Results 211 to 220 of about 212,260 (313)

Application of artificial neural network and general machine learning modelling on CO2 adsorption in moisture equilibrated South African high and medium rank coals

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study investigates the effect of moisture on CO2 adsorption in South African coals using both experimental and machine learning approaches. Three coal samples (SL, TN, and EM) with varying ranks (RoVmr: 3.49%, 1.26%, and 0.64%, respectively) were collected from different regions of South Africa.
Kasturie Premlall, Lawrence Koech, Douw Faurie, Khanyisile Lepota   +3 more
wiley   +1 more source

"Smart" harm reduction vending machines to improve public health: Evaluating the utilization. [PDF]

J Subst Use Addict Treat
Zhang A, Murphy J, Griffin PM, Goodman-Hinnershitz M, Pinto CN, Ballard SM, Grigson PS, Kawasaki SS, Tuan WJ, Zgierska AE.   +9 more
europepmc   +1 more source

Combating ESG Greenwashing Through AI Models: Evidence From Disaggregated AI Technologies, Mechanisms, and Thresholds

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines how artificial intelligence language models influence corporate environmental, social, and governance greenwashing (GWESG$$ {\mathrm{GW}}_{\mathrm{ESG}} $$) behavior, utilizing panel data from Chinese listed firms spanning 2012–2022.
Brahim Bergougui, Hamid Ghazi H. Sulimany, Abdulrahman Atllah Alharbi   +2 more
wiley   +1 more source

Colorimetric sensor array combined with machine learning for discriminating the geographical origins and grape varieties of Chinese red wines. [PDF]

Food Chem X
Meng Z, Qiang HQ, Lv Y, Yan ML, Zhang ZY, Wang JW, Wang ZJ, Yin XL, Gu HW.   +8 more
europepmc   +1 more source

Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
wiley   +1 more source

Artificial intelligence and machine learning in sports medicine: mapping clinical tasks and assessing clinical maturity - a scoping review. [PDF]

BMC Med Inform Decis Mak
Lindskog J, Heder Ternell K, Yu Y, Lindman I, Samuelsson K, Hamrin Senorski E.   +5 more
europepmc   +1 more source

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

Deep Underground Science and Engineering, EarlyView.
In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang, Maohui Wang, Ning Wang, Yixin Shen, Xuzhen He   +4 more
wiley   +1 more source

An Integrated Zero-Trust and Real-Time Detection Scheme for DDoS Protection in 5G IoT Systems. [PDF]

Sensors (Basel)
Luo YY, Cheng CH, Lian YR, Huang YF, Hsieh CH.   +4 more
europepmc   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Machine learning framework for cost effective deep mutational scanning through targeted substitution profiling. [PDF]

BMC Bioinformatics
Morgan E, Govender S, Singh P, Goodfellow I, Graham SC, Bishop NT, Bishop ÖT.   +6 more
europepmc   +1 more source