A method for identifying relevant topics of pilot simulator training based on clustering of flight safety reports by Z. R. Zabbarov, A. K. Volkov

“…Natural language processing (NLP) technologies, in one of their applications, provide effective research of patterns and trends in large sets of textual data. …”
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Personalised Affective Classification Through Enhanced EEG Signal Analysis by Joseph Barrowclough, Nonso Nnamoko, Ioannis Korkontzelos

“…This overlooks individual differences and may not accurately capture the unique emotional patterns of each person.Methods This study explored the performance of six machine learning algorithms in classifying a benchmark EEG dataset (collected with a MUSE device) for affective research. …”
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The Evolution of Service Ecosystems Based on the Lotka–Volterra Model by Binbin Shi, Yu Li, Tingting Liang, Xixi Sun, Liquan Cui, Haonan Zhang, Yuyu Yin

“…At present, research on the evolution of service ecosystems largely lacks sufficient theoretical underpinning and focuses on the supply–demand relationship relationship, which reduces the credibility of research conclusions and ignores the influence of multiple factors. …”
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Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…In contrast, the VAE-based approach leverages deep learning to model historical routing patterns and autonomously generate new heuristics tailored to problem-specific characteristics. …”
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Integrating single cell analysis and machine learning methods reveals stem cell-related gene S100A10 as an important target for prediction of liver cancer diagnosis and immunothera... by Shenjun Huang, Tingting Tu

“…We analyzed various datasets, applying negative matrix factorization alongside machine learning algorithms to reveal gene expression patterns and construct diagnostic models. …”
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Study on the interaction characteristics between pot seedling and planter based on hanging cup transplanter by Hongbin Bai, Fandi Zeng, Qiang Su, Ji Cui, Xuying Li

“…The research findings indicate that under different planting frequencies, the collision contact points and interaction relationships between the pot seedlings and the planter exhibit significant differences. …”
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Texas rural land market integration: A causal analysis using machine learning applications by Tian Su, Senarath Dharmasena, David Leatham, Charles Gilliland

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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

“…The combination of using DL algorithms, such as multi-layer perceptron (MLP) and long short-term memory (LSTM), which can process complex patterns in the data, and the inclusion of new data types, such as sequential data, helped to improve model performance. …”
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Investigating Potential Anti-Bacterial Natural Products Based on Ayurvedic Formulae Using Supervised Network Analysis and Machine Learning Approaches by Pei Gao, Ahmad Kamal Nasution, Naoaki Ono, Shigehiko Kanaya, Md. Altaf-Ul-Amin

“…The initial approach utilizes a supervised network analysis, which involves the application of distance measurement algorithms to scrutinize the interconnectivity and relational patterns within the network derived from Ayurvedic formulae. …”
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Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis by Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila

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A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons by Liya Li, Liya Li, Ying Hu, Ying Hu, Xiaojun Wang, Pei Sun, Tingwei Quan

“…Advances in molecular labeling techniques and optical imaging technologies have spurred extensive research into the patterns of long-range neuronal projections. …”
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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Buildings account for a substantial portion of global energy consumption, and research indicates that occupant behavior can significantly influence energy use and building performance. …”
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Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure by Petr Dejdar, Ondrej Mokry, Petr Munster, Tomas Horvath, Jiri Schimmel

“…This study presents a dataset comprising acoustic vibration patterns recorded by a commercial DAS system, providing valuable insights into the acoustic sensitivity of optical fibers. …”
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Aerial Biological Target Classification Based on Time–Frequency Multi-Scale Feature Fusion Network by Lianjun Wang, Rui Wang, Weidong Li, Jiangtao Wang, Yujia Yan, Cheng Hu

“…The algorithm proposed in this paper achieved a classification accuracy of 94.0% for insect and bird targets.…”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…Intense research has resulted in the recent approval by the U. …”
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ML‐UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper by Warren G. Hill, Bryce MacIver, Gary A. Churchill, Mariana G. DeOliveira, Mark L. Zeidel, Marcelo Cicconet

“…This should be a valuable tool for anyone performing lower urinary tract research using mouse models.…”
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A Data Fusion System for Simulation of Critical Scenarios and Decision-Making by Jimmy Anderson Flórez Zuluaga, Esteban Patino Carrasco, Jose David Ortega Pabón, Kelly Gallego León, O. Lucía Quintero Montoya

“…This document describes an investigation product resulted in a simulation system, based on a combination of fuzzy logic, genetic algorithms and decision trees which let modelled and simulated various entities and their automatic response according to simulated patterns and situations, in which, through operators, decision maker can modify entities behaviour, according to parameterized restrictions and physical conditions. …”
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QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors by Auwal Isa, Adamu Uzairu, umar Umar, Muhammad Tukur Ibrahim, Abdullahi Umar

“…A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts chemical activity (pGI50) against breast cancer receptors. …”
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Influenza virus genotype to phenotype predictions through machine learning: a systematic review by Laura K. Borkenhagen, Martin W. Allen, Jonathan A. Runstadler

“…Machine learning techniques have demonstrated promise in addressing this critical need for other pathogens because the underlying algorithms are especially well equipped to uncover complex patterns in large datasets and produce generalizable predictions for new data. …”
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Using the proximal policy optimization and prospect theory to train a decision-making model for managing personal finances by Vladyslav Didkivskyi, Dmytro Antoniuk, Tetiana Vakaliuk, Yevhen Ohinskyi

“…A graphical analysis of the recommended allocation percentages revealed significant patterns influenced by the value function parameters of Prospect Theory. …”
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