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Facial Image-Based Autism Detection:A Comparative Study of Deep Neural Network Classifiers

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Computers, Materials & Continua 2024年第1期78卷 105-126页

作者： Tayyaba Farhat Sheeraz akram Hatoon SAlSagri Zulfiqar Ali Awais ahmad Arfan Jaffar Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Faculty of Computer Science and Information TechnologyThe Superior UniversityLahore54600Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive *** and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like *** study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local *** research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate *** addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the *** findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation ***,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test *** validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD *** research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.

关键词： Autism Autism Spectrum Disorder(ASD) disease segmentation features optimization deep learning models facial images classification

Enhancing ChatGPT’s Querying Capability with Voice-Based Interaction and CNN-Based Impair Vision Detection Model

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Computers, Materials & Continua 2024年第3期78卷 3129-3150页

作者： Awais ahmad Sohail Jabbar Sheeraz akram Anand Paul Umar Raza Nuha Mohammed Alshuqayran College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudia Arabia 2 School of Computer Science and EngineeringKyungpook National UniversityDaegu41566South Korea 3 Department of EngineeringManchester Metropolitan UniversityManchesterM156BHUK

This paper presents an innovative approach to enhance the querying capability of ChatGPT,a conversational artificial intelligence model,by incorporating voice-based interaction and a convolutional neural network(CNN)-based impaired vision detection *** proposed system aims to improve user experience and accessibility by allowing users to interact with ChatGPT using voice ***,a CNN-based model is employed to detect impairments in user vision,enabling the system to adapt its responses and provide appropriate *** research tackles head-on the challenges of user experience and inclusivity in artificial intelligence(AI).It underscores our commitment to overcoming these obstacles,making ChatGPT more accessible and valuable for a broader *** integration of voice-based interaction and impaired vision detection represents a novel approach to conversational ***,this innovation transcends novelty;it carries the potential to profoundly impact the lives of users,particularly those with visual *** modular approach to system design ensures adaptability and scalability,critical for the practical implementation of these ***,the solution places the user at its *** responses for those with visual impairments demonstrates AI’s potential to not only understand but also accommodate individual needs and preferences.

关键词： Accessibility in conversational AI CNN-based impair vision detection ChatGPT voice-based interaction recommender system

Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis

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Computers, Materials & Continua 2024年第6期79卷 4963-4977页

作者： Iftikhar Naseer Tehreem Masood Sheeraz akram Zulfiqar Ali Awais ahmad Shafiq Ur Rehman Arfan Jaffar Faculty of Computer Sciences&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Information System Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Lung cancer is a leading cause of global mortality *** detection of pulmonary tumors can significantly enhance the survival rate of ***,various Computer-Aided Diagnostic(CAD)methods have been developed to enhance the detection of pulmonary nodules with high ***,the existing method-ologies cannot obtain a high level of specificity and *** present study introduces a novel model for Lung Cancer Segmentation and Classification(LCSC),which incorporates two improved architectures,namely the improved U-Net architecture and the improved AlexNet *** LCSC model comprises two distinct *** first stage involves the utilization of an improved U-Net architecture to segment candidate nodules extracted from the lung ***,an improved AlexNet architecture is employed to classify lung *** the first stage,the proposed model demonstrates a dice accuracy of 0.855,a precision of 0.933,and a recall of 0.789 for the segmentation of candidate *** suggested improved AlexNet architecture attains 97.06%accuracy,a true positive rate of 96.36%,a true negative rate of 97.77%,a positive predictive value of 97.74%,and a negative predictive value of 96.41%for classifying pulmonary cancer as either benign or *** proposed LCSC model is tested and evaluated employing the publically available dataset furnished by the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI).This proposed technique exhibits remarkable performance compared to the existing methods by using various evaluation parameters.

关键词： Lung cancer segmentation AlexNet U-Net classification

Probing the Efficiency of PPMG-Based Composite Electrolytes for Applications of Proton Exchange Membrane Fuel Cell

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Transactions of Tianjin University 2024年第3期30卷 262-283页

作者： Shakeel Ahmed Faizah Altaf Safyan akram Khan Sumaira Manzoor Aziz ahmad Muhammad Mansha Shahid Ali Ata-ur-Rehman Karl Jacob School of Material Science and Engineering Henan International Joint Laboratory of Nano-Photoelectric Magnetic MaterialsHenan University of TechnologyZhengzhou 450001China Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management King Fahd University of Petroleum and Minerals31261 DhahranSaudi Arabia School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGA 30332USA

PPMG-based composite electrolytes were fabricated via the solution method using the polyvinyl alcohol and polyvinylpyrrolidone blend reinforced with various contents of sulfonated inorganic *** acid was employed as the sulfonating agent to functionalize the external surface of the inorganic filler,i.e.,graphene *** proton conductivities of the newly prepared proton exchange membranes(PEMs)were increased by increasing the temperature and content of sulfonated graphene oxide(SGO),i.e.,ranging from 0.025 S/cm to 0.060 S/*** induction of the optimum level of SGO is determined to be an excellent route to enhance ionic *** single-cell performance test was conducted by sandwiching the newly prepared PEMs between an anode(0.2 mg/cm^(2) Pt/Ru)and a cathode(0.2 mg/cm^(2) Pt)to prepare membrane electrode assemblies,followed by hot pressing under a pressure of approximately 100 kg/cm^(2) at 60℃for 5–10 *** highest power densities achieved with PPMG PEMs were 14.9 and 35.60 mW/cm^(2) at 25℃and 70℃,respectively,at ambient pressure with 100%relative *** showed that the newly prepared PEMs exhibit good electrochemical *** results indicated that the prepared composite membrane with 6 wt%filler can be used as an alternative membrane for applications of high-performance proton exchange membrane fuel cell.

关键词： Proton exchange membrane fuel cell Sulfonated graphene oxide Polyvinylpyrrolidone Solution casting Membrane electrode assembly Fuel cell performance

On the calibration of a shear stress criterion for rock joints to represent the full stress-strain profile

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第2期16卷 379-392页

作者： akram Deiminiat Jonathan D.Aubertin Yannic Ethier Department of Construction Engineering École de Technologie Supérieure(ÉTS)MontréalCanada

Conventional numerical solutions developed to describe the geomechanical behavior of rock interfaces subjected to differential load emphasize peak and residual shear *** detailed analysis of preand post-peak shear stress-displacement behavior is central to various time-dependent and dynamic rock mechanic problems such as rockbursts and structural instabilities in highly stressed *** complete stress-displacement surface(CSDS)model was developed to describe analytically the pre-and post-peak behavior of rock interfaces under differential *** formulations of the CSDS model required extensive curve-fitting iterations which limited its practical applicability and transparent integration into engineering *** present work proposes modifications to the CSDS model aimed at developing a comprehensive and modern calibration protocol to describe the complete shear stressdisplacement behavior of rock interfaces under differential *** proposed update to the CSDS model incorporates the concept of mobilized shear strength to enhance the post-peak ***’s concepts of joint roughness coefficient(JRC)and joint compressive strength(JCS)are incorporated to facilitate empirical estimations for peak shear stress and normal closure ***/uniaxial compression test and direct shear test results are used to validate the updated model and exemplify the proposed calibration *** results illustrate that the revised model successfully predicts the post-peak and complete axial stressestrain and shear stressedisplacement curves for rock joints.

关键词： Full shear profile Post-peak shear behavior Rock joint Joint roughness coefficient(JRC) Axial stress-strain curve

Prevalence and clinical risk factors for esophageal candidiasis in non-human immunodeficiency virus patients:A multicenter retrospective case-control study

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World Journal of Gastrointestinal Endoscopy 2023年第6期15卷 480-490页

作者： Alexandra V Kimchy akramⅠahmad Lindsey Tully Connor Lester Kavya Sanghavi Joseph J Jennings Department of Internal Medicine MedStar Georgetown University HospitalWashingtonDC 20007United States Department of Internal Medicine MedStar Washington Hospital CenterWashingtonDC 20007United States Department of Internal Medicine Georgetown University School of MedicineWashingtonDC 20007United States Department of Biostatistics and Biomedical Informatics MedStar Research InstituteHyattsvilleMD 20781United States Department of Gastroenterology MedStar Georgetown University HospitalWashingtonDC 20007United States

BACKGROUND Although esophageal candidiasis(EC)may manifest in immunocompetent individuals,there is a lack of consensus in the current literature about predisposing conditions that increase the risk of *** To determine the prevalence of EC in patients without human immunodeficiency virus(HIV)and identify risk factors for *** We retrospectively reviewed inpatient and outpatient encounters from 5 regional hospitals within the United States(US)from 2015 to *** Classification of Diseases,Ninth and Tenth Revisions were used to identify patients with endoscopic biopsies of the esophagus and *** with HIV were *** with EC were compared to age,gender,and encounter-matched controls without *** demographics,symptoms,diagnoses,medications,and laboratory data were obtained from chart *** in medians for continuous variables were compared using the Kruskal-Wallis test and categorical variables using chi-square *** logistic regression was used to identify independent risk factors for EC,after adjusting for potential confounding *** Of the 1969 patients who had endoscopic biopsies of the esophagus performed from 2015 to 2020,295 patients had the diagnosis of EC.177 of 1969 patients(8.99%)had pathology confirming the diagnosis of EC and were included in the study for data collection and further *** comparison to controls,patients with EC had significantly higher rates of gastroesophageal reflux disease(40.10%vs 27.50%;P=0.006),prior organ transplant(10.70%vs 2%;P<0.001),immunosuppressive medication(18.10%vs 8.10%;P=0.002),proton pump inhibitor(48%vs 30%;P<0.001),corticosteroid(35%vs 17%;P<0.001),Tylenol(25.40%vs 16.20%;P=0.019),and aspirin use(39%vs 27.50%;P=0.013).On multivariable logistic regression analysis,patients with a prior organ transplant had increased odds of EC(OR=5.81;P=0.009),as did patients taking a proton pump inhibitor(OR=1.66;P=0.03)or corticost

关键词： Candidiasis Esophagus Endoscopy Proton pump inhibitors Transplants Glucocorticoids

Two-dimensional investigation of characteristic parameters and their gradients for the self-generated electric and magnetic fields of laser-induced zirconium plasma

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Plasma Science and Technology 2024年第5期26卷 138-155页

作者： Tayyaba SAJID Shazia BASHIR Mahreen akram Maira RAZZAQ Khaliq MAHMOOD Centre for Advanced Studies in Physics Institute of PhysicsGovernment College University LahoreLahore 54000Pakistan Department of Physics Institute of PhysicsGovernment College University LahoreLahore 54000Pakistan

Two-dimensional diagnosis of laser-induced zirconium(Zr)plasma has been experimentally performed using the time-of-flight method by employing Faraday cups in addition to electric and magnetic *** characteristic parameters of laser-induced Zr plasma have been evaluated as a function of different laser irradiances ranging from 4.5 to 11.7 GW cm-2 at different axial positions of 1–4 cm with a fixed radial distance of 2 cm.A well-supporting correlation between the plume parameters and the laser-plasma-produced spontaneous electric and magnetic(E and B)fields was *** measurements of the characteristic parameters and spontaneously induced fields were observed to have an increasing trend with the increasing laser ***,when increasing the spatial distance in both the axial and radial directions,the plasma parameters(electron/ion number density,temperature and kinetic energy)did not show either continuously increasing or decreasing trends due to various kinetic and dynamic processes during the spatial evolution of the ***,the E and B fields were observed to be always diffusing away from the *** radial component of electron number densities remained higher than the axial number density component,whereas the axial ion number density at all laser irradiances and axial distances remained higher than the radial ion number *** higher axial self-generated electric field(SGEF)values than radial SGEF values are correlated with the effective charge-separation mechanism of electrons and *** generation of a self-generated magnetic field is observed dominantly in the radial direction at increasing laser irradiance as compared to the axial one due to the deflection of fast-moving electrons and the persistence of two-electron temperature on the radial axis.

关键词： Faraday cup axial and radial expansion space-charge effect laser-induced zirconium plasma two-electron temperature distribution self-generated electric and magnetic fields

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基于变参神经动力学方法的分形生成方法研究

基于变参神经动力学方法的分形生成方法研究

作者：阿克林（akram ahmad）华南理工大学

学位级别：硕士

To solve static and time-varying non-linear complex-valued equations by neural dynamics,using two new kinds of varying-parameters discrete-time complex-valued neural dynamics（VP-DTCVND）,the two models has proposed and *** from fixedparameters discrete-time complex-valued neural dynamics（FP-DTCVND）,VP-DTCVND is based on monotonically increasing time-varying *** this dissertation,new fractals have yielded by using the two VP-DTCVND models via solving static and time-varying nonlinear equations in the complex domain,for generating new unique ***-type and power-type VP-DTCVND apply four different kinds of activation functions（i.e.,linear,power-sum,power-sigmoid and hyperbolic-sine activation functions）,and these activation functions have been introduced and used to create various neural *** proposed VP-DTCVND can determine static and time-varying non-linear equations,unlike Newton iterations which only can solve static non-linear *** yielded are different from Newton fractals;the fractals generated are unique of their *** of equations are solved to show different fractals and approve the validity of the proposed *** simulation results based on different activation functions demonstrate that the VP-DTCVND models can serve as new algorithm to generate new *** between FP-DTCVND fractals and VP-DTCND fractals finally presented to verify the uniqueness of the proposed two new models in generating *** effectiveness of the VP-DTCVND models using different activation functions for solving time-varying nonlinear complex equations reflected.

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Nodule Detection Using Local Binary Pattern Features to Enhance Diagnostic Decisions

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Computers, Materials & Continua 2024年第3期78卷 3377-3390页

作者： Umar Rashid Arfan Jaffar Muhammad Rashid Mohammed S.Alshuhri Sheeraz akram Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54600Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Department of Radiological Sciences and Medical Imaging College of AppliedMedical SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia

Pulmonary nodules are small, round, or oval-shaped growths on the lungs. They can be benign (noncancerous) or malignant (cancerous). The size of a nodule can range from a few millimeters to a few centimeters in diameter. Nodules may be found during a chest X-ray or other imaging test for an unrelated health problem. In the proposed methodology pulmonary nodules can be classified into three stages. Firstly, a 2D histogram thresholding technique is used to identify volume segmentation. An ant colony optimization algorithm is used to determine the optimal threshold value. Secondly, geometrical features such as lines, arcs, extended arcs, and ellipses are used to detect oval shapes. Thirdly, Histogram Oriented Surface Normal Vector (HOSNV) feature descriptors can be used to identify nodules of different sizes and shapes by using a scaled and rotation-invariant texture description. Smart nodule classification was performed with the XGBoost classifier. The results are tested and validated using the Lung Image Consortium Database (LICD). The proposed method has a sensitivity of 98.49% for nodules sized 3–30 mm.

关键词： Pulmonary nodules segmentation histogram thresholding