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Neural Regeneration Research 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay ali Syed Hammad Qaiser Mohammad Uzair Khalid al-Regaiey Roaa Khallaf Lubna Abdullah mohammed albassam Imdad Kaleem Xueyi Wang Ran Wang Mehwish SBhatti Shahid Bashir Atta-ur-Rahman School of Applied Biosciences(ASAB) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological Sciences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Physiology College of MedicineKing Saud UniversityRiyadhSaudi Arabia Department of Neurology Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Mental Health Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Biosciences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Psychiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Institute of Hebei Medical University ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuroscience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for *** aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as alzheimer's *** these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging *** these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect *** review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly alzheimer's disease.

关键词： alzheimer’s disease brain aging cognitive health dementia molecular mechanisms neuronal activity neuroplasticity neurotransmission

Chloride ingress and macro-cell corrosion of steel in concrete made with recycled brick aggregate

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Frontiers of Structural and Civil Engineering 2021年第6期15卷 1358-1371页

作者： Tarek Uddin mohammed Mahfuzur RAHMAN Ahmed SABBIR Mohammad Mehedi hasan Abdullah al MAMUN Department of Civil and Environmental Engineering Islamic University of TechnologyBoard BazarGazipur 1704Bangladesh Department of Civil Engineering University of Information Technology and SciencesBaridharaDhaka 1202Bangladesh Bangladesh Road Research Laboratory Roads and Highways DepartmentMirpurDhaka 1216Bangladesh

An investigation on chloride ingress and macro-cell corrosion of steel bars in concrete made with recycled brick aggregate(RBA)was carried *** control cases,virgin brick aggregate(BA)and stone aggregate(SA)were also *** cylindrical and cracked prism specimens were studied for 16 different *** prism specimens were made with a segmented steel bar providing electrical connection from outside of the specimens to measure macro-cell corrosion current continuously under seawater splash exposure for a period of 30 d using a data *** specimens were submerged in 3%NaCl solution at a temperature of 40℃ to investigate chloride ingress in concrete made with RBA,BA,and SA after 120 and 180 ***-cell potential,corrosion area,and depths of corrosion were also *** chloride ingress as well as corrosion of steel bars in concrete made with the different types of aggregate is ordered as RBA>BA>SA.

关键词： brick aggregate chloride ingress macro-cell corrosion recycled brick aggregate

Practical Fast Computation of Zernike Moments

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Journal of Computer Science & Technology 2002年第2期17卷 181-188页

作者： al-Rawi mohammed 杨杰 Image Processing and Pattern Recognition Institute Shanghai Jiaotong University Shanghai 200030 P.R. China

The fast computation of Zernike moments from normalized geometric moments has been developed in this paper. The computation is multiplication free and only additions are needed to generate Zernike moments. Geometric moments are generated using Hatamian's filter up to high orders by a very simple and straightforward computation scheme. Other kinds of moments (e.g., Legendre, pseudo Zernike) can be computed using the same algorithm after giving the proper transformations that state their relations to geometric moments. Proper normalizations of geometric moments are necessary so that the method can be used in the efficient computation of Zernike moments. To ensure fair comparisons, recursive algorithms are used to generate Zernike polynomials and other coefficients. The computational complexity model and test programs show that the speed-up factor of the proposed algorithm is superior with respect to other fast and/or direct computations. It perhaps is the first time that Zernike moments can be computed in real time rates, which encourages the use of Zernike momentfeatures in different image retrieval systems that support huge databases such as the XM experimental model stated for the MPEG-7 experimental core. It is concluded that choosing direct computation would be impractical.

关键词： Zernike moment fast algorithm digital filter invariant patternrecognition

Device-free human micro-activity recognition method using WiFi signals

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Geo-Spatial Information Science 2019年第2期22卷 128-137,I0005页

作者： mohammed A.A.al-qaness School of Computer Science Wuhan UniversityWuhanChina

Human activity tracking plays a vital role in human–computer *** human activity recognition(HAR)methods adopt special devices,such as cameras and sensors,to track both macro-and ***,wireless signals have been exploited to track human motion and activities in indoor environments without additional *** study proposes a device-free WiFi-based micro-activity recognition method that leverages the channel state information(CSI)of wireless *** from existed CSI-based microactivity recognition methods,the proposed method extracts both amplitude and phase information from CSI,thereby providing more information and increasing detection *** proposed method harnesses an effective signal processing technique to reveal the unique patterns of each *** applied a machine learning algorithm to recognize the proposed *** proposed method has been evaluated in both line of sight(LOS)and none line of sight(NLOS)scenarios,and the empirical results demonstrate the effectiveness of the proposed method with several users.

关键词： Human activity recognition channel state information WiFi device-free microactivity recognition machine learning

The PCDD/PCDF Dioxin Releases in the Climate of Environment of Jordan in the Period (2000-2008)

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Journal of Thermal Science 2010年第2期19卷 182-192页

作者： mohammed Awwad al-Dabbas Mechanical Engineering department Mutah University

Many environment problems of the full using of several categories of processing include mining,heat generators,direct combustion of forest fires,cement production,power plant,transport,medical ***/furan releases from these categories are one of these environment *** lines of reducing the PCDD/PCDF (Polychlorinated dibenzo-para-dioxins/Polychlorinated dibenzofurans) releases from these categories are *** contribution of this paper is present the identification and estimation of the latest figure of dioxin/furan releases in the climate of environment of Jordan in the period 2000-2008 from the following categories (cement,aluminum,ceramic,medical waste,power plant,land fill,ferrous and non-ferrous metals,uncontrolled combustion process (biomass burning,waste burning,accidental fires in house,transport).These finding shows the sign of growth of estimated PCDD/PCDF releases from categories which did not calculated and followed after *** result shows the highest PCDD/PCDF release from landfill fires (62.75 g TEQ/year),medical waste (8.8264 g TEQ/year),and transport (3.0145 g TEQ/year).Jordan seeks by next years,a reduction in total releases of dioxins and furans from sources resulting from human *** challenge will apply to the aggregate of releases to the air nationwide and of releases to the water within the Jordan *** should conduct air monitoring for dioxin in order to track fluctuations in atmospheric deposition levels.

关键词： Jordan transport sector PCB dioxin & furan POP PCDD/PCDF power plant biogas

Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

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Computers, Materials & Continua 2022年第9期72卷 4675-4689页

作者： mohammed Hadwan mohammed A.al-Hagery mohammed al-Sarem Faisal Saeed Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Inteligent Analytic Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Institute for Artificial Intelligence and Big Data Universiti Malaysia KelantanPengkalan ChepaKota Bharu16100KelantanMalaysia

Different types of pandemics that have appeared from time to time have changed many aspects of daily *** governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during *** Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these *** manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming ***,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these *** research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning *** the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi *** findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app *** methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

关键词： Arabic sentiment analysis software quality user satisfaction improving online governmental services machine learning intelligent systems mobile app

A Novel Cryptocurrency Prediction Method Using Optimum CNN

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Computers, Materials & Continua 2022年第4期71卷 1051-1063页

作者： Syed H.hasan Syeda Huyam hasan mohammed Salih Ahmed Syed Hamid hasan Iowa State University AmesUSA University of Texas at Arlington USA Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

In recent years,cryptocurrency has become gradually more significant in economic regions *** cryptocurrencies,records are stored using a cryptographic *** main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social *** is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media ***,this work focuses on extracting Tweets and gathering data from different sources to classify them into positive,negative,and neutral categories,and further examining the correlations between cryptocurrency movements and Tweet *** paper proposes an optimized method using a deep learning algorithm and convolution neural network for cryptocurrency prediction;this method is used to predict the prices of four cryptocurrencies,namely,Litecoin,Monero,Bitcoin,and *** results of analyses demonstrate that the proposed method forecasts prices with a high accuracy of about 98.75%.The method is validated by comparison with existing methods using visualization tools.

关键词： Cryptocurrency litecoin monero bitcoin ethereum twitter optimal CNN price prediction sentiment analysis

Identification of Tuberculosis and Coronavirus Patients Using Hybrid Deep Learning Models

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Computers, Materials & Continua 2023年第7期76卷 881-894页

作者： mohammed A.al Ghamdi Computer Science Department Umm Al-Qura UniversityMakkah City24243Saudi Arabia

Considerable resources,technology,and efforts are being utilized worldwide to eradicate the *** certain measures taken to prevent the further spread of the disease have been successful,efforts to completely wipe out the coronavirus have been *** patients have symptoms similar to those of chest Tuberculosis(TB)or pneumonia *** tuberculosis and coronavirus are similar because both diseases affect the lungs,cause coughing and produce an irregular respiratory *** diseases can be confirmed through X-ray *** is a difficult task to diagnose COVID-19,as coronavirus testing kits are neither excessively available nor very *** addition,specially trained staff and specialized equipment in medical laboratories are needed to carry out a coronavirus ***,most of the staff is not fully trained,and several laboratories do not have special equipment to perform a coronavirus ***,hospitals and medical staff are under stress to meet necessary *** of the time,these staffs confuse the tuberculosis or pneumonia patient with a coronavirus patient,as these patients present similar *** meet the above challenges,a comprehensive solution based on a deep learning model has been proposed to distinguish COVID-19 patients from either tuberculosis patients or healthy *** framework contains a fusion of Visual Geometry Group from Oxford(VGG16)and Residual Network(ResNet18)algorithms as VGG16 contains robust convolutional layers,and Resnet18 is a good *** proposed model outperforms other machine learning and deep learning models as more than 94%accuracy for multiclass identification has been achieved.

关键词： Tuberculosis coronavirus X-ray deep learning VGG16 and ResNet18

Human-Animal Affective Robot Touch Classification Using Deep Neural Network

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Computer Systems Science & Engineering 2021年第7期38卷 25-37页

作者： mohammed Ibrahim Ahmed al-mashhadani Theyazn H.H.aldhyani Mosleh Hmoud al-Adhaileh alwi M.Bamhdi mohammed Y.alzahrani Fawaz Waselallah alsaade hasan alkahtani al-Iraqia University College of EducationComputer DepartmentBaghdadIraq Community College of Abqaiq King Faisal UniversityAl-AhsaSaudi Arabia Deanship of E-learning and Distance Education King Faisal UniversityAl-AhsaSaudi Arabia UMM al-Qura University College of ComputingMakkahSaudi Arabia Department of Computer Sciences and Information Technology Albaha UniversityAl BahaSaudi Arabia College of Computer Science and Information Technology King Faisal UniversityAl-AhsaSaudi Arabia

Touch gesture recognition is an important aspect in human-robot interaction,as it makes such interaction effective and *** novelty of this study is the development of a system that recognizes human-animal affective robot touch(HAART)using a deep learning *** proposed system was used for touch gesture recognition based on a dataset provided by the Recognition of the Touch Gestures Challenge *** dataset was tested with numerous subjects performing different HAART gestures;each touch was performed on a robotic animal covered by a pressure sensor skin.A convolutional neural network algorithm is proposed to implement the touch recognition system from row inputs of the sensor *** leave-one-subject-out cross-validation method was used to validate and evaluate the proposed system.A comparative analysis between the results of the proposed system and the state-of-the-art performance is *** show that the proposed system could recognize the gestures in almost real time(after acquiring the minimum number of frames).According to the results of the leave-one-subject-out cross-validation method,the proposed algorithm could achieve a classification accuracy of 83.2%.It was also superior compared with existing systems in terms of classification ratio,touch recognition time,and data preprocessing on the same ***,the proposed system can be used in a wide range of real applications,such as image recognition,natural language recognition,and video clip classification.

关键词： Touch gesture recognition touch gesture classification deep learning