Results 171 to 180 of about 150,441 (331)

Strategic Prioritization of Environmental, Social, and Governance Goals: A Data‐Driven Efficiency Framework

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Organizations are increasingly required to integrate environmental, social, and governance (ESG) objectives alongside operational performance, yet empirical guidance on how firms should prioritize among ESG activities under resource constraints remains limited.
Minyoung Choi, Sangjin Park, Jae‐Suk Yang   +2 more
wiley   +1 more source

Advanced Machine Learning Techniques for Predicting Heart Disease: A Comparative Analysis Using the Cleveland Heart Disease Dataset

Applied Medical Informatics
The ability to predict heart illness was essential for prompt diagnosis and treatment. Using the Cleveland Heart Disease dataset, this study tested a number of machine learning models, including LSTM networks, Random Forest, Gradient Boosting, XGBoost ...
Dhadkan SHRESTHA
doaj  

Using Machine Learning to Analyze the Predictors of Life Satisfaction: Focus on Lifestyle Attitudes and Psychological Factors. [PDF]

Int J Methods Psychiatr Res
Alptekin FB, Torlak E, Asik Ö, Karaaslan B, Turgal E, Burhan HS, Aytac HM, Guclu O.   +7 more
europepmc   +1 more source

Advancing mine pillar design: Evaluating traditional methods and integrating AI for enhanced stability of pillars in the Great Dyke, Zimbabwe

Deep Underground Science and Engineering, EarlyView.
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza, Hendrik Grobler, Peter Apata Olubambi, Moshood Onifade, Manoj Khandelwal   +4 more
wiley   +1 more source

28-day cement strength prediction via transformer-based feature extraction and XGBoost. [PDF]

PLoS One
Ju D, Ma X, Zhang R, Liu Z, Wang X, Huang B.   +5 more
europepmc   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Predicting copper leaching from slag: an interpretable machine learning approach under oxidative sulfuric acid conditions. [PDF]

RSC Adv
Kim SJ, Kang SS, Pae KN, Pak SI, Jo HI, Kim RJ.   +5 more
europepmc   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Machine learning improves SNP microarray performance in challenged samples. [PDF]

Bioinform Adv
Chiao A, Crysup B, King JL, Coble MD, Woerner AE.   +4 more
europepmc   +1 more source

Toward a Paradigm Shift in Low‐Temperature SCR Catalyst Design: Defect Engineering and Data‐Driven Integration

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This work systematically reviews the key factors influencing the performance of low‐temperature NH3‐SCR. The mechanism and challenges of defect engineering strategies, such as oxygen vacancies, heteroatom doping, crystal facet exposure, and surface reconstruction, in controlling both activity and selectivity were analyzed.
Rongrong Kan, Pinjing He, Fan Lü, Hua Zhang   +3 more
wiley   +1 more source