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Cloud and cloud shadow cause information loss in optical remote sensing analysis. South East Asia, especially Vietnam, Sentinel-2 imagery has short re-visit cycle and observations tend to be contaminated with cloud and cloud shadow. Traditional cloud removal methods require close date multi-temporal data to avoid seasonal land cover changes. In this study, a method of integrating Deep Convolutional Neural Networks (DCNN) and Generative Adversarial Network (GAN) was proposed. This machine learning model estimates the information loss over cloud contaminated areas on a single Sentinel-2 image. The results show that for images with cloud cover rate under 25%, our model can reconstruct cloudless images with PSNR (25 – 40 dB) and SSIM (0.86 – 0.93) compared to real clear images. On the other hand, with cloud cover rate up to 40%, the model performance will be affected heavily by the distribution of cloud and cloud shadow areas. By investigating DCNN and GAN, our method has proven to be an effective tool to remove cloudy images with low and medium rates, which enriches the clear optical remote sensing data sources for environment monitoring.

Co x Pt 100−x nanoparticles ( x = 50, 59, and 73) were prepared by the chemical reduction of Cobalt (II) chloride and Chloroplatinic acid, then ultrasonicated for 2 h. After annealing at various temperatures from 450 °C to 700 °C for 1 h, structure change was observed and samples show hard magnetic properties which depend strongly on chemical composition and annealing temperature. The highest coercivity value of 1.15 kOe was obtained at room temperature for sample with x = 50 annealed at 500 °C. Chemical reduction combined with ultrasound is a useful method to prepare CoPt nanoparticles.

Demanding for high thermal and electrical conductive copper-based composites for structural, electrical and thermal applications are being indispensable. In this work, a method is proposed to improve the electrical and thermal conductivity of multi-walled carbon nanotubes/copper (MWCNTs/Cu) composites by applying the annealing process. The effect of annealing temperatures on the electrical and thermal properties of MWCNTs/Cu composite containing 0.5 vol% MWCNTs prepared by conventional sintering followed by cold rolling was investigated. The experimental results indicated that as increasing annealing temperature, the electrical and thermal conductivity increased due to the recovery, the recrystallization and the grain growth of the Cu matrix. The electrical and thermal conductivity of cold rolled MWCNTs/Cu composite annealed at 500 °C are improved up to 9% and 19% respectively compared to the composite without annealing. The coefficient of thermal expansion (CTE) of the MWCNTs/Cu composite is 8% lower compared to the pure Cu attributed to uniform dispersed MWCNTs, low coefficient of thermal expansion of MWCNTs, good bonding between CNTs and the matrix.

Multi-walled carbon nanotube (MWCNT)/Cu composite containing 0.5 vol% MWCNTs were prepared by a high energy ball milling followed by conventional sintering and finally cold rolling. Microstructure studies showed that MWCNTs were uniformly dispersed and implanted inside the Cu matrix. The MWCNT/Cu composites showed an improvement in hardness and tensile strength up to 37% and 44% respectively compared to those of pure Cu. The enhancement is attributed to the uniform dispersion and strengthening due to the addition of MWCNTs. The yield strength of the composite has been quantified by several strengthening mechanisms including grain boundary strengthening, dislocation strengthening, Orowan strengthening and load transfer. The calculated results indicated that the load transfer strengthening has the largest contribution to the yield strength of the composite which implied the key role of the interfacial bond strength between MWCNTs and Cu matrix on the strengthening behaviors. The friction coefficient and specific wear rate of the composites were reduced with the addition of MWCNT content due to the self-lubrication effect of CNTs and high mechanical properties.

Magnetic nanoparticles CoPt were prepared by the chemical reduction of cobalt (II) chloride and chloroplatinic acid, then the samples were ultrasonicated for 2 h. After annealing at various temperatures from 400°C to 700°C for 1 h, the samples showed hard magnetic properties with coercivity up to 1.15 kOe at room temperature.