ORCID Profile
0000-0002-0513-5823
Current Organisations
Liverpool Hospital
,
University of New South Wales
,
Nguyen Tat Thanh University
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Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 05-2023
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 08-2022
DOI: 10.1016/J.SCITOTENV.2022.155066
Abstract: A high-resolution soil moisture prediction method has recently gained its importance in various fields such as forestry, agricultural and land management. However, accurate, robust and non- cost prohibitive spatially monitoring of soil moisture is challenging. In this research, a new approach involving the use of advance machine learning (ML) models, and multi-sensor data fusion including Sentinel-1(S1) C-band dual polarimetric synthetic aperture radar (SAR), Sentinel-2 (S2) multispectral data, and ALOS Global Digital Surface Model (ALOS DSM) to predict precisely soil moisture at 10 m spatial resolution across research areas in Australia. The total of 52 predictor variables generated from S1, S2 and ALOS DSM data fusion, including vegetation indices, soil indices, water index, SAR transformation indices, ALOS DSM derived indices like digital model elevation (DEM), slope, and topographic wetness index (TWI). The field soil data from Western Australia was employed. The performance capability of extreme gradient boosting regression (XGBR) together with the genetic algorithm (GA) optimizer for features selection and optimization for soil moisture prediction in bare lands was examined and compared with various scenarios and ML models. The proposed model (the XGBR-GA model) with 21 optimal features obtained from GA was yielded the highest performance (R
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 08-2022
DOI: 10.1016/J.BIORTECH.2022.127341
Abstract: Clean energy like hydrogen can be a promising strategy to solve problems of global warming. Photo-fermentation (PF) is an attractive technology for producing biohydrogen from various biowastes cost-effectively and environmentally friendly. However, challenges of low light conversion efficiency and small yields of biohydrogen production still limit its application. Thus, advanced strategies have been investigated to enhance photo-fermentative biohydrogen production. This review discusses advanced technologies that show positive outcomes in improving biohydrogen production by PF, including the following. Firstly, genetic engineering enhances light transfer efficiency, change the activity of enzymes, and improves the content of ATP, ammonium and antibiotic tolerance of photosynthetic bacteria. Secondly, immobilization technology is refined. Thirdly, nanotechnology makes great strides as a scientific technique and fourthly, integration of dark and photo-fermentation technology is possible. Some suggestions for further studies to achieve high levels of efficiency of photo-fermentative biohydrogen production are mentioned in this paper.
Publisher: Wiley
Date: 31-12-2019
DOI: 10.1002/APP.48904
Publisher: Elsevier BV
Date: 2022
Location: No location found
No related grants have been discovered for Ngoc Bich Hoang.