of oxidizable *** incorporating 1 wt.%Fe into a 5Ni/10ZrAl catalyst,a higher CO_(2) interaction and formation of reducible"NiO-species having strong interaction with support"was observed,which led to an∼80%H_(2) yield in 420 min of Time on stream(TOs).Further increasing the Fe content to 2 wt.%led to the formation of additional reducible iron oxide species and a noticeable rise in H_(2) yield up to 84%.Despite the severe weight loss on Fe-promoted catalysts,high H_(2) yield was maintained due to the proper balance between the rate of CH_(4) decomposition and the rate of carbon deposit ***,incorporating 3 wt.%Fe into the 5Ni/10ZrAl catalyst resulted in the highest CO_(2) interaction,wide presence of reducible NiO-species,minimumgraphitic deposit and an 87%H_(2) *** findings suggest that ironpromoted zirconia-alumina-supported Ni catalysts can be a cheap and excellent catalytic system for H_(2) production via DRM.

关键词： Dry reforming of methane Coke resistant Hydrogen production Cheap catalyst Fe-promoted catalyst

Thymus serpyllum *** Oil:Phytochemistry and in Vitro and in silico screening of Its Antimicrobial,Antioxidant and Anti-Inflammatory Properties

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Phyton-International Journal of Experimental Botany 2025年第1期94卷 209-227页

作者： samiah Hamad Al-Mijalli Hanae Naceiri Mrabti Amine Elbouzidi Naglaa s.Ashmawy Amine Batbat Emad M.Abdallah Wafa Laaboudi mohammed Aladhadh Fahad M.Alshabrmi sulaiman mohammed Alnasser Mohamed Addi Naoufal El Hachlafi Department of Biology College of SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Pharmcology Laboratory of Epidemiology and Research in Health SciencesFaculty of MedicinePharmacy and DentistrySidi Mohamed Ben Abdellah UniversityFez30000Morocco Laboratoire d’Amélioration des Productions Agricoles Biotechnologie et Environnement(LAPABE)Facultédes SciencesMoroccodes SciencesUniversitéMohammed PremierOujda60000Morocco Department of Pharmaceutical sciences College of PharmacyGulf Medical UniversityAjmanP.O.Box 4184United Arab Emirates Department of Pharmacognosy Faculty of PharmacyAin Shams UniversityAbbassiaCairo11566Egypt Laboratory of Applied Organic Chemistry Faculty of Sciences and TechniquesSidi Mohamed Ben Abdellah UniversityImouzzer RoadFez30000Morocco Department of Biology College of ScienceQassim UniversityQassim51452Saudi Arabia High Institute of Nursing Professions and Health Techniques Fez Fez30050Morocco Department of Food science and Human Nutrition College of Agriculture and FoodQassim UniversityBuraydah51452Saudi Arabia Department of Medical Laboratories College of Applied Medical SciencesQassim UniversityBuraydah51452Saudi Arabia Department of Pharmacology and Toxicology College of PharmacyQassim UniversityBuraydah52571Saudi Arabia Faculty of Medicine and Pharmacy Ibn Zohr UniversityGuelmim81000Morocco

Thymus serpyllum L.,often known as wild thyme,has been used since ancient times due to its multifaceted culinary and medicinal *** is usually utilized in folk medicine to manage different health *** work aimed to investigate the chemical composition and biological characteristics of *** essential oil(EO),including its antimicrobial,antioxidant,and anti-inflammatory ***,we have prompted an in-silico simulation to reveal the underlying mode of action of these *** chemical characterization of ***(EO)by Gas Chromatography-Mass spectrometry(GC-Ms)indicated sabinene(17.33%),terpinen-4-ol(11.73%),phellandral(13.18%),and thymol(10.54%)as main *** antimicrobial screening utilized the disc-diffusion technique,MIC,and MBC *** disc-diffusion test’s results revealed significant anti-Candida activity and notable antibacterial *** MIC and MBC tests showed that *** EO effectively stops bacterial growth,including Gram-positive and Gram-negative strains and Candida *** tolerance level ratio demonstrated that this EO exhibits bactericidal and fungicidal effects on all tested bacteria and Candida ***,*** EO presented effective inhibitory activity against the 5-lipoxygenase(5-LOX)enzyme(IC50=744.19±0.1µg/mL)(pso effectively affected FRAP,β-carotene,DPPH,and ABTs *** light of these findings,*** holds promise for diverse applications across pharmaceuticals,nutraceuticals,and the food ***,further research and collaboration between traditional knowledge and modern medicine are crucial to fully realizing its potential benefits in these fields.

关键词： Thymus serpyllum GC-Ms antimicrobial oxidative stress anti-inflammatory in silico

Leveraging Artificial Intelligence to Achieve sustainable Public Healthcare services in saudi Arabia: A systematic Literature Review of Critical success Factors

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Computer Modeling in Engineering & sciences 2025年第2期142卷 1289-1349页

作者： Rakesh Kumar Ajay singh Ahmed subahi Ahmed Kassar mohammed Ismail Humaida sudhanshu Joshi Manu sharma Department of Health Management College of Public Health and Health InformaticsUniversity of Ha’ilHa’il81451Saudi Arabia Department of Management&Information systems College of Business AdministrationUniversity of Ha’ilHa’il81451Saudi Arabia Department of Public Health College of Public Health and Health InformaticsUniversity of Ha’ilHa’il81451Saudi Arabia school of Management Doon UniversityDehradunUttarakhand248001India Department of Management studies Graphic Era UniversityDehradunUttarakhand248002India

This review aims to analyze the development and impact of Artificial Intelligence(AI)in the context of saudi Arabia’s public healthcare system to fulfill Vision 2030 *** is extensively devoted to AI technology deployment relevant to disease management,healthcare delivery,epidemiology,and ***,its AI is culturally sensitive and ethically grounded in *** on the PRIsMA framework,an sLR evaluated primary academic literature,cases,and practices of saudi Arabia’s AI implementation in the public healthcare ***,it categorizes prior research based on how AI can work,the issues it poses,and its implications for the Kingdom’s healthcare *** saudi Arabian context analyses show that AI has increased the discreet prediction of diseases,resource management,and monitoring outbreaks during mass congregations such as ***,the study outlines critical areas for defining the potential for artificial intelligence and areas for enhancing digital development to support global healthcare *** key themes emerging from the review include saudi Arabia:(i)the effectiveness of AI with human interaction for sustainable health services;(ii)conditions and quality control to enhance the quality of health care services using AI;(iii)environmental factors as influencing factors for public health care;(iv)Artificial Intelligence,and advanced decision-making technology for Middle Eastern health care *** policymakers,healthcare managers,and researchers who will engage with AI innovation,the review proclaims that AI applications should respect the country’s socio-cultural and ethical practices and pave the way for sustainable healthcare *** empirical research is needed on the implementation issues with AI,creating culturally appropriate models of AI,and finding new applications of AI to address the increasing demand for healthcare services in saudi Arabia.

关键词： Artificial intelligence public health services sustainability healthcare saudi Arabia PRIsMA

Impact of Human Vulnerabilities on Cybersecurity

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Computer systems science & Engineering 2022年第3期40卷 1153-1166页

作者： Maher Alsharif shailendra Mishra mohammed alshehri Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia

Today,security is a major challenge linked with computer network companies that cannot defend against *** vulnerable factors increase security risks and cyber-attacks,including viruses,the internet,communications,and *** of Things(IoT)devices are more effective,and the number of devices connected to the internet is constantly increasing,and governments and businesses are also using these technologies to perform business activities ***,the increasing uses of technologies also increase risks,such as password attacks,social engineering,and phishing *** play a major role in the field of *** is observed that more than 39%of security risks are related to the human factor,and 95%of successful cyber-attacks are caused by human error,with most of them being insider *** major human factor issue in cybersecurity is a lack of user awareness of cyber *** study focuses on the human factor by surveying the vulnerabilities and reducing the risk by focusing on human nature and reacting to different *** study highlighted that most of the participants are not experienced with cybersecurity threats and how to protect their personal ***,the lack of awareness of the top three vulnerabilities related to the human factor in cybersecurity,such as phishing attacks,passwords,attacks,and social engineering,are major problems that need to be addressed and reduced through proper awareness and training.

关键词： Cybersecurity phishing attack password attack social engineering cybersecurity awareness security risk