Results 171 to 180 of about 303,008 (292)
Biotechnology and Bioengineering, EarlyView.ABSTRACT The growing demand for biopharmaceutical products reflects their effectiveness in medical treatments. However, developing new biopharmaceuticals remains a major bottleneck, often taking up to a decade before market approval. Machine learning (ML) models have the potential to accelerate this process, but their success depends on access to large
Mohammad Golzarijalal +2 more
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT This study examines the economic consequences of Digital Technologies Disclosure (DTD), focusing on its impact on the cost of capital. The increasing significance of digital transformation in shaping corporate strategies and market perceptions motivates the study.
Hussein Mohsen Saber Ahmed +2 more
wiley +1 more source
CompareSVM: supervised, Support Vector Machine (SVM) inference of gene regularity networks. [PDF]
BMC Bioinformatics, 2014 Gillani Z, Akash MS, Rahaman MD, Chen M.
europepmc +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT Environmental protection has emerged as a global priority in the contemporary context. As pivotal actors in the transition towards sustainable development, companies play a crucial role through the adoption of environmental innovations. This study investigates how organisational characteristics—specifically geographical location, business ...
Carlos de las Heras‐Rosas +3 more
wiley +1 more source
LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length. [PDF]
BMC Bioinformatics, 2016 Bao Y, Hayashida M, Akutsu T.
europepmc +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT The emerging concept of Hubs for Circularity (H4Cs) presents an opportunity to create collaborative, self‐sustaining regional industrial ecosystems that drive circular economy transitions at scale. However, the operationalisation of H4Cs faces financial, organisational and data‐driven challenges.
Aditya Tripathi +3 more
wiley +1 more source
Journal of Consumer Behaviour, EarlyView.ABSTRACT Grounded in ambivalence theories, this research examined factors shaping consumer ambivalence toward AI‐generated content and investigated differences between commercial and noncommercial contexts. As a preliminary study, sentiment analysis of Reddit data using a support vector machine (SVM) revealed that most consumer sentiment toward AI ...
Garim Lee +3 more
wiley +1 more source
Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions
Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
Carbon Energy, EarlyView.Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su +4 more
wiley +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
wiley +1 more source