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:
Internet of Things (IoT) is now one of the most challenging research fields that still has much to be discovered. Since it consists of a wide range of elements like devices, humans, animals, and others, there is a big need to find a simple way of its network simulation. Although there were previous trials to do this, a need exists to combine both modeling and simulation of IoT networks in one frame. In this work we propose a crossbreed approach that enables specialists to display IoT and reproduce OMNeT++, through giving mapping rules between the operator worldview and the OMNeT++ test system. The PDR and RTT results are plotted by varying the number of smart objects (SOs) and subnets for both large and low number scales. Increasing the number of subnetworks in a specific region badly influences both RTT and PDR
The government is actively encouraging food and energy independence to achieve development targets. So, it is necessary to make an inventory of existing rice fields. Identification of rice field area can be done using geographic information system (GIS). By doing so, a comparison of rice field a comparison of rice fields between data and interpretation results can be obtained and rice production in each district in the city of Lubuk Linggau can be predicted. Interpretation was carried out to get the classification of rice fields in the study area by using Landsat 8 Image. The interpretation of the image was carried out on a combination of band 653. The level of accuracy of the results of interpretation of rice fields in Lubuk Linggau City is 98.34%. The interpreted rice fields are smaller than the existing rice fields in the data, which is 55%