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Automated Classification of Snow-Covered Solar Panel Surfaces Based on Deep Learning Approaches

Computer Modeling in Engineering & Sciences 2023年第9期136卷 2291-2319页

作者： Abdullah Ahmed Al-Dulaimi Muhammet Tahir Guneser Alaa Ali Hameed mohammad Shukri salman Department of Electrical and Electronics Engineering Karabuk UniversityKarabuk78100Turkey Department of Computer Engineering Istinye UniversityIstanbul34303Turkey College of Engineering and Technology American University of the Middle EastEgaila54200Kuwait

Recently,the demand for renewable energy has increased due to its environmental and economic *** panels are the mainstay for dealing with solar energy and converting it into another form of usable *** panels work under suitable climatic conditions that allow the light photons to access the solar cells,as any blocking of sunlight on these cells causes a halt in the panels work and restricts the carry of these ***,the panels are unable to work under these conditions.A layer of snow forms on the solar panels due to snowfall in areas with low ***,it causes an insulating layer on solar panels and the inability to produce electrical *** detection of snow-covered solar panels is crucial,as it allows us the opportunity to remove snow using some heating techniques more efficiently and restore the photovoltaics system to proper *** paper presents five deep learning models,■-16,■-19,ESNET-18,ESNET-50,and ESNET-101,which are used for the recognition and classification of solar panel *** this paper,two different cases were applied;the first case is performed on the original dataset without trying any kind of preprocessing,and the second case is extreme climate conditions and simulated by generating motion ***,the dataset was replicated using the upsampling technique in order to handle the unbalancing *** conducted dataset is divided into three different categories,namely;all_snow,no_snow,and partial *** fivemodels are trained,validated,and tested on this dataset under the same conditions 60%training,20%validation,and testing 20%for both *** accuracy of the models has been compared and verified to distinguish and classify the processed *** accuracy results in the first case showthat the comparedmodels■-16,■-19,ESNET-18,and ESNET-50 give 0.9592,while ESNET-101 gives *** the second case,the models outperformed their counterparts in the first case by evaluating performan

关键词： Deep learning CNN models image classification solar panels solar panel defect detection

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Transparent and Accurate COVID-19 Diagnosis:Integrating Explainable AI with Advanced Deep Learning in CT Imaging

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3101-3123页

作者： mohammad Mehedi Hassan salman A.AlQahtani Mabrook S.AlRakhami Ahmed Zohier Elhendi Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Science Technology and Innovation Department King Saud UniversityRiyadh11543Saudi Arabia

In the current landscape of the COVID-19 pandemic,the utilization of deep learning in medical imaging,especially in chest computed tomography(CT)scan analysis for virus detection,has become increasingly *** its potential,deep learning’s“black box”nature has been a major impediment to its broader acceptance in clinical environments,where transparency in decision-making is *** bridge this gap,our research integrates Explainable AI(XAI)techniques,specifically the Local Interpretable Model-Agnostic Explanations(LIME)method,with advanced deep learning *** integration forms a sophisticated and transparent framework for COVID-19 identification,enhancing the capability of standard Convolutional Neural Network(CNN)models through transfer learning and data *** approach leverages the refined DenseNet201 architecture for superior feature extraction and employs data augmentation strategies to foster robust model *** pivotal element of our methodology is the use of LIME,which demystifies the AI decision-making process,providing clinicians with clear,interpretable insights into the AI’s *** unique combination of an optimized Deep Neural Network(DNN)with LIME not only elevates the precision in detecting COVID-19 cases but also equips healthcare professionals with a deeper understanding of the diagnostic *** method,validated on the SARS-COV-2 CT-Scan dataset,demonstrates exceptional diagnostic accuracy,with performance metrics that reinforce its potential for seamless integration into modern healthcare *** innovative approach marks a significant advancement in creating explainable and trustworthy AI tools for medical decisionmaking in the ongoing battle against COVID-19.

关键词： Explainable AI COVID-19 CT images deep learning

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A Novel Beamforming Emulating Photonic Nanojets for Wireless Relay Networks

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Computers, Materials & Continua 2021年第10期69卷 575-588页

作者： Samer Alabed Ibrahim Mahariq mohammad salman Mustafa Kuzuoglu College of Engineering and Technology American University of the Middle EastKuwait Department of Electrical and Electronics Engineering Middle East Technical UniversityAnkara06800Turkey

In this article,a low-cost electromagnetic structure emulating photonic nanojets is utilized to improve the efficiency of wireless relay *** spectral element method,due to its high accuracy,is used to verify the efficiency of the proposed structure by solving the associate field *** application of optimal single-relay selection method shows that full diversity gain with low complexity can be *** this paper,the proposed technique using smart relays combines the aforementioned two methods to attain the benefits of both methods by achieving the highest coding and diversity gain and enhances the overall network performance in terms of bit error rate(BER).Moreover,we analytically prove the advantage of using the proposed *** our simulations,it can be shown that the proposed technique outperforms the best known state-of-the-art single relay selection ***,the BER expressions obtained from the theoretical analysis are perfectly matched to those obtained from the conducted simulations.

关键词： Wireless relay networks cooperative diversity techniques relay selection network beamforming techniques

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Auto-tuning PVT data using multi-objective optimization: Application of NSGA-Ⅱ algorithm

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Petroleum 2024年第1期10卷 135-149页

作者： Abdolhadi Zarifi mohammad Madani mohammad Jafarzadegan Reservoir Engineering Systems Petroleum Engineering Department Main Office Building of National Iranian South Oil Company (NISOC) Combined Planning Management National Iranian Oil Company (NIOC) Reservoir Engineering Division Petroleum Engineering Department Petroleum Engineering and Development Company (PEDEC)

Reservoir simulation is known as perhaps the most widely used, accurate, and reliable method for field development in the petroleum industry. An integral part of a reliable reservoir simulation process is to consider robust and rigorous tuned EOS models. Traditionally, EOS models are tuned iteratively through arduous workflows against experimental PVT data. However, this comes with a number of drawbacks such as forcingly using weight factors, which upon alteration adversely affects the optimization *** objective of the current work is thus to introduce an auto-tune PVT matching tool using NSGA-II multi-objective optimization. In order to illustrate the robustness of the presented technique, three different PVT samples are used, including two black-oil and one gas condensate sample. We utilize PengRobinson EOS during all the manual and auto-tuning processes. Comparison of auto-tuned EOS-generated results with those of experimental and computed statistical error values for these samples clearly show that the proposed method is robust. In addition, the proposed method, contrary to the manual matching process, provides the engineer with several matched solutions, which allows them to select a match based on the engineering background to be best amenable to the problem at hand. In addition, the proposed technique is fast, and can output several solutions within less time compared to the traditional manual matching method.

关键词： Auto-tuning PVT Equation of state NSGA-II Multi-objective optimization

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Investigation of material composition,design,and performance of open-graded asphalt mixtures for semi-flexible pavement:A comprehensive experimental study

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第1期11卷 92-116页

作者： mohammad Taghipoor Abolfazl Hassani mohammad M.Karimi Department of Civil and Environmental Engineering Tarbiat Modares UniversityTehranIran

The primary goal of this study is the design and construction of semi-flexible pavement(SFP)mixture in accordance with the engineering and mechanical *** study involves the use of a range of gradation curves,air void contents,cellulose and synthesized fibers,and neat and modified asphalt binders to prepare the open-graded asphalt(OGA)*** analyze the characteristics of these mixtures,a variety of test,namely binder drainage,semi-circular bending(SCB),Cantabro,wheel tracking,indirect tensile strength(ITS),and permeability tests were ***,to analyze the prepared grouting material,flexural strength,compressive strength,and fluidity tests were *** the final stage,SFP was compared to HMA in terms of engineering characteristics and *** to the results,SFP was more resistant to skid,rutting,fire,and moisture damage,while HMA had a better performance in fracture tests,including SCB *** to the results of the mechanical performance tests conducted on OGA mixtures,the highest and lowest values for air void content to achieve the highest mechanical performance level were 30%-35%and 25%,***,based on the laboratory results,it was determined that the required void ratio for constructing OGA mixtures was 24%-26%based on the bitumen type and fibers amount in the ***,SFP mixture can be regarded as a viable alternative to common pavements thanks to its high resistance to rutting and moisture damage,long freezing-thawing fatigue life,and adequate fire and skid resistance.

关键词： Semi-flexible pavement mixture Open-graded asphalt mixture Engineering properties Cantabro test Hot mix asphalt

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Recent Progress in Bionic Hydrogels for Articular Cartilage:Tribological and Mechanical Characteristics

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Journal of Bionic Engineering 2024年第2期21卷 653-673页

作者： mohammad Javan Almasi Dangsheng Xiong School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing210094China

Cartilage regeneration and repair are considered clinical challenges since cartilage has limited capability for *** tissue-engineered materials have the ability to repair cartilage,they have weak mechanical characteristics and cannot resist long-term *** the other hand,surgery to replace the joint is frequently done to treat significant cartilage deterioration these ***,the materials that are being used for replacement have high friction coefficients,lack shock absorption functions,and lack *** research on natural articular cartilage structure and function may lead to bionic hydrogels,which have suitable physicochemical and biological characteristics(e.g.,tribological and mechanical properties and the ability to support loadbearing capability),but need *** on their tribological and mechanical characteristics,the current review highlights the most recent advancements of bionic hydrogels used for articular cartilage,highlighting both the field's recent progress and its potential for future *** this reason,firstly,some important property improvement methods of bionic hydrogels are discussed and then,the recent findings of various research on the making of those bionic materials are provided and *** seems that by using some modifications such as product design,surface treatments,animal tests,controlling the isoelectric point of hydrogels,and computer simulation,the intended mechanical and tribological characteristics of natural articular cartilage may be attained by the bionic hydrogels.

关键词： Bionic hydrogel Articular cartilage Mechanical property Tribological property Lubrication

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Ultrasensitive plasmonic sensor based on MDM waveguide containing Persian Orsi window cavities for refractive index and blood plasma sensing

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Optoelectronics Letters 2024年第7期20卷 406-411页

作者： mohammad Ghanavati mohammad Azim Karami School of Electrical Engineering Iran University of Science and Technology

We developed a plasmonic refractive index（RI） with a metal-dielectric-metal（MDM） structure that utilizes two Persian Orsi windows-like separated cavities with a high figure of merit（FoM） and ultrasensitivity. The simulated and optimized Ag-air-Ag MDM sensor for surface plasmon resonance（SPR） offers high RI sensitivity（SRI） and the ability to detect blood plasma concentration（BPC）. The results verified that structural parameters have an effect on S;RI;, full width at half maximum（FWHM）, FoM, sensitivity of blood plasma（S;p;） for right and left peaks, whose values are 1 345.45 nm·RIU;-1;, 32 nm, 42.04 RIU;-1;, 0.26 and 0.19 nm·L·g;-1;, respectively. The proposed design opens a new horizon in sensor development.

关键词： A

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The modeling non-sequential double ionization of helium atom under highintensity femtosecond laser pulses with shielding charge approximation

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Communications in Theoretical Physics 2024年第2期76卷 151-156页

作者： Marjan Zakavi mohammad Sabaeian Department of Physics Faculty of ScienceShahid Chamran University of AhvazIran Center for Research on Laser and Plasma Shahid Chamran University of AhvazIran

In this study,we successfully extracted the‘knee structure’for non-sequential double ionization(NSDI)in the helium *** achieve this,for the first time,we solved the time-dependent Schrödinger equation in three dimensions for the helium atom,utilizing the shielding charge *** findings corroborate prior observations by Wang et al[Wang and Eberly,***.105,083001(2010)],demonstrating that NSDI occurs within a narrower time window in circular polarization compared to linear *** a result,the yield of linear polarization was higher than that of circular polarization,aligning with the previously reported ***,in the case of circular polarization,the time window further narrows with increasing intensity,attributed to a decrease in the time-of-flight.

关键词： NSDI knee structure TDSE shielding charge helium 3D-TDSE

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Direct scaling of residual displacements for bilinear and pinching oscillators

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Earthquake Engineering and Engineering Vibration 2024年第1期23卷 129-149页

作者： mohammad Saifullah Vinay K.Gupta Department of Civil Engineering Indian Institute of Technology KanpurKanpur 208016India

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the *** attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model *** of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not *** statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model *** proposed scaling model is applicable to horizontal ground motions in the western *** earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

关键词： residual displacement spectrum bilinear hysteresis model pinching hysteresis model nonlinear analysis scaling model

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Interpretable Detection of Malicious Behavior in Windows Portable Executables Using Multi-Head 2D Transformers

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Big Data Mining and Analytics 2024年第2期7卷 485-499页

作者： Sohail Khan mohammad Nauman Computer Science Department Effat College of EngineeringEffat UniversityJeddah 23341Kingdom of Saudi Arabia

Windows malware is becoming an increasingly pressing problem as the amount of malware continues to grow and more sensitive information is stored on *** of the major challenges in tackling this problem is the complexity of malware analysis,which requires expertise from human *** developments in machine learning have led to the creation of deep models for malware ***,these models often lack transparency,making it difficult to understand the reasoning behind the model’s decisions,otherwise known as the black-box *** address these limitations,this paper presents a novel model for malware detection,utilizing vision transformers to analyze the Operation Code(OpCode)sequences of more than 350000 Windows portable executable malware samples from real-world *** model achieves a high accuracy of 0.9864,not only surpassing the previous results but also providing valuable insights into the reasoning behind the *** model is able to pinpoint specific instructions that lead to malicious behavior in malware samples,aiding human experts in their analysis and driving further advancements in the *** report our findings and show how causality can be established between malicious code and actual classification by a deep learning model,thus opening up this black-box problem for deeper analysis.

关键词： machine learning malware vision transformers Windows Protable Executable(PE)

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