Results 61 to 70 of about 13,817 (251)

Minimizing Off‐Target Effects of CRISPR‐Cas9 With Optimized sgRNA: Evaluation of Efficiency and Specificity in the Tumor Protein 53 (TP53) Region

Biotechnology and Bioengineering, EarlyView.
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) – Cas9‐based genome editing has emerged as a widely used tool across various disciplines, ranging from molecular biology to gene therapy. This revolutionary technology, which enables precise gene editing, represents a significant advancement in biotechnology, opening new frontiers for ...
Ali Mertcan Köse, Monia Ranalli, Drenka Trivanovic, Irina Maslovaric   +3 more
wiley   +1 more source

Machine learning‐assisted clone selection for intensified cell culture processes

Biotechnology Progress, EarlyView.
Abstract Intensified fed‐batch processes are becoming increasingly prevalent among biomanufacturers due to their superior space–time yields relative to traditional, non‐intensified fed‐batch processes. However, the shift towards intensified manufacturing has unexpectedly made optimal clone selection more challenging.
Nicolas Wolnick, John Schmitt, Christian Siltanen, Julia Armstrong, Shannon Hendrick, Ariel Atchley, Brandon Downey   +6 more
wiley   +1 more source

Implementation of Machine Learning Models to Predict Functionality of Pea Flour From Its Composition

Cereal Chemistry, EarlyView.
ABSTRACT Background and Objectives The goal of this research was to examine the relationship between the composition and functionality of pea flour using the following machine learning algorithms: linear regression, partial least squares regression (PLSR), Gaussian process regression (GPR), support vector regression, gradient‐boosted decision trees ...
Colten N. Nickerson, Sarah Hogarth, Andrea K. Stone, Gene C. Arganosa, Pankaj Bhowmik, Tom D. Warkentin, Jordan Ubbens, Michael T. Nickerson   +7 more
wiley   +1 more source

Adaptive Neural Sliding Mode Control of Active Power Filter

Journal of Applied Mathematics, 2013
A radial basis function (RBF) neural network adaptive sliding mode control system is developed for the current compensation control of three-phase active power filter (APF). The advantages of the adaptive control, neural network control, and sliding mode
Juntao Fei, Zhe Wang
doaj   +1 more source

Combined Prediction Energy Model at Software Architecture Level

IEEE Access, 2020
Accurate prediction of software energy consumption is of great significance for the sustainable development of the environment. In order to overcome the limitations of a single prediction method and further improve the prediction accuracy, a combined ...
Junke Li, Kai Liu, Mingjiang Li, Deguang Li   +3 more
doaj   +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

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network

Gong-kuang zidonghua, 2013
In view of problem that eddy-current sensor cannot reflect measured physical quantity accurately caused by higher nonlinear of output characteristic parameter, the paper proposed a scheme of using RBF neural network to fit output characteristic parameter
YOU Wen-jian, LIANG Bing, LI Yin-jun
doaj  

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

High-Dimensional Aerodynamic Modeling Prediction Based on Modified RBF Neural Network with Data Assimilation

气体物理
In this paper, the radial basis function (RBF) neural network was modified by data assimilation method to improve the modeling accuracy of high-dimensional aerodynamics. A correction factor γ was introduced into the kernel function of the traditional RBF
Ying ZHANG, Xin ZHANG, Weiguo ZHANG, Zichen DENG   +3 more
doaj   +1 more source