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Urdu Ligature Recognition System:An Evolutionary Approach

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Computers, Materials & Continua 2021年第2期66卷 1347-1367页

作者： Naila Habib Khan awais adnan AbdulWaheed Mahdi Zareei Abdallah Aldosary Ehab Mahmoud Mohamed Department of Computer Science Institute of Management SciencesPeshawar25000Pakistan Department of Information Technology Hazara UniversityMansehra21120Pakistan School of Electrical and Computer Engineering Seoul National UniversitySeoul08826South Korea Tecnologico de Monterrey School of Engineering and SciencesZapopan45201Mexico Department of Computer Science Prince Sattam Bin Abdulaziz UniversityAs Sulayyil11991Saudi Arabia Electrical Engineering Department College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Addwasir11991Saudi Arabia Electrical Engineering Department Faculty of EngineeringAswan UniversityAswan81542Egypt

Cursive text recognition of Arabic script-based languages like Urdu is extremely complicated due to its diverse and complex *** approaches like genetic algorithms have been used in the past for various optimization as well as pattern recognition tasks,reporting exceptional *** proposed Urdu ligature recognition system uses a genetic algorithm for optimization and *** the proposed recognition system observes the processes of pre-processing,segmentation,feature extraction,hierarchical clustering,classification rules and genetic algorithm optimization and *** pre-processing stage removes noise from the sentence images,whereas,in segmentation,the sentences are segmented into ligature *** features are extracted from each of the segmented ligature ***-feature hierarchical clustering is observed that results in clustered ***,classification rules are used for the representation of the clustered *** genetic algorithm performs an optimization mechanism using multi-level sorting of the clustered data for improving the classification rules used for recognition of Urdu *** conducted on the benchmark UPTI dataset for the proposed Urdu ligature recognition system yields promising results,achieving a recognition rate of 96.72%.

关键词： Classification rules genetic algorithm intra-feature hierarchical clustering ligature recognition Urdu script

Convolutional Neural Network for Histopathological Osteosarcoma Image Classification

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Computers, Materials & Continua 2021年第12期69卷 3365-3381页

作者： Imran Ahmed Humaira Sardar Hanan Aljuaid Fakhri Alam Khan Muhammad Nawaz adnan awais Center of Excellence in Information Technology Institute of Management SciencesPeshawarPakistan Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University(PNU)RiyadhSaudi Arabia

Osteosarcoma is one of the most widespread causes of bone cancer globally and has a high mortality *** diagnosis may increase the chances of treatment and survival however the process is time-consuming(reliability and complexity involved to extract the hand-crafted features)and largely depends on pathologists’*** Neural Network(CNN—an end-to-end model)is known to be an alternative to overcome the aforesaid ***,this work proposes a compact CNN architecture that has been rigorously explored on a Small Osteosarcoma histology Image Dataaseet(a high-class imbalanced dataset).Though,during training,class-imbalanced data can negatively affect the performance of ***,an oversampling technique has been proposed to overcome the aforesaid issue and improve generalization *** this process,a hierarchical CNN model is designed,in which the former model is non-regularized(due to dense architecture)and the later one is regularized,specifically designed for small histopathology ***,the regularized model is integrated with CNN’s basic architecture to reduce *** results demonstrate that oversampling might be an effective way to address the imbalanced class problem during *** training and testing accuracies of the non-regularized CNN model are 98%&78%with an imbalanced dataset and 96%&81%with a balanced dataset,*** regularized CNN model training and testing accuracies are 84%&75%for an imbalanced dataset and 87%&86%for a balanced dataset.

关键词： Convolutional neural network histopathological image classification osteosarcoma computer-aided diagnosis

Role of Air Staging in a Batch-Type Fixed Bed Biomass Combustor under Constant Primary Air

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Journal of Thermal Science 2024年第1期33卷 284-299页

作者： awais JUNEJO Yasir M.AL-ABDELI Jacobo PORTEIRO School of Engineering Edith Cowan UniversityJoondalupWA 6027Australia CINTECX Universidade de Vigo Grupo de Tecnoloxia Enerxetica(GTE)36310 VigoEspana

Staged combustion of biomass is the most suitable thermo-chemical conversion for achieving lower gaseous emissions and higher fuel conversion *** a staged fixed bed combustion of biomass,combustion air is supplied in two *** the first stage,primary air is provided below the fuel,whereas in the later stage,secondary air is supplied in the freeboard *** available literature on the effects of air staging(secondary air location) at a constant primary air flow rate on combustion characteristics in a batch-type fixed bed combustor is limited and hence warrants further *** study resolves the effect of air staging,by varying the location of secondary air in the freeboard at five secondary to total air ratios in a batch-type fixed bed *** are reported for the effects of these controlled parameters on fuel conversion rate,overall gaseous emissions(CO_(2),CO and NO_x) and temperature *** fuel used throughout was densified hardwood *** show that a primary freeboard length(distance between fuel bed top and secondary air injection) of200 mm has higher fuel conversion rates and temperatures as well as lower CO emissions,at a secondary to total air ratio of 0.75 as compared to primary freeboard length of 300 ***,NO_x emissions were found to be lower for a primary freeboard length of 300 mm as compared to 200 *** increase in secondary to total air ratio from 0.33 to 0.75 resulted in higher freeboard temperatures and lower CO as well as NO_x *** outcomes of this study will be helpful in the effective design of commercial scale biomass combustors for more efficient and environmentally friendly combustion.

关键词： fixed bed combustor biomass combustion air staging freeboard temperature burning rate gaseous emissions

Study of bending angle and shadow in a new Schwarzschild-like black hole affected by plasma and non-plasma mediums

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Chinese Physics C 2024年第5期48卷 309-318页

作者： Riasat Ali Tiecheng Xia Muhammad awais Rimsha Babar Department of Mathematics Newtouch Center for Mathematics of Shanghai UniversityShanghai 200444China Department of Mathematics University of Engineering and Technology Lahore-54890Pakistan Department of Mathematics GC University Faisalabad Layyah CampusLayyah-31200Pakistan

In this study,we analyze the models of the deflection angle of a new Schwarzschild-like black hole(BH)and employ the optical metric of the *** achieve this,we use the Gaussian curvature of the optical metric and the Gauss-Bonnet theorem,known as the Gibbons-Werner technique,to determine the deflection ***,we examine the deflection angle in the presence of a plasma medium and the effect of the plasma medium on the deflection *** deflection angle of the BH solution in the gauged super-gravity is computed using the Keeton-Petters *** the ray-tracing technique,we investigate the shadow of the corresponding BH and analyze the plots of the deflection angle and shadow to verify the influence of the plasma and algebraic thermodynamic parameters on the deflection angle and shadow.

关键词： new Schwarzschild-like black hole Gibbons-Werner and Keeton-Petters techniques deflection angle ray-tracing approach shadow

Evolution of light deflection and shadow from a gauge-potential-like AdS black hole under the influence of a non-magnetic plasma medium

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Communications in Theoretical Physics 2024年第9期76卷 83-94页

作者： Riasat Ali Xia Tiecheng Muhammad awais Rimsha Babar Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai-200444China Department of Mathematics University of Engineering and Technology Lahore-54890Pakistan Department of Mathematics GC University Faisalabad Layyah CampusLayyah-31200Pakistan

We investigate the light deflection in the weak field approximation from the accelerating charged AdS black *** this purpose,we apply the Gauss–Bonnet theorem to calculate the light deflection in the weak field area and use the Gibbons–Werner approach to analyze the optical geometry of the accelerating charged AdS black hole in the non-magnetic plasma absence/presence of a non-magnetic *** also represent the graphical behavior of the light deflection angle *** impact *** also compute the light deflection angle using Keeton and Petters approximations under the impact of accelerating charged AdS black hole ***,by using the ray-tracing approach,we determine the shadow in the nonmagnetic plasma presence and also demonstrate that graphical shadow has an impact on the gauge potential,non-magnetic plasma frequencies and charge.

关键词： accelerating charged Ad S black hole Gibbons-Werner approach deflection angle ray-tracing approach shadow

Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1729-1755页

作者： awais Khan Chomyong Kim Jung-Yeon Kim Ahsan Aziz Yunyoung Nam Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea ICT Convergence Research Center Soonchunhyang UniversityAsan31538Korea Emotional and Intelligent Child Care Convergence Research Center Soonchunhyang UniversityAsan31538Korea

Sleep posture surveillance is crucial for patient comfort,yet current systems face difficulties in providing compre-hensive studies due to the obstruction caused by *** posture assessment remains challenging because of the complex nature of the human body and variations in sleep ***,this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification,thereby enhancing the analysis of body position and *** method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras,which depict six commonly adopted postures:supine,left log,right log,prone head,prone left,and prone *** study involves 10 participants under two conditions:with and without ***,the database is normalized into a video *** subsequent step entails training a fine-tuned,pretrained Visual Geometry Group(VGG16)and ResNet50 *** the third phase,the extracted features are utilized for *** fourth step of the proposed approach employs a serial fusion technique based on the normal distribution to merge the vectors derived from both the RGB and thermal ***,the fused vectors are passed to machine learning classifiers for final *** dataset,which includes human sleep postures used in this study’s experiments,achieved a 96.7%accuracy rate using the Quadratic Support Vector Machine(QSVM)without the ***,the Linear SVM,when utilized with a blanket,attained an accuracy of 96%.When normal distribution serial fusion was applied to the blanket features,it resulted in a remarkable average accuracy of 99%.

关键词： Human sleep posture VGG16 deep learning ResNet50 fusion machine learning

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

Orchestrating seed storage protein and starch accumulation toward overcoming yield–quality trade-off in cereal crops

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Journal of Integrative Plant Biology 2024年第3期66卷 468-483页

作者： Shuanghe Cao Bingyan Liu Daowen Wang awais Rasheed Lina Xie Xianchun Xia Zhonghu He State Key Laboratory of Crop Gene Resources and Breeding/National Wheat Improvement Center Institute of Crop SciencesBeijing 100081China College of Agronomy Henan Agricultural UniversityZhengzhou 450002China International Maize and Wheat Improvement Center(CIMMYT)China Office Chinese Academy of Agricultural SciencesBeijing 100081China

Achieving high yield and good quality in crops is essential for human food security and ***,there is usually disharmony between yield and *** storage protein(SSP)and starch,the predominant components in cereal grains,determine yield and quality,and their coupled synthesis causes a yield–quality ***,dissection of the underlying regulatory mechanism facilitates simultaneous improvement of yield and ***,we summarize current findings about the synergistic molecular machinery underpinning SSP and starch synthesis in the leading staple cereal crops,including maize,rice and *** further evaluate the functional conservation and differentiation of key regulators and specify feasible research approaches to identify additional regulators and expand *** also present major strategies to leverage resultant information for simultaneous improvement of yield and quality by molecular ***,future perspectives on major challenges are proposed.

关键词： cereal crops grain yield and quality seed storage protein starch synergistic regulation