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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

An efficient improved Gradient Boosting for strain prediction in Near-Surface Mounted fiber-reinforced polymer strengthened reinforced concrete beam

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1148-1168页

作者： Abdelwahhab KHATIR Roberto CAPOZUCCA samir KHATIR Erica MAGAGNINI Brahim BENAISSA Thanh CUONG-LE Structural Section DICEA Polytechnic University of MarcheAncona 60131Italy Centre for Engineering Application&Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh City 70000Vietnam Design Engineering Laboratory Toyota Technological InstituteNagoya 468-8511Japan

The Near-Surface Mounted(NSM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent *** the past two decades,researchers have extensively studied its potential,advantages,and applications,as well as related parameters,aiming at optimization of construction ***,there is still a need to explore further,both from a static perspective,which involves accounting for the nonconservation of the contact section resulting from the bond-slip effect between fiber-reinforced polymer(FRP)rods and resin and is typically neglected by existing analytical models,as well as from a dynamic standpoint,which involves studying the trends of vibration frequencies to understand the effects of various forms of damage and the efficiency of *** address this gap in knowledge,this research involves static and dynamic tests on simply supported reinforced concrete(RC)beams using rods of NSM carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP).The main objective is to examine the effects of various strengthening *** research conducts bending tests with loading cycles until failure,and it helps to define the behavior of beam specimens under various damage degrees,including concrete *** analysis by free vibration testing enables tracking of the effectiveness of the reinforcement at various damage levels at each stage of the loading *** addition,application of Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)is proposed to optimize Gradient Boosting(GB)training performance for concrete strain prediction in NSM-FRP *** GB using Particle Swarm Optimization(GBPSO)and GB using Genetic Algorithm(GBGA)systems were trained using an experimental data set,where the input data was a static applied load and the output data was the consequent *** models of GBPSO and GBGA have been shown to provide highly accurate results for predicting *** model

关键词： NSM technique fiber-reinforced polymer rods static and dynamic analysis GB PSO GA finite element analysis

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

Computed tomography angiography-negative aortic dissection in a patient using Phencyclidine

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World Journal of Emergency Medicine 2018年第2期9卷 144-148页

作者： Daniel DeWeert Elise Lovell samir Patel Advocate Christ Medical Center 4440 95th St Oak Lawn IL 60453 USA

Although the average age of diagnosis for aorticdissection is 63,[1] this case demonstrates the need toconsider AD in younger patients, particularly in thepresence of risk factors or in the absence of anotherreasonable diagnosis. This case suggests PCP use as aprecipitant for hypertension and sympathomimetic stresson the aorta. Despite high sensitivity, false negativeCTA imaging for AD can occur. If pretest probabilityremains high, further imaging must be obtained. Duringresuscitation in the ED, focused point-of-care ultrasoundcan also assist with medical decision making.

关键词： Computed tomography angiography-negative aortic dissection a patient using Phencyclidine

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

Simulink Behavioral Modeling of a 10-bit Pipelined ADC

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International Journal of Automation and computing 2013年第2期10卷 134-142页

作者： samir Barra Souhil Kouda Abdelghani Dendouga N. E. Bouguechal Advanced Electronics Laboratory Department of Electronics University of Batna Avenue Chahid Boukhlouf Mohamed El Hadi05000Batna Algeria Department of electronics University of M'sila M'silaAlgeria Center for Development of Advanced Technologies Microelectronics and Nanotechnology DivisionAugust 20 1956 City BP 17 BabaHassen Algiers Algeria

The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specific data converter simulation environment has been developed which allows designers to perform time-domain behavioral simulations of pipelined analog to digital converters （ADCs）. All the necessary blocks of this specific simulation environment have been implemented using the popular Matlab simulink environment. The purpose of this paper is to present the behavioral models of these blocks taking into account most of the pipelined ADC non-idealities, such as sampling jitter, noise, and operational amplifier parameters （white noise, finite DC gain, finite bandwidth, slew rate, and saturation voltages）. Simulations, using a 10-bit pipelined ADC as a design example, show that in addition to the limits analysis and the electrical features extraction, designers can determine the specifications of the basic blocks in order to meet the given data converter requirements.

关键词： Behavioral modeling analog to digital converters (ADCs) pipelined ADC multiple digital to analog converter (MDAC) sample and hold (S/H)

Interaction analysis of back-to-back mechanically stabilized earth walls

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Journal of Rock Mechanics and Geotechnical Engineering 2016年第5期8卷 697-702页

作者： Sadok Benmebarek samir Attallaoui Nai'ma Benmebarek NMISSI Laboratory Biskra UniversityBiskra 07000Algeria

Back-to-back mechanically stabilized earth walls （BBMSEWs） are encountered in bridge approaches, ramp ways, rockfall protection systems, earth dams, levees and noise barriers. However, available design guidelines for BBMSEWs are limited and not applicable to numerical modeling when back-to-back walls interact with each other. The objective of this paper is to investigate, using PLAXIS code, the effects of the reduction in the distance between BBMSEW, the reinforcement length, the quality of backfill material and the connection of reinforcements in the middle, when the back-to-back walls are close. The results indicate that each of the BBMSEWs behaves independently if the width of the embankment between mechanically stabilized earth walls is greater than that of the active zone. This is in good agreement with the result of FHWA design guideline. However, the results show that the FHWA design guideline underestimates the lateral earth pressure when back-to-back walls interact with each other. Moreover, for closer BBMSEWs, FHWA design guideline strongly overestimates the maximum tensile force in the reinforcement. The investigation of the quality of backfill material shows that the minor increase in embankment cohesion can lead to significant reductions in both the lateral earth pressure and the maximum tensile force in geosynthetic. When the distance between the two earth walls is close to zero, the connection of reinforcement between back-to-back walls significantly improves the factor of safety.

关键词： Back-to-back walls Numerical analysis Geosynthetic Factor of safety Lateral earth pressure Maximum tensile force Reinforcement

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

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

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