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

“…Results obtained from electrical circuit models with varying complexity show that not all AL sampling strategies outperform conventional DOE strategies, depending on the available data volume, the complexity of the dataset, and data uncertainties. …”
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Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM by Pampa Sinha, Kaushik Paul, Asit Mohanty, IM Elzein, Chandra Sekhar Mishra, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Ahmed Althobaiti, Hany S Hussein, Thamer AH Alghamdi, Ahmed M Ewais

“…The proposed approach demonstrates superior frequency selectivity, adaptability, and computational efficiency, making it suitable for robust PQ disturbance identification and a wide range of signal-processing tasks.…”
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Transforming higher education with robotic process automation: enhancing efficiency, innovation, and student-centered learning by Vivek Bhardwaj, Mukesh Kumar

“…The findings underscore the transformative potential of RPA while highlighting the complexities of its integration into educational settings. …”
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Molecular mechanisms induced by phase modifiers used in hydrometallurgy: consequences on transfer efficiency and process safety by El Maangar, Asmae, Prévost, Sylvain, Dourdain, Sandrine, Zemb, Thomas

“…Finally, the consequences of these mechanisms on the extraction efficiency and selectivity are discussed.…”
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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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HLSK-CASMamba: hybrid large selective kernel and convolutional additive self-attention mamba for hyperspectral image classification by Xiaoqing Wan, Yupeng He, Feng Chen, Ziqi Sun, Dongtao Mo

“…Conversely, transformers, despite their efficacy in modeling spectral-spatial dependencies, introduce significant computational overhead due to their complexity. Mamba, leveraging the state space model (SSM), presents a compelling alternative that efficiently captures long-range dependencies in HSIs while ensuring computational efficiency with linear complexity. …”
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IT Outsourcing Vendor Selection for Digital Transformation Projects in Public Sector using Interval-Valued Spherical Fuzzy AHP by Murat Levent Demircan

“…Consequently, determining the selection criteria of the outsourcing companies that will take part in digital transformation projects in the public sector and the selection methodology to be applied is of great importance. …”
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A novel hybrid MCDM framework combining TOPSIS, PROMETHEE II, and VIKOR for peach drying method selection by Burak Gülmez

“…The selection of optimal drying technologies for peach processing presents a complex decision-making challenge due to multiple conflicting criteria. …”
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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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Embedded feature fusion for multi-label criteria selection via local search strategy and particle swarm optimization by Suhua Chen, Xu Fang, Feng Zhai, Li Wang, Lin Lv

“…Despite its importance, feature selection remains a complex issue without straightforward solutions, and various approaches using AI and evolutionary algorithms have been proposed to tackle it. …”
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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

“…To develop algorithms for selecting physical factors depending on the clinical and functional state of patients after radical surgical treatment of breast cancer (BC) in the early postoperative period. …”
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Sustainability in pharmaceutical analysis: greenness assessment of HPLC methods for paclitaxel by Ruchita Rajput, Sonal Desai

“…Abstract Sustainability in pharmaceutical analysis is gaining significant attention, driven by global initiatives to reduce environmental impact and enhance operational efficiency. This study evaluates the greenness of HPLC-based methods for paclitaxel quantification using seven assessment tools: NEMI, Complex NEMI, Analytical Eco-Scale, SPMS, ChlorTox, RGBfast, and BAGI. …”
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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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Optimization Design of the Transmission System of Small-size Shrub Brush Cutter based on MATLAB by Yang Chunmei, Guo Minghui, Ma Yan, Liu Qianjun, Yang Tie

“…By determining the objective function of the transmission system,selecting the independent design variables,determining the constraints,the mathematical model of transmission system is established.The analysis and optimization of the design variables,objective function and the boundary conditions are carried out,the complex method optimization program of MATLAB is written,and by using its powerful ability of optimization design to optimize the transmission system of the brush cutter. …”
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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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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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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks by Mateus Basso, João Paulo da Ponte Souza, Guilherme Furlan Chinelatto, Luis Augusto Antoniossi Mansini, Alexandre Campane Vidal

“…The use of ML enables the analysis of large datasets, the identification of complex patterns, and can save time and reduce costs compared to conventional approaches. …”
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