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Journal of Environmental Sciences 2022年第2期34卷 331-342页

作者： Hussien Ahmed Abbas Rabab Ahmed Nasr Rose-Noelle Vannier Tarek samir.Jamil Inorganic Chemistry Department National Research CentreCairo 12622Egypt Water Pollution Control Department National Research CenterCairo 12622Egypt Univ.Lille CNRSCentrale LilleENSCLUniv.ArtoisUMR 8181Unite de Catalyse et Chimie du Solide(UCCS)Lille 59000France

Nanosized Ba_(1-x)Bi_(x)Fe_(1-x)Cu_(x)O_(3)(12–50 nm)with x values of 0,0.01,0.05,and 0.1 system was prepared using the Pechini ***,morphological,surface and optical characterizations were performed for the prepared *** phase was the predominant phase for the undoped BaFeO_(3)and Bi and Cu co-doped BaFeO_(3)*** phases of monoclinic Ba_(2)Fe_(2)O_(5),orthorhombic BaFe_(2)O_(4)and orthorhombic BaCO_(3)were identified for all the prepared ***_(0.95)Bi_(0.05)Fe_(0.95)Cu_(0.05)O_(3)sample has the lowest band gap(2.43 e V).98.1%paracetamol removal was achieved with 0.75 g/L of Ba_(0.95)Bi_(0.05)Fe_(0.95)Cu_(0.05)O_(3)at pH9 after 120 *** paracetamol degradation follows the pseudo first-order ***·is the main oxidative species responsible for the paracetamol *** chromatography–mass spectrometry(GC–MS)analysis was performed at the end of the photocatalytic degradation experiment under optimum operating condition using Ba_(0.95)Bi_(0.05)Fe_(0.95)Cu_(0.05)O_(3)to explain the reaction mechanism and identify the intermediate by-products which is confirmed by ultraviolet/visible(UV/Vis)spectroscopy study at different reaction times.

关键词： Ba_(1-x)Bi_(x)Fe_(1-x)Cu_(x)O_(3) Photocatalytic degradation Nanomaterials Paracetamol

Transfer Learning-Based Semi-Supervised Generative Adversarial Network for Malaria Classification

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Computers, Materials & Continua 2023年第3期74卷 6335-6349页

作者： Ibrar Amin Saima Hassan samir.Brahim Belhaouari Muhammad Hamza Azam Institute of Computing Kohat University of Science and TechnologyKohat26000K.P.KPakistan College of Science and Engineering Hamad bin Khalifa UniversityDohaQatar Centre of Research in Data Science Computer and Information Sciences DepartmentUniversiti Teknologi PETRONASSeri Iskandar32610PerakMalaysia

Malaria is a lethal disease responsible for thousands of deaths worldwide every *** methods of malaria diagnosis are timeconsuming that require a great deal of human expertise and *** automated diagnosis of diseases is progressively becoming *** deep learning models show high performance in the medical field,it demands a large volume of data for training which is hard to acquire for medical ***,labeling of medical images can be done with the help of medical experts *** recent studies have utilized deep learning models to develop efficient malaria diagnostic system,which showed promising ***,the most common problem with these models is that they need a large amount of data for *** paper presents a computer-aided malaria diagnosis system that combines a semi-supervised generative adversarial network and transfer *** proposed model is trained in a semi-supervised manner and requires less training data than conventional deep learning *** of the proposed model is evaluated on a publicly available dataset of blood smear images(with malariainfected and normal class)and achieved a classification accuracy of 96.6%.

关键词： Generative adversarial network transfer learning semi-supervised malaria VGG16

Assessment of the Hydrogeochemical Characteristics of Groundwater Resources at some Wadis in the East of El Minia Governorate,Eastern Desert,Egypt

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Acta Geologica Sinica(English Edition) 2022年第3期96卷 1082-1097页

作者： Alzahraa Abo HABIBAH Kamal DAHAB Ashraf SHABANA samir.KAMH Hekmat IBRAHIM Geology Department Faculty of ScienceMenoufia UniversityShebin ElkoomEgypt Geology Department Desert Research CenterCairoEgypt Geology Department Faculty of ScienceTanta UniversityTantaEgypt

The El Minia governorate lies within the Nile Valley,surrounded by calcareous plateaus to the east and *** present study focuses on the hydrogeochemistry of the Eocene limestone aquifer at some wadis in the east El Minia governorate,Eastern Desert,***,two main aquifers are encountered in the study area,namely the Maghagha marly limestone and the Samalut chalky limestone *** Maghagha aquifer is composed of alternating layers of marly limestone and shale with thicknesses ranging from 3.49 m to 177.05 m and a groundwater depth ranging from 8.5 m to 59.27 m which reflects low groundwater *** groundwater salinity representing this aquifer ranges from 603.5 mg/L to 978.5 mg/L,reflecting fresh water *** aquifer is made up of chalky,cavernous and fractured limestone with thickness ranging from 30 m to 205 m and groundwater depth ranging from 9 m to 86.77 m,which indicates good groundwater *** groundwater salinity of the concerned aquifer ranges from 349.7 mg/L to 2043.9 mg/L,reflecting fresh to possibly brackish water *** in the study area is of meteoric water origin;recent recharge is mainly controlled through the presence of fractures and their *** majority of groundwater samples in the study area are suitable for drinking and irrigation purposes.

关键词： groundwater limestone aquifers El Minia governorate Eastern Desert

A Blockchain-Based Architecture for Securing Industrial IoTs Data in Electric Smart Grid

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Computers, Materials & Continua 2023年第3期74卷 5389-5416页

作者： samir.M.Umran Songfeng Lu Zaid Ameen Abduljabbar Xueming Tang School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan430074China Iraqi Ministry of Industrial and Minerals Iraqi Cement State CompanyBaghdad10011Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518057China Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq

There are numerous internet-connected devices attached to the industrial process through recent communication technologies,which enable machine-to-machine communication and the sharing of sensitive data through a new technology called the industrial internet of things(IIoTs).Most of the suggested security mechanisms are vulnerable to several cybersecurity threats due to their reliance on cloud-based services,external trusted authorities,and centralized architectures;they have high computation and communication costs,low performance,and are exposed to a single authority of failure and *** technology(BC)is widely adopted in the industrial sector for its valuable features in terms of decentralization,security,and *** our work,we propose a decentralized,scalable,lightweight,trusted and secure private network based on blockchain technology/smart contracts for the overhead circuit breaker of the electrical power grid of the Al-Kufa/Iraq power plant as an industrial *** proposed scheme offers a double layer of data encryption,device authentication,scalability,high performance,low power consumption,and improves the industry’s operations;provides efficient access control to the sensitive data generated by circuit breaker sensors and helps reduce power *** also address data aggregation operations,which are considered challenging in electric power smart *** utilize a multi-chain proof of rapid authentication(McPoRA)as a consensus mechanism,which helps to enhance the computational performance and effectively improve the *** advanced reduced instruction set computer(RISC)machinesARMCortex-M33 microcontroller adopted in our work,is characterized by ultra-low power consumption and high performance,as well as efficiency in terms of real-time cryptographic algorithms such as the elliptic curve digital signature algorithm(ECDSA).This improves the computational execution,increases the implementation speed of the asymmetric c

关键词： Smart grids industrial IoTs electric power system blockchain technology IoT applications industry 4.0 decentralization applications

Recent developments in the asymmetric synthesis and functionalization of symmetrical and unsymmetrical gem-diborylalkanes

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Organic Chemistry Frontiers 2022年第3期9卷 838-852页

作者： Swagata Paul Kanak Kanti Das Debasis Aich samir.Manna Santanu Panda Department of Chemistry Indian Institute of TechnologyKharagpur721302India

gem-Diborylalkanes are an important class of organoboron compounds as they function as a key building block in organic *** the last decade,there has been growing interest in the enantioselective synthesis of gem-diborylalkanes to access a sp^(3) chiral center with two functionalizable *** review summarizes the recent development of the enantioselective synthesis of gem-diborylalkanes and their application in asymmetric synthesis.

关键词： synthesis alkanes synthesis

Deep Reinforcement Learning Model for Blood Bank Vehicle Routing Multi-Objective Optimization

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Computers, Materials & Continua 2022年第2期70卷 3955-3967页

作者： Meteb M.Altaf Ahmed samir.Roshdy Hatoon S.AlSagri Director of Advanced Manufacturing and Industry 4.0 Center King Abdul-Aziz City for Science and Technology RiyadhSaudi Arabia Data Science and AI Senior Manager Vodafone CairoEgypt Information System Department Al Imam Mohammad Ibn Saud Islamic UniversityRiyadhSaudi Arabia

The overall healthcare system has been prioritized within development top lists *** many national populations are aging,combined with the availability of sophisticated medical treatments,healthcare expenditures are rapidly *** banks are a major component of any healthcare system,which store and provide the blood products needed for organ transplants,emergency medical treatments,and routine *** delivery of blood products is vital,especially in emergency ***,blood delivery process parameters such as safety and speed have received attention in the literature,as well as other parameters such as delivery *** this paper,delivery time and cost are modeled mathematically and marked as objective functions requiring simultaneous optimization.A solution is proposed based on Deep Reinforcement Learning(DRL)to address the formulated delivery functions as Multi-objective Optimization Problems(MOPs).The basic concept of the solution is to decompose the MOP into a scalar optimization sub-problems set,where each one of these sub-problems is modeled as a separate Neural Network(NN).The overall model parameters for each sub-problem are optimized based on a neighborhood parameter transfer and DRL training *** optimization step for the subproblems is undertaken collaboratively to optimize the overall *** solutions can be directly obtained using the trained ***,the multi-objective blood bank delivery problem is addressed in this *** technical advantage of this approach is that once the trainedmodel is available,it can be scaled without the need formodel *** scoring can be obtained directly using a straightforward computation of the NN layers in a limited *** proposed technique provides a set of technical strength points such as the ability to generalize and solve rapidly compared to othermulti-objective *** model was trained and tested on 5 major hospi

关键词： Optimization blood bank deep neural network reinforcement learning blood centers multi-objective optimization

LDSVM: Leukemia Cancer Classification Using Machine Learning

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Computers, Materials & Continua 2022年第5期71卷 3887-3903页

作者： Abdul Karim Azhari Azhari Mobeen Shahroz samir.Brahim Belhaouri Khabib Mustofa Department of Computer Science&Electronics Universitas Gadjah MadaYogyakarta55281Indonesia Department of Artificial Intelligence The Islamia University of BahawalpurBahawalpur63100Pakistan Division of Information&Computer Technology College of Science&EngineeringHamad Bin Khalifa UniversityDoha5825Qatar

Leukemia is blood cancer, including bone marrow and lymphatictissues, typically involving white blood cells. Leukemia produces an abnormalamount of white blood cells compared to normal blood. Deoxyribonucleicacid (DNA) microarrays provide reliable medical diagnostic services to helpmore patients find the proposed treatment for infections. DNA microarraysare also known as biochips that consist of microscopic DNA spots attachedto a solid glass surface. Currently, it is difficult to classify cancers usingmicroarray data. Nearly many data mining techniques have failed becauseof the small sample size, which has become more critical for ***, they are not highly effective in improving results and are frequently employed by doctors for cancer diagnosis. This study proposes a novelmethod using machine learning algorithms based on microarrays of leukemiaGSE9476 cells. The main aim was to predict the initial leukemia *** learning algorithms such as decision tree (DT), naive bayes (NB),random forest (RF), gradient boosting machine (GBM), linear regression(LinR), support vector machine (SVM), and novel approach based on thecombination of Logistic Regression (LR), DT and SVM named as ensembleLDSVM model. The k-fold cross-validation and grid search optimizationmethods were used with the LDSVM model to classify leukemia in patientsand comparatively analyze their impacts. The proposed approach evaluatedbetter accuracy, precision, recall, and f1 scores than the other ***, the results were relatively assessed, which showed LDSVMperformance. This study aims to successfully predict leukemia in patientsand enhance prediction accuracy in minimum time. Moreover, a Syntheticminority oversampling technique (SMOTE) and Principal compenent analysis(PCA) approaches were implemented. This makes the records generalized andevaluates the outcomes well. PCA reduces the feature count without losing anyinformation and deals with class imbalanced dataset

关键词： Leukemia GSE9476 cancer genes classification machine learning ensemble LDSVM classifier

A Novel Convolutional Neural Network Model for Malaria Cell Images Classification

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Computers, Materials & Continua 2022年第9期72卷 5889-5907页

作者： Esraa Hassan Mahmoud Y.Shams Noha A.Hikal samir.Elmougy Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt Department of Information Technology Faculty of Computers and InformationMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computers and InformationMansoura UniversityMansoura35516Egypt

Infectious diseases are an imminent danger that faces human beings around the *** is considered a highly contagious *** diagnosis of various diseases,including malaria,was performed manually,but it required a lot of time and had some human ***,there is a need to investigate an efficient and fast automatic diagnosis *** deep learning algorithms can provide a solution in which they can learn complex image patterns and have a rapid improvement in medical image *** study proposed a Convolutional Neural Network(CNN)model to detect malaria automatically.A Malaria Convolutional Neural Network(MCNN)model is proposed in this work to classify the infected *** focuses on detecting infected cells,which aids in the computation of parasitemia,or infection *** proposed model achieved 0.9929,0.9848,0.9859,0.9924,0.0152,0.0141,0.0071,0.9890,0.9894,and 0.9780 in terms of specificity,sensitivity,precision,accuracy,F1-score,and Matthews Correlation Coefficient,respectively.A comparison was carried out between the proposed model and some recent works in the *** comparison demonstrates that the proposed model outperforms the compared works in terms of evaluation metrics.

关键词： Deep learning malaria dataset diagnostic medical approach

EJUSTCO:Monte Carlo radiation transport code hybrid with ANN model for gamma-ray shielding simulation

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Nuclear Science and Techniques 2023年第9期34卷 155-176页

作者： Joseph Konadu Boahen Ahmed S.G.Khalil Mohsen A.Hassan samir.A.Elsagheer Mohamed Materials Science and Engineering Department School of Innovative Design EngineeringEgypt-Japan University of Science and Technology(E-JUST)179New Borg El-Arab CityEgypt Physics Department Environmental and Smart Technology GroupFaculty of ScienceFayoum UniversityFayoum 63514Egypt Faculty of Engineering Aswan UniversityAswanEgypt

Gamma ray shielding is essential to ensure the safety of personnel and equipment in facilities and environments where radiation *** Monte Carlo technique is vital for analyzing the gamma-ray shielding capabilities of *** this study,a simple Monte Carlo code,EJUSTCO,is developed to cd simulate gamma radiation transport in shielding materials for academic *** code considers the photoelectric effect,Compton(incoherent)scattering,pair production,and photon annihilation as the dominant interaction mechanisms in the gamma radiation shielding *** reduction techniques,such as the Russian roulette,survival weighting,and exponential transformation,are incorporated into the code to improve computational *** the exponential transformation parameter typically requires trial and error as well as ***,a deep learning neural network is proposed as a viable method for predicting this parameter for the first *** model achieves an MSE of 0.00076752 and an R-value of *** exposure buildup factors and radiation dose rates due to the passage of gamma radiation with different source energies and varying thicknesses of lead,water,iron,concrete,and aluminum in single-,double-,and triple-layer material systems are validated by comparing the results with those of MCNP,ESG,ANS-6.4.3,MCBLD,MONTEREY MARK(M),PENELOPE,and *** errors of 5.6%,2.75%,and 10%are achieved for the exposure buildup factor in single-,double-,and triple-layer materials,respectively.A significant parameter that is not considered in similar studies is the gamma ray *** the EJUSTCO code,the total number and energy albedos have been *** results are compared with those of MCNP,FOTELP,and *** general,the EJUSTCO-developed code can be employed to assess the performance of radiation shielding materials because the validation results are consistent with theoretical,experimental,and literary results.

关键词： Monte Carlo Gamma rays Shielding Artificial neural network Simulation

Wearable UWB Antenna-Based Bending and Wet Performances for Breast Cancer Detection

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Computers, Materials & Continua 2022年第12期73卷 5575-5587页

作者： Ali Hanafiah Rambe Muzammil Jusoh samir.Salem Al-Bawri Mahmoud A.Abdelghany Department of Electrical Engineering Universitas Sumatera UtaraMedan20155Indonesia Advanced Communication Engineering(ACE) Centre of ExcellenceFaculty of Electronic Engineering TechnologyUniversiti Malaysia PerlisMalaysia Department of General Educational Development Faculty of Science and Information Technology(FSIT)Daffodil International UniversityDhaka1341Bangladesh Space Science Centre Climate Change InstituteUniversiti Kebangsaan MalaysiaBangiMalaysia Department of Electronics and Communication Engineering Faculty of EngineeringHadhramout UniversityAl-MukallaYemen Electrical Engineering Department College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Addwasir11991Saudi Arabia Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt

This paper proposed integrating the communication system on the garment,which can be utilized to detect breast cancer at an early stage by using an ultra-wideband(UWB)wearable *** cancer is an abnormal cell that is located in the breast *** detection of breast cancer plays an important role,and it helps in the long term for all *** proposed UWB wearable antenna successfully operates at 3.1-10.6 GHz under an acceptable reflection coefficient of−10 *** fabricated wearable antenna was made from Shieldit Super and felt both conductive and nonconductive wearable *** measurement studies of bending angles have been carried out that covered 2°,4°,6°,8°,and 10°.In addition,the performance of UWB antennas in wet environments is studied in four stages:in water,instantly wet,nearly dry,and entirely *** is good agreement between the measured and simulated *** on the experimental results,the proposed antenna could be helpful for a home breast cancer detection system.

关键词： Wearable antenna UWB antenna bioelectromagnetic antenna propagation