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Deflection behavior of a prestressed concrete beam reinforced with carbon fibers at elevated temperatures

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Frontiers of Structural and Civil Engineering 2019年第1期13卷 81-91页

作者： mohammed FARUQI mohammed Sheroz khan Department of Civil and Architectural Engineering Texas A&M University--KingsvilleTexasUSA

Fiber reinforced polymer(FRP) have unique advantages like high strength to weight ratio,excellent corrosion resistance,improving deformability and cost *** advantages have gained wide acceptance in civil engineering *** tendons for prestressing applications are emerging as one of the most promising technologies in the civil engineering ***,the behavior of such members under the influence of elevated temperatures is still *** knowledge and application of this could lead to a cost effective and practical considerations in fire safety ***,this study examines the deflection behavior of the carbon fiber reinforced polymer(CFRP) prestressed concrete beam at elevated *** this article,an analytical model is developed which integrates the temperature dependent changes of effective modulus of FRP in predicting the deflection behavior of CFRP prestressed concrete beams within the range of practical *** model is compared with a finite element mode (FEM) of a simply supported concrete beam prestressed with CFRP subjected to practical elevated *** addition,comparison is also made with an indirect reference to the real behavior of the *** results of the model correlated reasonably with the finite element model and the real ***,a practical application is provided.

关键词： FRP CFRP concrete elevated temperatures deflections prestress

Numerical evaluation of enhanced green infrastructures for mitigating urban heat in a desert urban setting

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Building Simulation 2023年第9期16卷 1691-1712页

作者： Afifa mohammed Ansar khan Mattheos Santamouris Faculty of Built Environment University of New South WalesSydneyAustralia Department of Geography Lalbaba CollegeUniversity of CalcuttaKolkataIndia

The cities of desert climates are anticipated to recognize a synergy of urban heat island(UHI)and severe heat waves during *** improve the urban thermal environment,the present study aims quantitatively explore a strategically designed network of vegetation patches called green infrastructure(GI)in subtropical desert cities such as *** achieve a more comfortable temperature environment,we built and simulated four GI situations with higher GI fractions,GI25,GI50,GI75,and *** a mesoscale urban model,the mosaic approach is utilized to test potential thermal improvement and urban climate impact,and a portion of each urban grid cell in the model domain is altered with various species of urban vegetation patches by 25%,50%,75%,and 100%.The daily peak reduction in ambient temperature at 17:00LT is similar to 0.0168℃ per unit of GI increase when compared to the untreated scenario;however,the maximum anticipated daytime summer temperature decline for GI25,GI50,GI75,and GI100 is 0.6℃,1.1℃,1.4℃,and 1.7℃,*** associated reduction in nighttime ambient temperature per unit increase in the GI is 0.0432℃,with a maximum temperature drop of around 2.4℃ for the GI100 *** GI reduces the height of the planetary boundary layer(PBL)by up to 468 m,which might lead to greater pollution *** GI-based cooling has a significant influence on delayed sea breeze and humidity,it may raise the risk of heat discomfort in the indoor building *** study adds to our understanding of the potential for GI mitigation as well as the seasonal impact of developing GIs on the desert urban boundary layer.

关键词： green infrastructure heat mitigation urban heat WRF-SLUCM Dubai city

Power Allocation in NOMA-CR for 5G Enabled IoT Networks

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Computers, Materials & Continua 2022年第9期72卷 5515-5530页

作者： mohammed Basheri Mohammad Haseeb Zafar Imran khan Department of Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityCardiffCF52YBUK Department of Electrical Engineering University of Engineering&TechnologyPeshawar25120Pakistan

In the power domain,non-orthogonal multiple access(NOMA)supports multiple users on the same time-frequency resources,assigns different transmission powers to different users,and differentiates users by user channel ***-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC)is performed at the receiving end to demodulate the necessary user *** contrast to the orthogonal transmission method,the non-orthogonal method can achieve higher spectrum ***,it will increase the receiver *** the development of microelectronics technology,chip processing capabilities continue to increase,laying the foundation for the practical application of non-orthogonal transmission *** NOMA,different users are differentiated by different power ***,the power allocation has a considerable impact on the NOMA system *** address this issue,the idea of splitting power into two portions,intra-subbands and intersubbands,is proposed in this study as a useful ***,such optimization problems are solved using proportional fair scheduling and water-filling ***,the error propagation was modeled and analyzed for the residual *** proposed technique effectively increased the system throughput and performance under various operating settings according to simulation findings.A comparison is performed with existing algorithms for performance evaluation.

关键词： NOMA wireless networks power domain 5G networks

Unveiling the impact:COVID-19's influence on bacterial resistance in the Kingdom of Bahrain

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World Journal of Virology 2025年第1期14卷 83-98页

作者： Nermin K Saeed Safiya K Almusawi Noor A Albalooshi mohammed Al-Beltagi Medical Microbiology Section Department of PathologySalmaniya Medical ComplexGovernmental HospitalsManama 12Bahrain Medical Microbiology Section Department of PathologyRoyal College of Surgeons in Ireland-Medical University of BahrainBusaiteen 15503MuharraqBahrain Department of Paediatrics Faculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Pediatric University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityManama 26671AlgharbiaBahrain

BACKGROUND Antibiotic resistance is a growing global health threat,and understanding local trends in bacterial isolates and their susceptibility patterns is crucial for effective infection control and antimicrobial *** coronavirus disease 2019(COVID-19)pandemic has introduced additional complexities,potentially influencing these *** To analyze trends in bacterial isolates and their antibiotic susceptibility patterns at Salmaniya Medical Complex from 2018 to 2023,with a specific focus on the impact of the COVID-19 pandemic on these *** A retrospective analysis of microbiological data was conducted,covering the period from 2018 to *** study included key bacterial pathogens such as Escherichia coli(***),Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,and Staphylococcus aureus,among *** antibiotic susceptibility profiles of these isolates were assessed using standard laboratory *** contextualize the findings,the findings were compared with similar studies from other regions,including China,India,Romania,Saudi Arabia,the United Arab Emirates,Malaysia,and United *** The study revealed fluctuating trends in the prevalence of bacterial isolates,with notable changes during the COVID-19 *** example,a significant increase in the prevalence of Staphylococcus aureus was observed during the pandemic years,while the prevalence of *** showed a more variable *** resistance rates varied among the different pathogens,with a concerning rise in resistance to commonly used antibiotics,particularly among Klebsiella pneumoniae and ***,the study identified an alarming increase in the prevalence of multidrug-resistant(MDR)strains,especially within Klebsiella pneumoniae and *** *** impact of the COVID-19 pandemic on these trends was evident,with shifts in the frequency,resistance patterns,and the emergence of MDR bacteria among several key ***

关键词： Multidrug-resistant organisms Antibiotic susceptibility COVID-19 pandemic Antimicrobial stewardship Bacterial isolates Salmaniya Medical Complex Bahrain

Mutated Leader Sine-Cosine Algorithm for Secure Smart IoT-Blockchain of Industry 4.0

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Computers, Materials & Continua 2022年第12期73卷 5367-5383页

作者： Mustufa Haider Abidi Hisham Alkhalefah Muneer khan mohammed Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box-800Riyadh11421Saudi Arabia

In modern scenarios,Industry 4.0 entails invention with various advanced technology,and blockchain is one among *** are incorporated to enhance privacy,data transparency aswell as security for both large and small scale *** 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target ***,because numerous devices and machines are involved,data security and privacy are always *** achieve intelligence in Industry 4.0,blockchain technologies can overcome potential cybersecurity ***,the blockchain and internet of things(IoT)are gaining more attention because of their favorable outcome in several *** they generate massive data that need to be effectively optimized and in this research work,deep learning-based techniques are employed for *** paper proposes a novel mutated leader sine cosine algorithm-based deep convolutional neural network(MLSC-DCNN)in order to attain a secure and optimized IoT blockchain for Industry ***,an MLSC is hybridized using a mutated leader and sine cosine algorithm to enhance the weight function and minimize the loss factor of ***,the experimentation is carried out for various simulation *** comparative analysis is made for Best Tip Selection Method(BTSM),Smart Block-Software Defined Networking(SDN),and the proposed *** evaluation results show that the proposed approach attains better performances than BTSM and SDN.

关键词： Industry 4.0 internet of things(IoT) blockchain deep convolutional neural network mutated leader

Importance of Features Selection,Attributes Selection,Challenges and Future Directions for Medical Imaging Data:A Review

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Computer Modeling in Engineering & Sciences 2020年第10期125卷 315-344页

作者： Nazish Naheed Muhammad Shaheen Sajid Ali khan mohammed Alawairdhi Muhammad Attique khan Faculty of Engineering&Information Technology Foundation University IslamabadIslamabadPakistan College of Computing and Informatics Saudi Electronic UniversityRayadhSaudi Arabia Department of Computer Science HITEC UniversityTaxilaPakistan

In the area of pattern recognition and machine learning,features play a key role in *** famous applications of features are medical imaging,image classification,and name a few *** the exponential growth of information investments in medical data repositories and health service provision,medical institutions are collecting large volumes of *** data repositories contain details information essential to support medical diagnostic decisions and also improve patient care *** the other hand,this growth also made it difficult to comprehend and utilize data for various *** results of imaging data can become biased because of extraneous features present in larger *** selection gives a chance to decrease the number of components in such large *** selection techniques,ousting the unimportant features and selecting a subset of components that produces prevalent characterization *** correct decision to find a good attribute produces a precise grouping model,which enhances learning pace and forecast *** paper presents a review of feature selection techniques and attributes selection measures for medical *** review is meant to describe feature selection techniques in a medical domainwith their pros and cons and to signify its application in imaging data and data mining *** review reveals the shortcomings of the existing feature and attributes selection techniques to multi-sourced ***,this review provides the importance of feature selection for correct classification of medical *** the end,critical analysis and future directions are provided.

关键词： Medical imaging imaging data feature selection data mining attribute selection medical challenges future directions

Beneficial effects of date palm fruits on neurodegenerative diseases

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Neural Regeneration Research 2016年第7期11卷 1071-1072页

作者： Musthafa Mohamed Essa mohammed Akbar mohammed Abdul Sattar khan Department of Food Science and Nutrition College of Agriculture and Marine SciencesSultan Qaboos University Ageing and Dementia Research Group Sultan Qaboos University Section of Molecular Pharmacology and Toxicology Laboratory of Membrane Biochemistry and BiophysicsNational Institute on Alcohol Abuse and AlcoholismNational Institutes of Health Department of Anesthesia Critical Care and Pain MedicineShriners Hospitals for Children~?Massachusetts General Hospital and Harvard Medical School

Date palm tree（Phoenix dactylifera L.）is an important crop,which is cultivated in many countries extending from North Africa to the Middle East,including many of the GCC（Gulf Cooperation Council）Countries（Allaith... 详细信息

关键词： fruits Phoenix climatic cultivated Africa neuronal Middle amyloid poorly occlusion

Application of the Deep Convolutional Neural Network for the Classification of Auto Immune Diseases

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Computers, Materials & Continua 2023年第10期77卷 647-664页

作者： Fayaz Muhammad Jahangir khan Asad Ullah Fasee Ullah Razaullah khan Inayat khan mohammed ElAffendi Gauhar Ali Department of Computer Science and Information Technology Sarhad University of Science and Information TechnologyPeshawar25000Pakistan Department of Computer Science University of Engineering and TechnologyMardan23200Pakistan EIAS Data Science and Blockchain Lab College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia

IIF(Indirect Immune Florescence)has gained much attention recently due to its importance in medical *** primary purpose of this work is to highlight a step-by-step methodology for detecting autoimmune *** use of IIF for detecting autoimmune diseases is widespread in different medical *** 80 different types of autoimmune diseases have existed in various body *** IIF has been used for image classification in both ways,manually and by using the Computer-Aided Detection(CAD)*** data scientists conducted various research works using an automatic CAD system with low *** diseases in the human body can be detected with the help of Transfer Learning(TL),an advanced Convolutional Neural Network(CNN)*** baseline paper applied the manual classification to the MIVIA dataset of Human Epithelial cells(HEP)type II cells and the Sub Class Discriminant(SDA)analysis technique used to detect autoimmune *** technique yielded an accuracy of up to 90.03%,which was not reliable for detecting autoimmune disease in the mitotic cells of the *** the current research,the work has been performed on the MIVIA data set of HEP type II cells by using four well-known models of *** augmentation and normalization have been applied to the dataset to overcome the problem of overfitting and are also used to improve the performance of TL *** models are named Inception V3,Dens Net 121,VGG-16,and Mobile Net,and their performance can be calculated through parameters of the confusion matrix(accuracy,precision,recall,and F1 measures).The results show that the accuracy value of VGG-16 is 78.00%,Inception V3 is 92.00%,Dense Net 121 is 95.00%,and Mobile Net shows 88.00%accuracy,***,DenseNet-121 shows the highest performance with suitable analysis of autoimmune *** overall performance highlighted that TL is a suitable and enhanced technique compared to its ***,the proposed technique is used

关键词： Indirect immune fluorescence computer-aided diagnosis transfer learning confusion matrix

Intelligent Forecasting Model of COVID-19 Novel Coronavirus Outbreak Empowered with Deep Extreme Learning Machine

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Computers, Materials & Continua 2020年第9期64卷 1329-1342页

作者： Muhammad Adnan khan Sagheer Abbas Khalid Masood khan mohammed AAl Ghamdi Abdur Rehman Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science Umm Al-Qura UniversityMakkah23500Saudi Arabia

An epidemic is a quick and widespread disease that threatens many lives and damages the *** epidemic lifetime should be accurate so that timely and remedial steps are *** include the closing of borders schools,suspension of community and commuting *** forecast of an outbreak effectively is a very necessary but difficult task.A predictive model that provides the best possible forecast is a great challenge for machine learning with only a few samples of training *** work proposes and examines a prediction model based on a deep extreme learning machine(DELM).This methodology is used to carry out an experiment based on the recent Wuhan coronavirus *** optimized prediction model that has been developed,namely DELM,is demonstrated to be able to make a prediction that is fairly *** results show that the new methodology is useful in developing an appropriate forecast when the samples are far from abundant during the critical period of the *** the investigation,it is shown that the proposed approach has the highest accuracy rate of 97.59%with 70%of training,30%of test and *** results validate the prediction effectiveness of the proposed scheme.

关键词： Coronavirus nCoV DELM Mis rate SERS-CoV WHO COVID-19