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:
Kongzhi yu Juece/Control and Decision
Azerbaijan Medical Journal
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Zhonghua yi shi za zhi (Beijing, China : 1980)
Changjiang Liuyu Ziyuan Yu Huanjing/Resources and Environment in the Yangtze Valley
Tobacco Science and Technology
Shenyang Jianzhu Daxue Xuebao (Ziran Kexue Ban)/Journal of Shenyang Jianzhu University (Natural Science)
General Medicine (ISSN:1311-1817)
Twitter is social media that can be used to exchange ideas and give opinions. Twitter users can write their opinions on the issue of President Joko Widodo's government. Tweet data or public opinion can be done sentiment analysis method to analyze public opinion. The Naïve Bayes method is used to classify Twitter data to determine sentiment and grouping into positive class and negative class. Furthermore, topic modeling is carried out with the Latent Dirichlet Allocation (LDA) method to determine the topic of discussion in each sentiment group. In the classification process, the value of accuracy depends on the preprocessing stage and relies on the data amount. In train data 80% and test data 20% obtained accuracy 84.58%, recall 85%, precision 85% and F1-Score 85%. At the LDA stage, performance testing with perplexity resulted in a perplexity value of 7.1049 based on the number of iterations of 30 for the positive sentiment group. Furthermore, the perplexity value is 7.3165, with the number of iterations is 60 for the negative sentiment group.
Direction of arrival (DOA) estimation methods of electromagnetic wave sources are necessary for very critical and significant applications, which is considered as a significant branch in array signal processing. There is a need to monitor spectrum and broadcast sources specifically in the military applications, which is very important for monitoring the direction of any threat. DOA is a set of calculations that employ for estimating the direction and number of incoming waves on the antenna elements at a specific range of frequency, which allows target detection and tracking. This paper presents types of super-resolution DOA algorithms with using uniform linear array (ULA) in case of white noise. As well as it clarifies the DOA estimation concepts with its mathematical model for each method. Consequently, we use MATLAB simulations to simulate each DOA method with various cases to evaluate its performance to obtain the required accuracy with the resolution for each DOA algorithm. Therefore, the main goal of this paper to show, which DOA algorithm achieves the best performance and better resolution for the all possible angles with the same number of antenna, and gives very high accuracy in target location estimation and its tracking.
