Results 121 to 130 of about 5,416,756 (285)

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Cuneiform Text Dialect Identification Using Machine Learning Algorithms and Natural Language Processing (NLP)

Iraqi Journal of Information & Communication Technology
Due to a lack of resources and the tokenization issue, it is challenging to identify the languages inscribed in cuneiform symbols. Sumerian and six dialects of the Akkadian language-Old Babylonian, Middle Babylonian Peripheral, Standard Babylonian ...
Elaf A. Saeed, Ammar D. Jasim , Munther A. Abdul Malik   +2 more
doaj   +1 more source

Multidimensional and Multifunctional Laser‐Induced Graphene (LIG) for Point‐of‐Care and Wearable Biosensing, Theranostics, and Bioactive Interfaces Toward Personalized Healthcare and Regenerative Medicine

Advanced Science, EarlyView.
Multidimensional laser‐induced graphene (LIG) spanning from 0D to 3D architectures is comprehensively reviewed for multifunctional biomedical platforms, including biosensing, theranostics, and bioactive interface applications, which highlights its potentials for point‐of‐care diagnostics, wearable health monitoring, smart drug delivery, and tissue ...
Li Zhang, Yurou Yuan, Xiaohong Ding, Wing Cheung Mak   +3 more
wiley   +1 more source

Decoupling and predicting natural gas deviation factor using machine learning methods

Scientific Reports
Accurately predicting the deviation factor (Z-factor) of natural gas is crucial for the estimation of natural gas reserves, evaluation of gas reservoir recovery, and assessment of natural gas transport in pipelines.
Shaoyang Geng, Shuo Zhai, Jianwen Ye, Yajie Gao, Hao Luo, Chengyong Li, Xianshan Liu, Shudong Liu   +7 more
doaj   +1 more source

Machine Learning Offers Opportunities to Advance Library Services

Evidence Based Library and Information Practice
A Review of: Wang, Y. (2022). Using machine learning and natural language processing to analyze library chat reference transcripts. Information Technology and Libraries, 41(3). https://doi.org/10.6017/ital.v41i3.14967 Objective – The study sought to
Samantha Kaplan
doaj   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Predicting Compressive Strength of High-Performance Concrete Using Hybridization of Nature-Inspired Metaheuristic and Gradient Boosting Machine

Mathematics
This study proposes a novel integration of the Extreme Gradient Boosting Machine (XGBoost) and Differential Flower Pollination (DFP) for constructing an intelligent method to predict the compressive strength (CS) of high-performance concrete (HPC) mixes. The former is employed to generalize a mapping function between the mechanical property of concrete
Hoang, Nhat-Duc, Tran, Van-Duc, Tran, Xuan-Linh   +2 more
openaire   +2 more sources

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Compressive strength prediction of coconut fiber reinforced concrete using PSO optimized explainable machine learning

Scientific Reports
The use of natural fibers in concrete is a sustainable strategy to improve ductility and crack resistance; however, coconut fiber can introduce nonlinear interactions among mix constituents that complicate compressive strength prediction.
Ahmed A. Alawi Al-Naghi, Tariq Ali, Inamullah Inam, Muhammad Sarmad Mahmood, Muhammad Zeeshan Qureshi, Khaled Mohamed Elhadi, Abdelkader Mabrouk, Ali Ajwad   +7 more
doaj   +1 more source

An Analysis of UK Natural Gas Prices Comparing Regression, Neural Nets and Gradient Boosting Techniques

, 2023
I denne masteroppgaven ble det utført en komparativ analyse av de tre ulike modelleringsmetodene: multippel lineær regresjon, gradient boosting metoden XGBoost og det nevrale nettverket Long Short-Term Memory (LSTM). For ˚a sammenligne modellene ble tidsserie data for naturgassprisen i UK brukt. M˚alet med denne masteroppgaven var ˚a utforske i hvilken
openaire   +1 more source