Error probability in coding theory

Results 161 to 170 of about 298,987 (213)

Animal‐Based Brands Taking the Plant‐Based Opportunity: A Tasting Experiment Exploring Consumer Acceptance of Plant‐Based Brand Extensions

Agribusiness, EarlyView.
ABSTRACT This study investigates how consumer taste and brand equity perceptions shape the acceptance of plant‐based milk products. Using a blind/informed tasting experiment, we evaluated consumers' willingness to buy (WTB) and taste perception of a plant‐based milk alternative produced by a traditional dairy brand, compared with competing plant‐based ...
Federico Parmiggiani +6 more
wiley +1 more source

Consumers' Willingness to Pay a Premium for Climate‐Friendly Food Production: The Role of Production Method Information and Social Norms

Agribusiness, EarlyView.
ABSTRACT This study examines whether information about production methods and social norms can increase consumers' willingness to pay (WTP) a price premium for food produced using climate‐friendly farming methods. A randomized survey experiment was conducted with 1568 respondents across Denmark, Lithuania, and Spain, who were assigned to one of four ...
Kassa Tarekegn Erekalo +5 more
wiley +1 more source

Punishments Enhance Reward Learning by Modulating Striatal Prediction Errors. [PDF]

J Neurosci
Carvalheiro J +6 more
europepmc +1 more source

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

Agribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source

The Role of Mutations, Addition of Amino Acids, and Exchange of Genetic Information in the Coevolution of Primitive Coding Systems. [PDF]

Int J Mol Sci
Pawlak K +3 more
europepmc +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source

Prediction model for the dissemination of AI-generated deepfake videos in the intelligent entertainment paradigm. [PDF]

Sci Rep
Ma X, Wang J, Ji E, Wang Z.
europepmc +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen +5 more
wiley +1 more source

Towards a theory of human creativity sustained by embodied collective intelligence. [PDF]

Front Psychol
Daikoku T.
europepmc +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Advanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source