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Emerging strategies and developments in oxygen reduction reaction using high-performance platinum-based electrocatalysts

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Nano Research 2024年第5期17卷 3516-3532页

作者： Asad ali Aatto Laaksonen Guo Huang shahid Hussain shuiping Luo Wen Chen Pei Kang shen Jinliang Zhu Xiaoyan Ji Energy Engineering Division of Energy ScienceLuleåUniversity of Technology97187 LuleåSweden Department of Materials and Environmental Chemistry Arrhenius LaboratoryStockholm UniversitySE-10691 StockholmSweden Center of Advanced Research in Bionanoconjugates and Biopolymers “Petru Poni”Institute of Macromolecular ChemistryIasi 700469Romania state Key Laboratory of Materials-Oriented and Chemical Engineering Nanjing Tech UniversityNanjing 211816China College of Materials science and Engineering Shenzhen UniversityShenzhen 518060China school of Resources Environment and MaterialsState Key Laboratory of Processing for Non-ferrous Metal and Featured MaterialsGuangxi UniversityNanning 530004China

The global practical implementation of proton exchange membrane fuel cells(PEMFCs)heavily relies on the advancement of highly effective platinum(Pt)-based electrocatalysts for the oxygen reduction reaction(ORR).To achieve high ORR performance,electrocatalysts with highly accessible reactive surfaces are needed to promote the uncovering of active positions for easy mass *** this critical review,we introduce different approaches for the emerging development of effective ORR electrocatalysts,which offer high activity and *** strategies,including morphological engineering,geometric configuration modification via supporting materials,alloys regulation,core-shell,and confinement engineering of single atom electrocatalysts(sAEs),are discussed in line with the goals and requirements of ORR performance *** review the ongoing development of Pt electrocatalysts based on the syntheses,nanoarchitecture,electrochemical performances,and *** eventually explore the obstacles and research directions on further developing more effective electrocatalysts.

关键词： oxygen reduction reaction(ORR) Pt-based electrocatalysts proton exchange membrane fuel cells(PEMFCs) morphology and alloys strategies single atom electrocatalysts(sAEs)

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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

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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

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Adaptive Cloud Intrusion Detection system Based on Pruned Exact Linear Time Technique

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Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah Md.siraj Bander ali saleh Al-rimy sultan Noman Qasem Tawfik Al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia school of science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** security solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection systems(CIDs).Existing adaptive CIDs solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall security *** address these challenges,we propose ACIDs(Adaptive Cloud Intrusion Detection system)-*** novel Adaptive CIDs framework leverages the Pruned Exact Linear Time(PELT)algorithm and a support Vector Machine(sVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HsO-sU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential security threats with improved precision compared to existing approaches.(3)Training set:Labeled network traffic data forms the training set used to train the sVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing set:The testing set evaluates ACIDs-PELT’s performance by measuring its accuracy,precision,and recall in detecting security threats within the cloud *** evaluate the performance of ACIDs-PELT using the NsL-KDD benchmark *** results demonstrate that ACIDs-PELT outperf

关键词： Adaptive cloud IDs harmony search distributed denial of service(DDos) PELT machine learning sVM IsOTCID NsL-KDD

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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

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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

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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

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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

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Enhancing secure Development in Globally Distributed software Product Lines: A Machine Learning-Powered Framework for Cyber-Resilient Ecosystems

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Computers, Materials & Continua 2024年第6期79卷 5031-5049页

作者： Marya Iqbal Yaser Hafeez Nabil Almashfi Amjad Alsirhani Faeiz Alserhani sadia ali Mamoona Humayun Muhammad Jamal University Institute of Information Technology PMAS-Arid Agriculture UniversityRawalpindiPakistan Department of software Engineering College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Computer science College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Computer Engineering&Networks College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Information systems College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72388Saudi Arabia Department of Mathematics Pir Mehr Ali Shah Arid Agriculture UniversityRawalpindiPakistan

Embracing software product lines(sPLs)is pivotal in the dynamic landscape of contemporary software ***,the flexibility and global distribution inherent in modern systems pose significant challenges to managing sPL variability,underscoring the critical importance of robust cybersecurity *** paper advocates for leveraging machine learning(ML)to address variability management issues and fortify the security of *** the context of the broader special issue theme on innovative cybersecurity approaches,our proposed ML-based framework offers an interdisciplinary perspective,blending insights from computing,social sciences,and ***,it employs ML for demand analysis,dynamic feature extraction,and enhanced feature selection in distributed settings,contributing to cyber-resilient *** experiments demonstrate the framework’s superiority,emphasizing its potential to boost productivity and security in *** digital threats evolve,this research catalyzes interdisciplinary collaborations,aligning with the special issue’s goal of breaking down academic barriers to strengthen digital ecosystems against sophisticated attacks while upholding ethics,privacy,and human values.

关键词： Machine Learning variability management cybersecurity digital ecosystems cyber-resilience

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Fabrication of MXene-Bi_(2)WO_(6)heterojunction by Bi_(2)Ti_(2)O_(7)hinge for extraordinary LED-light-driven photocatalytic performance

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Nano Research 2024年第6期17卷 4729-4736页

作者： Zhiwen Li Liangliang Xu Zaheer Ud Din Babar ali Raza Yifei Zhang Xinrui Gu Yu-Xin Miao Zhen Zhao Gao Li Institute of Catalysis for Energy and Environment College of Chemistry and Chemical EngineeringShenyang Normal UniversityShenyang 110034China state Key Laboratory of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China scuola superiore Meridionale(ssM) University of Naples Federico IILargo S.Marcellino1080138Italy Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology(KAIST)Daejeon 34141Republic of Korea University of Chinese Academy of sciences Beijing 100049China

Heterojunction composites with intimate interfaces can shorten the diffusion distance,which leads to a shorter path for photogenerated carriers,thereby increasing photocatalytic ***,we report the fabrication of Ti_(3)C_(2)-Bi_(2)WO_(6)(TC-BW)heterojunctions hinged by Bi_(2)Ti_(2)O_(7)joints via an in situ hydrothermal reaction of Ti_(3)C_(2)in the presence of Na_(2)WO_(4)and Bi(NO_(3))_(3).The TC-BW was characterized using X-ray diffraction(XRD),scanning transmission electron microscopy(sTEM),and Raman ***-BW showed superior photocatalytic activity(productivity over 15TC-WB reaches up to 5.0 mmolreacted BA·gcat.^(−1)·h^(−1))in the oxidation of benzyl alcohol using light-emitting diode(LED)light,arising from the surface defects and intimate heterojunction interface between the Ti_(3)C_(2)MXene and Bi_(2)WO_(6)***-BW heterojunctions provide an enhanced separation efficiency of photogenerated charges,which in turn yields superior photocatalytic ***,it is well substantiated by density functional theory(DFT)*** summary,this study elucidates the preparation of heterojunction composites with intimate interfaces for highly efficient photooxidation.

关键词： MXene-Bi_(2)WO_(6) heterojunction LED-light-driven photocatalysis Bi_(2)Ti_(2)O_(7) photooxidation

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