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Developing a Model for Parkinson’s Disease Detection Using Machine Learning Algorithms

Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif Al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost

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Social Media-Based Surveillance systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of information system College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2421-2444页

作者： Fady Samann Shavan Askar Department of Energy Engineering Technical College of EngineeringDuhok Polytechnic UniversityDuhok42001Iraq Department of information system Engineering Technical College of EngineeringErbil Polytechnic UniversityErbil44001Iraq

Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are simplistic,with fast performance and relative ***,their implementation depends on the initial selection of clusters number(K),the initial clusters’centers,and the clustering *** paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time(LET)as a clustering *** traffic flows were considered for three maps,namely Highway,Traffic Light junction,and Roundabout junction,to study the effect of road layout on estimating the K number.A fast version of the PAM algorithm was used for clustering with a modification to reduce time *** Affinity propagation algorithm sets the baseline for the estimated K number,and the Medoid Silhouette method is used to quantify the ***++,Veins,and SUMO were used to simulate the traffic,while the related algorithms were implemented in *** Scott’s formula estimation of the K number only matched the baseline when the road layout was ***,the clustering algorithm required one iteration on average to converge when used with LET.

关键词： Clustering vehicular network Scott’s formula FastPAM

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An Improved Deep Learning Framework for Automated Optic Disc Localization and Glaucoma Detection

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1429-1457页

作者： Hela Elmannai Monia Hamdi Souham Meshoul Amel Ali Alhussan Manel Ayadi Amel Ksibi Department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of information system College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Glaucoma disease causes irreversible damage to the optical nerve and it has the potential to cause permanent loss of *** ranks as the second most prevalent cause of permanent *** glaucoma diagnosis requires a highly experienced specialist,costly equipment,and a lengthy wait *** automatic glaucoma detection,state-of-the-art glaucoma detection methods include a segmentation-based method to calculate the cup-to-disc *** methods include multi-label segmentation networks and learning-based methods and rely on hand-crafted *** the optic disc(OD)is one of the key features in retinal images for detecting retinal diseases,especially for glaucoma disease *** approach presented in this study is based on deep classifiers for OD segmentation and glaucoma ***,the optic disc detection process is based on object detection using a Mask Region-Based Convolutional Neural Network(Mask-RCNN).The OD detection task was validated using the Dice score,intersection over union,and accuracy *** OD region is then fed into the second stage for glaucoma ***,considering only the OD area for glaucoma detection will reduce the number of classification artifacts by limiting the assessment to the optic disc *** this task,VGG-16(Visual Geometry Group),Resnet-18(Residual Network),and Inception-v3 were pre-trained and *** also used the Support Vector Machine *** feature-based method uses region content features obtained by Histogram of Oriented Gradients(HOG)and Gabor *** final decision is based on weighted fusion.A comparison of the obtained results from all classification approaches is *** metrics including accuracy and ROC curve are compared for each classification *** novelty of this research project is the integration of automatic OD detection and glaucoma diagnosis in a global ***,the fusion-based decision system uses the g

关键词： Optic disc glaucoma fundus image deep learning

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Efficient Object Segmentation and Recognition Using Multi-Layer Perceptron Networks

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Computers, Materials & Continua 2024年第1期78卷 1381-1398页

作者： Aysha Naseer Nouf Abdullah Almujally Saud S.Alotaibi Abdulwahab Alazeb Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia information system Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Object segmentation and recognition is an imperative area of computer vision andmachine learning that identifies and separates individual objects within an image or video and determines classes or categories based on their *** proposed system presents a distinctive approach to object segmentation and recognition using Artificial Neural Networks(ANNs).The system takes RGB images as input and uses a k-means clustering-based segmentation technique to fragment the intended parts of the images into different regions and label thembased on their ***,two distinct kinds of features are obtained from the segmented images to help identify the objects of *** Artificial Neural Network(ANN)is then used to recognize the objects based on their *** were carried out with three standard datasets,MSRC,MS COCO,and Caltech 101 which are extensively used in object recognition research,to measure the productivity of the suggested *** findings from the experiment support the suggested system’s validity,as it achieved class recognition accuracies of 89%,83%,and 90.30% on the MSRC,MS COCO,and Caltech 101 datasets,respectively.

关键词： K-region fusion segmentation recognition feature extraction artificial neural network computer vision

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Lead-free perovskite Cs_(2)AgBiBr_(6)photodetector detecting NIR light driven by titanium nitride plasmonic hot holes

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Photonics Research 2024年第3期12卷 522-533页

作者： ZIJIAN LIU YUYING XI WENBO ZENG TING JI WENYAN WANG SITONG GUO LINLIN SHI RONG WEN YANXIA CUI GUOHUI LI college of Physics College of Electronic Information and Optical EngineeringKey Laboratory of Advanced Transducers and Intelligent Control System of Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030032China

Lead-free perovskite Cs_(2)AgBiBr_(6)manifests great potential in developing high-performance,environmentally friendly,solution-processable photodetectors(PDs).However,due to the relatively large energy bandgap,the spectrum responses of Cs_(2)AgBiBr_(6)PDs are limited to the ultraviolet and visible region with wavelengths shorter than 560 *** this work,a broadband Cs_(2)AgBiBr_(6)PD covering the ultraviolet,visible,and near infrared(NIR)range is demonstrated by incorporating titanium nitride(TiN)nanoparticles that are prepared with the assistance of self-assembled polystyrene sphere *** addition,an atomically thick Al2O3layer is introduced at the interface between the Cs_(2)AgBiBr_(6)film and TiN nanoparticles to alleviate the dark current deterioration caused by nanoparticle *** a result,beyond the spectrum range where Cs_(2)AgBiBr_(6)absorbs light,the external quantum efficiency(EQE)of the TiN nanoparticle incorporated Cs_(2)AgBiBr_(6)PD is enhanced significantly compared with that of the control,displaying enhancement factors as high as 2000 over a broadband NIR wavelength *** demonstrated enhancement in EQE arises from the photocurrent contribution of plasmonic hot holes injected from TiN nanoparticles into Cs_(2)AgBiBr_(6).This work promotes the development of broadband solution-processable perovskite PDs,providing a promising strategy for realizing photodetection in the NIR region.

关键词： perovskite titanium ultraviolet

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Fast measurement and prediction method for electromagnetic susceptibility of receiver

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Journal of systems Engineering and Electronics 2024年第2期35卷 275-285页

作者： CHEN Yan LU Zhonghao LIU Yunxia State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and information system College of Electronic Science and TechnologyNational University of Defense TechnologyChangsha 410073China State Key Laboratory of Astronautic Dynamics Xi’an 710043China

Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone ***,two signal generators are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the intermediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent ***,the IF output response data are modeled and analyzed to construct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the *** experiment performed on a radar receiver confirms the reliability of the method proposed in this *** shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity *** on this,fast and comprehensive evaluation and prediction of the receiver’s EMS in complex environment can be efficiently realized.

关键词： electromagnetic susceptibility(EMS) receiver dualchannel multi-frequency nonlinear response frequency domain power domain

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Non-adiabatic holonomic quantum operations in continuous variable systems

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 12-19页

作者： Hao-Long Zhang Yi-Hao Kang Fan Wu Zhen-Biao Yang Shi-Biao Zheng Fujian Key Laboratory of Quantum information and Quantum Optics College of Physics and Information EngineeringFuzhou UniversityFuzhou 350116China

Quantum operations by utilizing the underlying geometric phases produced in physical systems are favoured due to their potential *** a system in a non-degenerate eigenstate undergoes an adiabatically cyclic evolution dominated by its Hamiltonian,it will get a geometric phase,referred to as the Berry *** a non-adiabatically cyclic evolution produces an Aharonov-Anandan geometric *** two types of Abelian geometric phases are extended to the non-Abelian cases,where the phase factors become matrix-valued and the transformations associated with different loops are *** and non-Abelian(holonomic)operations are prevalent in discrete variable systems,whose limited(say,two)energy levels,form the *** their developments in continuous systems have also been investigated,mainly due to that,bosonic modes(in,such as,cat states)with large Hilbert spaces,provide potential advantages in fault-tolerant quantum *** we propose a feasible scheme to realize non-adiabatic holonomic quantum logic operations in continuous variable systems with cat *** construct arbitrary single-qubit(two-qubit)gates with the combination of single-and two-photon drivings applied to a Kerr Parametric Oscillator(KPO)(the coupled KPOs).Our scheme relaxes the requirements of the previously proposed quantum geometric operation strategies in continuous variable systems,providing an effective way for quantum control.

关键词： cat qubit continuous variable systems non-Abelian

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Highly adaptive triboelectric tactile sensor on the foot of autonomous wall-climbing robots for detecting the adhesion state and avoiding the hazard

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Nano Research 2024年第7期17卷 6518-6526页

作者： Zhaoyang Wang Jianhua Liu Ziyu Wang Chang Liu Qingyu Chen Chaofan Zhang Wenbo Zhang Jicang Si Xiu Xiao Peng Xu Minyi Xu Dalian Key Lab of Marine Micro/Nano Energy and Self-powered system Marine Engineering CollegeDalian Maritime UniversityDalian 116026China information Science and Technology college Dalian Maritime UniversityDalian 116026China Navigation college Dalian Maritime UniversityDalian 116026China Intelligent Biomimetic Design Lab College of EngineeringPeking UniversityBeijing 100871China

Due to the excellent maneuverability and obstacle crossing of legged robots,it is possible for an autonomous legged wallclimbing robots to replace manual inspection of ship exterior ***,when the magnetic adsorption legged wallclimbing robot steps on the convex point or convex line of the wall,or even when the robot missteps,the robot is likely to detach from the ferromagnetic ***,this paper proposes a tactile sensor for the legged magnetic adsorption wall-climbing robot to detect the magnetic adsorption state and improve the safety of the autonomous crawling of the *** tactile sensor mainly comprises a three-dimensional(3D)-printed shell,a tactile slider,and three isometric sensing units,with an optimized *** experiment shows that the triboelectric tactile sensor can monitor the sliding depth of the tactile slider and control the light-emitting device(LED)signal *** addition,in the demonstration experiment of detecting the adsorption state of the robot's foot,the triboelectric tactile sensor has strong adaptability to various ferromagnetic wall ***,this study establishes a robot gait control system to verify the feedback control ability of the triboelectric tactile *** results show that the robot equipped with the triboelectric tactile sensor can recognize the dangerous area on the crawling wall and autonomously avoid the ***,the proposed triboelectric tactile sensor has great potential in realizing the tactile sensing ability of robots and enhancing the safety and intelligent inspection of ultra-large vessels.

关键词： legged wall-climbing robot ship inspection tactile perception triboelectric sensor

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A Review on the Recent Trends of Image Steganography for VANET Applications

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Computers, Materials & Continua 2024年第3期78卷 2865-2892页

作者： Arshiya S.Ansari Department of information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside *** vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation *** steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy *** paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality *** to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network *** this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and *** study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.

关键词： Steganography image steganography image steganography techniques information exchange data embedding and extracting vehicular ad hoc network(VANET) transportation system

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