Finite family groups for fermionic and leptoquark mixing patterns by Jordan Bernigaud, Ivo de Medeiros Varzielas, Jim Talbert

“…Assuming experimentally interesting CKM and PMNS matrix elements, our algorithm finds an abundance of predictive non-Abelian flavour groups and therefore provides promising directions for future model building in the flavoured leptoquark space, regardless of whether the anomalous R K ∗ $$ {\mathcal{R}}_{K^{\left(\ast \right)}} $$ measurements withstand further experimental scrutiny.…”
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Multi objective optimization and experimental investigation of the stirring performance of a novel micro actuator by Zhuowei He, Junjie Lei, Jingjing Yang, Huba Zhu

“…Subsequently, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized for Multi-Objective Optimization to identify the optimal combination of structural parameters. …”
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Use artificial neural network to recommend the lumbar spinal endoscopic surgical corridor by Chien-Min Chen, Pei-Chen Chen, Ying-Chieh Chen, Guan-Chyuan Wang

“…The SHapley Additive exPlanations algorithm was utilized to explain the relative importance of each factor. …”
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Regenerative Braking in PV-Mounted Electric Vehicle With Reduced Switch VSI-Driven BLDC Motor and HAP-FUP Controller by Ron Carter S. B., Thangavel S.

“…Maximum energy is extracted from the PV module via employment of a particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm, while propulsion is provided through utilization of a brushless direct current (BLDC) motor driven by reduced switch voltage source inverter (VSI). …”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…The results confirm the efficacy of ML in predicting sustainability outcomes when supported by robust experimental data. …”
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CB-SEM vs PLS-SEM comparison in estimating the predictors of investment intention by Marija Vuković

“…Additionally, the consistent PLS algorithm (PLSc) was taken into consideration in the methods comparison. …”
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A Study on the Financial Health of Listed Real Estate Companies via Multicriteria Decision-Making Methods by Wenbao Wang, Wenhe Lin, Enhao Chen, Zhizhuan Zheng

“…This study constructs a financial health evaluation model for real estate development enterprises on the basis of the entropy-VIKOR algorithm. Using China as a case study, this research selects real estate companies listed on the Shanghai and Shenzhen Stock Exchanges before the end of 2016 as the sample for empirical analysis. …”
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Innovative Design of Marketing Ecosystems by А. I. Vasiliev, I. А. Brusakova

“…The transition from Industry 4.0 to Industry 5.0 is accompanied by the creation of the necessary software and algorithmic base of quantum computing, introduction of technologies for visualisation of management decisions, development of neuromorphic models of enterprise architecture, digital twins of business processes.The purpose of the study is to develop approaches to designing a marketing ecosystem within the framework of Industry 5.0 and Industry 4.0, which is necessary for building effective interactions between innovative enterprises of different business spheres. …”
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Automation of reversible steganographic coding with nonlinear discrete optimisation by Ching-Chun Chang

“…A fundamental element of reversible steganography is predictive analytics, for which powerful neural network models have been effectively deployed. …”
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Revolutionizing Midwifery Education : A Scoping Review of Artificial Intelligence Methods by Harridhil Silmi, Ari Indra Susanti

“…Despite these advancements, challenges such as ethical concerns (algorithmic bias, privacy issues), poor data quality, limited AI expertise among educators, and resistance to change in traditional learning environments were noted. …”
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Modelling trial-by-trial changes in the mismatch negativity. by Falk Lieder, Jean Daunizeau, Marta I Garrido, Karl J Friston, Klaas E Stephan

“…It has been used to demonstrate that the brain learns the statistical structure of its environment and predicts future sensory inputs. However, the algorithmic nature of these computations and the underlying neurobiological implementation remain controversial. …”
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Anemia Classification System Using Machine Learning by Jorge Gómez Gómez, Camilo Parra Urueta, Daniel Salas Álvarez, Velssy Hernández Riaño, Gustavo Ramirez-Gonzalez

“…In this study, a system was developed to predict anemia using blood count data and supervised learning algorithms. …”
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Intelligent hydraulic fracturing under industry 4.0—a survey and future directions by Jing Jia, Qinghu Fan, Jianglu Jing, Kehui Lei, Lichang Wang

“…It identifies four technical challenges: integrating heterogeneous data, developing intelligent decision-making algorithms, adaptive surface equipment adjustments, and multi-machine collaborative control. …”
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Adaptive Filter Updating for Energy-Efficient Top- Queries in Wireless Sensor Networks Using Gaussian Process Regression by Jiping Zheng, Baoli Song, Yongge Wang, Haixiang Wang

“…The mechanism can reduce transmissions of redundant data by utilizing filters. However, existing algorithms based on filters consume a vast amount of energy due to filter updating. …”
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Application of Artificial Neural Networks for Developing Temperature-Dependent Fragility Curves for Vulnerability Assessment of I-Girder Bridges by Saeed Sabori Ghomi, Saman Shiravand, Mohammad Mahdi Zare Zardeyni, Najib Rabiee

“…Accordingly, column reduction factors were computed via Eurocode provisions. …”
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High-Performance Identification and Control of MIMO (Multiple Input—Multiple Output) Experimental Module with Fractional-Order Approach Application by Alexandre Marques de Almeida, Alisson Luan Daga, Rafael Palma Setti Penteado Lanzarini, Ervin Kaminski Lenzi, Marcelo Kaminski Lenzi

“…The results demonstrate the superior performance and robustness of the FOPI-PSO fractional control, which achieves up to 79.6% reduction in ITAE and 72.1% reduction in ITSE criteria. …”
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Machine Learning Enhances Soil Aggregate Stability Mapping for Effective Land Management in a Semi-Arid Region by Pegah Khosravani, Ali Akbar Moosavi, Majid Baghernejad, Ndiye M. Kebonye, Seyed Roohollah Mousavi, Thomas Scholten

“…Machine learning algorithms coupled with environmental and soil covariates were used. …”
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Pattern recognition in SARS cases: insights from t-SNE and k-means clustering applied to COVID-19 symptomatology by Julliana Gonçalves Marques, Bruno Motta de Carvalho, Luiz Affonso Guedes, Márjory Da Costa-Abreu

“…This study proposes a dimensionality reduction approach combined with a clustering technique to visually analyse structural similarities among SARS-infected individuals, aiming to determine whether aspects such as case progression and diagnosis impact these patterns.MethodsThis analysis utilised the t-Distributed Stochastic Neighbour Embedding (t-SNE) algorithm for dimensionality reduction, combined with Gower's distance to handle categorical data, and k-means clustering. …”
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The features of the first trimester of pregnancy course in first-time mothers over 40 years old by Т. V. Lescheva

“…The purpose of the work is the pregnancy miscarriage frequency reduction in primiparous women over 40 years old on the basis of the clinical-echographic, endocrinological, biochemical and microbiological changes study. …”
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Diagnosis Method for High-Speed Train Axle Box Bearing Slight Faults Based on Improved SAE and Temperature-Vibration Fusion by XU Xiao, SONG Dongli, WANG Zifan

“…Then, by optimizing the dimensionality reduction algorithm based on SAE (stacked auto encoder), an effective fusion method of temperature-vibration features is proposed to achieve nonlinear fusion and dimensionality reduction of temperature and vibration features. …”
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