Digital Transformation in Aftersales and Warranty Management: A Review of Advanced Technologies in I4.0 by Vicente González-Prida, Carlos Parra Márquez, Pablo Viveros Gunckel, Fredy Kristjanpoller Rodríguez, Adolfo Crespo Márquez

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Sports data analysis of track and field athletes based on IID-OPK and NonIID-OPK algorithms by Xiaofeng Chen

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Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
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A New Paradigm in AC Drive Control: Data-Driven Control by Learning Through the High-Efficiency Data Set—Generalizations and Applications to a PMSM Drive Control System by Madalin Costin, Ion Bivol

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Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

“…The model performance was evaluated through five independent unseen tests with nested 5-fold cross-validation. The predictive power of each feature was assessed using a composite measure derived from individual algorithm estimates.ResultsThe model demonstrated a mean AUC-ROC of 0.75-0.76, with mean sensitivity of 0.77-0.81, precision (also referred to as Positive Predictive Value) of 0.77-0.79 and specificity of 0.63-0.66 across the criteria. …”
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Algoritmos Implementation of PID Control Algorithms and Fuzzy Logic based on robotics teaching with arduino applied to students by MILAGROS DEL CARMEN CASTAÑEDA BARBARAN

“… This research paper addresses the implementation of robotic control algorithms applied to the educational environment, with the objective of improving the teaching of robotics to students. …”
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Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge by Maximilian Zenk, Ujjwal Baid, Sarthak Pati, Akis Linardos, Brandon Edwards, Micah Sheller, Patrick Foley, Alejandro Aristizabal, David Zimmerer, Alexey Gruzdev, Jason Martin, Russell T. Shinohara, Annika Reinke, Fabian Isensee, Santhosh Parampottupadam, Kaushal Parekh, Ralf Floca, Hasan Kassem, Bhakti Baheti, Siddhesh Thakur, Verena Chung, Kaisar Kushibar, Karim Lekadir, Meirui Jiang, Youtan Yin, Hongzheng Yang, Quande Liu, Cheng Chen, Qi Dou, Pheng-Ann Heng, Xiaofan Zhang, Shaoting Zhang, Muhammad Irfan Khan, Mohammad Ayyaz Azeem, Mojtaba Jafaritadi, Esa Alhoniemi, Elina Kontio, Suleiman A. Khan, Leon Mächler, Ivan Ezhov, Florian Kofler, Suprosanna Shit, Johannes C. Paetzold, Timo Loehr, Benedikt Wiestler, Himashi Peiris, Kamlesh Pawar, Shenjun Zhong, Zhaolin Chen, Munawar Hayat, Gary Egan, Mehrtash Harandi, Ece Isik Polat, Gorkem Polat, Altan Kocyigit, Alptekin Temizel, Anup Tuladhar, Lakshay Tyagi, Raissa Souza, Nils D. Forkert, Pauline Mouches, Matthias Wilms, Vishruth Shambhat, Akansh Maurya, Shubham Subhas Danannavar, Rohit Kalla, Vikas Kumar Anand, Ganapathy Krishnamurthi, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Divya Reddy, Yudhajit Das, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph Maldjian, Gaurav Singh, Jianxun Ren, Wei Zhang, Ning An, Qingyu Hu, Youjia Zhang, Ying Zhou, Vasilis Siomos, Giacomo Tarroni, Jonathan Passerrat-Palmbach, Ambrish Rawat, Giulio Zizzo, Swanand Ravindra Kadhe, Jonathan P. Epperlein, Stefano Braghin, Yuan Wang, Renuga Kanagavelu, Qingsong Wei, Yechao Yang, Yong Liu, Krzysztof Kotowski, Szymon Adamski, Bartosz Machura, Wojciech Malara, Lukasz Zarudzki, Jakub Nalepa, Yaying Shi, Hongjian Gao, Salman Avestimehr, Yonghong Yan, Agus S. Akbar, Ekaterina Kondrateva, Hua Yang, Zhaopei Li, Hung-Yu Wu, Johannes Roth, Camillo Saueressig, Alexandre Milesi, Quoc D. Nguyen, Nathan J. Gruenhagen, Tsung-Ming Huang, Jun Ma, Har Shwinder H. Singh, Nai-Yu Pan, Dingwen Zhang, Ramy A. Zeineldin, Michal Futrega, Yading Yuan, Gian Marco Conte, Xue Feng, Quan D. Pham, Yong Xia, Zhifan Jiang, Huan Minh Luu, Mariia Dobko, Alexandre Carré, Bair Tuchinov, Hassan Mohy-ud-Din, Saruar Alam, Anup Singh, Nameeta Shah, Weichung Wang, Chiharu Sako, Michel Bilello, Satyam Ghodasara, Suyash Mohan, Christos Davatzikos, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Christopher Hess, John Mongan, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, Raymond Y. Huang, Ken Chang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Ker^kovský, Tereza Kopr^ivová, Marek Dostál, Václav Vybíhal, Marco C. Pinho, James Holcomb, Marie Metz, Rajan Jain, Matthew D. Lee, Yvonne W. Lui, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Rivka R. Colen, Aikaterini Kotrotsou, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Martin Bendszus, Wolfgang Wick, Abhishek Mahajan, Carmen Balaña, Jaume Capellades, Josep Puig, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Hassan F. Shaykh, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Pamela LaMontagne, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B. Chambless, Akshitkumar Mistry, Reid C. Thompson, Ashok Srinivasan, J. Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, John Garrett, Matthew Larson, Robert Jeraj, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Alexandre Xavier Falcão, Samuel B. Martins, Bernardo C. A. Teixeira, Flávia Sprenger, David Menotti, Diego R. Lucio, Simone P. Niclou, Olivier Keunen, Ann-Christin Hau, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Richard McKinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A. Velastin, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M. Buatti, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I. Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M. Kardamakis, Bing Luo, Laila M. Poisson, Ning Wen, Martin Vallières, Mahdi Ait Lhaj Loutfi, David Fortin, Martin Lepage, Fanny Morón, Jacob Mandel, Gaurav Shukla, Spencer Liem, Gregory S. Alexandre, Joseph Lombardo, Joshua D. Palmer, Adam E. Flanders, Adam P. Dicker, Godwin Ogbole, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu’aibu Hikima, Mayowa Soneye, Farouk Dako, Adeleye Dorcas, Derrick Murcia, Eric Fu, Rourke Haas, John A. Thompson, David Ryan Ormond, Stuart Currie, Kavi Fatania, Russell Frood, Amber L. Simpson, Jacob J. Peoples, Ricky Hu, Danielle Cutler, Fabio Y. Moraes, Anh Tran, Mohammad Hamghalam, Michael A. Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Lisa Cimino, Cynthia Price, Brian Bialecki, Sailaja Marella, Charles Apgar, Andras Jakab, Marc-André Weber, Errol Colak, Jens Kleesiek, John B. Freymann, Justin S. Kirby, Lena Maier-Hein, Jake Albrecht, Peter Mattson, Alexandros Karargyris, Prashant Shah, Bjoern Menze, Klaus Maier-Hein, Spyridon Bakas

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Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

“…The commonly used algorithm for prediction in ANN is Backpropagation, which yields high accuracy but tends to be slow during the training process and is prone to local minima. …”
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Severity Classification of Freezing of Gait Using Machine-Learning Algorithms: A Hidden State Model Approach by Aditi Site, Elena Simona Lohan, Jari Nurmi

“…We also trained an ensemble algorithm to model the prediction of severity levels marked by HMM model. …”
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Forecasting Wind Farm Production in the Short, Medium, and Long Terms Using Various Machine Learning Algorithms by Gökhan Ekinci, Harun Kemal Ozturk

“…The results indicate that Min-Max Scaling improved short-term predictions with KNN, while XGBoost and Random Forest provided more stable and accurate forecasts in medium- and long-term predictions. …”
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Enhancing flood susceptibility mapping in Meghna River basin by introducing ensemble Naive Bayes with stacking algorithms by Abu Reza Md. Towfiqul Islam, Md. Uzzal Mia, Nourin Akter Nova, Rabin Chakrabortty, Md. Sanjid Islam Khan, Bonosri Ghose, Subodh Chandra Pal, A. B. M. Mainul Bari, Edris Alam, Md Kamrul Islam, Mohammed Ali Alshehri, Hazem Ghassan Abdo, Romulus Costache

“…This article intends to assess flood susceptibility mapping in Meghna River basin (MRB) and identified flood susceptible regions using three benchmark models including random forest (RF), support vector machine (SVM) and bagging with Naïve Bayes (NB) stacking ensemble algorithms (e.g. RF-NB; SVM-NB and Bagging-NB). The flood sample was partitioned into a training set (70%), and a validation set (30%), and the capability of prediction of flood-influencing variables was quantified by the multi-collinearity test. …”
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Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting by Wensheng Dai, Jui-Yu Wu, Chi-Jie Lu

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Smart Tool-Related Faults Monitoring System Using Process Simulation-Based Machine Learning Algorithms by Arash Ebrahimi Araghizad, Faraz Tehranizadeh, Kemal Kilic, Erhan Budak

“…These findings have been supported by actual measurement data, with a notable accuracy rate of 93% in the predictions. Furthermore, the results indicate that process simulation-based machine learning algorithms will have a significant impact on the tools condition monitoring and the efficiency of manufacturing processes more generally. …”
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Assessing Volatility Behaviors of Cross-Currency Derivatives in India's Exchange Markets Using Machine Learning Algorithms by Aman Shreevastava, Bharat Kumar Meher, Virgil Popescu, Ramona Birau, Mritunjay Mahato

“…This paper studies the volatility of INR based cross country futures (USD, JPY and EUR) and performs forecasting using ML Algorithm and utilizes LSTM for prediction. The study proves to be a first of its kind study involving cross-country futures and is a beacon of hope for all future research on similar subjects. …”
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Identification and validation of NETs-related biomarkers in active tuberculosis through bioinformatics analysis and machine learning algorithms by Shengfang Xia, Qi An, Rui Lin, Yalan Tu, Zhu Chen, Dongmei Wang

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Forecasting Foreign Direct Investment Inflow to Egypt and Determinates: Using Machine Learning Algorithms and ARIMA Model by Mohamed F. Abd El-Aal, Ali Algarni, Aisha Fayomi, RAahayu Abdul Rahman, Khudir Alrashidi

“…This study aims to determine the primary determination of FDI inflow to Egypt using machine learning algorithms and the ARIMA model and get an accurate prediction of FDI inflow to Egypt during the current decade (2020–2030) and approved that the gradient boosting model is the most accurate algorithms. …”
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Construction of Empirical Models of Complex Oscillation Processes with Non-Multiple Frequencies Based on the Principles of Genetic Algorithms by Mykhailo Horbiychuk, Olha Bila, Nataliia Lazoriv

“…The resulting empirical model can be used to predict the water level depending on weather conditions.…”
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A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset by Rulyansyah Permata Putra, Amarudin Amarudin

“…The research methodology includes the collection of the NSL-KDD dataset, followed by data transformation, cleaning, normalization, and partitioning into training and testing sets. Each algorithm was trained using tuned parameters, and performance was evaluated using metrics such as accuracy, precision, recall, F1-score, and an analysis of training and prediction time. …”
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Combined Forecasting Schemes Based on Random Forest Regression and Meta-heuristic Algorithms for Maximum Dry Density by Huaxuan Lu

“…All the created schemes, particularly RFGJ—a hybrid of the RFR and the GJO algorithm—exhibited exceptional performance in predicting MDD values, attaining the top R² of 0.9966 and the least RMSE of 13.688.…”
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