Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…Furthermore, the CFOPS-BSBEA technique has the potential to inspire further research in secure cloud computing environments, making the way for the development of more robust and efficient security measures.…”
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An Effective and Interpretable Sleep Stage Classification Approach Using Multi-Domain Electroencephalogram and Electrooculogram Features by Xin Xu, Bei Zhang, Tingting Xu, Junyi Tang

“…Recent research efforts on automated sleep staging have focused on complex deep learning architectures that have achieved modest improvements in classification accuracy but have limited real-world applicability due to the complexity of model training and deployment and a lack of interpretability. …”
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The Optimal Acoustic Measurement Point Selection for UHV Reactors in Substations Based on Equivalent Impedance and Information Entropy Theory by Yingwen Li, Zhen Wei, Huilian Liao, Lin Li, Peizhong Zhang, Jingyun Zhao

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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…In this vein, optimal conductor size selection and phase balancing are among the most common strategies for improving these indicators, which involves dealing with complex optimization problems. …”
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Principles of physical factor selection in the early postoperative period of breast cancer treatment: a randomized controlled study by Inna S. Evstigneeva

“…The study found that general magnetic therapy normalizes the microcirculation efficiency index and the bypass index, reducing congestion on the operated side, and improves the quality of life. …”
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Synthetic graphs for link prediction benchmarking by Alexey Vlaskin, Eduardo G Altmann

“…Predicting missing links in complex networks requires algorithms that are able to explore statistical regularities in the existing data. …”
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Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

“…Multi-principal element alloys (MPEAs), distinguished by their complex compositions and exceptional mechanical properties, pose significant challenges for conventional predictive approaches in mechanical property optimization. …”
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A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights by Anruo Shen, Jingnan Sun, Xiaogang Chen, Xiaorong Gao

“…However, most EEG-based machine learning diagnostic studies focus on boosting classification accuracy through complex algorithms and small, homogenous datasets. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. The proposed explainable artificial intelligence feature selection method was compared to conventional feature selection techniques, including mutual information, chi-square coefficient, maximal information coefficient, Fisher separation criterion and variance thresholding. …”
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Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…However, creating diversity, selecting genotypes, and studying different traits will help scientists in this direction. …”
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Balancing cleaner energy and geopolitical interests in the complex transition of the European electricity mix: from Fukushima to the Ukraine war by Marcio Cataldi, Nieves Espinosa, Sonia Jerez, Juan Pedro Montávez, Larissa Haringer Martins Da Silveira, Jairton Dupont, Marcos Alexandre Teixeira

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AutoML based workflow for design of experiments (DOE) selection and benchmarking data acquisition strategies with simulation models by Xukuan Xu, Donghui Li, Jinghou Bi, Michael Moeckel

“…Abstract Design of experiments (DOE) is an established method to allocate resources for efficient parameter space exploration. Model based active learning (AL) data sampling strategies have shown potential for further optimization. …”
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Optimization Method of Wind Turbine Locations in Complex Terrain Areas Using a Combination of Simulation and Analytical Models by Dinh Van Thin, Le Quang Sang, Nguyen Huu Duc

“…For areas with complex terrain, wind resource characteristics depend largely on terrain features, so the selection of turbine installation locations is very important. …”
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Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing by Balint Toth, Zsolt Szalay

“…By addressing the need for a structured and efficient scenario selection method, this work supports the advancement of systematic safety assurance for autonomous vehicles and provides a scalable solution for authorities and vehicle testing companies.…”
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PROBLEMS OF FORMATION OF FINANCIAL-INVESTMENT PROJECTION OF A BALANCED SCORECARD IN VALUE-BASED ENTERPRISES OF MINING-METALLURGICAL COMPLEX by S. Faizova, M. Ivanova, S. Sannikova, O. Varyanichenko

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Enhancing IDS for the IoMT based on advanced features selection and deep learning methods to increase the model trustworthiness. by Ahmed Muqdad Alnasrallah, Maheyzah Md Siraj, Hanan Ali Alrikabi

“…This study indicates that the proposed strategy decreases computational complexity and enhances IDS efficiency in resource-constrained IoMT environments.…”
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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…Then, the Memo Search Algorithm (MSA), a metaheuristic approach is proposed to efficiently reduce feature space. Through comprehensive comparisons with established algorithms such as the Artificial Bee Colony (ABC) and Gray Wolf Optimizer (GWO), MSA refined the selection, identifying 'elevation’ and 'distance to streams’ as optimal factors. …”
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Integrated feature selection-based stacking ensemble model using optimized hyperparameters to predict breast cancer with smart web application by Rajib Kumar Halder, Marzana Akter Lima, Mohammed Nasir Uddin, Md.Aminul Islam, Adri Saha

“…Early detection is paramount as it significantly improves survival rates and reduces the complexity and cost of treatment. Machine learning has revolutionized this field, providing more precise, efficient, and personalized diagnostic methods. …”
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Identifying the Challenges of the Processes of Introducing and Commercializing Domestic Medical Equipment to the Market by Shahnaz Seyedi Dolatabad, Hessam Zandhessami, Hamed Afshari, Shirin Jalalinia

“…Conclusion: The research results showed that the process faces major challenges such as complexity of implementation steps, time-consuming nature, high costs, lack of transparency, and lack of coordination between regulatory agencies. …”
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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…It has been specifically designed to efficiently process and analyze vast and complex datasets commonly encountered in the financial sector, showcasing adaptability to the dynamic nature of big data environments. …”
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