Results 51 to 60 of about 36,209 (267)

Unveiling financial well-being: Insights from retired people in Third Age group in Poland, Spain and Denmark

Economics and Business Review
The study investigates the financial well-being of older people in Poland, Spain and Denmark, with a particular focus on their ability to make ends meet.
Jajko-Siwek Alicja
doaj   +1 more source

Análisis de licitaciones públicas en Ecuador: aplicación de técnicas de explicabilidad en modelos de aprendizaje automático

Revista Odigos
Las licitaciones públicas permiten a las instituciones contratar bienes, obras y servicios esenciales para el crecimiento del país. Este trabajo consistió en analizar los procesos de licitaciones públicas en Ecuador mediante la aplicación de técnicas de ...
Maria Fernanda Molina Miranda, Ángel Cuenca Ortega, Luis Espín Pazmiño, Miguel Molina Villacís   +3 more
doaj   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Malnutrition Severity Drives Mortality in Geriatric Heart Failure: A Multicenter Extreme Gradient Boosting Analysis

Reviews in Cardiovascular Medicine
Background: Heart failure (HF) and malnutrition frequently coexist in older patients (≥65 years) and are major determinants of in-hospital mortality.
Yiming Chen, Min He, Mengyu He, Ziting Yuan, Xiao Chen   +4 more
doaj   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Explainable Machine Learning for Food Vulnerability Prediction in Indonesia

Journal of Applied Informatics and Computing
Food insecurity remains a strategic multidimensional issue in Indonesia, requiring precise and transparent predictive frameworks for evidence-based policy.
Marizka Riffiy Alfiyah, Fadiah Tussholiha, Nyimas Princessa Syapeni, Halona Daffakhansa Nabila, Ken Ditha Tania, Allsela Meiriza, Ahmad Rifai   +6 more
doaj   +1 more source

Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression

CoRR
Feature selection is an essential process in machine learning, especially when dealing with high-dimensional datasets. It helps reduce the complexity of machine learning models, improve performance, mitigate overfitting, and decrease computation time. This paper presents a novel feature selection framework, shap-select.
Egor Kraev, Baran Koseoglu, Luca Traverso, Mohammed Topiwalla   +3 more
openaire   +2 more sources

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

АВТОМАТИЗОВАНЕ ВИЯВЛЕННЯ АНОМАЛІЙ У ТРАФІКУ КОРПОРАТИВНИХ БЕЗДРОТОВИХ МЕРЕЖ ЗА ДОПОМОГОЮ PYTHON: МЕТОДИ, РЕАЛІЗАЦІЯ ТА ОЦІНКА ЕФЕКТИВНОСТІ

Кібербезпека: освіта, наука, техніка
Представлено результати дослідження, присвяченого розробці та порівнянню моделей автоматизованого виявлення аномалій у трафіку корпоративних бездротових мереж.
Ізабелла Соболенко, Артем Платоненко   +1 more
doaj   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source