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 surge of water flow (SWF) in a river is a dangerous phenomenon that occurs along the water stream. SWF can create an even more dangerous situation called tidal head (TH). High rainfall rates cause river water levels to rise, with high currents leading to TH. Heavy downpour at the upstream creates sudden increase in river water and brings along silts, rocks, branches, and logs, where it rams everything in its path as water travels downstream. In tropical countries, rivers are one of the most popular recreational spots. Tourists engaged in activities such as swimming are unaware of the presence of TH, and they have no time to evacuate. This situation can cause injuries and even fatality. One of the ways to prevent the catastrophic effects of TH is to detect it early. Hence, a TH warning system based on LoRa network technology is developed to prevent accidents or death risks. The system is designed to provide early warning to tourists and the safety personnel monitoring the river and the waterfall. The warning comes in the form of a physical siren and an alert notification via a website accessible through a computer or smartphone. The system prototype consists of LoRa module that remotely transmits warning data with the help of Arduino and water sensors. The prototype is designed to monitor part of the river where the sensors are mounted to the distance where the siren can be heard, and a web application is monitored by the safety personnel or forest wardens to alert the tourists about the occurrence of a TH.
The important role in project management is to estimate the software effort. Inaccurate results may cause to over or under in estimating effort, which can have afflictive outcome on the resources of project. The Constructive Cost Model (COCOMO II) is one of the most mathematical models widely and known for estimating software effort which is influenced by two parameters. To estimate these parameters, there are many techniques used for this purpose. The optimized model produces optimal parameters to estimate the software effort. In this paper, a hybrid model of ant-lion optimization algorithm and cuttlefish algorithm (HALOCF) have been proposed for optimizing two parameters of COCOMO II to solve the parameters estimation problem. The proposed model is performed using two sets of data: NASA 93 and NASA 60 datasets to verify the accuracy of it and evaluated by using Magnitude of Relative Error (MMRE). The results showed that the effort estimation MMRE for the proposed model is more effective than COCOMO II and many other technologies