Results 111 to 120 of about 774,383 (293)

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

open access: yesAdvanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang   +2 more
wiley   +1 more source

The Use of Generative Artificial Intelligence in the Field of Business: A Bibliometric Analysis

open access: yesTrends in Business and Economics
The aim of this study is to examine the development trends and underlying knowledge structures of generative artificial intelligence which has gained popularity in recent years within the disciplines of “business“ and “management“ using bibliometric ...
Sinan Emre Kurtaal   +2 more
doaj   +1 more source

Cyber Attack Prediction: From Traditional Machine Learning to Generative Artificial Intelligence

open access: yesIEEE Access
The escalating sophistication of cyber threats poses significant risks to individuals, organizations, and nations. Cybercrime, encompassing activities like hacking and data breaches, has severe economic and societal consequences.
Shilpa Ankalaki   +5 more
semanticscholar   +1 more source

Rise of Generative Artificial Intelligence in Science

open access: yesAcademy of Management Proceedings
Abstract Generative Artificial Intelligence (GenAI) has rapidly emerged as a tool in scientific research. To examine its diffusion and impact relative to other AI technologies, we conduct an empirical analysis using the OpenAlex bibliometric database to retrieve GenAI and other AI relevant publications.
Liangping Ding   +2 more
openaire   +3 more sources

The PRIMA Thesaurus for Materials Science and Engineering

open access: yesAdvanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa   +8 more
wiley   +1 more source

Challenging human creativity: an exercise of co-creation with generative artificial intelligence

open access: yesCreativity Studies
This paper explores the collaborative potential between humans and generative artificial intelligence in creative contexts through a co-creation framework.
Bernardo Flores Heymann   +1 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

open access: yesAdvanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara   +8 more
wiley   +1 more source

An Innovative Approach in Arts Education: Student Experiences of Abstract Art Practices Supported by Generative Artificial Intelligence

open access: yesSAGE Open
This study aimed to identify the experiences of students on the reflections of arts education supported by generative artificial intelligence in their abstract art practices.
Yahya Hiçyilmaz
doaj   +1 more source

Perceptions and Intentions to Use Generative AI Among First-Year Medical Students in Japan: Cross-Sectional Survey Study

open access: yesJMIR Medical Education
An April 2025 survey of 118 first-year Japanese medical students found high use of generative artificial intelligence (84.7%) but limited formal learning (49.2%), with strong learning interest yet neutral assignment use, indicating a need for structured ...
Hiroshi Tajima   +4 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

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