Method for recognizing abnormal operation patterns in hydraulic support machine-following and shifting control by MA Zhitao, FU Xiang, LI Haojie, NIU Penghao, JIA Yifan

“…Then, data preprocessing was performed, including outlier removal, calculation of differences between adjacent data points, and merging data based on the sign of the differences. …”
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Rehabilitation and Motion Symmetry Analysis With a TACX Smart Cycling Trainer Using Computational Intelligence by Hana Charvatova, Daniel Martynek, Alexandra Molcanova, Ales Prochazka

“…The research objectives include analysis of motion patterns, evaluation of motion symmetry under varying loads, and examination of heart rate responses to load variations. Signal processing is conducted using advanced methods that include computational intelligence, digital signal processing, and artificial intelligence tools for data classification. …”
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Palmprint Recognition Using Bifurcation Line Direction Coding by Hongxia Wang, Xulei Cao

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Cross-device federated unsupervised learning for the detection of anomalies in single-lead electrocardiogram signals. by Maximilian Kapsecker, Stephan M Jonas

“…The model was integrated into a mobile application that supports ECG data recording, preprocessing into heartbeat segments, and participation in a federated learning pipeline as a client node. …”
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Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain by Ruchika Sharma, Sameena Naaz, Pankaj Vaidya

“…This paper proposes a modified AlexNet architecture for detecting diseases through images at an early stage and to increase the production rate by cultivating good quality crops. This model combines steps such as tomato leaf image data collection, image data preprocessing, and classification and detection of disease. …”
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An enhanced pivot-based neural machine translation for low-resource languages by Danang Arbian Sulistyo, Aji Prasetya Wibawa, Didik Dwi Prasetya, Fadhli Almuíini Ahda

“…Parallel text corpora were created by collecting and preprocessing data, thereafter, utilized to train and assess the NMT models. …”
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Securing and optimizing optical transmission in quantum wells using OAM and advanced modulation techniques by Muhammad Ahmad, Zhiping Wang, Ming Fang, Zhixiang Huang, Guoda Xie

“…Finally, the Fast Fourier Transform with a Fiber Optical Performance monitoring tool (FFT-FOPM) is proposed for efficient signal processing and comprehensive network monitoring. The simulation results show that the proposed system achieved a low bit error rate (BER) of (17.63%), network throughput of (0.96 Mbps), data integrity rate of (75%), signal quality of (0.3 dB), and blocking probability of (0.03%), which outperforms the state-of-the-art. …”
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A Review on Machine Learning Models in Injection Molding Machines by Senthil Kumaran Selvaraj, Aditya Raj, R. Rishikesh Mahadevan, Utkarsh Chadha, Velmurugan Paramasivam

“…Some problems include data division, collection, and preprocessing steps, such as considering the inputs, networks, and outputs, algorithms used, models utilized for testing and training, and performance criteria set during validation and verification. …”
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Implementation of the Support Vector Machine (SVM) Algorithm on Sentiment Analysis of Public Opinion on The Prohibition of the use of Syrupy Drugs for Kidney Health by Galih Purnomo, Rumini Rumini, Tri Susanto

“…The comments will be classified using the Support Vector Machine (SVM) method, and the most effective kernel among linear, sigmoid, polynomial, and RBF will be identified. Data was collected through web scraping with 5000 initial data, and after preprocessing, 4794 data were processed. …”
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Gender differences in L1 vertebral strength in adults 50+ using automated CT-based finite element analysis by Hsiang-Ho Chen, Chieh-Wei Wu, Yen Cheng, Mao-Chieh Su, Yu-Jhen Chen, Po-Liang Lai

“…This study aims to develop customized MATLAB programs to automate the creation of heterogeneous bone models, streamlining preprocessing to reduce time, computational costs, and minimize variability from manual processes. …”
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Nameplate Detection and Recognition of Smart Meter Communication Module Based on ResSE-SegNet by ZHAI Xiaohui, SUN Kai, ZHAO Jifu, SUN Yanling, XING Yu, GUO Kaixuan, WANG Haiying

“…The experimental results show that this method achieves a recall rate of 92.34%, a precision rate of 93.97%, and an F1-Score of 92.14%. …”
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Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model. by Hui Zhang, Weihua Zhang

“…For example, on the S&P 500 historical data set, our model achieved a precision rate of 93.84% and a recall rate of 95.75%, further verifying its effectiveness in predicting risk events. …”
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Measurement Techniques and Methods for the Pressure Coefficient of Viscosity of Polymer Melts by Yang Liao, Yeyuan Hu, Yunxiang Tan, Kosuke Ikeda, Ryoji Okabe, Ruifen Wu, Ryota Ozaki, Qingyan Xu

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A Non-Invasive Fetal QRS Complex Detection Method Based on a Multi-Feature Fusion Neural Network by Zhuya Huang, Junsheng Yu, Ying Shan, Xiangqing Wang

“…Firstly, a signal entropy data quality detection algorithm based on the blind source separation method is designed to select maternal ECG signals that meet the quality requirements from all channel ECG data, followed by data preprocessing operations such as denoising and normalization on the signals. …”
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Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility by Bafren K. Raoof, Ali Rabia, Usama Alameedy, Pshtiwan Shakor, Moses Karakouzian

“…The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. …”
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Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models by Ayub Mohammadi, Khalil Valizadeh Kamran, Sadra Karimzadeh, Himan Shahabi, Nadhir Al-Ansari

“…We used software of Sentinel application platform, Waikato Environment for Knowledge Analysis, ArcGIS, and Statistical Package for the Social Sciences for preprocessing, processing, and postprocessing of the data. …”
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Near-infrared spectroscopy analysis to predict urinary allantoin in dairy cows by Leonardo A.C. Ribeiro, Guilherme L. Menezes, Tiago Bresolin, Sebastian I. Arriola Apelo, Joao R.R. Dórea

“…The partial least squares regression model achieved an R2 of 0.55, a concordance correlation coefficient of 0.73, and a root mean squared error of prediction (RMSEP) of 3.63 mmol/L to predict allantoin concentration from the spectra data set without preprocessing. However, the use of the first derivative (FirstDev) as a preprocessing step reduced the RMSEP from 3.63 mmol/L to 3.25 mmol/L and increased the R2 from 0.55 to 0.62. …”
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Recognition of Eudiscoaster and Heliodiscoaster using SOM Neural Network by Raid AL-Nima

“…First: applying image processing techniques on the fossils picture for data acquisition. …”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…In this study, we present a technique that combines real-time runtime batch normalization and data augmentation for data preprocessing, along with n-grams and one-hot encoding for feature extraction of opcode sequence information from the bytecode. …”
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A method to modelling oil spill using combination of logistic regression and cellular automata by Yihan Zhang, Shanshan Li

“…This study proposes a logistic regression-integrated cellular automata (CA) model for oil spill simulation, addressing challenges in parameter determination of traditional CA models. The method involves data preprocessing (geospatial alignment, resampling, normalization), Monte Carlo sampling for training data, logistic regression-based weight assignment to impact factors, neighborhood function and stochastic term computation, and iterative oil spill simulation. …”
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