• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.4
• /
• pp.563-568
• /
• 2007

This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

• Journal of KIISE:Computing Practices and Letters
• /
• v.5 no.6
• /
• pp.782-792
• /
• 1999

효과적인 ATM 망의 관리는 연결 지향 환경, 다양한 서비스 등급, 대규모 트래픽, 가상 망 구성 그리고 여러가지 트래픽 유형 등과 같은 다양한 ATM 특성을 다룰 수 있어야만 한다. 이를 위해 ATM 포럼에서는 ATM 장치, 사설망, 공중망 및 그들간의 상호작용을 지원하기 위한 ATM 망 관리 참조 모델을 정의하였으며, 그 중 하나가 서로 다른 판매자로부터의 ATM 장비들간의 상호동작성을 보장하기 위해 SNMP 기반 망 관리 프로토콜을 통해 상호 연결된 인터페이스를 관리할 수 있도록 정의된 통합 지역 관리 인터페이스(ILMI) 프로토콜이다. ILMI의 목적은 두 인접한 ATM 장치로 하여금 그들 간에 공통의 ATM 링크에 대한 동작 파라메타를 자동적으로 구성할 수 있도록 함으로서, 관리자에 의해 수동 구성이 아닌 ATM 장치 상호간의 플러그 앤 플러그 기능을 지원하는데 있다. 본 논문에서는 이러한 ILMI 기술을 바탕으로 공중망 ATM 교환기에 연결된 가입자의 물리 인터페이스, ATM 계층 인터페이스, VPC 및 VCC의 구성 및 상태 정보를 효율적으로 관리하며, 가입자 시스템의 ATM 주소를 자동으로 등록, 관리할 수 있도록 하는 가입자 인터페이스 관리 시스템(SIMS)을 설계하고, 구현하였다. Abstract An effective ATM management must address the various features of ATM such as connection-oriented environment, varying class of service, large scale traffic, virtual network configurations and, and multiple traffic types. For this, ATM network management reference model defined by ATM Forum describes the various types of network management needed to support ATM devices, private networks, public networks, and the interaction between them. One of these types is Integrated Local Management Interface (ILMI) defined to manage interconnected interface through SNMP-based network management protocol for ensuring the interoperability of ATM devices from different vendors. The purpose of ILMI is to enable two adjacent ATM devices to automatically configure the operation parameters of the common ATM link between them and then to provide a Plug and Plug function to any ATM devices with not a passive configuration by manager but a automatic configuration. This paper design and implement a Subscriber Interface Management System (SIMS) which provide automatic registration and management of ATM address of subscriber system and efficiently manages physical interface of subscriber who is connected to public ATM switch, ATM layer interface, configuration information and status information of VPC and VCC.

• Journal of Digital Convergence
• /
• v.17 no.9
• /
• pp.259-269
• /
• 2019

This study analyzed convergent factors related to self-leadership of female freshmen in health majors studying TOEIC. The survey was conducted from April 29, 2019 to May 10, 2019 using unregistered self-administered questionnaire for 201 female freshmen in health majors and they were randomly selected from TOEIC class in college located in J city. The results of hierarchical multiple regression analysis show the following. The self-leadership of respondents turned out to be significantly higher in following groups: a group in which self-competence is higher, a group in which subdivision task self-efficacy and coping self-efficacy is higher, and a group in which subdivision chance of locus control from locus of control is lower. Their explanatory power was 49.7%. The results of the study indicate that the efforts to manage self-competence, self-efficacy, and locus of control are required to improve the self-leadership of female freshmen in health majors studying TOEIC. These results can be used for academic counseling guidance to enhance self-leadership of female freshmen in health majors studying TOEIC. In the future research, it is necessary to establish and analyze a structural equation model that affects self-leadership of male and female college students in health majors studying TOEIC.

• Journal of IKEEE
• /
• v.23 no.1
• /
• pp.112-119
• /
• 2019

In this paper, we propose a deep learning structure suitable for embedded system. The flame detection process of the proposed deep learning structure consists of four steps : flame area detection using flame color model, flame image classification using deep learning structure for flame color specialization, $N{\times}N$ cell separation in detected flame area, flame image classification using deep learning structure for flame shape specialization. First, only the color of the flame is extracted from the input image and then labeled to detect the flame area. Second, area of flame detected is the input of a deep learning structure specialized in flame color and is classified as flame image only if the probability of flame class at the output is greater than 75%. Third, divide the detected flame region of the images classified as flame images less than 75% in the preceding section into $N{\times}N$ units. Fourthly, small cells divided into $N{\times}N$ units are inserted into the input of a deep learning structure specialized to the shape of the flame and each cell is judged to be flame proof and classified as flame images if more than 50% of cells are classified as flame images. To verify the effectiveness of the proposed deep learning structure, we experimented with a flame database of ImageNet. Experimental results show that the proposed deep learning structure has an average resource occupancy rate of 29.86% and an 8 second fast flame detection time. The flame detection rate averaged 0.95% lower compared to the existing deep learning structure, but this was the result of light construction of the deep learning structure for application to embedded systems. Therefore, the deep learning structure for flame detection proposed in this paper has been proved suitable for the application of embedded system.

• Journal of Digital Convergence
• /
• v.17 no.11
• /
• pp.269-278
• /
• 2019

This study ascertained convergent influence on self-leadership and its association with self-competence, self-efficacy and locus of control among female freshmen in health majors studying TOEIC. Data collection was carried out using a self-administered questionnaire from April 29, 2019 to May 10, 2019 and the target was randomly selected 201 female freshmen in health majors in TOEIC class from college located in J city. Self-leadership was positively correlated with self-competence, self-efficacy and locus of control. The covariance structure analysis showed that the higher self-competence, the higher self-efficacy and the lower locus of control tend to increase self-leadership. The results of the study indicate that the efforts, to increase self-competence and self-efficacy, to decrease locus of control, are required to improve self-leadership of female freshmen in health majors studying TOEIC. These results are expected to be used for educational counseling and intervention efforts to enhance self-leadership among female freshmen in health majors studying TOEIC. In future studies, further research on additional factors affecting self-leadership is needed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.362-373
• /
• 2021

This is an action research study of mixed methodology design to confirm the implementation process and effects of applying visual thinking and window paning on improving nursing ethics and professional courses. Based on the conceptual model for action research, a quantitative and qualitative approach was taken. The data was collected and analyzed in an integrated manner. The survey analysis was done using the SPSS WIN 23.0 program. The participants were interviewed after experiencing the techniques in class and content analysis was used on the answers. As a result of applying visual thinking and window paning, ethical decision-making confidence (t=6.748, p<.001) and nursing professional intuition (t=-3.52, p<.001) showed statistically significant changes. There was, however, no significant change in biomedical ethics consciousness (t=1.291, p=.199). Qualitative analysis found that they had fresh experience, an unfamiliar but comfortable feeling, feeling of being mine, insufficient time, systematic case study approach based on theory, were able to cultivate cooperation and coordination ability through discussion and experience in various professional fields, pride, ethical responsibility consciousness and were able to apply learning content in the field. Visual thinking and window paning foster diverse competencies in nursing education and help integrative learning. Therefore, based on the results it is proposed that visual thinking and window paning are applied to the improvement of instruction in other courses to develop core nursing competency.

• Journal of the Korea Convergence Society
• /
• v.12 no.11
• /
• pp.185-191
• /
• 2021

The purpose of this study is to develop middle school English classes using Problem-Based Learning(PBL) based on flipped learning and to examine its effects. Recently, various attempts to combine flipped learning and PBL have been made; however, many studies have not been applied to middle and high school curriculums yet. The attempt of this study is expected to have theoretical and practical significance. The instructional model was derived from the review of previous studies, and the development of instructional program followed the general design procedure(analysis-design-development-implement-evaluation), and its validity was secured with the advice of related experts. To verify the effectiveness of the program, the English academic achievement test and the English key competency test were conducted before and after the program. Changes in English academic achievement were analyzed by the paired-sample t-test, and the effect of key competency and the level of achievement test performance (high vs, low) on the pre-post score change was analyzed by the mixed effects repeated measures ANOVA. As a result of the analysis, both academic achievement and key competencies increased, and the low-level students in the pre-academic achievement test showed more improvements. In conclusion, the PBL class based on flipped learning is effective in improving the English academic achievement and key competencies of middle school students, and in particular, it is shown to be an effective teaching method for students with low academic achievement.

• Journal of Korean Home Economics Education Association
• /
• v.33 no.4
• /
• pp.31-48
• /
• 2021

The purpose of this study was to provide an understanding of the trajectories of multidimensional health among older adults, including depression, chronic diseases, and cognitive function. Data were drawn from the 1-6 waves of the Korean Longitudinal Study of Ageing(KLoSA), and a sample of 2,059 respondents aged 65 and older at baseline was used for the analyses. Latent growth curve models and growth mixture models were used to explore the changes in depression, chronic diseases, cognitive function, and heterogeneous trajectories among them. One-way ANOVAs with Scheffé post-hoc analysis and chi-square tests were used to find differences in sociodemographic characteristics, health behaviors, and life satisfaction across the latent trajectory classes. Latent growth curve models revealed that depressive symptoms and the number of chronic diseases increased over time, while cognitive function showed gradual decreases. Three heterogeneous patterns of multidimensional health trajectories were identified: normal aging, increase in chronic diseases, and chronic deterioration. Significant differences were observed in sociodemographic characteristics, health behaviors, and life satisfaction across the three latent classes. In particular, low educational attainment, household income, and life satisfaction were associated with the chronic deterioration class. Based on the findings, we discussed suggestions for health promotion education targeting older adults. This study also emphasizes the importance of home economics education in promoting health literacy across the life course.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.273-275
• /
• 2022

The use of drugs by pregnant women poses a potential risk to the fetus. Therefore, it is essential to classify drugs that pregnant women should prohibit. However, the fetal toxicity of most drugs has not been identified. This takes a lot of time and cost. In silico approaches, such as virtual screening, can identify compounds that may present a high risk to the fetus for a wide range of compounds at the low cost and time. We collected class information of each drug from the hazard classification lists for prescribing drugs in pregnancy by the government of Korea and Australia. Using the structural and chemical features of each drug, various machine learning models were constructed to predict fetal toxicity of drugs. For all models, the quantitative performance evaluation was performed. Based on the attention algorithm, important molecular substructures of compounds were identified in the process of predicting the fetal toxicity of the drug by the proposed model. From the results, we confirmed that drugs with a high risk of fetal toxicity can be predicted for a wide range of compounds by machine learning. This study can be used as a pre-screening tool for fetal toxicity predictions, as it provides key molecular substructures associated with the fetal toxicity of compounds.

• Journal of the Korean earth science society
• /
• v.45 no.1
• /
• pp.48-71
• /
• 2024

Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.