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:
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Interventional Pulmonology
This study aims to analyze the forecasting the GHG emission, population, GDP growth of energy consumption in the Industries sectors. The scope of the study covers the analysis of energy consumption, and the forecasting of GHG emission population, GDP growth of energy consumption for the next 10 years (2016-2025), and 20 years (2016-2035) by using Vector Autoregressive Model: VAR Model from the Input-output table of Thailand. The result show that petroleum has the highest level of energy consumption, followed by Other Petroleum Products, Cement, Ceramic and Earthen Wares, Cosmetic, fertilizer and pesticides, soap and cleaning preparations, rubber sheet and block rubber, and petroleum refineries, respectively. The prediction results show that these models are effective in forecasting measured by using RMSE, MAE, and MAPE. The results forecast of each model are as follows: 1) Model 1(2,1,1) shows that GHG emission will, increasing steadily to 25.71% by the year 2025 in comparison to 2016.2) Model 2 (2,1,2) shows that GHG emission will rise steadily, increasing to 45.20% by the year 2035 in comparison to 2016
Malicious software or widely known as malware has inflicted a great number of computers and causing many intrusion and damages that wasted a lot of money and resource. Despite having a new variant and type of malware appeared almost every day, traditional worm such as Blaster are still posing threats these days due to its rapid distribution through the internet. This research is previously analyzed manually using packet analyzer namely tcpdump and wireshark which is time-consuming and inefficient. To overcome this problem, an automated script known as Malware Attack Visualization (MAV) Script is developed to automate the visualization of the malware attack scenario. This script is capable to analyze and dissect the network traffic and represent the scenario in visualization. This information is crucial as it helps to identify the sources of the attack and the location of the incurred damage. Thus, this script will help to determine and visualize the malware attack scenario which eases the process of finding the Attacker, Victim, and Victim/Attacker of the attack
