Investigation of Personalized Visual Stimuli via Checkerboard Patterns Using Flickering Circles for SSVEP-Based BCI System by Nannaphat Siribunyaphat, Natjamee Tohkhwan, Yunyong Punsawad

“…Commands classification was carried out using a proposed decision rule–based algorithm. The results were compared with those of a conventional checkerboard pattern with flickering squares. …”
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Blended Ensemble Learning for Robust Normal Behavior Modeling of Wind Turbines by Jianghao Zhu, Tingting Pei, Le Su, Bin Lan, Wei Chen

“…Our mixed ensemble approach, synthesizing LightGBM, random forest, and decision tree algorithms, demonstrated exceptional performance across diverse operational conditions, achieving R² values of 0.9995 in primary testing. …”
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Swarm intelligence based classification rule induction (CRI) framework for qualitative and quantitative approach: An application of bankruptcy prediction and credit risk analysis by J. Uthayakumar, T. Vengattaraman, P. Dhavachelvan

“…In this paper, a unified framework for qualitative and quantitative bankruptcy analysis using Ant Colony Optimization (ACO) based ant-miner algorithm is proposed. Three different natured datasets are used to present a trustworthy result. …”
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The use of ridge regression for estimating the severity of acute pancreatitis by D. V. Cherdantsev, A. V. Stroev, E. S. Mangalova, N. V. Kononova, O. V. Chubarova

“…The classifier of three degrees of acute pancreatitis severity was developed. …”
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Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System by M. Y. Shams, M. R. Darwesh, Roheet Bhatnagar, N. S. A. Al-Sattary, A. A. Salama, M. S. Ghoname

“…Artificial intelligence algorithms were employed to predict quality and calculate regression coefficients. …”
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Winemaking terroir – the guideline for choosing of grape rootstocks for soils with different characteristics by А. А. Averianov, E. D. Androsova, A. V. Rusakov

“…The sample reduction scenario, based on the prioritization of the above stressors, reduced the number of varieties considered to three variants: 1103 Paulsen, 140 Ruggeri, and Fercal, which were scored against each other and considering the local terroir conditions of the plot, for further comparison in terms of market and logistics in making the final design decision.…”
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Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest by Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, Robert Fahey, Thomas Worthley

“…The principal objective of this study is to utilize the random forest (RF) algorithm to build predictive AGB models. We utilized 67 explanatory variables, which were extracted from three RS sources resulting in nine RF models. …”
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Towards Intelligent Unmanned Adversarial Games: A Reinforcement Learning Framework with the PHP-ROW Method by Guoqing Shi, Yi Cao, Dinghan Wang, Qiming Yang, Jiandong Zhang, Zhuoyong Shi

“…This study introduces a novel framework for intelligent unmanned BVR maneuver control within the context of adversarial games. The emphasis lies on three pivotal aspects: situational awareness, maneuver decision-making, and precise maneuver control. …”
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Optimizing sustainable blended concrete mixes using deep learning and multi-objective optimization by Rupesh Kumar Tipu, Preeti Rathi, Kartik S. Pandya, Vijay R. Panchal

“…The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm finds multiple optimal solutions which simultaneously optimize three competing objectives that include strength maximization and cost minimization and cement reduction. …”
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A comprehensive study of recent maximum power point tracking techniques for photovoltaic systems by Mohammed Hamouda Ali, Mohammad Zakaria, Sally El-Tawab

“…The MPPT-based methodologies fall into three categories: artificial intelligence (AI), metaheuristic, and conventional. …”
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A Framework for Synergy Measurement Between Transportation and Production–Living–Ecological Space Using Volume-to-Capacity Ratio, Accessibility, and Coordination by Xiaoyi Ma, Mingmin Liu, Jingru Huang, Ruihua Hu, Hongjie He

“…By introducing an improved accessibility evaluation model and developing a coordination measurement algorithm, a three-dimensional evaluation mechanism covering development potential assessment, service efficiency diagnosis, and resource allocation optimization is established. …”
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Prediction on Slip Modulus of Screwed Connection for Timber–Concrete Composite Structures Based on Machine Learning by Wen-Wu Lu, Yu-Wei Chen, Ji-Gang Xu, Hui-Feng Yang, Hao-Tian Tao, Wei Zheng, Ben-Kai Shi

“…Four ML methods, including decision tree (DT), random forest (RF), adaptive boosting machine (AdaBoost), and gradient boosting regression tree (GBRT), are adopted to develop the ML algorithm. …”
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Deep Reinforcement Learning-Based Enhancement of Robotic Arm Target-Reaching Performance by Ldet Honelign, Yoseph Abebe, Abera Tullu, Sunghun Jung

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Efficient sensor network planning based on approximate potential games by Su-Jin Lee, Young-Jin Park, Han-Lim Choi

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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

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Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data by Denglin Li, Luxin Zhang, Lifei Xu, Renhe Zhai, Hanyu Gao, Junlan Gao, Minghai Wei, Ningwei Che, Yeting He

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Last-Train Timetabling under Transfer Demand Uncertainty: Mean-Variance Model and Heuristic Solution by Shuo Yang, Kai Yang, Ziyou Gao, Lixing Yang, Jungang Shi

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INFORMED VOLUNTARY CONSENT IN PAEDIATRICIAN PRACTICE ORIGINAL ARTICLE by N. O. Bazhanov, N. S. Ivanenko

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Hierarchical reinforcement learning based on macro actions by Hao Jiang, Gongju Wang, Shengze Li, Jieyuan Zhang, Long Yan, Xinhai Xu

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Mode of delivery in placental abruption: A case report on difficulty in distinguishing between uterine rupture and placental abruption due to clinical features that overlap by Stephen Darko, Nnabuike Chibuoke Ngene

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