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A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

Computers, Materials & Continua 2023年第4期75卷 165-182页

作者： Muhammad Azhar Sehat ullah khalil ullah Habib Shah Abdallah Namoun Khaliq Ur Rahman Department of Computer Science&IT University of MalakandChakdara18800Pakistan Department of Software Engineering University of MalakandChakdara18800Pakistan College of Computer Science King Khalid UniversityAbha62529Saudi Arabia Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan

Human biometric analysis has gotten much attention due to itswidespread use in different research areas, such as security, surveillance,health, human identification, and classification. Human gait is one of the keyhuman traits that can identify and classify humans based on their age, gender,and ethnicity. Different approaches have been proposed for the estimation ofhuman age based on gait so far. However, challenges are there, for which anefficient, low-cost technique or algorithm is needed. In this paper, we proposea three-dimensional real-time gait-based age detection system using a machinelearning approach. The proposed system consists of training and testingphases. The proposed training phase consists of gait features extraction usingthe Microsoft Kinect (MS Kinect) controller, dataset generation based onjoints’ position, pre-processing of gait features, feature selection by calculatingthe Standard error and Standard deviation of the arithmetic mean and bestmodel selection using R2 and adjusted R2 techniques. T-test and ANOVAtechniques show that nine joints (right shoulder, right elbow, right hand, leftknee, right knee, right ankle, left ankle, left, and right foot) are statisticallysignificant at a 5% level of significance for age estimation. The proposedtesting phase correctly predicts the age of a walking person using the resultsobtained from the training phase. The proposed approach is evaluated on thedata that is experimentally recorded from the user in a real-time *** (50) volunteers of different ages participated in the experimental *** the limited features, the proposed method estimates the age with 98.0%accuracy on experimental images acquired in real-time via a classical generallinear regression model.

关键词： Age estimation gait biometrics classical linear regression model

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Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali Maqbool Khan khalil Khan Rehan ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

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Automatic Detection of Outliers in Multi-Channel EMG Signals Using MFCC and SVM

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Intelligent Automation & Soft Computing 2023年第4期36卷 169-181页

作者： Muhammad Irfan khalil ullah Fazal Muhammad Salman Khan Faisal Althobiani Muhammad Usman Mohammed Alshareef Shadi Alghaffari Saifur Rahman Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Software Engineering University of MalakandDir LowerPakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science University of Engineering and TechnologyMardan23200Pakistan

The automatic detection of noisy channels in surface Electromyogram(sEMG)signals,at the time of recording,is very critical in making a noise-free EMG *** an EMG signal contaminated by high-level noise is recorded,then it will be useless and can’t be used for any healthcare *** this research work,a new machine learning-based paradigm is proposed to automate the detection of low-level and high-level noises occurring in different channels of high density and multi-channel sEMG signals.A modiﬁed version of mel fre-quency cepstral coefﬁcients(mMFCC)is proposed for the extraction of features from sEMG channels along with other statistical parameters i-e complexity coef-ﬁcient,hurst exponent,and root mean *** state-of-the-art classiﬁers such as Support Vector Machine(SVM),Ensemble Bagged Trees,Ensemble Sub-space Discriminant,and Logistic Regression are used to automatically identify an EMG channel either bad or good based on these extracted ***-based analyses of these classiﬁers have also been considered based on total classi-ﬁcation accuracy,prediction speed(observations/sec),and processing *** proposed method is tested on 320 simulated EMG channels as well as 640 experi-mental EMG *** is used as our main classiﬁer for the detection of noisy channels which gives a total classiﬁcation accuracy of 99.4%for simulated EMG channels whereas accuracy of 98.9%is achieved for experimental EMG channels.

关键词： Machine learning surface electromyography support vector machine classiﬁcation features

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Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

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Computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： Abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani khalil ullah Khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

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Ethnoveterinary medicines used against various livestock disorders in the flora of Shamozai Valley, Swat,KP Pakistan

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Traditional Medicine Research 2020年第5期5卷 377-388页

作者： Noor Muhammad Muhammad khalil ullah Khan Nisar Uddin Niaz Ali Shariat ullah Muhammad Umer College of Horticulture Hebei Agricultural UniversityBaoding 071000China Department of Botany Hazara UniversityMansehra 21300KPPakistan Department of Botany University of MalakandChakdara 18800KPPakistan College of Plant Protection Hebei Agricultural UniversityBaoding 071000China

Background:The Shamozai Valley of Swat District is remarkable with various plant *** information offers folk remedies for livestock,which are cheaper than standard treatment methods and are readily ***:Different trips were organized for gathering(harvesting)and recording medicinal plants in the area during 2018.A total of 140 local residents were ***,the obtained data were evaluated using used value,relative frequency citations,fidelity level,consensus index,and informant consensus ***:In this study,41 plants were presented,and these plants were used commonly as medication for treating various livestock *** therapeutic plants with most used value were Artemisia scoparia(0.607),Berberis lyceum Royle(0.610),Bromus japonicus(0.491),Avena sativa(0.482),Cannabis sativa L.(0.473),Capsicum annum L.(0.471),Cedrus deodara(0.462),and Chenopodium murale(0.453).On the basis of relative frequency citations values,the most quoted plant species by the indigenous people are Artemisia scoparia(0.760),Berberis lyceum(0.742),Bromus japonicus(0.731),Avena sativa(0.721),and Cannabis sativa L.(0.711).Consensus index percentage showed the highest for Artemisia scoparia(83.109%),followed by Berberis lyceum Royle(80.454%),whereas the ethnomedicinal plant species with most fidelity level were Artemisia scoparia(76.320%),Berberis lyceum Royle(73.403%),Bromus japonicus(72.013%),Avena sativa(71.024%),Cannabis sativa L.(69.322%),Capsicum annum L(68.344%),Cedrus deodara(67.215%),and Chenopodium murale(66.060%)for various *** consensus factor ranged from 0.947 to 1.000,whereas different ailments ***-causing agent,carminative treatment,eye diseases,mouth ulcers,myiasis,pediculosis,septicemia,and tick infestation had maximum informant consensus factor ***:The publics of Shamozai are deeply reliant on ethomedicinal plants for treating numerous livestock *** information always offers a

关键词： Ethnoveterinary practices Medicinal plants Folk knowledge Livestock ailments Shamozai Valley

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Annual growth of Fagus orientalis is limited by spring drought conditions in Iran’s Golestan Province

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Journal of Forestry Research 2024年第1期35卷 128-142页

作者： khalil Ghorbani Jahangir Mohammadi Laleh Rezaei Ghaleh Department of Water Engineering Faculty of Water and Soil EngineeringGorgan University of Agricultural Sciences and Natural ResourcesGorganIran Department of Forestry Gorgan University of Agricultural Sciences and Natural ResourcesGorganIran Department of Water Engineering Faculty of AgricultureUrmia UniversityUrmiaIran

Due to the lack of a uniform and accurate defi-nition of‘drought’,several indicators have been introduced based on different variables and methods,and the efficiency of each of these is determined according to their relationship with *** relationship between two drought indices,SPI(standardized precipitation index)and SPEI(standard-ized precipitation-evapotranspiration index)in different sea-sons was investigated using annual rings of 15 tree samples to determine the effect of drought on the growth of oriental beech(Fagus orientalis Lipsky)in the Hyrcanian forests of northern *** different evapotranspiration calcula-tion methods were evaluated on SPEI efficiency based on Hargreaves-Samani,Thornthwaite,and Penman-Monteith methods using the step-by-step M5 decision tree regression *** results show that SPEI based on the Penman-Monteith in a three-month time scale(spring)had similar temporal changes and a better relationship with annual tree rings(R^(2)=0.81)at a 0.05 significant *** change and a decreasing trend in the time series of annual tree rings are similar to the variation in the SPEI based on the Penman-Monteith *** affecting evapotranspiration,temperature,wind speed,and sunshine hours(used in the Penman-Monteith method),increased but precipitation *** non-linear modeling methods,SPEI based on Penman-Monteith best illustrated climate changes affecting tree growth.

关键词： Climate change Drought index Hyrcanian forests SPEI'Annual growth rings Fagus orientalis

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ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

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Intelligent Automation & Soft Computing 2024年第2期39卷 301-317页

作者： Aiman Muhammad Arshad Bilal Khan khalil Khan Ali Mustafa Qamar Rehan ullah Khan Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstanaKazakhstan Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and *** improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and *** evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are *** findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,*** metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling *** study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and *** results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

关键词： Machine learning author profiling AdaBoostM1 random forest ensemble learning text classification

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Pore-scale study of the effects of DTPA chelating agent flooding on oil recovery utilizing a clay-coated micromodel

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Petroleum Research 2024年第2期9卷 228-237页

作者： Hojjat Mohammadzadeh Jamshid Moghadasi khalil Shahbazi Shahin Kord Department of Petroleum Engineering Ahwaz Faculty of Petroleum EngineeringPetroleum University of TechnologyAhwazIran

The use of diethylenetriaminepentaacetic acid(DTPA)chelating agent has shown promising results for enhanced oil recovery(EOR)in prior *** mechanisms,mainly resulting from rock-fluid interaction,have been proposed for chelating agent flooding;however,little attention has been paid to fluid-fluid interaction thus *** assessment of these mechanisms has primarily relied on macroscopic techniques such as core *** paper aims to investigate the injection of DTPA brine and its dominant mechanisms at the pore scale using a clay-coated *** micromodel tests were performed under oil-wet and water-wet *** a more precise examination of fluid/fluid interactions,the dynamic interfacial tension(IFT)and Zeta potential were *** was observed that the injection of DTPA brine in water-wet state changed the saturation distribution and increased oil *** on visual inspections,this change in saturation distribution could potentially be linked to the formation of micro-dispersions and viscoelastic interfacial ***-dispersions facilitate flow to unswept areas,and viscoelastic interface formation reshapes the interface between oil and brine,causing disconnected oil droplets to coalesce and thus increase *** the oil-wet state,the micro-dispersion formation and wettability alteration can be the dominant mechanisms,and the amount of recovered oil was higher than that observed in the water-wet ***,Zeta potential measurements at the interface between brine and oil showed a more negative value for DTPA brine,which is effective in wettability alteration and micro-dispersions *** results indicate that IFT reduction was not significant enough to be considered the dominant mechanism,although it assists in DTPA brine penetration into the crude oil and subsequent micro-dispersion formation.

关键词： Enhanced oil recovery technique Chelating agent Micromodel Fluid/fluid interaction Micro-dispersions Viscoelastic interface

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Exploring the molecular landscape of NNK-induced transformation:A comprehensive genome-wide CRISPR/Cas9 screening

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Genes & Diseases 2024年第4期11卷 42-44页

作者： Trang Dinh Mira Rahm Zhenghe Wang Christopher McFarland Athar khalil Department of Genetics and Genome Sciences Case WesternReserve UniversityClevelandOH44106USA

Lung cancer is the leading cause of cancer-related deaths worldwide,with an estimated 1.8 million deaths in 2020 alone.1 While several risk factors are associated with lung cancer,smoking remains the most significant environmental cause of the disease.1 One of the most potent carcinogens in tobacco smoke is 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone(NNK),which is produced from nicotine through a series of metabolic reactions.

关键词： CRISPR/Cas9 NNK lung

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Numerical Exploration of Asymmetrical Impact Dynamics: Unveiling Nonlinearities in Collision Problems and Resilience of Reinforced Concrete Structures

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Structural Durability & Health Monitoring 2024年第3期18卷 223-254页

作者： AL-Bukhaiti khalil Yanhui Liu Shichun Zhao Daguang Han School of Civil Engineering Southwest Jiaotong UniversityChengdu610031China Faculty of Civil Engineering Southeast UniversityNanjingChina

This study provides a comprehensive analysis of collision and impact problems’ numerical solutions, focusing ongeometric, contact, and material nonlinearities, all essential in solving large deformation problems during a *** initial discussion revolves around the stress and strain of large deformation during a collision, followedby explanations of the fundamental finite element solution method for addressing such issues. The hourglassmode’s control methods, such as single-point reduced integration and contact-collision algorithms are detailedand implemented within the finite element framework. The paper further investigates the dynamic responseand failure modes of Reinforced Concrete (RC) members under asymmetrical impact using a 3D discrete modelin ABAQUS that treats steel bars and concrete connections as bond slips. The model’s validity was confirmedthrough comparisons with the node-sharing algorithm and system energy relations. Experimental parameterswere varied, including the rigid hammer’s mass and initial velocity, concrete strength, and longitudinal and stirrupreinforcement ratios. Findings indicated that increased hammer mass and velocity escalated RC member damage,while increased reinforcement ratios improved impact resistance. Contrarily, increased concrete strength did notsignificantly reduce lateral displacement when considering strain rate effects. The study also explores materialnonlinearity, examining different materials’ responses to collision-induced forces and stresses, demonstratedthrough an elastic rod impact case study. The paper proposes a damage criterion based on the residual axialload-bearing capacity for assessing damage under the asymmetrical impact, showing a correlation betweendamage degree hammer mass and initial velocity. The results, validated through comparison with theoreticaland analytical solutions, verify the ABAQUS program’s accuracy and reliability in analyzing impact problems,offering valuable insights into collision

关键词： Geometric nonlinearity contact nonlinearity material nonlinearity collision problems finite element method stress and strain damage criterion RC members asymmetrical impact

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