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Enhancing Communication Accessibility:UrsL-CNN Approach to Urdu sign Language Translation for Hearing-Impaired Individuals

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Computer Modeling in Engineering & sciences 2024年第10期141卷 689-711页

作者： Khushal Das Fazeel Abid Jawad Rasheed Kamlish Tunc Asuroglu shtwai alsubai.safeeullah soomro Department of Computer Engineering Modeling Electronics and Systems EngineeringUniversity of CalabriaRende Cosenza87036Italy Department of Information systems University of Management and TechnologyLahore54770Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of software Engineering Istanbul Nisantasi UniversityIstanbul34398Turkey Department of Computer science COMSATS University IslamabadLahore CampusLahore54700Pakistan Faculty of Medicine and Health Technology Tampere UniversityTampere33720Finland Department of Computer science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia second Department of Computer science College of Engineering and ComputingGeorge Mason UniversityFairfaxVA 4418USA

Deaf people or people facing hearing issues can communicate using sign language(sL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other sLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrsL)using the UrsL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrsL alphabets dataset demonstrated the superiority of UrsL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.

关键词： Convolutional neural networks Pakistan sign language visual language

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Improving Prediction of Chronic Kidney Disease Using KNN Imputed sMOTE Features and TrioNet Model

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Computer Modeling in Engineering & sciences 2024年第6期139卷 3513-3534页

作者： Nazik Alturki Abdulaziz Altamimi Muhammad Umer Oumaima saidani Amal Alshardan shtwai alsubai.Marwan Omar Imran Ashraf Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department College of Computer science and Engineering University of Hafr Al-BatinHafarAl-Batin39524Saudi Arabia Department of Computer science&Information Technology The Islamia University of BahawalpurP.O.Box 63100BahawalpurPakistan Department of Computer science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Information Technology and Management Illinois Institute of TechnologyChicagoIL 60616-3793USA Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Chronic kidney disease(CKD)is a major health concern today,requiring early and accurate *** learning has emerged as a powerful tool for disease detection,and medical professionals are increasingly using ML classifier algorithms to identify CKD *** study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California,UC Irvine Machine Learning *** research introduces TrioNet,an ensemble model combining extreme gradient boosting,random forest,and extra tree classifier,which excels in providing highly accurate predictions for ***,K nearest neighbor(KNN)imputer is utilized to deal withmissing values while synthetic minority oversampling(sMOTE)is used for class-imbalance *** ascertain the efficacy of the proposed model,a comprehensive comparative analysis is conducted with various machine learning *** proposed TrioNet using KNN imputer and sMOTE outperformed other models with 98.97%accuracy for *** in-depth analysis demonstrates the model’s capabilities and underscores its potential as a valuable tool in the diagnosis of CKD.

关键词： Precisionmedicine chronic kidney disease detection sMOTE missing values healthcare KNNimputer ensemble learning

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Efficient and secure IoT Based smart Home Automation Using Multi-Model Learning and Blockchain Technology

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Computer Modeling in Engineering & sciences 2024年第6期139卷 3387-3415页

作者： Nazik Alturki Raed Alharthi Muhammad Umer Oumaima saidani Amal Alshardan Reemah M.Alhebshi shtwai alsubai.Ali Kashif Bashir Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Computer science and Engineering University of Hafr Al-BatinHafar Al-BatinSaudi Arabia Department of Computer science&Information Technology The Islamia University of BahawalpurBahawalpurPakistan Department of Computer science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen school of Business Woxsen UniversityHyderabadIndia Department of Computer science and Mathematics Lebanese American UniversityBeirutLebanon

The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device *** home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical *** paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in *** have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT *** system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing *** have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache *** feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time *** is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation ***,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber *** trial results support the proposed system and demonstrate its potential for use in everyday life.

关键词： Blockchain Internet of Things(IoT) smart home automation cybersecurity

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Effect of Eu3+,Bi3+,and Li+ doping on luminescent property of GdNbO4

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Journal of Rare Earths 2024年第1期42卷 66-75页

作者： s.W.Wi Y.s.Lee Department of Physics and Integrative Institute of Basic sciences Soongsil University

We investigated the emission properties of Eu3+-doped GdNbO4-based oxide phosphors,aiming at improving the Eu3+emission by codoping of Bi3+and Li+.Eu3+singly doped,Eu3+and Bi3+doubly doped,and Eu3+,Bi3+,and Li+triply doped GdNbO4were prepared using a high-temperature solid-state reaction *** red-orange emissions from Eu3+in the singly doped samples are significantly improved by the codoping of Bi3+,mainly due to the energy transfer from Bi3+to Eu3+.The additional codoping of Li+is found to increase the Eu3+emission *** improvement might be attributed to the increase in the photoluminescent quantum yield originating from larger grain sizes and better crystallinity.A detailed analysis of the X-ray diffraction pattern and the asymmetric ratio estimated from the photoluminescence spectra show that the local lattice environment around Eu3+in GdNbO4does not change significantly with the codoping of Bi3+and Li+.Our results indicate that Li+doping is a promising way to improve the emission properties of rare-earth ion-doped GdNbO4phosphors.

关键词： Eu 3+ GdNbO 4 Codoping of Li + Photoluminescence sensitizer Rare earths

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A Hybrid Deep Fused Learning Approach to segregate Infectious Diseases

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Computers, Materials & Continua 2023年第2期74卷 4239-4259页

作者： Jawad Rasheed shtwai alsubai Department of software Engineering Nisantasi UniversityIstanbul34398Turkey Dapartment of Computer science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia

Humankind is facing another deadliest pandemic of all times in history,caused by *** from this challenging pandemic,World Health Organization(WHO)considers tuberculosis(TB)as a preeminent infectious disease due to its high infection ***,both TB and COVID-19 severely affect the lungs,thus hardening the job of medical practitioners who can often misidentify these diseases in the current ***,the time of need calls for an immediate and meticulous automatic diagnostic tool that can accurately discriminate both *** one of the preliminary smart health systems that examine three clinical states(COVID-19,TB,and normal cases),this study proposes an amalgam of image filtering,data-augmentation technique,transfer learning-based approach,and advanced deep-learning classifiers to effectively segregate these *** first employed a generative adversarial network(GAN)and Crimmins speckle removal filter on X-ray images to overcome the issue of limited data and *** pre-processed image is then converted into red,green,and blue(RGB)and Commission Internationale de l’Elcairage(CIE)color spaces from which deep fused features are formed by extracting relevant features using DenseNet121 and *** feature extractor extracts 1000 most useful features which are then fused and finally fed to two variants of recurrent neural network(RNN)classifiers for precise discrimination of threeclinical *** analysis showed that the proposed Bi-directional long-short-term-memory(Bi-LsTM)model dominated the long-short-termmemory(LsTM)network by attaining an overall accuracy of 98.22%for the three-class classification task,whereas LsTM hardly achieved 94.22%accuracy on the test dataset.

关键词： Computer-aided diagnosis decision support system deep transfer learning deep fused features tuberculosis COVID-19

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First evidence for chiral wobbling of triaxial nuclei

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Nuclear science and Techniques 2024年第7期35卷 4-7页

作者： s.Frauendorf Department of Physics and Astronomy University of Notre DameNotre DameIN 46556USA

Chirality(Greek“handiness”)is a property of many com-plex *** molecules exist in two forms,one being the mirror image of the *** for our hands,it is impossible to make the images identical by a suitable *** two forms are called left-handed and *** have the same binding energy,because the electro-magnetic interaction,which holds the molecule together,does not change under a *** properties that are insensitive to the geometry are also the *** different geometry is the reason why the left-handed form turns the polarization plane of transmitted light in one direction by some angle while the right-handed form turns it in the oppo-site direction by the same ***,the geometrical differences between the two species may have other *** two species of the carvon molecule shown in Fig.1 taste quite differently.

关键词： turns Chiral mirror

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Tribological behavior of lubricant-impregnated porous polyimide

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Friction 2024年第4期12卷 711-725页

作者： Jinbang LI Ningning ZHOU Janet s.s.WONG school of Mechanical Engineering and Mechanics Ningbo UniversityNingbo 315211China Beijing Key Laboratory of Long-life Technology of Precise Rotation and Transmission Mechanisms Beijing Institute of Control EngineeringBeijing 100029China Department of Mechanical Engineering Imperial College LondonLondon SW72AZUK

Porous materials impregnated with lubricants can be used in conditions where limited lubricant is *** this work,three porous polyimides(PPI)with different densities were ***(PAO)impregnated PPI(iPPI)discs were rubbed against steel and sapphire *** operando observations of the iPPI-sapphire contacts show that oil is released under an applied load,forming a meniscus around *** at the outlet is created at high sliding *** amount of released oil increases with increasing PPI *** moduli,E*,estimated based on the actual contact size show that trapped oil in iPPIs contributes to load *** higher speeds,tribological rehydration of the contact occurs in low density iPPI,with that E*rises with *** high density PPIs,high speeds give a constantly high E*which is limited by the viscoelastic properties of the PPI network and possibly the rate of oil *** of iPPI-steel contacts is governed by the mechanical properties of the PPI,the flow of the lubricant,and the roughness of the PPI *** low-and medium-density(highly porous,high roughness)PPIs,large amount of oil is released,and lubrication is mainly via lubricant restricted in the contact in the pores and possibly tribological *** high density(low porosity)PPI,with lower roughness,hydrodynamic lubrication is achieved which gives the lowest *** results show that polymeric porous materials for effective lubrication require the optimization of its surface roughness,stiffness,oil flow,and oil retentions.

关键词： polyimide porous material friction mechanism polymer limited lubrication

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Enhancing fatigue performance of AZ31 magnesium alloy components fabricated by cold metal transfer-based wire arc directed energy deposition through LPB

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Journal of Magnesium and Alloys 2024年第4期12卷 1638-1662页

作者： shambhu Kumar Manjhi srikanth Bontha A.s.s.Balan Department of Mechanical Engineering National Institute of Technology KarnatakaSurathkalSrinivasanagarMangaloreKarnataka 575025India

Cold Metal Transfer-Based Wire Arc Directed Energy Deposition(CMT-WA-DED)presents a promising avenue for the rapid fabrication of components crucial to automotive,shipbuilding,and aerospace ***,the susceptibility to fatigue of CMT-WA-DED-produced AZ31 Mg alloy components has impeded their widespread adoption for critical load-bearing *** this study,a comprehensive investigation into the fatigue behaviour of WA-DED-fabricated AZ31 Mg alloy has been carried out and compared to commercially available wrought AZ31 *** findings indicate that the as-deposited parts exhibit a lower fatigue life than wrought Mg alloy,primarily due to poor surface finish,tensile residual stress,porosity,and coarse grain microstructure inherent in the WA-DED *** Plasticity Burnishing(LPB)treatment is applied to mitigate these issues,which induce significant plastic deformation on the *** treatment resulted in a remarkable improvement of fatigue life by 42%,accompanied by a reduction in surface roughness,grain refinement and enhancement of compressive residual stress ***,during cyclic deformation,WA-DED specimens exhibited higher plasticity and dislocation density compared to both wrought and WA-DED+LPB specimens.A higher fraction of Low Angle Grain Boundaries(LAGBs)in WA-DED specimens contributed to multiple crack initiation sites and convoluted crack paths,ultimately leading to premature *** contrast,wrought and WA-DED+LPB specimens displayed a higher percentage of High Angle Grain Boundaries(HAGBs),which hindered dislocation movement and resulted in fewer crack initiation sites and less complex crack paths,thereby extending fatigue *** findings underscore the effectiveness of LPB as a post-processing technique to enhance the fatigue performance of WA-DED-fabricated AZ31 Mg alloy *** study highlights the importance of LPB surface treatment on AZ31 Mg components produced by CMT-WA-DED to remove surface d

关键词： Wire arc additive manufacturing AZ31 Mg alloy Low plasticity burnishing Low cycle fatigue test strain amplitude

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Ren-integrable and ren-symmetric integrable systems

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Communications in Theoretical Physics 2024年第3期76卷 62-69页

作者： s Y Lou school of Physical science and Technology Ningbo UniversityNingbo315211China

A new type of symmetry,ren-symmetry,describing anyon physics and corresponding topological physics,is ***-symmetry is a generalization of super-symmetry which is widely applied in super-symmetric physics such as super-symmetric quantum mechanics,super-symmetric gravity,super-symmetric string theory,super-symmetric integrable systems and so *** and Grassmann numbers are,in some sense,dual conceptions,and it turns out that these conceptions coincide for the ren situation,that is,a similar conception of ren-number(R-number)is devised for *** particular,some basic results of the R-number and ren-symmetry are exposed which allow one to derive,in principle,some new types of integrable systems including ren-integrable models and ren-symmetric integrable *** examples of ren-integrable KdV-type systems and ren-symmetric KdV equations are explicitly given.

关键词： symmetries integrable systems anyon physics extended supersymmetry ren-symmetry

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AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

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Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： s.Jayanthi s.Prasanna Devi Department of Computer science and Engineering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

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