This paper is concerned with the modeling and identification of time series data corrupted by noise. As modeling techniques, nonsingleton fuzzy logic system (NFLS) is employed for the modeling of corrupted time series. Main characteristic of the NFLS is a fuzzy system whose inputs are modeled as fuzzy number. So the NFLS is especially useful in cases where the available training data or the input data to the fuzzy logic system are corrupted by noise. Simulation results of the Mackey-Glass time series data will be demonstrated to show the performance of the modeling methods. As a result, NFLS does a much better job of modeling noisy time series data than does a traditional Mamdani FLS.
This descriptive investigation aims to identify a relationship between QOL, depression, and anxiety in hemodialysis patients. I conducted this research on 130 subjects aged 19 or above who have received dialysis for at least one month in the hemodialysis unit at N hospital in the city of S. However, it came to 112 as I took out those who either quit, died, or filled out a questionnaire in the incorrect manner. In regards to average points of QOL on a 100-point scale, it is 57.77, demonstrating quite low QOL. Concerning average points of depression and anxiety, it is 12.25 and 10.52, respectively, showing quite a high figure. With regard to a correlation, there is a significant correlation between the three factors in hemodialysis patients: there is a negative correlation between QOL and depression (r=-.782, p<.001); a negative correlation between QOL and anxiety (r=-.719, p<.001); and a positive correlation between depression and anxiety (r=.873, p<.001). The outcome of multiple regression analysis on factors affecting QOL shows that depression is the element influencing QOL (β=-.585). Therefore, this study is significant in providing basic data for establishing intervention strategies aiming to reduce levels of depression which has the strongest impact on QOL in the patients and for developing a nursing intervention program intending to improve their QOL.
The purpose of study was to analyze the trends of 2005 to 2018 revised 'convergence technology research' through text network analysis using NetMiner4.0 program. Data analysis was conducted by using keyword analysis, centrality analysis of 653 authors' keyword from 177 journals. The results of the study are as follows. First, Research on Converging Technology has been studied steadily over the past 13 years in Department of Industry Convergence. Second, the results of the search term frequency analysis show that the 'convergence technology', 'technology convergence', 'convergence', 'design', 'convergence education', 'STEAM', 'convergence research' were used as the main keywords of convergence technology research. Third, Community analysis results show that five communities have been classified five categories according to the characteristics of the search terms 'only IT', 'Cultural industry utilizing Convergence contents', 'Technology innovation and research analysis' And patent development'. Based on these results, we proposed the future directions of convergence technology research.
In this paper, we developed a chatbot system using the Django framework using the KakaoTalk API so that college students can easily search for important information in their university. Unlike existing chatbot systems that provide only specific information, the chatbot developed in this research automatically provides search results for various types of user queries such as weather, YouTube, Naver real-time ranking search and language translation as well as important information within their own university. We developed a module using Apache, Python and Django in AWS Ubuntu server and developed a chatbot system that automatically responds to user queries by communicating with KakaoTalk server using KakaoTalk API and BeautifulSoup. The system developed in this study is expected to be applicable to the future university entrance information promotion and election promotion system.
This paper examines smart warning triangles to prevent secondary accidents on roads. After a traffic accident on the road, a safety tripod must be installed to notify the accident. However, it can cause secondary accidents during warning triangle installation. To solve this problem, a smart warning triangle was proposed and implemented. A smart warning triangle acts as a triangle through a logo light projector when it detects an impact. Arduino functions as an impact detector and a logo light projector. The proposed smart safety tripod is expected to help prevent secondary accidents by acting as a safety tripod if the brightness of illumination is complemented.