Fast Ways to Detect Outliers by Emad Obaid Merza, Nashaat Jasim Mohammed

“…In this research, we aim to develop easy methods for detecting outliers in big data, as the problem that this research addresses is that many of the newly developed methods for detecting outliers suffer from computational complexity or are efficient when the sample size is small. …”
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Metal Complexes of Bispidine Derivatives: Achievements and Prospects for the Future by Altynay B. Kaldybayeva, Valentina K. Yu, Feyyaz Durap, Murat Aydemir, Khaidar S. Tassibekov

“…Multidentate bispidine ligands, including tetra-, penta-, hexa-, hepta-, and octadentate variants, exhibit strong coordination tendencies due to their intrinsic rigidity, significant reorganization potential, and ability to efficiently encapsulate metal ions. These structural attributes profoundly influence the thermodynamic stability, metal ion selectivity, redox behavior, and spin-state configuration of the resulting complexes. …”
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Cost optimization on example of hotel-restaurant complex enterprises by Volkovska I.V.

“…The author has developed the sequence of cost optimization on the example of enterprises of the hotel-restaurant complex, which helps to structure the process of cost management. …”
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Integrating Correlation-Based Feature Selection and Clustering for Improved Cardiovascular Disease Diagnosis by Agnieszka Wosiak, Danuta Zakrzewska

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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

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Modern Methods for Diagnosing Faults in Rotor Systems: A Comprehensive Review and Prospects for AI-Based Expert Systems by Oleksandr Roshchupkin, Ivan Pavlenko

“…Working conditions nowadays are characterized by intensive rotation speeds, complex structures, and dynamic loads, contributing to different mechanical faults. …”
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Econometric Modeling to Measure the Efficiency of Sharpe’s Ratio with Strong Autocorrelation Portfolios by Karime Chahuán-Jiménez, Rolando Rubilar-Torrealba, Hanns de la Fuente-Mella

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Differential Evolution with Autonomous Selection of Mutation Strategies and Control Parameters and Its Application by Zhenyu Wang, Zijian Cao, Zhiqiang Du, Haowen Jia, Binhui Han, Feng Tian, Fuxi Liu

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Selective electrocatalytic nitrate reduction to dinitrogen: Mechanisms, catalysts, and challenges by Jiayu Chen, Anni Wu, Yongfeng Xie, Yumin Zhang, Hu Zheng, Wei Teng

“…While extensive research has focused on ammonia production, selective N2 production remains challenging due to complex pathways, limitations in detection, and the difficulty of controlling reaction on the electrocatalysts. …”
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The analysis of landscape design and plant selection under deep learning by Lian Li, JiYon Lee

“…Abstract This paper explores the application of deep learning (DL) techniques in landscape design and plant selection, aiming to enhance design efficiency and quality through automated plant leaf image recognition (PLIR). …”
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A New Ritodrine Selective Electrode and its Pharmaceutical Application by Reda Ammar

“…A novel ritodrine hydrochloride ion-selective PVC membrane electrode based on ion-pair complex of ritodrine-tetra phenyl borate was prepared with di-n-butyl phosphate as a plasticizer. …”
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AIN-Based Action Selection Mechanism for Soccer Robot Systems by Yin-Tien Wang, Zhi-Jun You, Chia-Hsing Chen

“…This AIN-based action-select provides an efficient and robust algorithm for robot role selection. …”
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RSNet: Compact-Align Detection Head Embedded Lightweight Network for Small Object Detection in Remote Sensing by Qing Dong, Tianxin Han, Gang Wu, Baiyou Qiao, Lina Sun

“…Detecting small objects in high-resolution remote sensing images presents persistent challenges due to their limited pixel coverage, complex backgrounds, and dense spatial distribution. …”
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Self-trainable and adaptive sensor intelligence for selective data generation by Arghavan Rezvani, Wenjun Huang, Hanning Chen, Yang Ni, Mohsen Imani

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Data selection strategies for minimizing measurement time in materials characterization by Alexander Liehr, Kristina Dingel, Daniel Kottke, Sebastian Degener, David Meier, Bernhard Sick, Thomas Niendorf

“…Obviously, this kind of approach is extremely time-consuming and, eventually, not efficient. The present study highlights that specific selection strategies, taking into account the prevailing microstructure of the alloy in focus, can decrease counting times in X-ray energy dispersive diffraction experiments without any detrimental effect on data quality for the subsequent analysis. …”
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Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning by Łukasz Jeleń, Izabela Stankiewicz-Antosz, Maria Chosia, Michał Jeleń

“…The results demonstrate that optimized feature sets, paired with SVM classifiers, achieve classification performance comparable to those of CNNs while significantly reducing computational complexity. This finding underscores the potential of feature reduction techniques in creating efficient diagnostic frameworks. …”
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Quality Improvement in Critical Care: Selection and Development of Quality Indicators by Carla A. Chrusch, Claudio M. Martin, The Quality Improvement in Critical Care Project

“…Caring for critically ill patients is complex and resource intensive. An approach to monitor and compare the function of different intensive care units (ICUs) is needed to optimize outcomes for patients and the health system as a whole. …”
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Nonlocal flat optics for size-selective image processing and denoising by Sandeep Kumar Chamoli, Chunqi Jin, Yandong Fan, Mehdi Kiani, Heedong Goh, Chen Huang, Shuyu Guo, Yuntong Wang, Fei Zhu, Guohua Xing, Bo Li, Tian Bai, Andrea Alù, Wei Li

“…So far, the proposed devices have been focusing on canonical operations, such as differentiations to perform edge detection across all objects in a complex scene. Yet, undesired background noise and clutter can hinder such operations, requiring target selection with digital post-processing which inherently limits the overall accuracy, efficiency and speed. …”
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Investigation and selection of initial materials as possible sources for obtaining sorbents by I. A. Таgaev, S. U. Tursunova, L. S. Andriyko

“… The information about selection of initial materials based on bentonite, brown coal and technical soot for obtaining new sorbents is presented in this article. …”
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Limitations of XGBoost in Predicting Material Parameters for Complex Constitutive Models by Prates Pedro, Mitreiro Dário, Andrade-Campos António

“…These findings suggest that simply expanding the dataset or reducing dimensionality is insufficient to address the complexities of CPB′06. Instead, alternative approaches such as advanced feature selection, hybrid ML-physics-based models, or regularization techniques may be required to improve generalization. …”
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