Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…However, this task remains challenging due to variable high-altitude viewpoints, complex environmental interference, and limitations in algorithmic efficiency. …”
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USING THE GENERAL ELECTRIC / MCKINSEY MATRIX IN THE PROCESS OF SELECTING THE CENTRAL AND EAST EUROPEAN MARKETS by Nicolae Răzvan Decuseară

“…Due to the large number and diversity of markets that can choose, analyze of the market attractiveness and the selection the most interesting is a complex process. …”
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A Review on Pyroprocessing Techniques for Selected Wastes Used for Blended Cement Production Applications by Protus Nalobile, Jackson Muthengia Wachira, Joseph Karanja Thiong’o, Joseph Mwiti Marangu

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Deep Ensemble Learning for Application Traffic Classification Using Differential Model Selection Technique by Ui-Jun Baek, Yoon-Seong Jang, Ju-Sung Kim, Yang-Seo Choi, Myung-Sup Kim

“…However, achieving accuracy while maintaining time-efficiency and high generalization performance remains a challenge. …”
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Complex Path Planning for Manipulators Based on an Improved NSGA-III Algorithm With Hopfield Network by Xiaoxiang Sun, Jue Wang, Wei Wang

“…To enhance planning efficiency and convergence accuracy, this paper proposes an improved NSGA-III multi-objective optimization algorithm based on Hopfield neural network. …”
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PCMINN: A GPU-Accelerated Conditional Mutual Information-Based Feature Selection Method by Nikolaos Papaioannou, Georgios Myllis, Alkiviadis Tsimpiris, Stamatis Aggelopoulos, Vasiliki Vrana

“…The parallelized approach allows for the efficient processing of large datasets, making PCMINN a valuable tool for high-dimensional feature selection tasks. …”
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Fermatean Fuzzy CRADIS Approach Based on Triangular Divergence for Selecting Online Shopping Platform by Mijanur Rahaman Seikh, Arnab Mukherjee

“…By leveraging the CRADIS method alongside Fermatean fuzzy set theory, decision-makers can navigate the complex landscape of online shopping platforms with greater confidence and efficiency, ultimately leading to more satisfactory outcomes for both consumers and businessesalike.…”
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Federated Learning for Fall Detection With Multimodal Residual Fusion and Pareto-Optimized Client Selection by Bao-Quan Wang, Fan Yang, Yi Wang, Fan Zhao, Yun-Fei Han, Yu-Peng Ma

“…Finally, a Pareto-optimized client selection method is introduced to efficiently select reliable clients for global aggregation, ensuring both the stability and robustness of the global model. …”
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Patient-specific vascular models for optimal catheter selection: Two aneurysm embolization cases by Ryo Morita, MD, PhD, Daisuke Abo, MD, PhD, Takaaki Fujii, MD, Naoya Kinota, MD, Daisuke Kato, MD, Kouji Yamasaki, MD, Motoma Kanaya, MD, Taisuke Harada, MD, PhD, Osamu Sugita, Ph.D, Norio Kawamura, MD, PhD, Akinobu Taketomi, MD, PhD, Kohsuke Kudo, MD, PhD

“…Patient-specific vascular models enhance preoperative planning in interventional radiology, particularly in complex and anatomically challenging cases. This report presents two cases of complex aneurysm coil embolization in which three-dimensional, printed, patient-specific vascular hollow models were key to selecting optimal catheters, leading to successful interventions. …”
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Dynamic selection of optimal tunnel convergence prediction model for a probabilistic deformation prediction by Peng ZENG, Zhiqiang ZHANG, Tianbin LI, Hao Tang, Zulong YAN, Lubo MENG

“…Objective In high geostress or complex geological conditions, tunnel convergence frequently exceeds the threshold, resulting in damage to support structures and, in extreme cases, tunnel collapse. …”
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An MILP Model for Optimizing Quality Inspection Allocation with Technology Selection and Variable Sampling Rates by Michele Ronchi, Cristian Cafarella, Matteo Gabellini, Alberto Regattieri, Mauro Gamberi

“…Quality inspection is critical for ensuring efficiency and compliance in assembly lines. The increasing adoption of AI-driven technologies, such as machine vision systems, offers significant potential to enhance detection performance and reduce inspection costs. …”
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Selection and Application of the Data Transfer Operating Protocol Software Architecture for the Software-Defined Radio by Oleg V. Vorobyov, Alexey I. Rybakov

“…The study examined the corrective ability of codes in the case of a supplementary Gaussian channel with binary phase modulation (OFDM-modulation, 2PSK and 4PSK absolute phase manipulation) in the selection of an energy-efficient approach to the design of ionospheric radio communication system. …”
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Investigation of printing turn angle effects on structural deformation and stress in selective laser melting by Ruqing Bai, Shengbo Shi, Jingzhe Wang, Jun Luo, Huayan Pu, Wenhan Lyu, Hakim Naceur, Daniel Coutellier, Li Wang, Yangkun Du

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Selective Extraction of Zirconium from Sulfuric Acid Solutions at High Concentration with Trioctylamine (TOA) by Shuo Tian, Jing Song, Hongqian Sun, Congcong Zhao, Zhiyu Zhang, Mingming Han, Tao Qi

“…The current extraction methods have defects, such as low efficiency at high metal concentration. In this article, a zirconium (Zr)/hafnium (Hf) solvent extractive separation from sulfuric acid solutions using trioctylamine (TOA) as the extractant was researched at room temperature. …”
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Selective Separation of Scandium in Acidic Water Using Carboxyl Functionalized Covalent Phosphonitrile Polymers by Yu BAI, Ayinuer WUSHUER, Lei OUYANG, Lijin HUANG, Qin SHUAI

“…Considering that acid treatment is often required when processing raw materials such as Sc containing tailings, it is crucial to prepare adsorbents that can efficiently and selectively recover Sc(III) in acidic media.　　…”
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Complex Approach to the Conversion of Existing Refrigeration Systems to A2L Group Refrigerants by Serhii M. Molskyi, Oleksandr S. Molskyi, Anna L. Vorontsova

Assessing data and sample complexity in unmanned aerial vehicle imagery for agricultural pattern classification by Linara Arslanova, Sören Hese, Marcel Fölsch, Friedemann Scheibler, Christiane Schmullius

“…The study investigates the data and sample complexity required to develop an effective machine/deep learning (ML/DL) model, using techniques such as the Jeffries-Matusita Distance for assessment of class separability and feature importance ranking for feature and layer selection, semivariogram analysis for determining minimum sample patch sizes.The results demonstrate distinct classification capabilities based on spectral information in differentiating between sub-classes such as weed infestation, bare soil, disturbed canopy areas, and undisturbed canopy areas. …”
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An improved Red-billed blue magpie feature selection algorithm for medical data processing. by Chenyi Zhu, Zhiyi Wang, Yinan Peng, Wenjun Xiao

“…Experiments demonstrate that IRBMO exhibits high efficiency, generality and excellent generalization ability in feature selection tasks. …”
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Improved Low-Complexity, Pilot-Based Channel Estimation for Large Intelligent Surface Systems by Ali Gashtasbi, Mário Marques da Silva, Rui Dinis

“…In Large Intelligent Surface (LIS) systems, achieving accurate channel estimation is essential for enhancing communication quality and system efficiency. The main focus of this study is on using the Least Squares (LS) method to estimate pilot-based channels. …”
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Genomic signal selection analysis reveals genes related to the lambing trait of Hotan sheep by XinKun Wang, Wei Li, QiaoYan Huang, HuiPing Sun, LeXiao Zhu, RuoHuai Gu, Feng Xing

“…Objective Lambing in ewes is a complex and crucial aspect of sheep production that directly influences economic viability and production efficiency. …”
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