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Journal of Energy Chemistry 2013年第3期22卷 426-435页

作者： Galip Akay C.Andrea Jordan abdulaziz h.mohamed Process Intensification and Miniaturization Centre School of Chemical Engineering and Advanced MaterialsNewcastle UniversityNewcastle upon TyneNE1 7RUUK ITI Energy Limited Advanced Manufacturing ParkBrunel WayRotherham S60 5WGUK

Sulphonated nano-structured micro-porous ion exchange polymers, known as sulphonated PolyhIPE Polymers （s-PhPs） were used in syngas cleaning to investigate their impact on tar composition, concentration and dew point depression during the gasification of fuel cane bagasse as a model biomass. The results showed that the s-PhPs used as a secondary syngas treatment system, was highly effective at adsorbing and reducing the concentration of all class of tars in syngas by 95%-80% which resulted in tar dew point depression from 90 ~C to 73 ~C. It was shown that tars underwent chemical reactions within s-PhPs, indicating that tar diffusion from syngas was driven by chemical potential. It was also observed that s-PhPs also captured ash forming elements from syngas. The use of s-PhPs in gasification as well as in an integrated thermochemical biorefinery technology is discussed since the tar loaded s-PhPs can be used as natural herbicides in the form of soil additives to enhance the biomass growth and crop yield.

关键词： biorefinery biomass downdraft gasifier gasification PolyhIPE Polymer syngas cleaning tar removal

Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

BhJO: A Novel hybrid Metaheuristic Algorithm Combining the Beluga Whale, honey Badger, and Jellyfish Search Optimizers for Solving Engineering Design Problems

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad harous abdulaziz S.Almazyad Ali Wagdy mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the honey Badger Algorithm(hBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BhJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,hBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BhJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BhJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BhJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BhJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 801-816页

作者： D.Dorathy Prema Kavitha L.Francis Raj Sandeep Kautish abdulaziz S.Almazyad Karam M.Sallam Ali Wagdy mohamed Department of Mathematics Voorhees CollegeVelloreTamil NaduIndia Chandigarh Group of Colleges JhanjeriMohaliPunjabIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Science and Technology School of IT and SystemsUniversity of CanberraCanberraAustralia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan

The intuitive fuzzy set has found important application in decision-making and machine *** enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images *** image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye *** degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal *** proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between *** methodology was used to clarify the input images and make them adequate for the process of glaucoma *** objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were *** the peak regions were identified,the recurrence relationships among those peaks were then *** partitioning was done due to varying degrees of similar and dissimilar concentrations in the *** and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and *** distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.

关键词： Convolutional Neural Network(CNN) glaucomatous eyes fuzzy difference equation intuitive fuzzy sets image segmentation retinal images

Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for human-Machine Collaboration(hUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

Robust Facial Biometric Authentication System Using Pupillary Light Reflex for Liveness Detection of Facial Images

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 725-739页

作者： Puja S.Prasad Adepu Sree Lakshmi Sandeep Kautish Simar Preet Singh Rajesh Kumar Shrivastava abdulaziz S.Almazyad hossam M.Zawbaa Ali Wagdy mohamed CSE Department Geethanjali College of EngineeringHyderabadTelangana501301India Department of Computer Science LBEF CampusKathmandu44600Nepal School of Computer Science Engineering and Technology(SCSET) Bennett UniversityGreater Noida201310India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia CeADAR Ireland’s Centre for AI Technological University DublinDublinD07 EWV4Ireland Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan

Pupil dynamics are the important characteristics of face spoofing *** face recognition system is one of the most used biometrics for authenticating individual *** main threats to the facial recognition system are different types of presentation attacks like print attacks,3D mask attacks,replay attacks,*** proposed model uses pupil characteristics for liveness detection during the authentication *** pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light *** proposed framework consists of two-phase *** the first phase,the pupil’s diameter is calculated by applying stimulus(light)in one eye of the subject and calculating the constriction of the pupil size on both eyes in different video *** above measurement is converted into feature space using Kohn and Clynes model-defined *** Support Vector Machine is used to classify legitimate subjects when the diameter change is normal(or when the eye is alive)or illegitimate subjects when there is no change or abnormal oscillations of pupil behavior due to the presence of printed photograph,video,or 3D mask of the subject in front of the *** the second phase,we perform the facial recognition ***-invariant feature transform(SIFT)is used to find the features from the facial images,with each feature having a size of a 128-dimensional *** features are scale,rotation,and orientation invariant and are used for recognizing facial *** brute force matching algorithm is used for matching features of two different *** threshold value we considered is 0.08 for good *** analyze the performance of the framework,we tested our model in two Face antispoofing datasets named Replay attack datasets and CASIA-SURF datasets,which were used because they contain the videos of the subjects in each sample having three modalities(RGB,IR,Depth).The CASIA-SURF datasets showed an 89.9%Equal Err

关键词： SIFT pupil CASIA-SURF pupillary light reflex replay attack dataset brute force

A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering hot Dry Rock Co-Generation

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1387-1404页

作者： hao Qi mohamed Sharaf Andres Annuk Adrian Ilinca mohamed A.mohamed College of Electrical and New Energy China Three Gorges UniversityYichang443002China Department of Industrial Engineering College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia Institute of Forestry and Engineering Estonian University of Life SciencesTartu51006Estonia Department of Mechanical Engineering école de Technologie SupérieureMontréalQC H3C 1K3Canada Electrical Engineering Department Faculty of EngineeringMinia UniversityMinia61519Egypt

hot dry rock(hDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and *** this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering hDR co-generation is ***,the hDR-enhanced geothermal system(hDR-EGS)is introduced into the ***-EGS realizes the thermoelectric decoupling of combined heat and power(ChP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in ***,peak-hour loads are shifted using price demand response guidance in the context of time-of-day ***,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with *** simulating a real small-scale RIES,the results show that hDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.

关键词： Energy harvesting integrated energy systems optimum scheduling time-of-use pricing demand response geothermal energy

A new technique for fault diagnosis in transformer insulating oil based on infrared spectroscopy measurements

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high Voltage 2024年第2期9卷 319-335页

作者： mohamed M.F.Darwish.mohamed h.A.hassan Nagat M.K.Abdel-Gawad Matti Lehtonen Diaa-Eldin A.Mansour Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland Department of Electrical Power Engineering Egypt-Japan University of Science and Technology(E-JUST)New Borg El-Arab CityEgypt Department of Electrical Power and Machines Engineering Faculty of EngineeringTanta UniversityTantaEgypt

Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical *** gas analysis(DGA)is frequently used for this ***,DGA lacks the necessary level of accuracy to identify all equipment faults,particularly in their initial stages of ***,it does not have the capability for real-time monitoring and relies on manual sampling and laboratory testing,causing potential delays in fault ***,the interpretation of DGA data necessitates specialised expertise,which may pose difficulties for smaller entities that have limited access to ***,the contribution of this research is to use infrared spectroscopy measurements as a new effective technique substituting the DGA method for fault diagnosis in insulating *** inception faults that were considered in this study were the electrical fault(discharges of high energy)and the thermal fault(300°Chat,two test cells were crafted especially for serving the simulation processes inside the laboratory for both types of inception ***,six samples of pure paraffinic mineral oil were taken to be degraded in the *** that,all of them besides another sample that were not subjected to any kind of faults were taken to be examined by Fourier transform infrared(FTIR)spectroscopy to obtain an overview of the oil's behaviour in each fault *** that,the FTIR analysis was initially verified utilising the DGA ***,for further affirmation,the dielectric dissipation factor(DDF)for all samples was *** the final analysis,the verification tests provide experimental evidence about the outperformance of this new optical technique in detecting the transformer's inception faults in addition to proving its potential for being a superior alternative to the well-known traditional diagnostic techniques.

关键词： fault diagnosis spectroscopy

Ballistic design and testing of a composite armour reinforced by CNTs suitable for armoured vehicles

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Defence Technology（防务技术） 2024年第2期32卷 173-195页

作者： Evangelos Ch.Tsirogiannis Evangelos Daskalakis mohamed h.hassan Abdalla M.Omar Paulo Bartolo EODh SA Research and Development DepartmentLakkoma Chalkidikis63080Greece School of Mechanical Aerospace and Civil EngineeringUniversity of ManchesterManchesterM139PLUK Singapore Centre for 3D Printing School of Mechanical and Aerospace EngineeringNanyang Technological University639798Singapore

This paper is investigating the use of composite armour reinforced by nanomaterials, for the protection of light armoured(LAV) and medium armoured military vehicles(MAV), and the interaction between the composite materials and high-performance ballistic projectiles. Four armour materials, consisted of front hybrid fibre reinforced polymer cover layer, ceramic strike-face, fibre reinforced polymer intermediate layer and the metal matrix composite reinforced backplate, were manufactured and assembled by adhesive technology. The proposed laminated protection system is suitable for armoured ground vehicles;however, it could be used as armour on ground, air and naval platforms. The design of the protection system, including material selection and thickness, was elaborated depending on the performance requirements of Level 4 + STANAG 4569 military standard(projectile 14.5 mm × 114 mm API B32) and especially on a design philosophy which is analysed with the specifications. The backplate of this new composite is a hybrid material of Metal Matrix Composite(MMC) reinforced with carbon nanotubes(CNTs), manufactured with the use of powder metallurgy technique. The composite backplate material was morphologically, mechanically and chemically analysed. Results show that all plates are presenting high mechanical properties and ballistic characteristics, compared to commonly used armour plates. Real military ballistic tests according to AEP-STANAG 4569 were carried out for the total composite armour systems. After the ballistic tests, AA2024-CNT3 showed the best protection results, compared with the other plates(AA2024-CNT1 and AA2024-CNT2), with the projectile being unable to fully penetrate the composite plate.

关键词： Passive armour protection Protective armour Ballistic performance hybrid composites Vehicle protection

Dysprosium oxide,alumina,and graphene oxide reinforced polycaprolactone thin films:Thermal stability,morphology,and cell viability

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Journal of Rare Earths 2024年第7期42卷 1337-1343,I0005页

作者： mohamed Tharwat Elabbasy mohamed R.Atteya Mai A.Samak Mousa Abdelrahman Tahani AlMahmoud M.A.El-Morsy A.A.Menazea M.F.h.Abd El-Kader Department of Public health College of Public Health and Health InformaticsUniversity of Ha'ilHa'il2440Saudi Arabia Food Control Department Faculty of Veterinary MedicineZagazig UniversityZagazig44519Egypt Department of Physical Therapy College of Applied Medical SciencesUniversity of Ha'ilHa'ilSaudi Arabia Department of histology and Cell Biology Faculty of MedicineZagazig UniversityZagazig44519Egypt College of Nursing University of Ha'ilHa'ilSaudi Arabia College of Science and humanities in Al-Kharj Physics DepartmentPlasma Technology and Material Science UnitPrince Sattam Bin Abdulaziz UniversityAl-kharj11942Saudi Arabia Physics Department Faculty of ScienceUniversity of DamiettaNew Damietta34517Egypt Spectroscopy Department Physics Research InstituteNational Research CentreDokki12622GizaEgypt Biophysics Department Faculty of ScienceCairo UniversityGizaEgypt

Developing a biomaterial for wound healing applications is still a ***,dysprosium oxide(Dy_(2)O_(3)),aluminum oxide(Al_(2)O_(3)),and graphene oxide(GO)were embedded in cast films based on polycaprolactone(PCL)to be examined for wound dressing *** techniques were used to characterize the fabricated films including X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),Raman,and scanning electron microscopy(SEM),besides their biological *** thermogravimetric analysis(TGA)exhibits high thermal stability as the scaffold weight decreases slightly to 98.6%after raising the temperature from room temperature to 280℃.The cell viability was investigated and it is shown that the viable cells grow up to approximately 93%at 75μg/***,the cell attachment shows excellent behavior as the cells attach on most of the surface of the modified PCL which shows high biocompatibility.

关键词： Wound healing Polycaprolactone Dy_(2)O_(3) Al_(2)O_(3) Biocompatible Rare earths