Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
The advent of the Internet, the increased processing power as well as increased memory allocation cum usage has continued to advance various frontiers with underlying technologies that seeks to secure and uphold data integrity. Also, with the rising trend of adversaries, new emerging paradigms and platforms seek to create safer means for disseminating data from one source to another. This birthed the emergence of block-chain alongside cryptocurrencies – that have today minimized the sole dependence on banking institutions and the adoption of fiat legacy tenders across borders. With its applications therein, cryptocurrencies have evolved as new transaction paradigm to buy/sell assets amongst other usages. However, the inherent challenges of the block-chain network has continued to call for a shift in focus as well as to address the issues therein. The study presents Pi-Chain network, a directed acyclic graph (DAG) network based on chemical isomerism of position, size and structure of a node. It adapts the many benefits of the block-chain – while evolving the weaknesses therein via reshuffled user model method, which allocates that splits network into two halves via the MLLM (most, least, least, most) scheme.
Watershed modelling is one of the most important factors in the analysis of rainfall-runoff transformations. As an agent of transformation, the catchment plays an important role in determining flow characteristics, especially peak flow as one of flood hydrograph parameters. The main characteristic of this catchment is expressed in the form of surface topography as the basis for determining network channels and its boundaries. The accuracy of determining these two characteristics is largely determined by the type of baseline data used to model the watershed. This study aims to build a watershed model using medium resolution Digital Elevation Model (DEM) data as a flood simulation means. DEM data is derived from Shuttle Radar Topography Mission (SRTM) data with a resolution of 30 meters and is obtained from USGS Earth Explorer for the Bangga Catchment, as one of the flood-prone areas in Central Sulawesi, Indonesia. Channel network derivation and catchment delineation were performed using Raster (R. *), one of QGIS Processing Toolbox. The result of the catchment analysis using this data was also compared with the low-resolution DEM data of 90 meters to determine the effect of DEM resolution on stream network configuration and catchment boundary. Based on this watershed, flood prediction is carried out using the ITS-2 Model, one of the flood estimation models in the form of synthetic unit hydrographs based on river network configuration. The analysis results indicate that the utilization of DEM data with a higher resolution produces smoother catchment features and influences the accumulative length of drainage channels and the area of the catchment. The hydrology simulation using the watershed with the input of design rainfalls shows that the peak flood discharge in the study area for certain return periods is relatively very large for a catchment of fewer than 100 km2 in area
