[HTML][HTML] Short-term exposure to sulphur dioxide (SO2) and all-cause and respiratory mortality: A systematic review and meta-analysis
P Orellano, J Reynoso, N Quaranta - Environment international, 2021 - Elsevier
Background Many studies have assessed the harmful effects of ambient air pollution on
human mortality, but the evidence needs further exploration, analysis, and refinement, given …
human mortality, but the evidence needs further exploration, analysis, and refinement, given …
Real-time data-driven missing data imputation for short-term sensor data of marine systems. A comparative study
C Velasco-Gallego, I Lazakis - Ocean Engineering, 2020 - Elsevier
In the maritime industry, sensors are utilised to implement condition-based maintenance
(CBM) to assist decision-making processes for energy efficient operations of marine …
(CBM) to assist decision-making processes for energy efficient operations of marine …
Impact of energy structure on carbon emission and economy of China in the scenario of carbon taxation
J Liu, J Bai, Y Deng, X Chen, X Liu - Science of the Total Environment, 2021 - Elsevier
As the largest CO 2 emitter in the world, China intends to achieve the peak of carbon
emissions in around 2030. Unlike many other countries' targets of reducing the amount the …
emissions in around 2030. Unlike many other countries' targets of reducing the amount the …
A city-based PM2. 5 forecasting framework using Spatially Attentive Cluster-based Graph Neural Network model
Urban environments globally are under threat due to recent climate changes caused by a
variety of factors such as growing industrialization, rapid migration, increasing traffic flow …
variety of factors such as growing industrialization, rapid migration, increasing traffic flow …
[HTML][HTML] Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network
The expected performance of Green Stormwater Infrastructure (GSI) is typically quantified
through numerical models based on hydrologic parameters and physics-based equations …
through numerical models based on hydrologic parameters and physics-based equations …
[HTML][HTML] Development of real-world emission factors for on-road vehicles from motorway tunnel measurements
In India, there is uncertainty in vehicular emission estimation due to the lack of reliable
emission factors (EFs) that represent the real-world driving conditions. In this study, real …
emission factors (EFs) that represent the real-world driving conditions. In this study, real …
Energy consumption prediction of a CNC machining process with incomplete data
Energy consumption prediction of a CNC machining process is important for energy
efficiency optimization strategies. To improve the generalization abilities, more and more …
efficiency optimization strategies. To improve the generalization abilities, more and more …
SENERGY: a novel deep learning-based auto-selective approach and tool for solar energy forecasting
Researchers have made great progress in developing cutting-edge solar energy forecasting
methods. However, these methods are far from optimal in terms of their accuracy …
methods. However, these methods are far from optimal in terms of their accuracy …
[PDF][PDF] A review of missing data handling techniques for machine learning
Real-world data are commonly known to contain missing values, and consequently affect
the performance of most machine learning algorithms adversely when employed on such …
the performance of most machine learning algorithms adversely when employed on such …
Assessing temporal correlation in environmental risk factors to design efficient area-specific COVID-19 regulations: Delhi based case study
Amid ongoing devastation due to Serve-Acute-Respiratory-Coronavirus2 (SARS-CoV-2), the
global spatial and temporal variation in the pandemic spread has strongly anticipated the …
global spatial and temporal variation in the pandemic spread has strongly anticipated the …