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Hill forest vegetation cover in the southeastern part of Bangladesh has been facing degradation and depletion over a few decades. The forest estimation and mapping of this country are well documented and mainly restricted to the mangrove extent. However, the monitoring of the hill forest vegetation of Bangladesh is limited till now. This study monitor and analyzes the forest vegetation cover changes using Landsat imagery from 1974 to 2020, specifically in Khagrachari and Rangamati hill district, Bangladesh. We preprocess the satellite imagery and then perform a decision tree classification algorithm based on the spectral indexes derived from the imagery. The initial assessment indicates the negative change of dense vegetation/forest vegetation cover (FVC) in most parts of the study area since 1974. Further results show that ~57.17%, ~39.3%, ~31.27%, and ~24.97% of the total area were classified as FVC type in 1989,1999, 2010 and 2020, respectively. Besides, this study briefly discusses how the change of FVC impacts the life of the local indigenous community living around the area. This preliminary investigation highlights deforestation over the ~46 years around the study area, which could be beneficial for planning to manage and conserve forest resources, and protect the local indigenous community. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is one of the most significant vegetable crops grown globally, especially in developing countries. Over the last few years, global potato production has been increasing. This growth has created many opportunities for developing a wide range of value-added products from these crops. However, this requires monitoring the quality components of the tubers, such as moisture content, starch content, and soluble solid content. In particular, moisture content is one of the key quality parameters important for ensuring quality control throughout the supply chain and processing for consumer consumption. Ideally, moisture content would be estimated at the field level; however, current methods used by the industry to assess moisture content are time-consuming, labor-intensive, and destructive. Hence, the purpose of this study is to investigate the feasibility of hyperspectral imaging to quantify the moisture content of unpeeled potatoes before they were subsequently stored and processed. Hyperspectral images are collected from 47 intact potato tubers, with partial least squares regression (PLSR) models developed to predict moisture content from these spectra. The models showed predictive abilities for moisture content with acceptable ratios of prediction to deviation (RPDs) when considering the complete wavelength range (R2 = 0.53, RPD = 1.46, root mean square error (RMSE) = 5.04%) or the β-coefficient wavelength selection technique (R2 = 0.53, RPD = 1.47, RMSE = 5.02%). Furthermore, the prediction ability increased by more than 10% when the model wavelength was narrowed down to 733–970 nm. This study demonstrates the potential of using hyperspectral imaging for the quality assessment of intact, unpeeled potatoes, although further work is required to improve the model quality and implement this approach using remote sensing imagery. [ABSTRACT FROM AUTHOR]

Our earth is a water planet; nearly two thirds of the earth’s surface is covered by ocean water. But the shortage of fresh water is a major problem in many areas, especially in rural villages near to the sea or islands. Now, renewable energy-based desalination system is rising around the world due to the adverse environmental effect and high-energy requirements of the conventional fuel-based desalination system. This paper describes the prospect of an off-grid stand-alone wave-powered reverse osmosis desalination system for those areas. A simulation model for the prediction of the wave power delivered for a given value of the wave height and period is adopted. Based on the availability of the wave data, the amount of the water produced at different sites of Malaysia can be calculated in this paper. In addition, this paper deals with an economical analysis of wave energy production for reverse osmosis desalination system. [ABSTRACT FROM PUBLISHER]

Energy is one of the most important factors in the socioeconomic development of a country. In a developing country like Malaysia, the development of islands is mostly related to the availability of electric power. As an island surrounded by sea, power generated by wave energy source will become one of the most promising solutions for the electrification of island areas. But, the unpredictable nature of the wave energy source is the main drawback. This paper presents a novel stand-alone wave energy supply system modeling with maximum power tracking and an energy storage-based power management algorithm in MATLAB/Simulink environment. The main contributions of this research work are eliminating the intermittent power generation nature of wave energy and efficiently extract the maximum wave power. In the proposed stand-alone system, a DC–DC bidirectional buck-boost converter controller is used to maintain the constant dc-link voltage. It also accumulates the surplus wave power in the battery bank and supplies this power to the load during the wave power shortage. A three-phase complex vector control scheme voltage source inverter is used to control the load-side voltage in terms of the frequency and voltage amplitude. Based on the simulation results obtained from MATLAB/Simulink, it has been found that the overall system is capable of working under variable weather and load conditions, and it can also able to extract the maximum wave power. [ABSTRACT FROM PUBLISHER]

Today, the whole world faces a great challenge to overcome the environmental problems related to global energy production. Most of the islands throughout the world depend on fossil fuel importation with respect to energy production. Recent development and research on green energy sources can assure sustainable power supply for the islands. But unpredictable nature and high dependency on weather conditions are the main limitations of renewable energy sources. To overcome this drawback, different renewable sources and converters need to be integrated with each other. This paper proposes a standalone hybrid photovoltaic- (PV-) wave energy conversion system with energy storage. In the proposed hybrid system, control of the bidirectional buck-boost DC-DC converter (BBDC) is used to maintain the constant dc-link voltage. It also accumulates the excess hybrid power in the battery bank and supplies this power to the system load during the shortage of hybrid power. A three-phase complex vector control scheme voltage source inverter (VSI) is used to control the load side voltage in terms of the frequency and voltage amplitude. Based on the simulation results obtained from Matlab/Simulink, it has been found that the overall hybrid framework is capable of working under the variable weather and load conditions.