Gamified Engagement for Data Crowdsourcing and AI Literacy: An Investigation in Affective Communication Through Speech Emotion Recognition by Eleni Siamtanidou, Lazaros Vrysis, Nikolaos Vryzas, Charalampos A. Dimoulas

“…Additionally, these approaches offer significant educational benefits, providing users with knowledge about emotional speech and artificial intelligence (AI) mechanisms while promoting digital skills. …”
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A Data-Driven Approach for Energy Consumption Modeling and Optimization of Welding Robot Systems by Minling Pan, Bingqi Jia, Lei Zhang, Haihong Pan, Lin Chen

“…To solve the optimization problem, an improved whale optimization algorithm (IWOA) was employed. Experimental validations with a welding robot demonstrate that the proposed method not only accurately predicted EC with a MAPE of 2.66% but also reduced the robot system’s EC by 6.72%, outperforming the traditional method focused solely on joint motor EC, which achieved a 4.08% reduction. …”
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Harnessing Machine Learning for Intelligent Networking in 5G Technology and Beyond: Advancements, Applications and Challenges by Kristi Dulaj, Abdulraqeb Alhammadi, Ibraheem Shayea, Ayman A. El-Saleh, Mohammad Alnakhli

“…This research investigates ML approaches in 5G networks for adaptive spectrum usage, quality of service (QoS) management, predictive maintenance, and network optimization. By leveraging ML algorithms, 5G networks can forecast user behavior, allocate resources optimally, and dynamically adjust to changing conditions, enhancing performance and dependability. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management by Thein Oak Kyaw Zaw, Kalaiarasi Sonai Muthu Anbananthen, Saravanan Muthaiyah, Baarathi Balasubramaniam, Suraya Mohammad, Yunus Yusoff, Khairul Shafee Kalid

“…The framework leverages enterprise architecture principles to integrate learning algorithms, image detection, and systematic plantation mapping within a structured approach that enhances data organization, rust severity visualization, and predictive analysis. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Machine learning models were developed to classify suspicious web domains and predict their vulnerability to XSS attacks. Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Simulation of Quantum Dynamics Based on the Quantum Stochastic Differential Equation by Ming Li

“…The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. …”
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Diurnal distribution of phytoplankton in large shallow lakes based on time series clustering by Yanhong Chen, Haibin Cai, Yiqing Gong, Kun Lu, Jingqiao Mao, Weiyu Chen, Kang Wang, Huan Gao, Mingming Tian

“…This study demonstrates the potential of employing unsupervised clustering algorithms for identifying the diurnal dynamics of the phytoplankton distribution under complex influences, which can aid in optimizing the management and monitoring of shallow lakes.…”
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A Comprehensive Overview of the Development and Research of Energy Savings of Electric Wheel Loader by Xiaotao Fei, Zuo Cheng, Shaw Voon Wong, Muhammad Amin Azman, Dawei Wang, Xiuxian Zhang, Qiuchen Shao, Qingqiu Lin

“…The analysis reveals that integrating optimal control strategies with machine learning algorithms—such as model predictive control (MPC)—is a critical pathway to achieving energy-efficient and assisted driving in next-generation EWLs. …”
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Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…Radiomics, an emerging field, focuses on extracting high-dimensional quantitative features from medical imaging data and utilizing them to construct predictive models for disease diagnosis, prognosis, and treatment evaluation. …”
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Combination of Remote Sensing and Artificial Intelligence in Fruit Growing: Progress, Challenges, and Potential Applications by Danielle Elis Garcia Furuya, Édson Luis Bolfe, Taya Cristo Parreiras, Jayme Garcia Arnal Barbedo, Thiago Teixeira Santos, Luciano Gebler

“…The analysis included the use of remote sensing (orbital and proximal) imagery and ML/DL algorithms to map crop areas, detect diseases, and monitor crop development, among other analyses. …”
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Artificial intelligence-driven modeling of biodiesel production from fats, oils, and grease (FOG) with process optimization via particle swarm optimization by Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau

“…A ML model evaluation, using various algorithms, identify XGBoost, Extra Trees, Gradient Boosting, LGBM, and Random Forest demonstrate the best performer for predicting process parameters, achieving an R2 value of nearly to 1. …”
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Determining of the laser heat flux for three-dimensional conduction model by the sequential method by Nguyen Nhat Phi Long, Son Hoai Nguyen, Nguyen Quan

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Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). …”
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The relationship between epigenetic biomarkers and the risk of diabetes and cancer: a machine learning modeling approach by Shiqi Zhang, Shiqi Zhang, Jianan Jin, Benfeng Xu, Qi Zheng, Haibo Mou

“…Nine machine learning algorithms were used to build models: AdaBoost, GBM, KNN, lightGBM, MLP, RF, SVM, XGBoost, and logistics. …”
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Engineering Synthetic Microbial Communities: Diversity and Applications in Soil for Plant Resilience by Arneeb Tariq, Shengzhi Guo, Fozia Farhat, Xihui Shen

“…Artificial intelligence-driven models can predict complex microbial interactions, while machine learning algorithms can analyze vast datasets to identify key microbial taxa and their functions. …”
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Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities by Hanyue Xu, Kah Phooi Seng, Li-Minn Ang, Wei Wang, Jeremy Smith

“…The framework’s efficacy is validated through predictive modeling of autonomous vehicle passenger demand using real-world IoT data. …”
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Applications of fault-tolerant control system in the design of wind turbine generation systems: A comprehensive review and future prospects by Arslan Ahmed Amin, Muhammad Irfan, Turki Alsuwian, Saifur Rahman, Ansa Mubarak, Saba Waseem

“…The review also discusses the relevant research gaps and future works, such as using computational algorithms to develop novel material and implementing the utilization of digital twins to improve fault management.…”
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Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0 by Mohsin Ali, Abdul Razaque, Joon Yoo, Uskenbayeva Raissa Kabievna, Aiman Moldagulova, Satybaldiyeva Ryskhan, Kalpeyeva Zhuldyz, Aizhan Kassymova

“…On the other hand, the capabilities of AI-driven credit assessment algorithms enable more precise, effective, and customized credit choices that are specifically tailored to meet the unique financial profiles of manufacturers and importers. …”
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