Results 61 to 70 of about 8,190 (251)
Agribusiness, EarlyView.ABSTRACT The origin of a product, if associated with good quality, can contribute to building a positive collective reputation, leading to a potential price premium. However, it is conceivable that a producer markets a product by evoking symbols, images, words, and values typical of places other than where it was designed or produced, creating a ...
Annalisa Caloffi +2 more
wiley +1 more source
South African Journal of Economic and Management Sciences, 2015 This study examines the potential impact of industrial unrest and the outbreak of violence at Marikana on 16 August 2012 on the share prices of mining companies listed on the Johannesburg Stock Exchange (JSE) using an event methodology.
Nicholas Hill, Warren Maroun
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Causal Inference in Educational Data Mining
The domain of causal inference, encompassing fields of statistics, philosophy, economics, and computer science, has seen rapid advancements. This emerging science addresses the challenges involved in estimating effects amidst complex situations in which confounding variables can obscure results.
Anthony F. Botelho +4 more
openaire +2 more sources
Mining Markov Blankets Without Causal Sufficiency
IEEE Transactions on Neural Networks and Learning Systems, 2018 Markov blankets (MBs) in Bayesian networks (BNs) play an important role in both local causal discovery and large-scale BN structure learning. Almost all existing MB discovery algorithms are designed under the assumption of causal sufficiency, which states that there are no latent common causes for two or more of the observed variables in data. However,
Kui Yu +3 more
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Evolution of Physical Intelligence Across Scales
Advanced Intelligent Discovery, EarlyView.By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
IEEE Access, 2019 Naive Bayes classifier (NBC) is an effective classification technique in data mining and machine learning, which is based on the attribute conditional independence assumption.
Ming Li, Kefeng Liu
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Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
Advanced Intelligent Discovery, EarlyView.This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
CAUSALITY IN THE OFFENCES UNDER ARTICLES 143 AND 216 OF THE CRIMINAL CODE
Вестник Кемеровского государственного университета, 2015 The paper focuses on analysis of causality in violations of labour protection requirements (Art. 143 of the Criminal Code) and criminal violations of safety regulations during mining, construction and other works (Art. 216 of the Criminal Code).
T. G. Chernenko, A. A. Naumov
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