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Modelling and Characterization of Basalt/Vinyl Ester/siC Micro-and Nano-hybrid Biocomposites Properties Using Novel ANN–GA Approach

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Journal of Bionic Engineering 2024年第2期21卷 938-952页

作者： Yesudhasan Thooyavan Lakshmi Annamali Kumaraswamidhas Robinson Dhas Edwin Raj Joseph selvi Binoj Bright Brailson Mansingh Antony sagai Francis Britto alamry ali Department of Mechanical Engineering Indian Institute of Technology Dhanbad(ISM)DhanbadJharkhand826004India Gati shakti Vishwavidyalaya(GsV-A Central University Funded By GoI in the Ministry of Railways) LalbaugVadodaraGujarat390004India Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennaiTamilnadu602105India Metal Joining Research Centre Department of Mechanical EngineeringSri Ramakrishna Engineering CollegeCoimbatoreTamilnadu641022India Department of Mechanical Engineering Rohini College of Engineering and TechnologyPalkulamTamil Nadu629401India Department of Mechanical Engineering College of Engineering in Al-KharjPrince Sattam Bin Abdulaziz University11942Al-KharjSaudi Arabia

Basalt fiber reinforcement in polymer matrix composites is becoming more and more popular because of its environmental friendliness and mechanical qualities that are comparable to those of synthetic *** fiber strengthened vinyl ester matrix polymeric composite with filler addition of nano-and micro-sized silicon carbide(siC)element spanning from 2 weight percent to 10 weight percent was studied for its mechanical and wear *** application of Artificial Neural Network(ANN)to correlate the filler addition composition for optimum mechanical properties is required due to the non-linear mechanical and tribological features of *** stuffing blend and composition of the composite are optimized using the hybrid model and Genetic algorithm(GA)to maximize the mechanical and wear-resistant *** predicted and tested ANN–GA optimal values obtained for the composite combination had a tensile,flexural,impact resilience,hardness and wear properties of 202.93 MPa,501.67 MPa,3.460 J/s,43 HV and 0.196 g,respectively,for its optimum combination of filler and *** can be noted that the nano-sized siC filler particle enhances most of the properties of the composite which diversifies its *** predicted mechanical and wear values of the developed ANN–GA model were in closer agreement with the experimental values which validate the model.

关键词： Hybrid polymer composite Prediction Process modelling Artificial neural networks Genetic algorithm

Mechanical performance of cold mix asphalt containing cup lump rubber as a sustainable bio-modifier

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第3期11卷 424-440页

作者： syed Abdul Ghafar Muhammad Naqiuddin Mohd Warid Norhidayah Abdul Hassan Zulfiqar ali Jattak Ashraf Abdalla Mohammed Radwan Faculty of Civil Engineering Universiti Teknologi MalaysiaSkudai 81310Malaysia Department of Civil Engineering Balochistan University of Information TechnologyEngineering&Management SciencesQuettaPakistan Department of Civil Engineering Balochistan University of Engineering and TechnologyKhuzdarPakistan Department of Civil Engineering Faculty of EngineeringUniversity of TripoliTripoliLibya

The road construction industry aims to contribute to the protection of already compromised *** mix asphalt(CMA)is a measure initiated by the road industry to protect the environment and preserve *** having additional benefits,CMA has attracted little attention due to its inferior ***'s performance is enhanced using a sustainable binder bio-modifier,natural cup lump rubber(CLR)is one of *** study evaluated the tensile properties,rutting,moisture susceptibility,and adhesion properties of CLR-modified CMA(CMA-CR).The tensile property was enhanced by 26%due to CLR ***-CR had excellent rutting resistance of less than 2 mm rut depth at 10,000 load cycles,showing 70%improvement compared with conventional *** susceptibility evaluation indicated that CMA-CR had tensile strength ratio(TsR)value of 104%,satisfying the minimum 80%requirement of AAsHTO *** also retained more than 96%bitumen *** moisture damage resistance was improved by 12%and 10%in terms of TsR and stripping,*** durability results revealed that the CMA-CR mixture prevented higher mass loss,representing 14%improvement compared with conventional CMA.

关键词： Cup lump rubber Cup lump modified cold mix asphalt Moisture damage Tensile property Rutting Digital imaging

Contrast Normalization strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer Modeling in Engineering & sciences 2024年第8期140卷 1539-1562页

作者： samar M.alqhtani Toufique A.soomro Faisal Bin Ubaid Ahmed ali Muhammad Irfan Abdullah A.Asiri Department of Information systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various *** resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain *** plays a crucial role in the diagnosis of brain tumors and the examination of other brain ***,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely ***,early diagnosis of brain tumors is intricate,necessitating the use of computerized *** research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain *** proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third *** final step involves classification using the support Vector Machine(sVM)*** classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)*** proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice score(DsC)of ***,this method exhibits a shorter processing time of 0.44 s compared to existing *** performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and *** enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classi

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

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Computers, Materials & Continua 2024年第1期78卷 357-374页

作者： Ch Avais Hanif Muhammad ali Mughal Muhammad Attique Khan Nouf Abdullah almujally Taerang Kim Jae-Hyuk Cha Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer science and Mathematics Lebanese American UniversityBeirutLebanon Department of Computer science HITEC UniversityTaxila47080Pakistan Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer science Hanyang UniversitySeoul04763Korea

The demand for a non-contact biometric approach for candidate identification has grown over the past ten *** on the most important biometric application,human gait analysis is a significant research topic in computer *** have paid a lot of attention to gait recognition,specifically the identification of people based on their walking patterns,due to its potential to correctly identify people far *** recognition systems have been used in a variety of applications,including security,medical examinations,identity management,and access *** systems require a complex combination of technical,operational,and definitional *** employment of gait recognition techniques and technologies has produced a number of beneficial and well-liked *** proposes a novel deep learning-based framework for human gait classification in video *** framework’smain challenge is improving the accuracy of accuracy gait classification under varying conditions,such as carrying a bag and changing *** proposed method’s first step is selecting two pre-trained deep learningmodels and training fromscratch using deep transfer ***,deepmodels have been trained using static hyperparameters;however,the learning rate is calculated using the particle swarmoptimization(PsO)***,the best features are selected from both trained models using the Harris Hawks controlled sine-Cosine optimization *** algorithm chooses the best features,combined in a novel correlation-based fusion ***,the fused best features are categorized using medium,bi-layer,and tri-layered neural *** the publicly accessible dataset known as the CAsIA-B dataset,the experimental process of the suggested technique was carried out,and an improved accuracy of 94.14% was *** achieved accuracy of the proposed method is improved by the recent state-of-the-art techniques that show the significance of this wor

关键词： Gait recognition covariant factors biometric deep learning fusion feature selection

From longan peel waste to energy storage: Porous activated carbon as a cathode matrix for advanced Li/Na-selenium batteries

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Progress in Natural science:Materials International 2024年第2期34卷 329-337页

作者： Mustafa Khan suxia Yan Mujahid ali Faisal Mahmood Yang Zheng Xiaohui song Guochun Li Junfeng Liu Yong Wang Institute for Energy Research Jiangsu University school of Energy and Power Engineering Jiangsu University school of Materials science and Engineering Hefei University of Technology

This paper explores the potential of Longan peel waste（LPw） as a sustainable and cost-effective matrix for selenium-based cathodes in Li-se and Na-se *** activation,we created LP2—a designation for the carbon precursor derived from LPw,activated at a 1:2 ratio of carbonized LPw to *** nomenclature,where'LP' stands for 'Longan peel' and '2' reflects the optimization of this ratio,led to a hierarchical porous structure with an average pore size of 3.0307 nm and a significant BET surface area of 111.9386 m2g-1selenium was incorporated into the LP2matrix using a simple melt diffusion technique,yielding the composite se@*** Li-se batteries,se@LP2exhibited an initial discharge capacity of 1033.75 mAh g-1at *** a 1C rate,the composite demonstrated a capacity retention of 301.14 mAh g-1after 550 cycles and 380.91 mAh g-1after 100 ***,for Na-se batteries,the composite showcased a capacity retention of 347.18 mAh g-1after 100 cycles *** findings underscore LP2's potential as a viable and efficient matrix for selenium-based cathodes,revealing promising prospects for the advancement of highly efficient Li-se and Na-se batteries.

关键词： Hierarchical porous structure Li/Na-se batteries Longan peel waste Melt diffusion technique selenium-based cathode

Concept of Artificial Intelligence (AI) and Its Use in Orthopaedic Practice: Applications and Pitfalls: A Narrative Review

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Open Journal of Orthopedics 2024年第1期14卷 32-40页

作者： Mir sadat-ali Department of Orthopaedic surgery Haifa Medical Complex Al Khobar Kingdom of Saudi Arabia

Background: The growth and use of Artificial Intelligence (AI) in the medical field is rapidly rising. AI is exhibiting a practical tool in the healthcare industry in patient care. The objective of this current review is to assess and analyze the use of AI and its use in orthopedic practice, as well as its applications, limitations, and pitfalls. Methods: A review of all relevant databases such as EMBAsE, Cochrane Database of systematic Reviews, MEDLINE, science Citation Index, scopus, and Web of science with keywords of AI, orthopedic surgery, applications, and drawbacks. all related articles on AI and orthopaedic practice were reviewed. A total of 3210 articles were included in the review. Results: The data from 351 studies were analyzed where in orthopedic surgery. AI is being used for diagnostic procedures, radiological diagnosis, models of clinical care, and utilization of hospital and bed resources. AI has also taken a chunk of share in assisted robotic orthopaedic surgery. Conclusions: AI has now become part of the orthopedic practice and will further increase its stake in the healthcare industry. Nonetheless, clinicians should remain aware of AI’s serious limitations and pitfalls and consider the drawbacks and errors in its use.

关键词： Artificial Intelligence Healthcare Pitfalls Drawbacks

Classification and Comprehension of software Requirements Using Ensemble Learning

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Computers, Materials & Continua 2024年第8期80卷 2839-2855页

作者： Jalil Abbas Arshad Ahmad syed Muqsit shaheed Rubia Fatima sajid shah Mohammad Elaffendi Gauhar ali school of Computer science and Technology Anhui UniversityHefei230039China school of Computing sciences Pak Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer science and IT University of LahoreLahore55150Pakistan Department of Computer science Emerson UniversityPunjabMultan60000Pakistan EIAs(Emerging Intelligent Autonomous systems)Data science Lab Prince Sultan UniversityRiyad12435Saudi Arabia

The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy sliding Window(AsW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMIsE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

关键词： Ensemble learning machine learning non-functional requirements requirement engineering accuracy sliding window

The Contribution of AI-Powered Mobile Apps to smart City Ecosystems

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Journal of software Engineering and Applications 2024年第3期17卷 143-154页

作者： Zaki ali Bayashot Ministry of Municipal and Rural Affairs and Housing Riyadh Kingdom of Saudi Arabia

In the groundbreaking study “The Contribution of AI-powered Mobile Apps to smart City Ecosystems,” authored by Zaki ali Bayashot, the transformative role of artificial intelligence (AI) in urban development is meticulously examined. This comprehensive research delineates the multifaceted ways in which AI-powered mobile applications can significantly enhance the efficiency, sustainability, and livability of urban environments, marking a pivotal step towards the realization of smart cities globally. Bayashot meticulously outlines the critical areas where AI-powered apps offer unprecedented advantages, including urban mobility, public safety, energy management, and environmental monitoring. By leveraging AI’s capabilities, these applications not only streamline city operations but also foster a more sustainable interaction between city dwellers and their environment. The paper emphasizes the importance of data-driven decision-making in urban planning, showcasing how AI analytics can predict and mitigate traffic congestion, optimize energy consumption, and enhance emergency response strategies. The author also explores the social implications of AI in urban settings, highlighting the potential for these technologies to bridge the gap between government entities and citizens. Through engaging case studies, Bayashot demonstrates how participatory governance models, enabled by AI apps, can promote transparency, accountability, and citizen engagement in urban management. A significant contribution of this research is its focus on the challenges and opportunities presented by the integration of AI into smart city ecosystems. Bayashot discusses the technical, ethical, and privacy concerns associated with AI applications, advocating for a balanced approach that ensures technological advancements do not come at the expense of civil liberties. The study calls for robust regulatory frameworks to govern the use of AI in public spaces, emphasizing the need for ethical AI practices

关键词： Mobile Applications smart Cities Artificial Intelligence IoT

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel segmentation in Fundus Images

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Computers, Materials & Continua 2024年第5期79卷 2565-2583页

作者： syed Ayaz ali shah Aamir shahzad Musaed alhussein Chuan Meng Goh Khursheed Aurangzeb Tong Boon Tang Muhammad Awais Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabad22060Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Information and Communication Technology University Tunku Abdul RehmanKampar CampusKampar31900Malaysia Centre for Intelligent signal and Imaging Research University Teknologi PETRONASBandar Seri IskandarPerak32610Malaysia school of Computing sciences University of East AngliaNorwichNR47TJUK

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood *** task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different ***,the speed of the retinal vessel segmentation system is of utmost *** the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the *** address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical *** algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the structure Analysis of Retina(sTARE)*** experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for sTARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for sTARE ***,our algorithmexhibits competitive performance with state-of-the-art ***,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for sTARE *** is worth noting that these results were achieved using Matlab scripts containing multiple *** suggests that the processing time can be further reduced by replacing loops with *** the proposed algorithm can be deployed in real time *** summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

关键词： Line detector vessel detection localization mathematical morphology image processing