Gaussian Processes for Predictive QSAR Modeling of Chromatographic Processes
Biotechnology and Bioengineering, EarlyView.ABSTRACT Chromatography is a key unit operation in the biopharmaceutical manufacturing process used for protein purification and polishing. Design and optimization of these processes are resource‐intensive resulting from the complex combinatorial design space.
Harini Narayanan +7 more
wiley +1 more source
Denoising autoencoder framework for reconstructing missing periodontal clinical records. [PDF]
Front Dent MedMathew A, Yadalam PK.
europepmc +1 more source
Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges
Biotechnology and Bioengineering, EarlyView.ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz +3 more
wiley +1 more source
Synonym‐based multi‐keyword ranked search with secure k‐NN in 6G network
IET Networks, EarlyView., 2022 Abstract Sixth Generation (6G) integrates the next generation communication systems such as maritime, terrestrial, and aerial to offer robust network and massive device connectivity with ultra‐low latency requirement. The cutting edge technologies such as artificial intelligence, quantum machine learning, and millimetre enable hyper‐connectivity to ...
Deebak Bakkiam David, Fadi Al‐Turjman
wiley +1 more source
GAN-based bone suppression using a combined loss function. [PDF]
Front Artif IntellJochymek L +3 more
europepmc +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
Insulator fault feature extraction system of substation equipment based on machine vision
IET Networks, EarlyView., 2022 Abstract The artificial intelligence technology and intelligent automation are more and more widely used, the insulators play a supporting and insulating role in the operation of the grid. The use of machine vision inspection technology to detect insulator faults has become an inevitable trend of the times.
Keruo Jiang +4 more
wiley +1 more source
Unsupervised multimodal deep learning for galaxy morphology taxonomy: integrating ConvNeXtEmbeddings and morphological parameters for scalable survey science. [PDF]
Sci RepSelim IM +3 more
europepmc +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
Green AI architectures: Navigating the security-sustainability paradox in critical infrastructure protection. [PDF]
Environ Sci EcotechnolLee J +3 more
europepmc +1 more source