Examining Nasdaq Market Data and Presenting an Optimized Model by Extreme Gradient Boosting Regression and Artificial Bee Colony by Ali Ahmadpour

“…The study introduces an Extreme Gradient Boosting Regression (XGBR) model optimized with three distinct metaheuristic algorithms: Battle Royal Optimization (BRO), Moth Flame Optimization (MFO), and Artificial Bee Colony (ABC). …”
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Energy Efficiency for 5G and Beyond 5G: Potential, Limitations, and Future Directions by Adrian Ichimescu, Nirvana Popescu, Eduard C. Popovici, Antonela Toma

“…Reinforcement learning, heuristic algorithms, genetic algorithms, Markov Decision Processes, and the hybridization of various standard algorithms inherent to 5G and 5G NR represent a subset of the available solutions that shall undergo scrutiny. …”
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Real-Time Integration of Optical Coherence Tomography Thickness Map Overlays for Enhanced Visualization in Epiretinal Membrane Surgery: A Pilot Study by Ferhat Turgut, Keisuke Ueda, Amr Saad, Tahm Spitznagel, Luca von Felten, Takashi Matsumoto, Rui Santos, Marc D. de Smet, Zoltán Zsolt Nagy, Matthias D. Becker, Gábor Márk Somfai

“…Subsequently, for consecutive frames, feature point extraction (the Shi–Tomasi method) and optical flow computation (the Lucas–Kanade algorithm) were used to calculate frame-by-frame transformations, which were applied to the OCT image to maintain alignment in near real time. (3) Results: The method achieved a 92.7% success rate in optical flow detection and maintained an average processing speed of 7.56 frames per second (FPS), demonstrating the feasibility of near real-time application. (4) Conclusions: The developed approach facilitates enhanced intraoperative visualization, providing surgeons with easier retinal structure identification which results in more comprehensive data-driven decisions. …”
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Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks by Ihor Blinov, Virginijus Radziukynas, Pavlo Shymaniuk, Artur Dyczko, Kinga Stecuła, Viktoriia Sychova, Volodymyr Miroshnyk, Roman Dychkovskyi

“…Given the presence of anomalies and missing values in the operational data, a two-stage preprocessing algorithm incorporating DBSCAN clustering was applied for data cleansing and imputation. …”
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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

“…Once the model fine-tunes the eGFR estimations, it feeds them into various algorithms for CKD stage classification, including Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). …”
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Factors affecting refractoriness or recurrence in diffuse large B-cell lymphoma: development and validation of a novel predictive nomogram by Yiwei Guo, Jie Lian, Yao Chen, Lina Quan, Xiuchen Guo, Jingbo Zhang, Zhiqiang Liu, Aichun Liu

“…These variables were also prioritized using a random forest algorithm. The developed nomogram was evaluated with the receiver-operator characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) for its clinical utility.Results Univariable analysis pinpointed several factors significantly associated with refractoriness/recurrence, including pathological subtype, lactate dehydrogenase (LDH), International Prognostic Index (IPI), treatment, absolute lymphocyte count (ALC), lymphocyte/monocyte ratio (LMR), and prognostic nutritional index (PNI). …”
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RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation by Marco La Salandra, Rosa Colacicco, Simone Panza, Giovanni Fumai, Pierfrancesco Dellino, Domenico Capolongo

“…This self-contained, edge-computing module integrates custom hardware with real-time machine learning and optical flow algorithms, enabling onboard water segmentation and river surface velocity estimation. …”
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Fuzzy Logic-Based Performance Enhancement of FSO Systems Under Adverse Weather Conditions by Hassan Yousif Ahmed, Medien Zeghid, Akhtar Nawaz Khan, Somia A. Abd El-Mottaleb

“…The FLC module operates through an algorithm comprising eight well-defined steps, ensuring robust and adaptive control of the BER. …”
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Ranking polycystic ovarian syndrome (PCOS) drugs using degree-based indices in QSPR models and CRITIC-driven MCDM methods by Muhammad Waheed Rasheed, Abid Mahboob, Laiba Amin, Aysha Hussain

“…We rate these medications using three different multi-criteria decision-making (MCDM) algorithms: CRITIC, CoCoSo, and MABAC. …”
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BIM and AI Integration for Dynamic Schedule Management: A Practical Framework and Case Study by Heap-Yih Chong, Xinyi Yang, Cheng Siew Goh, Yan Luo

“…The framework comprises three layers: a data layer for collecting BIM and real-time site data, an analysis layer powered by AI algorithms for predictive analytics and optimization, and an application layer for visualizing progress and supporting decision-making. …”
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Artificial Intelligence-Based Prediction Model for Maritime Vessel Type Identification by Hrvoje Karna, Maja Braović, Anita Gudelj, Kristian Buličić

“…The presented model is therefore a hybrid approach that uses the Inception v3 deep learning model for the purpose of image vectorization and a combination of SVM, kNN, logistic regression, Naïve Bayes, neural network, and decision tree algorithms for final image classification. …”
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Machine learning evidence towards eradication of malaria burden: A scoping review by Idara JAMES, Veronica OSUBOR

“…This paper presents a scoping review covering the years 2018 to 2024, utilizing the PRISMA-ScR protocol, with articles retrieved from three scholarly databases: Science Direct (9%), PubMed (41%), and Google Scholar (50%). …”
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Reinforcement Q-Learning-Based Adaptive Encryption Model for Cyberthreat Mitigation in Wireless Sensor Networks by Sreeja Balachandran Nair Premakumari, Gopikrishnan Sundaram, Marco Rivera, Patrick Wheeler, Ricardo E. Pérez Guzmán

“…A Hybrid Policy Derivation Algorithm is introduced to balance encryption complexity and computational overhead by dynamically switching between these learning models. …”
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Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Pro... by Zixiang Ye, Zhangyu Lin, Enmin Xie, Chenxi Song, Rui Zhang, Hao-Yu Wang, Shanshan Shi, Lei Feng, Kefei Dou

“…Model performance was compared using multiple parameters, and the optimal algorithm was selected. Model interpretability was facilitated by Shapley Additive Explanations (SHAP), identifying the top 6 coronary angiographic features with the highest SHAP values. …”
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Optimizing Multi-Tier Scheduling and Secure Routing in Edge-Assisted Software-Defined Wireless Sensor Network Environment Using Moving Target Defense and AI Techniques by As’ad Mahmoud As’ad Alnaser, Said S. Saloum, Ahmed A. M. Sharadqh, Hazem (Moh’d Said) Hatamleh

“…The proposed SORP includes the Alibaba and Forty Thieves (AFT) and Multi Criteria Decision Making (MCDM) algorithms for selecting and ranking the optimal routes. …”
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Significance of Immune-Related Genes in the Diagnosis and Classification of Intervertebral Disc Degeneration by Bo Wu, Xinzhou Huang, Mu Zhang, Wei Chu

“…Based on the selected significant IRGs, a consensus clustering approach was used to differentiate disc degeneration patients into two immune patterns (immune cluster A and B). The PCA algorithm was constructed to compute immune scores for every sample, to quantify immune patterns. …”
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Application of Gaussian Mixture Model to Solve Inter-Symbol Interference in PAM8 Underwater Visible Light System Communication by Xingbang Wu, Fangchen Hu, Peng Zou, Nan Chi

“…When the forward error correction (FEC) threshold is met, the Q factor of Gaussian mixture models(GMM) that join three adjacent symbols is 1.19 dB greater than without the GMM clustering algorithm. …”
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Logical-semantic knowledge model for the knowledge base of a lecturer by Serhii Dotsenko, Olga Banit, Dmytro Nor, Olga Morozova

“…This paper proposes an architecture for a three-factor graphical logical-semantic knowledge representation model, which defines an algorithm to form the corresponding knowledge base. …”
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Comparative performance of twelve machine learning models in predicting COVID-19 mortality risk in children: a population-based retrospective cohort study in Brazil by Adriano Lages dos Santos, Maria Christina L. Oliveira, Enrico A. Colosimo, Robert H. Mak, Clara C. Pinhati, Stella C. Gallante, Hercílio Martelli-Júnior, Ana Cristina Simões e Silva, Eduardo A. Oliveira

“…To create subsets for training and testing the machine learning (ML) models, we divided the primary dataset into three parts. Using these subsets, we developed and trained 12 ML algorithms to predict the outcomes. …”
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Development of a justification process for selecting alternative risk reduction measures by Pavlo Saik, Vitalii Tsopa, Olena Yavorska, Serhii Cheberiachko, Mariia Brezitska, Andrii Yavorskyi, Vasyl Lozynskyi, Vasyl Lozynskyi

“…An eleven-step risk management process was designed to determine alternative preventive measures, characterized by feedback loops that enable the selection of optimal risk reduction strategies.ResultsThis study presents algorithms for solving three types of decision-making problems regarding the selection of combinations of preventive measures from a defined set of alternatives. …”
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