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Condition Monitoring and Maintenance Management with Grid-Connected Renewable Energy Systems

Computers, Materials & Continua 2022年第8期72卷 3999-4017页

作者： Md.Mottahir Alam Ahteshamul Haque mohammed ali khan Nebras M.Sobahi Ibrahim Mustafa Mehedi Asif Irshad khan Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah 21589Saudi Arabia Advance Power Electronics Research Lab Department of Electrical EngineeringJamia Millia IslamiaNew Delhi 110025India Department of Electrical Power Engineering Faculty of Electrical Engineering and CommunicationBrno University of TechnologyBrno 61600Czech Republic Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia

The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of *** with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow,monitoring and maintenance are a few of the prime *** problems were addressed widely in the literature,but most of the research has drawbacks due to long detection time,and high misclassification *** to overcome these drawbacks,and to develop an accurate monitoring approach,this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic(PV)system and highlighted along with a brief overview on existing fault detection *** on the drawback a data-driven machine learning approach has been used for the identification of fault and indicating the maintenance unit regarding the operation and maintenance ***,the system was tested with a 4 kWp grid-connected PV system,and a decision tree-based algorithm was developed for the identification of a *** results identified 94.7%training accuracy and 14000 observations/sec prediction speed for the trained classifier and improved the reliability of fault detection nature of the grid-connected PV operation.

关键词： Fault detection machine learning fault ride through

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Integrated photonic fractional convolution accelerator

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Photonics Research 2024年第8期12卷 1828-1839页

作者： KEVIN ZELAYA mohammed-ali MIRI Department of Physics Queens College of the City University of New YorkQueensNew York 11367USA Physics Program The Graduate Center of the City University of New YorkNew YorkNew York 10016USA

An integrated photonic circuit architecture to perform a modified-convolution operation based on the discrete fractional Fourier transform(DFrFT) is introduced. This is accomplished by utilizing two nonuniformly coupled waveguide lattices with equally spaced eigenmode spectra, the lengths of which are chosen so that the DFrFT and its inverse operations are achieved. A programmable modulator array is interlaced so that the required fractional convolution operation is performed. Numerical simulations demonstrate that the proposed architecture can effectively perform smoothing and edge detection tasks even for noisy input signals, which is further verified by electromagnetic wave simulations. Notably, mild lattice defects do not jeopardize the architecture performance, showing its resilience to manufacturing errors.

关键词： fractional convolution utilizing

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Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model

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Computers, Materials & Continua 2024年第5期79卷 2673-2696页

作者： Hina Naz Zuping Zhang mohammed Al-Habib Fuad A.Awwad Emad A.A.Ismail Zaid ali khan School of Computer Science and Engineering Central South UniversityChangsha410003China Department of Quantitative analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia Electrical and Computer Engineering University of VictoriaVictoriaV9A1B8Canada

Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat

关键词： Image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer

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MoBShield:A Novel XML Approach for Securing Mobile Banking

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Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： Saeed Seraj ali Safaa Sadiq OmprakashKaiwartya Mohammad Aljaidi Alexandros Konios mohammed ali mohammed Abazeed Department of Computer Science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK Department of Computer Science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and *** is due to the growing number of mobile baking applications and their reachability and usefulness to ***,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking *** literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security *** this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training *** dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission ***,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s *** evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false ***,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art *** promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking ***,MoBShield has the potential to significantly enhance the security and trustworthiness of

关键词： Security malware detection deep learning convolutional neural networks deep neural networks

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PI-RADS V1和PI-RADS V2对前列腺癌诊断准确性比较研究的系统回顾

PI-RADS V1和PI-RADS V2对前列腺癌诊断准确性比较研究的系统回顾

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作者： mohammed Ameer ali khan Afrose 苏州大学

学位级别：硕士

目的:-通过对文献的系统回顾复习,探讨PI-RADS v1和PI-RADS v2对前列腺癌诊断的准确性。材料及方法:-系统回顾复习文献的来源:MEDLINE、PUBMED、谷歌学术。文献搜索截止日期为2018年3月30日。研究包括:以前列腺系统穿刺活检或前列腺癌... 详细信息

目的:-通过对文献的系统回顾复习,探讨PI-RADS v1和PI-RADS v2对前列腺癌诊断的准确性。材料及方法:-系统回顾复习文献的来源:MEDLINE、PUBMED、谷歌学术。文献搜索截止日期为2018年3月30日。研究包括:以前列腺系统穿刺活检或前列腺癌根治术后标本病理诊断结果为标准,比较PI-RADS v1和PI-RADS v2对前列腺临床显著癌的诊断准确性。结论:-与PI-RADS V1相比,PI-RADS V2因在确定总体评分时标准较为明确,在前列腺癌检出方面更有优势。

关键词： -PI-RADS V1 PI-RADS V2 前列腺癌 mp-MRI DWI DCE-MRI MRS

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Base Pressure Control with Semi-Circular Ribs at Critical Mach Number

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Fluid Dynamics & Materials Processing 2024年第9期20卷 2007-2028页

作者： Ambareen khan Sher Afghan khan mohammed Nishat Akhtar Abdul Aabid Muneer Baig School of Aerospace Engineering Universiti Sains MalaysiaPenang11600Malaysia Department of Mechanical and Aerospace Engineering Faculty of EngineeringInternational Islamic University MalaysiaKuala Lumpur59000Malaysia Department of Engineering Management College of EngineeringPrince Sultan UniversityP.O.Box 66833Riyadh11586Saudi Arabia

When better fuel-air mixing in the combustion chamber or a reduction in base drag are required in vehicles,rockets,and aeroplanes,the base pressure control is *** the base pressure and drag is necessary in both *** this work,semi-circular ribs with varying diameters(2,4,and 6 mm)positioned at six distinct positions(0.5D,1D,1.5D,2D,3D,and 4D)inside a square duct with a side of 15 mm are proposed as an efficient way to apply the passive control ***-depth research is done on optimising rib size for various rib *** to this study,the base pressure rises as rib height ***,the optimal location for the semi-circular ribs with a diameter of 2 mm is at *** 1D location appears to be optimal for the 4 mm size as *** the 6 mm size,however,the 4D position fills this function.

关键词： Base pressure nozzle pressure ratio base drag sonic Mach number passive control

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Experimental and numerical study of effecting core configurations on the static and dynamic behavior of honeycomb plate with aluminum material

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DEFENCE TECHNOLOGY 2024年第9期39卷 177-192页

作者： Hamza, Nehad Abid Allah AL-Fatlwe, Fatima mohammed K. Talib, Muna ali Al Qasim Green Univ Engn Coll Babylon 51013 Iraq Al Furat Al Awsat Tech Univ ATU Engn Tech Coll Al Najaf Najaf 54003 Iraq

The sandwich panel incorporated a honeycomb core, a widely utilized composite structure recognized as a fundamental classification of composite materials. Comprised a core resembling a honeycomb, possessing thickness and softness, and is flank by rigid face sheets that sandwich various shapes and materials. This paper presents an examination of the static and dynamic analysis of lightweight plates made of aluminum honeycomb sandwich composites. Honeycomb sandwich plate samples are 300 mm long, and 300 mm wide, the heights of the core have been varied at four values ranging from 10 to 25 mm. The honeycomb core is manufactured from Aluminum material by using a novel technique namely resistance spot welding (RSW) instead of using adhesive material, which is often used when an industrial flaw is detected. Numerical optimization based on response surface methodology (RSM) and design of experiment software (DOE) was used to verify the current work. A theoretical examination of the crashworthiness behavior (maximum bending load, maximum deflection) and vibration attributes (natural frequency, damping ratio, transient temporal response) of honeycomb sandwich panels with different design parameters was also carried out. In addition, the finite element method-based ANSYS software was used to confirm the theoretical conclusions. The findings of the present work showed that the relationship between the natural frequency, core height, and cell size is direct. In contrast, the relationship between the natural frequency and the thickness of the cell wall is inverse. Conversely, the damping ratio is inversely proportional to the core height and cell size but directly proportional to the thickness of the cell wall. The study indicates that altering the core height within 10-25 mm leads to a significant increase of 82 % in the natural frequency and a notable decrease of 49% in the damping ratio. These findings are based on a specific cell size value of 0.01 m and a cell wall thicknes

关键词： Honeycomb Load Transient response Free vibration Natural frequency SANDWICH PANELS

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Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad ali Zeb Hani Alshahrani mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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Kaoline-based catalyst for a high stability desulfurization of sour heavy naphtha in a three-phase oscillatory baffled reactor

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Particuology 2024年第1期84卷 249-260页

作者： Hassan M.Hmood Saba A.Gheni Safaa M.R.Ahmed Mudheher M.ali Hamid Yonis Saleh mohammed H.mohammed Awad E.mohammed Marwan A.Mahomood Hiba R.mohammed Ahmed A.Hassan Adam Harvey North Refineries Company Ministry of OilIraq Chemical Engineering Department Tikrit UniversityIraq Ministry of Oil Iraq AL-Hawija Technical Institute Northern Technical UniversityMoselIraq School of Engineering Newcastle UniversityUK

To meet the rapidly increasing demand for energy and the dramatic depletion of conventional crude oil,it is imperative to utilize sour *** no coke being produced,oxidative desulfurization(ODS)of naphtha lowers its sulfur content and average molecular *** this article,we outline a method for heavy naphtha non-extractive ODS using a very stable *** technique involves the use of a solid catalyst with oxygen gas as the *** necessitated relatively high mixing intensities;hence a three-phase Oscillatory Baffled Reactor(OBR)was *** catalyst was based on the zeolite ZSM-5,prepared from natural kaolin by a series of delamination and activation steps and impregnated with Fe.A TiO2 nanolayer was applied,using the sol-gel method,to prevent rapid *** reactor performance was evaluated to minimize the sulfur content in the naphtha *** to the protective coating,the sulfur conversion stabilized at 90%.The results of this work establish the use of natural clay-based catalysts in a continuous,three-phase ODS,particularly with regard to proving long-term *** also showed that modest ODS can be achieved using an environmentally friendly oxidant,at mild operating conditions,whilst maintaining stability.

关键词： Natural kaoline Desulfurization Three-phase Oscillatory baffled reactor

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Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.Alrayes mohammed Zakariah Syed Umar Amin Zafar Iqbal khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

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