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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

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

Metformin effect on internal carotid artery blood flow assessed by area under the curve of carotid artery Doppler in women with polycystic ovarian syndrome

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World Journal of Clinical Cases 2023年第6期11卷 1318-1329页

作者： Wisam akram Wassan Nori Muna Abdul Ghani Zghair Department of Obstetrics and Gynecology MustansiriyahAl Saydihya 10052BaghdadIraq Department of Radiology MustansiriyahAl Saydihya 10052BaghdadIraq

BACKGROUND Insulin resistance(IR)was reported in most polycystic ovarian syndrome(PCOS)***,a biguanide drug,successfully reduced *** Model Assessment for IR(HOMA-IR)and Doppler parameters assessed metformin's *** To verify whether the area under the curve of the internal carotid artery(AUC-ICA)Doppler wave can be a useful marker for assessing IR among PCOS cases who presented with menstrual irregularity and were treated with metformin over 6 *** An observational,cross-sectional study recruited 54 eligible PCOS women;the anthropometrics were as follows:age,body mass index(BMI),menstrual cycle days,biochemical serum cholesterol,low and high-density lipoprotein,sex hormone-binding globulin,fasting blood glucose,and HOMA-IR,hormonal testosterone,luteinizing hormone over follicle-stimulating hormone ratio,and ultrasonic pulsatility index(PI)and resistance index(RI),carotid artery intima-media thickness(CIMT)and(AUC-ICA)parameters were initially recorded and repeated 3 mo and 6 mo later with metformin tab 500 mg;three times/day for 6 *** addition,AUC-ICA was assessed by taking repeated systolic and diastolic wave height *** Metformin caused a progressive reduction in BMI,menstrual cycle days,biochemical hormonal,and Doppler parameters(CIMT,PI,RI,and AUC-ICA).AUC-ICA correlated strongly to all PCOS ***-ICA correlated inversely with treatment time(r=-0.98,P<0.001)and positively with HOMA-IR(r=0.98,P<0.0001).Via the best subset regression model,the AUC-ICA had the highest predictive value for *** AUC-ICA preceded PI,RI,and CIMT with a strong,meaningful correlation to all PCOS parameters,making it a reliable marker for the assessment of IR,especially during metformin *** studies are recommended to promote the application in practice.

关键词： Carotid artery intima-media thickness Insulin resistance Internal carotid artery Doppler Metformin Polycystic ovarian syndrome

Deep brain stimulation for psychiatric disorders: roleof imaging in identifying/confirming DBS targets,predicting, and optimizing outcome and unravellingmechanisms of action

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Psychoradiology 2021年第3期1卷 118-151页

作者： Dejan Georgiev Harith akram Marjan Jahanshahi Department of Clinical and Movement Neurosciences UCL Queen Square Institute of NeurologyQueen SquareLondonWC1N 3BGUK Department of Neurology University Medical Centre LjubljanaZaloska cesta 21000 LjubljanaSlovenia Artificial Intelligence Laboratory Faculty of Computer and Information ScienceUniversity of LjubljanaVecna pot 1131000 LjubljanaSlovenia The Clinical Hospital of Chengdu Brain Science Institute MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengdu611731China

Following the established application of deep brain stimulation(DBS)in the treatment of movement disorders,new non-neurological indications have emerged,such as for obsessive–compulsive disorders,major depressive disorder,dementia,Gilles de la Tourette Syndrome,anorexia nervosa,and *** DBS is a network mod-ulation surgical treatment,the development of DBS for both neurological and psychiatric disorders has been partly driven by advances in neuroimaging,which has helped explain the brain networks *** in magnetic resonance imaging connectivity and electrophysiology have led to the development of the con-cept of modulating widely distributed,complex brain ***,the increasing number of targets for treating psychiatric disorders have indicated that there may be a convergence of the effect of stimulating dif-ferent targets for the same disorder,and the effect of stimulating the same target for different *** aim of this paper is to review the imaging studies of DBS for psychiatric ***,and particularly connectivity analysis,offers exceptional opportunities to better understand and even predict the clinical out-comes of DBS,especially where there is a lack of objective biomarkers that are essential to properly guide DBS pre-and *** future,imaging might also prove useful to individualize DBS ***,one of the most important aspects of imaging in DBS is that it allows us to better understand the brain through observing the changes of the functional connectome under neuromodulation,which may in turn help explain the mechanisms of action of DBS that remain elusive.

关键词： deep brain stimulation psychiatric disorders major depressive disorder obsessive–compulsive disorder dementia

2-Methylimidazole assisted ultrafast synthesis of carboxylate-based metal–organic framework nano-structures in aqueous medium at room temperature

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Science Bulletin 2019年第15期64卷 1103-1109页

作者： Shaheed Ullah Bilal akram Hassan Ali Hao Zhang Haozhou Yang Qingda Liu Xun Wang Key Laboratory of Organic Opteoelectronics and Molecular Engineering Department of Chemistry Tsinghua University

Carboxylate-based metal–organic frameworks(CMOFs)have received considerable attentions for their high stability,catalytic activity,and ***,synthesis of CMOFs requires high temperature,pressure,and long reaction ***,we explored the activity of 2-methylimidazole(2-MIM)for ultrafast synthesis of CMOF nanostructures(CMOFNs),in aqueous medium at room temperature and reaction time of 10 *** CMOFNs have been synthesized by using Al3+,Cr3+,Cu2+,Fe3+,In3+,or Cd2+salt and1,4-bezenedicarboxylic acid,or 1,3,5-benzenetricarboxylic *** this technique,the CMOFs with space time yield 181–501 kgcrystal sizes of ca.200–700 nm was obtained.

关键词： Metal-organic framework Carboxylate 2-Methylimidazole Room temperature synthesis Nanostructures

Binary phase solid-state photopolymerization of acrylates： design, characterization and biomineralization of 3D scaffolds for tissue engineering

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Frontiers of Materials Science 2017年第4期11卷 307-317页

作者： Inamullah MAITLO Safdar ALI Muhammad Yasir akram Farooq Khurum SHEHZAD Jun NIE State Key Laboratory of Chemical Resource Engineering & Beijing Laboratory of Biomedical Materials Beijing University of Chemical Technology Beijing 100029 China

Porous polymer scaffolds designed by the cryogel method are attractive materials for a range of tissue engineering applications. However, the use of toxic cross- linker for retaining the pore structure limits their clinical applications. In this research, acrylates （HEA/PEGDA, HEMA/PEGDA and PEGDA） were used in the low-temperature solid-state photopolymerization to produce porous scaffolds with good structural retention. The morphology, pore diameter, mineral deposition and water absorption of the scaffold were characterized by SEM and water absorption test respectively. Elemental analysis and cytotoxicity of the biomineralized scaffold were revealed by using XRD and MTT assay test. The PEGDA-derived scaffold showed good water absorption ability and a higher degree of porosity with larger pore size compared to others. XRD patterns and IR results confirmed the formation of hydroxyapatite crystals from an alternative socking process. The overall cell proliferation was excellent, where PEGDA-derived scaffold had the highest and the most uniform cell growth, while HEMAJPEGDA scaffold showed the least. These results suggest that the cell proliferation and adhesion are directly proportional to the pore size, the shape and the porosity of scaffolds.

关键词： binary phase solid-state photopolymerization phase separation tissue engineering biomineralization MTT

Adsorptive removal of phosphate by the bimetallic hydroxide nanocomposites embedded in pomegranate peel

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Journal of Environmental Sciences 2020年第5期32卷 189-198页

作者： Muhammad akram Xing Xu Baoyu Gao Qinyan Yue Shang Yanan Rizwan Khan Muhammad Ali Inam Shandong Key Laboratory of Water Pollution Control and Resource Reuse School of Environmental Science and EngineeringShandong UniversityQingdao 266200China Department of Chemical Engineering Quaid-e-Awam University of EngineeringScience and Technology(QUEST)Naiuabshah 67480SindfiPakistan Institute of Environmental Sciences and Engineering(IESE) School of Civil and Environmental Engineering(SCEE)National University of Sciences and Technology(NUST)H-12 CampusIslamabad 44000Pakistan

This study aimed to fabricate new and effective material for the efficiency of phosphate *** types of adsorbent materials,the zirconium hydroxides embedded in pomegranate peel(Zr/Peel)and zirconium-lanthanum hydroxides embedded in pomegranate peel(Zr-La/Peel)were *** electronic microscopy(SEM),x-ray photoelectron spectroscopy(XPS)and x-ray diffraction(XRD)were evaluated to give insight into the physicochemical properties of these ***-La/Peel exceeded the adsorption efficiency of Zr/Peel adsorbents in batch adsorption experiments at the same pH *** peel as a host can strive to have a strong"shielding effect"to increase the steadiness of the entrenched Zr and La *** and Zr are hydroxide metals that emit many hydrogen ions during the hydrolysis reaction,which contribute to protonation and electrostatic *** highest adsorption capacity of La-Zr/Peel for phosphate was calculated to be40.21 mg/g,and pseudo second-order equation is very well fitted for kinetic *** adsorption efficiency was reduced by an increase of *** the background of coexisting Cl-,little effect on adsorption efficiency was observed,while adsorption capacities were reduced by almost 20-30%with the coexistence of SO42-,NO3-and humic acid(HA).

关键词： Bimetallic hydroxides Pomegranate peel Phosphate Adsorption

Fuzzy Based Hybrid Focus Value Estimation for Multi Focus Image Fusion

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Computers, Materials & Continua 2022年第4期71卷 735-752页

作者： Muhammad Ahmad M.Arfan Jaffar Fawad Nasim Tehreem Masood Sheeraz akram The Superior University Lahore 54000Pakistan University of Pittsburgh 15213USA

Due to limited depth-of-field of digital single-lens reflex cameras,the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred(out-of-focus)in the ***-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same *** this paper,a new Fuzzy Based Hybrid Focus Measure(FBHFM)for multi-focus image fusion has been *** block size is very critical step for multi-focus image *** Swarm Optimization(PSO)algorithm has been used to find optimal size of the block of the images for extraction of focus measure *** finding optimal blocks,three focus measures Sum of Modified Laplacian,Gray Level Variance and Contrast Visibility has been extracted and combined these focus measures by using intelligent fuzzy *** based hybrid intelligent focus values were estimated using contrast visibility measure to generate focused *** sets of multi-focus images have been used in detailed experimentation and compared the results with state-of-the-art existing techniques such as Genetic Algorithm(GA),Principal Component Analysis(PCA),Laplacian Pyramid discrete wavelet transform(DWT),and aDWT for image *** has been found that proposed method performs well as compare to existing methods.

关键词： Fuzzy logic multi-focus image fusion defocus focus contrast visibility focus measure

Weber Law Based Approach for Multi-Class Image Forgery Detection

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Computers, Materials & Continua 2024年第1期78卷 145-166页

作者： Arslan akram Javed Rashid Arfan Jaffar Fahima Hajjej Waseem Iqbal Nadeem Sarwar Department of Computer Science Superior UniversityLahore54000Pakistan Information Technology Services University of OkaraOkara56300Pakistan Departmet of Computer Science MLC LabOkara56300Pakistan Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science Bahria UniversityLahore CampusLahore54600Pakistan

Today’s forensic science introduces a new research area for digital image analysis formultimedia ***,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered *** forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing ***,an image can contain one or more types of *** study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial ***,images are divided into equal blocks to get scale-invariant *** law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing *** proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and ***(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and *** average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

关键词： Copy-Move and splicing non-overlapping block division texture features weber law spatial domain xgboost