ABSTRACT:Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Shuttle Radar Topography Mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available Digital Elevation Model (DEM) datasets for environmental modeling and studies. The quality of spatial resolution and vertical accuracy of the DEM data source has a great influence particularly on the accuracy specifically for inundation mapping. Most of the coastal inundation risk studies used the publicly available DEM to estimated the coastal inundation and associated damaged especially to human population based on the increment of sea level. In this study, the comparison between ground truth data from Global Positioning System (GPS) observation and DEM is done to evaluate the accuracy of each DEM. The vertical accuracy of SRTM shows better result against ASTER and GMTED10 with an RMSE of 6.054 m. On top of the accuracy, the correlation of DEM is identified with the high determination of coefficient of 0.912 for SRTM. For coastal zone area, DEMs based on airborne light detection and ranging (LiDAR) dataset was used as ground truth data relating to terrain height. In this case, the LiDAR DEM is compared against the new SRTM DEM after applying the scale factor. From the findings, the accuracy of the new DEM model from SRTM can be improved by applying scale factor. The result clearly shows that the value of RMSE exhibit slightly different when it reached 0.503 m. Hence, this new model is the most suitable and meets the accuracy requirement for coastal inundation risk assessment using open source data. The suitability of these datasets for further analysis on coastal management studies is vital to assess the potentially vulnerable areas caused by coastal inundation.

This study presents a case study of a novel hybrid solar chimney power plant (HSCPP) design’s performance in the city of Doha, Qatar. The HSCPP construction is similar to the traditional solar chimney power plant (SCPP) but with the addition of water sprinklers installed at the top of the chimney. This allowed the solar chimney (SC) to operate as a cooling tower (CT) during the nighttime and operate as an SC during the daytime, hence providing a continuous 24-h operation. The results showed that the HSCPP produced ~633 MWh of electrical energy per year, compared to ~380 MWh of energy produced by the traditional SCPP. The results also showed that the HSCPP was able to produce 139,000 tons/year of freshwater, compared to 90,000 tons/year produced by the traditional SCPP. The estimated CO2 emission reduction (~600 tons/year) from the HSCPP is twice that of the traditional SCPP (~300 tons/year). The results clearly show that the HSCPP outperformed the traditional SCPP.

An accurate measurement of intrinsic hand muscle strength (IHMS) is required by clinicians for effective clinical decision-making, diagnosis of certain diseases, and evaluation of the outcome of treatment. In practice, the clinicians use Intrins-o-meter and Rotterdam Intrinsic Hand Myometer for IHMS measurement. These are quite bulky, expensive, and possess poor interobserver reliability (37-52%) and sensitivity. The purpose of this study was to develop an alternative lightweight, accurate, cost-effective force measurement device with a simple electronic circuit and test its suitability for IHMS measurement. The device was constructed with ketjenblack/deproteinized natural rubber sensor, 1-MΩ potential divider, and Arduino Uno through the custom-written software. Then, the device was calibrated and tested for accuracy and repeatability within the force range of finger muscles (100 N). The 95% limit of agreement in accuracy from -1.95 N to 2.06 N for 10 to 100 N applied load and repeatability coefficient of ±1.91 N or 6.2% was achieved. Furthermore, the expenditure for the device construction was around US$ 53. For a practical demonstration, the device was tested among 16 participants for isometric strength measurement of the ulnar abductor and dorsal interossei. The results revealed that the performance of the device was suitable for IHMS measurement.

Abstract. Coastal vulnerability Index (CVI), is one of the predictive approaches to coastal classification by incorporating various coastal variables. This approach is favoured in the coastal investigation as it simplifies a number of complex parameters. However, it comes greatly as to why such assessment is developed in the first place; a) to facilitate coastal management in recent coastal condition, b) to classify potential shoreline responses to future sea-level rise, and c) for management of data storage. Index development in coastal investigation is one of the present-day technique used to estimate the vulnerability of the coast and is affected by a diverse range of variables. The widespread use of contemporary technology nowadays has led to a favourable coastal component to be considered in determining coastal vulnerability and environmental risk analysis. Therefore, it must be guided by acknowledging appropriate data to be used at spatial scale of interest, the geomorphology of the area concerns and etc. USA and European countries like Northern Ireland are one of the forefront country in addressing the significance of CVI in protecting coastal area. A stepwise approach to development of CVI is discussed in detail in this paper. Besides, the potential of including coastal components based on special characteristic at particular coasts for coastal vulnerability analysis are also reviewed. CVI eventually will assist coastal communities in providing guidance for mitigation of coastal threats in future urban development.

ABSTRACT:The advancement of satellite altimeter technology has generated many evolutions to oceanographic and geophysical studies. A multimission satellite altimeter consists with TOPEX, Jason-1 and Jason-2, ERS-2, Envisat-1, CryoSat-2 and Saral are extracted in this study and has been processed using Radar Altimeter Database System (RADS) for the period of January 2005 to December 2015 to produce the sea surface height (hereinafter referred to SSH). The monthly climatology data from SSH is generated and averaged to understand the variation of SSH during monsoon season. Then, SSH data are required to determine the localised and new mean sea surface (MSS). The differences between Localised MSS and DTU13 MSS Global Model is plotted with root mean square error value is 2.217 metres. The localised MSS is important towards several applications for instance, as a reference for sea level variation, bathymetry prediction and derivation of mean dynamic topography.