Results 71 to 80 of about 35,671 (228)

Unmet needs in the post-direct-acting antivirals era: The risk and molecular mechanisms of hepatocellular carcinoma after hepatitis C virus eradication [PDF]

Clinical and Molecular Hepatology
Hepatitis C virus (HCV) infection is one of the major etiologies of hepatocellular carcinoma (HCC) with approximately 30% of HCC being due to HCV infection worldwide.
Chung-Feng Huang, Manar Hijaze Awad, Meital Gal-Tanamy, Ming-Lung Yu   +3 more
doaj   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

The Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan, Ryan Gosselin, Nicolas Abatzoglou   +2 more
wiley   +1 more source

Gauge Deterioration Prediction of Urban Rail Transit Lines Based on CEEMD and SVR

Chengshi guidao jiaotong yanjiu
［Objective］ In order to strengthen the status ma-nagement of urban rail transit line sections, it is necessary to predict the overall deterioration trend of the gauge in space.
JIA Qingtian, LIN Haijian, JIN Zhong
doaj   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Greening the Workplace: Unlocking Green Performance Through Human Resource Management and Employee Behaviour

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study explores the role of green human resource management (GHRM) and employees' green behaviour (GB) in enhancing firms' green performance. Specifically, it investigates how GHRM practices contribute to improving the firm's overall environmental performance by fostering employees' GB.
María Isabel Barba‐Aragón, Raquel Sanz‐Valle, José Piñera‐Salmerón   +2 more
wiley   +1 more source

PERFORMANCE EVALUATION OF SEASONAL ARIMA-SVR AND SEASONAL ARIMAX-SVR HYBRID METHODS ON FORECASTING PADDY PRODUCTION

Barekeng
This study explores advances in forecasting time series data by combining linear and non-linear models. Traditional methods such as ARIMA and its variant ARIMAX are effective for linear data but have limitations when dealing with non-linearity.
I'lmisukma Risnawati, Farit Mochamad Afendi, I Made Sumertajaya   +2 more
doaj   +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

Comparison Of Machine Learning Algorithms For Rice Production Prediction

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Rice production forecasting plays an important role in supporting future agricultural planning, food supply management, and food security. Accurate yield prediction allows governments and farmers to estimate production outcomes and develop appropriate ...
Abdul Karim, Yuwaldi Away, Syahrial, Roslidar, Jeperson Hutahaean, William Ramdhan, Yessica Siagian   +6 more
doaj   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Verteilungsfragen in Deutschland: Herausforderungen der Messung und der zielgerichteten Umverteilung

Wirtschaftsdienst, 2020
Lars P. Feld, Jan L. Fries, Malte Preuß, Christoph M. Schmidt   +3 more
doaj   +1 more source