A Hybrid Proactive Caching System in Vehicular Networks Based on Contextual Multi-Armed Bandit Learning by Qiao Wang, David Grace

“…The two parallel prediction algorithms are based on Contextual Multi-armed bandit (cMAB) learning, called Dual-context cMAB and Single-context cMAB. …”
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A Multilevel and Hierarchical Approach for Multilabel Classification Model in SDGs Research by Berliana Sugiarti Putri, Lya Hulliyyatus Suadaa, Efri Diah Utami

“…This study aimed to implement and evaluate problem transformation methods and machine learning classification algorithms with a multilevel and hierarchical approach to categorize research publications into SDG levels. …”
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Machine Learning-Based Methodologies for Cyber-Attacks and Network Traffic Monitoring: A Review and Insights by Filippo Genuario, Giuseppe Santoro, Michele Giliberti, Stefania Bello, Elvira Zazzera, Donato Impedovo

“…Also, the ensembles are tested. The algorithms are evaluated on the KDD-99, NSL-KDD, UNSW-NB15, IoT-23, and UNB-CIC IoT 2023 datasets. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…Additionally, the immune and pathway scores of the training dataset samples were evaluated using the ESTIMATE, MCP-counter, and ssGSEA algorithms to establish the relationship between the hub genes and immune and pathways. …”
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Prognostic analysis of sepsis-induced myocardial injury patients using propensity score matching and doubly robust analysis with machine learning-based risk prediction model develo... by Pan Guo, Pan Guo, Li Xue, Fang Tao, Kuan Yang, YuXia Gao, Chongzhe Pei

“…This study aimed to evaluate the prognostic impact of SIMI and develop validated predictive models using advanced machine learning (ML) algorithms for identifying SIMI in critically ill sepsis patients.MethodsData were sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v3.0) database. …”
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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…Using demographic, clinical and laboratory data of the patients, six different machine learning algorithms (SVM, KNN, ANN, Decision Tree, Naive Bayes and Discriminant Analysis) were used for classification. …”
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PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning by Boris I. Evstatiev, Dimitar T. Trifonov, Katerina G. Gabrovska-Evstatieva, Nikolay P. Valov, Nicola P. Mihailov

“…One of these factors is the soiling of the PV surface, which could be observed in different forms, such as dust and bird droppings. In this study, visible spectrum data and machine learning algorithms were used for the identification of soiling. …”
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A Framework for Assessment of Perception Systems in Autonomous Vehicles by Hussein Hennaoui, Daniel Paluszczyszyn, Lipika Deka, Serhan Cosar

“…The results demonstrate that the sensors with the respective algorithms in the simulation are adapted to different lighting conditions, ensuring consistent sensory performance. …”
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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 preprocessing effectiveness was assessed using the Root Mean Square Error (RMSE) and tracking accuracy was evaluated through detection rate metrics. The results demonstrate a 25% to 30% improvement in detection accuracy and show that the pipeline can aid industry even with sparse object representation across different frames. …”
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Building trust for traffic flow forecasting components in intelligent transportation systems via interpretable ensemble learning by Jishun Ou, Jingyuan Li, Chen Wang, Yun Wang, Qinghui Nie

“…To evaluate the effectiveness of the framework, the developed tree-ensemble models and another three typical categories of baseline models, including statistical time series, shallow learning, and deep learning, were compared on three datasets collected from different types of roads (i.e., arterial, expressway, and freeway). …”
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Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…The results highlight a significant comparative analysis of prediction accuracy across different algorithms, emphasizing the importance of employing multiple receiver operating characteristic curves, areas under the curves, and a one-vs-rest classification approach when target features are represented as letter grades. …”
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Single target tracking in high-resolution satellite videos: a comprehensive review by Xin Huang, Ding Wang, Qiqi Zhu, Ying Zheng, Qingfeng Guan

“…To identify emerging research trends and opportunities, we classify established and emerging algorithms into three main categories and evaluate their performance on typical satellite videos. …”
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Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data by Munib Mesinovic, Peter Watkinson, Tingting Zhu

“…We also evaluated the framework for clinical risk analysis by comparing it to the standard APACHE IV system in active use. …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…Emphasizing flexibility and adaptability, the proposed LMS caters to various training levels, being able to accommodate the needs of learners across different domains. To identify the appropriate solution, a comparative analysis was conducted, evaluating various platforms based on functionality, intuitive presentation, and customization options. …”
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Solid breast tumors phantom emulating oxy and deoxyhemoglobin concentrations for near infrared imaging. by María Victoria Waks-Serra, Demián Augusto Vera, Nicolás Abel Carbone, Héctor Alfredo García, Pamela Alejandra Pardini, Juan Antonio Pomarico, Daniela Inés Iriarte

“…The use of phantoms has proven to be a very powerful way to evaluate different experimental approaches as well as to test possible diagnostics equipment. …”
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Analysis and Prediction of Wear in Interchangeable Milling Insert Tools Using Artificial Intelligence Techniques by Sonia Val, María Pilar Lambán, Javier Lucia, Jesús Royo

“…This study analyzes the flank wear of cutting tools in milling machines, with an emphasis on evaluating different approaches to predict their lifespan. …”
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Charting new territories: fuzzy systems in English language teaching and learning by Xiaomei Wen, Deng Pan

“…Expert systems based on fuzzy logic, suggested in this study, can handle teacher and student evaluations even when faced with imprecise information and uncertainty; this is necessary since academic performance is being indexed in multiple international databases using impact indices at different scales. …”
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Assessment of seasonal variations in the air quality index (2019–2022) in Al-Jahra city, Kuwait by Alsowaidan S., Al-Hurban A., Alsaber A.

“…An assessment of air quality indices was carried out by using different algorithms models, including random forest (RF), an artificial neural network (ANN), and extreme gradient boosting (XGBoost). …”
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Comparison of sequence- and structure-based antibody clustering approaches on simulated repertoire sequencing data. by Katharina Waury, Stefan Lelieveld, Sanne Abeln, Henk-Jan van den Ham

“…Here, we aim to explore the promise of structure-based clustering algorithms to replace or augment the standard sequence-based approach, specifically by identifying low-sequence identity groups. …”
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A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…In step 3, after filtering out non-grassland pixels, the performance of RF, SVM, and GTB classifiers was evaluated with combined S1 and S2 data to distinguish different grassland types. …”
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