Results 101 to 110 of about 3,102 (223)

Beyond Online Association Rules: Governing Semantic Drift in Numerical Stream Mining

Este trabajo propone una reformulación del online numerical association rule mining desde una perspectiva de gobernanza del conocimiento. Aunque los enfoques clásicos han sido eficaces en términos de eficiencia computacional, actualización incremental y optimización de métricas estadísticas, suelen asumir implícitamente la estabilidad semántica y ...
openaire   +2 more sources

AIM2 framework for smart marketing innovation using AI driven consumer analytics with SOR neural networks and XGBoost in Saudi retail. [PDF]

Sci Rep
Alarfaj FK, Badouch M, Khan HU, Boutaounte M.   +3 more
europepmc   +1 more source

The Role of Actual and Purported Origin in e‐Commerce Wine Pricing: Evidence From Italian and French Names on Labels

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, Amir Maghssudipour, Gianluca Stefani   +2 more
wiley   +1 more source

Assessing Occupational Work-Related Stress and Anxiety of Healthcare Staff During COVID-19 Using Fuzzy Natural Language-Based Association Rule Mining. [PDF]

Healthcare (Basel)
Alkabaa AS, Taylan O, Alqabbaa HS, Guloglu B.   +3 more
europepmc   +1 more source

Asking the 5 W's for designing next‐generation bioprocessing

AIChE Journal, EarlyView.
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook, Karoline Maria Vieira Nogueira, Raj Sukumar, Jenna Miller, Hal S. Alper   +4 more
wiley   +1 more source

A Neuro-Symbolic Bioinformatics Framework for Unlocking Chordate Physiological Dark Data and Validating Allometric Scaling. [PDF]

Biology (Basel)
Duan Z, Zhao G, Li C, Liu B.
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

FUSION-AD: interpretable AI framework for risk assessment and subgroup discovery in Alzheimer's disease. [PDF]

Front Neuroinform
Iqbal A, Arif S, Husnain G, Ayouni S.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source