Numerical model of cutting tool blade wear by Panchuk V., Onysko O., Kotwica K., Barz C., Borushchak L.

“…It showed that in the case of lathe machining of the thread of NC23 type, the deviation from the nominal half profile of the obtained thread is only 0.02°. …”
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Prediction of Rut Depth in Soil Caused by Wheels Using Artificial Neural Networks by N. Farhadi, A. Mardani, A. Hosainpour, B. Golanbari

“…The complexity of these interactions necessitates using machine learning models, especially artificial neural networks (ANNs), to predict rut depth based on input parameters. …”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…This work leverages advanced natural language processing, machine learning, and deep learning algorithms to effectively detect fake and AI–generated content. …”
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Dynamic and low-dimensional modeling of brain functional connectivity on Riemannian manifolds by Mingyu Wang, Yueming Wang, Yuxiao Yang

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Impurity rates detection for pepper harvesting based on YOLOv8n-Seg-ASB and random forest by Lijian Lu, Jin Lei, Chenming Cheng, Shiguo Wang, Chengfu Wang, Xinyan Qin

“…To address the inaccuracies and inefficiencies of pepper impurity rates detection caused by complex material compositions and variable harvesting environments, this paper proposes a detection technique based on deep and machine learning algorithms. First, a machine vision-based image acquisition device for pepper material is designed to reliably capture high-quality real-time images. …”
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A Novel Fractional Filter Design and Cross-Term Elimination in Wigner Distribution by Jiexiao Yu, Kaihua Liu, Liang Zhang, Peng Luo

“…Without any prior knowledge of signal and noise, this method can meet the reliability and universality simultaneously for filter design and realize the global optimization of filter parameters by machine learning even in the case of strong coupling between signal and noise. …”
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内啮合摆线齿轮泵摆线轮齿廓参数化设计分析 by 王振, 刘忠明

“…Internal meshing cycloidal gear pump has many advantages in application: small size、light weight、low noise、excellent self-absorption、good flow on the pulse and so on.However,because of the complex shape of tooth profile,the machining is more difficult.Base on the gear meshing principle,the equation of cycloidal gear tooth profile has been derived in the paper,and the approach of two type fillers is discussed.Using Visual Basic6.0 in AutoCAD platform,the parameter drawing of the full gear tooth curve is achieved.It is of great significance for further analysis of the meshing character and the special mechanical properties of the gear pumps.…”
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Screw Conveyor Rotor Multi-objective Optimization Design by ZHANG Yuan, JIANG Xiao-han, FAN Hua-ping, LI Xi-han

“…A parameterized association model was set up, spiral rib width and the rotor radius were refered as the correlated parameters.The response surface method was used to optimize the natural frequency and shape variables. …”
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Predicting Carbon Residual in Biomass Wastes Using Soft Computing Techniques by Preety Verma, J. Godwin Ponsam, Rajeev Shrivastava, Ajay Kushwaha, Neelabh Sao, AL Chockalingam, Leena Bojaraj, null JaikumarR, S. Chandragandhi, Assefa Alene

“…To resolve this multiobjective formulation, we use a machine learning classifier that maps systematically the CO2 adsorption as a function of compositional and textural properties and adsorption parameters. …”
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Optimization of the control system of BP-PID rice polishing unit based on WAO algorithm by HUANG Jinliang, ZHOU Jin, YU Wei

“…ObjectiveAddress the current issues of poor internal flow stability, low single-machine efficiency, and subpar polishing quality in rice polishing units.MethodsFirstly, the traditional polishing machine was improved, its control parameters were clarified, and the mathematical model of the rice polishing unit was established. …”
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变截面摆线传动的齿廓曲率研究 by 王淑妍, 陈兵奎

“…The variable cross section cycloid drive can realize lower backlash by adjusting the axial location of the variable cross cycloid gear pair.The curvature radius is an important parameter in design and machining process such as undercut,contact stress calculation and determination of machining tool radius.The profile surface’s curvature of variable cross section cycloid gear is studied based on kinematics.The paper covers the following topics:（i） the curvature of profile surfaces of variable cross section cycloid gear is studied,and general equation of variable cross section cycloid gear’s curvature is derived based on the curvature of pins and the motion parameters;（ii） the profile surface’s curvature of linear variable cross section cycloid gear as conic cycloid gear and nonlinear as drum cycloid gear are developed,and related numerical calculation examples are given.…”
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齿轮热滚挤过程中滑动系数变化对齿形误差的影响 by 郑鹏, 周国祥, 段振云

“…This research proves to be helpful to analyze completely machining error in ausform finishing, and it provides an important parameter in profile design of rolling dies.…”
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Classification of Prominent Cacao Pod Diseases Using Multi-Feature Visual Analysis and k-Nearest Neighbors Algorithm by Earl Clarence San Diego, Seph Gerald Rodrin, Edwin Arboleda

“…In response to this problem, the study devised an algorithm based on k-Nearest Neighbors that can detect whenever a cacao pod was infected with the three most prominent diseases: black pod rot, Monilia, and pod borer infestations. The machine training model was preceded with visual feature extraction of color and texture parameters representing the cacao pod samples. …”
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Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
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Fusion of Deep and Time–Frequency Local Features for Melanoma Skin Cancer Detection by Hamidreza Eghtesaddoust, Morteza Valizadeh, Mehdi Chehel Amirani

“…The Bayesian optimizer finds the optimum parameters of the SDA and Gaussian kernel of the support vector machine (SVM) classifier to maximize the classification accuracy. …”
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On the Determination of the Output Power in Mono/Multicrystalline Photovoltaic Cells by Xia Liu, Yongqiu Liu, Mohammad Eslami

“…Adaptive neuro-fuzzy inference system (ANFIS) and Least-squares support vector machine (LSSVM) are applied for the output power calculations. …”
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Development of a Simplified Human Body Model for Movement Simulations by Michał Olinski, Przemysław Marciniak

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AI-Driven Spatial Data Analysis of Groundwater Level and Gravimetric Data in Roorkee Region, India by H. Sarkar, C. S. P. Ojha, S. K. Ghosh

“…The study evaluates the use of K-Nearest Neighbour (KNN), Random Forest (RF), Support Vector Machine (SVM), XG Boost and Polynomial regression models, using two groups of input parameters. …”
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Side Wear Prediction of a Subway Outer Rail on Small Radius Curves Based on System Dynamics of Discrete Supported Track by Xianxian Yin, Linlin Kou, Xiukun Wei, Haichao Zheng

“…This paper proposes three prediction models based on the response surface methodology (RSM), support vector machine (SVM), and the relative vector machine (RVM) to estimate the remaining useful life (RUL) of a metro outer rail at a small radius curve determined by rail side wear. …”
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Intelligent Stroke Disease Prediction Model Using Deep Learning Approaches by Chunhua Gao, Hui Wang

“…Finally, the proposed method is compared with commonly used machine learning-based classification algorithms such as decision tree, random forest, support vector machine, and artificial neural networks. …”
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