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 roughness coefficient determines the flow resistance in a channel and its accurate estimation is essential for channel design and hydraulic modeling of water systems. Several studies have proposed different equations and methods for their calculation. However, authors differ between each other due to the variability of the flow, thus the coefficient calculation has become a challenging task because of the associated level of uncertainty. In this paper an extensive review of the methods habitually used to calculate the roughness of uniform and natural channels was carried out, considering the regimes associated with the bed microforms. Likewise, the mathematical models developed by different authors for the prediction of bedforms and the calculation of the roughness coefficient are detailed. Finally, a table is presented as a summary exposing each of the proposed equations and their conditions of use to simplify the selection process by readers and encourage the execution of research where the applicability of the different proposals is compared.
This paper discusses the traffic signs recognition by Android Studio and Java language with OpenCV library. This is the first project implemented in this way with clarifying the steps scientifically explained. It has a great impact in our daily life which gives notification about our speed and the traffic signs during driving car and makes us less accidents and avoid drivers from over speeding and doesn’t miss the traffic signs by the drivers and provide the drivers with pieces of information which help in driving safe and conveniently. The aim of this paper is to amalgamate state of the art technique for Road Sign Detection and Recognition with the goal of conquering greater accuracy with a real-time performance. An extra level of driver assistance is furnished by the Road Sign Detection and Recognition (RSDR)
In the present study, the test of the susceptibility of the plant Bassia muricata L., through the effect of the extract of hot water on the bacteria (Pseudomonas aeruginosa). Where the plant was collected from Baghdad and different areas along the banks of the Tigris River. The histological sections of the stem were examined and studied. The stems of the young plant were characterized by thick Sclerenchyma. Soil samples were collected from different areas on the banks of the Tigris River after soil examination was isolated and diagnosed with Pseudomonas aeruginosa.
Results showed laboratory study, the hot water extract of Bassia muricata L. was highly effective in inhibiting the growth of Pseudomonas aeruginosa. The objectives of the study are the need to look for alternatives to antibiotics for diseases; given the risks posed by the use of antibiotics; the development of microbial resistance; and the inefficiency of traditional methods to control disease elimination. There is a need to encourage researchers to find plant alternatives and less toxicity, less toxic, less dangerous, and cheap and effective, not as polluting to the environment as possible, for this reason, this study of the effect of hot water for Bassia muricata L. extract on the growth of bacteria in the laboratory. This plant has been selected for its abundance as a wild plant prevalent in Baghdad. The main objective of this study is to use alternative medicines, which will be available, safe, and cheap instead of the high costs and somewhat harmful drugs.
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
