Hybrid-CID: Securing IoT with Mongoose Optimization by S. Merlin Sheeba, R. S. Shaji

“…Initially, the incoming data are standardized by removing the irrelevant information through preprocessing to ensure the performance of detection models. …”
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Analisis Kinerja Model Deteksi Objek Yolo, Ssd, dan Faster R-Cnn pada Citra Penglihatan Malam untuk Pengenalan Tindak Kejahatan by Hendriyawan Achmad, Arif Pramudwiatmoko, Muhammad Satrio Gumilang, Bahrul Al Karim, Hadi Wiyono

“…The dataset utilized for this investigation comprises 1,006 photographic images obtained from various klitih crime occurrences. The data processing procedures encompassed multiple phases, commencing with preprocessing wherein all images were standardized to dimensions of 640x640 pixels. …”
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A comprehensive deep learning approach to improve enchondroma detection on X-ray images by Ayhan Aydin, Caner Ozcan, Safak Aydın Simsek, Ferhat Say

“…This study aimed to identify and present cases of bone tissue enchondromas to field specialists as preliminary data. In this study, authentic X-ray radiographs of patients were obtained following ethical approval and subjected to preprocessing. …”
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Seal Pipeline: Enhancing Dynamic Object Detection and Tracking for Autonomous Unmanned Surface Vehicles in Maritime Environments by Mohamed Ahmed, Bader Rasheed, Hadi Salloum, Mostafa Hegazy, Mohammad Reza Bahrami, Mikhail Chuchkalov

“…The approach begins with an innovative preprocessing stage that integrates data from the Inertial Measurement Unit (IMU) with LiDAR sensors to correct tilt-induced distortions in LiDAR point cloud data and reduce ripple effects around objects. …”
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Fault Diagnosis for Compressor Liquid Floodback based on PCA-Clustering by Zhou Zhenxin, Li Shaobin, Tan Zehan, Chen Huanxin, Wang Jiangyu, Liu Jiangyan, Guo Yabin, Sun Shaobo

“…First, data quality was improved by data preprocessing; secondly, the principal component analysis (PCA) method was employed to obtain the new dimensional variable data; finally, the new principal variables were clustered to get the classification label of liquid refrigerant floodback fault data. …”
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A multi-dimensional student performance prediction model (MSPP): An advanced framework for accurate academic classification and analysis by V. Balachandar, K. Venkatesh

“…The model also helps to bring down the False Positive Rate (FPR) substantially at a 0.15 level, which ensures more reliable predictions for student classification. • The model of the MSPP includes contextual information and multi-layered analysis in order to improve prediction accuracy, placing a sound basis for predicting students in different performance categories such as distinction, pass, fail or withdrawn. • Our approach is obviously to generalize and extract those sparse, heterogeneous academic data in the form of structured training record using domain specific preprocessing integrating with multi-class classification mechanisms that improves on precision-recall across multiple categories.…”
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Non-Intrusive Monitoring and Detection of Mobility Loss in Older Adults Using Binary Sensors by Ioan Susnea, Emilia Pecheanu, Adina Cocu, Adrian Istrate, Catalin Anghel, Paul Iacobescu

“…After data preprocessing—including filtering irrelevant sensor events and aggregation into behaviorally meaningful places (BMPs)—a time series forecasting model (Prophet) was used to predict normal mobility patterns. …”
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Implementasi Metode Longest Common Subsequences untuk Perbaikan Kata pada Kasus Analisis Sentimen Opini Pembelajaran Daring di Media Sosial Twitter by Alfisyar Jefry Pranata, Yuita Arum Sari, Edy Santoso

“…This opinion will be used in this research and will be processed first in the stage preprocessing. The method used in this research is Longest Common Subsequences (LCS) and Support Vector Machine (SVM) with 500 data divided into 250 data labeled positive and 250 data labeled negative. …”
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Customer Attrition Detection Using the LGBM Model by Huang Jie

“…To select the most suitable model for accurately detecting customer churn, this study performs preprocessing, including data cleaning, feature engineering, and feature selection. …”
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Investigation of the Kinetics of Heat and Moisture Exchange during Heat Treatment and Drying of Thin Wet Thermal Insulation Materials by A. I. Ol’shanskii, A. N. Golubev

“…The techniques of processing experimental data by zonal methods of A.V. …”
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2- D Slice of Tri- coherency Coefficient Spectrum in the Application of Fault Diagnosis of Marine Gear by Geng Wenfei, Mei Erzhao, Wu Wenbing

“…In order to solve the problem of fault diagnosis of marine gear,a method of comparing 2- D slice of tri- coherency coefficients figure under different frequency of vibration is proposed. Through the sampling data of vibration of marine gear,the tri- coherency function deal with is carried out after preprocessing.The 2- D slice of tri- coherency coefficients figures of data of working vibration of marine gear system are compared under different frequencies,and the result is different obviously. …”
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Optimization of Management Mode of Small- and Medium-Sized Enterprises Based on Decision Tree Model by Yuzhu Diao, Qing Zhang

“…After theoretical analysis, C4.5 algorithm is chosen to analyze the performance appraisal results, and the decision tree for performance appraisal is generated by collecting data, data preprocessing, calculating information gain rate, determining splitting attributes, and postpruning. …”
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Analisis Perbandingan Model Bert Dan Xlnet Untuk Klasifikasi Tweet Bully Pada Twitter by Teuku Radillah, Okta Veza, Sarjon Defit

“…Metodologi penelitian ini melibatkan pengumpulan dataset tweet yang telah dilabeli sebagai bullying atau non-bullying. Proses preprocessing teks dilakukan untuk membersihkan dan menyiapkan data sebelum digunakan dalam pelatihan model. …”
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Spatial evaluation of methane emissions in the communities of Warints and Yawi, Ecuador by Sandra López, Juan Haro, Carla Haro, William Carrillo, Justo Moises Narvaez Brito, Burkhanov Aktam Usmanovich, Ulugbek Tulakov, Tulovov Erkinjon, Mullabayev Baxtiyarjon, Mansurov Zuxriddin Xalilillayevich

“…The methodological process was non-experimental, with a descriptive–longitudinal design; 3 satellite images were taken from the OLI and TIRS 8 sensor from the virtual repository (USGS Earth Explorer), years 2013, 2016, and 2020; ArcGIS and ENVI were used during preprocessing and processing: Normalized Difference Vegetation Index (NDVI), emissivity, surface temperature, and methane emissions were determined through the empirical model based on temperatures. …”
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An optimized stacking-based TinyML model for attack detection in IoT networks. by Anshika Sharma, Shalli Rani, Mohammad Shabaz

“…The experiments have been conducted using the publicly available ToN-IoT dataset, comprising a total of 461,008 labeled instances with 10 types of attacks categories. Some amount of data preprocessing has been done applying methods such as label encoding, feature selection, and data standardization. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…This study aims to develop a patient anxiety level classification model in the ED using the Support Vector Machine (SVM) algorithm with the application of the Synthetic Minority Oversampling Technique (SMOTE) to address the class imbalance issue. The data used consists of 734 patient samples divided into 80% training data and 20% testing data, including physiological parameters such as systolic and diastolic blood pressure, respiratory rate, heart rate, and demographic data such as age and gender. …”
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Exploring the Effectiveness of Machine Learning and Deep Learning Techniques for EEG Signal Classification in Neurological Disorders by Souhaila Khalfallah, William Puech, Mehdi Tlija, Kais Bouallegue

“…We present a detailed workflow that begins with EEG data acquisition using a headset, followed by data preprocessing with Finite Impulse Response (FIR) filters and Independent Component Analysis (ICA) to eliminate noise and artifacts. …”
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Application of Machine Learning Techniques for Bearing Fault Diagnosis by Sarra Eddai, Nabih Feki, Ahmed Ghorbel, Abdelkhalak El Hami, Mohamed Haddar

“…Notably, the SVM algorithm demonstrates exceptional performance, attaining a 99.2% accuracy rate in inner-race fault identification. This investigation provides a comprehensive analysis of the Case Western Reserve University (CWRU) dataset, data preprocessing procedures, feature extraction techniques, and machine learning algorithms utilized for fault detection. …”
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Federated Learning-Assisted Coati Deep Learning-Based Model for Intrusion Detection in MANET by S. Faizal Mukthar Hussain, S. M. H. Sithi Shameem Fathima

“…The proposed HIDE-MAN framework initiates by preprocessing malicious data packets through data cleaning and data transformation resulting in the creation of high-dimensional vectors. …”
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Analysis of E-Commerce Marketing Strategy Based on Xgboost Algorithm by Hong Chen, Wei Wan

“…After data cleaning and preprocessing, XGboost algorithm is used to predict whether the customer will process the credit card. …”
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