• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.411-420
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• 2018

This study was conducted to identify the effects of interpersonal communication between health care providers after receiving supplementary education. The participants of this study were 433 health care providers who work at 29 general hospitals in Gwangju Metropolitan City and Jeollanamdo Province. Data were collected from June 8 to June 25, 2018 and evaluated by t-tests, dispersion analysis, correlation analysis and stepwise regression. The results were produced by investigating interpersonal communications according to socio-demographic and health-related characteristics including age, education level, bed size of the hospital at which the participant worked, job satisfaction, hospital location, personal health status, experience with health care management and experience with depression. There were significant differences in communication observed according to supplemental education awareness regarding age, bed size of hospital, occupation, wage, type of medical institution of employment, job satisfaction, work location, health status, health care education experience and chronic disease. There were positive correlations between supplemental education awareness in health workers and their interpersonal communication. The factors that had positive effects on interpersonal communication were level of education and health-related education experience, while age, hospital bed size and job dissatisfaction had negative effects. Finally, support environment, learning transfer and results were identified as sub-factors of supplemental education. Based on the results above, it was proposed that educational training to enhance results, provide a supportive environment and foster learning transfer be developed to increase communication between health workers and provide a safe health service for patients.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.267-277
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• 2021

Both teachers and learners should participate in non-face-to-face class due to COVID-19. The non-face-to-face class has brought about many problems, where they made adequate preparations for such abrupt situation. This study attempted to understand and improve problems occurring during non-face-to-face midi class. The findings are as follows: First, there were differences in equipment available to contact and non-face-to-face class. Such a problem could be improved by using Reaper, DAW which can be installed and freely utilized without any functional limits, regardless of the types of operating systems. Second, latency could not be reduced, when the screen share function of Zoom was used, since it was impossible to select audio interface's drivers in DAW. This problem was improved by again receiving audio output as input and sending it, from the perspectives of teachers. In addition, learners who used the operating system of Windows and have no audio interfaces usually suffer from latency during practices. The latency can be reduced by installing Asio4all. Third, image degradation and screen disconnection phenomena occurred due to the lack of resource. Two computers were connected by using a capture board and the screen disconnection phenomena could be improved by distributing resources and maintaining high-resolution. The system for allowing non-face-to-face midi class could be successfully established, as one more computer was connected by using Vienna Ensemble Pro and more plug-ins were used by securing additional resources. Consequently, the problems of non-face-to-face midi class could be understood and improved.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.215-226
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• 2022

This study analyzed the trends and causes of the decline in Korean students' positive experiences about science (PES). To do this, 4th to 10th grade students were sampled by grade at general elementary, middle, and high schools in Seoul, and then a questionnaire was administered to ask the students about their PES and the causes for their decline. The results of one-way ANOVA for Test for Indicators of Positive Experiences about Science (TIPES) revealed that there were no statistically significant differences according to grade and school level in the overall mean of TIPES scores. However, the results were slightly different for each sub-component. That is, in 'science academic emotion,' the mean of elementary school students was statistically significantly higher than that of middle school students. In addition, the mean of 4th graders was significantly higher than the mean of middle school 1st graders, middle school 3rd graders, and high school 1st graders, respectively. The mean of high school students was statistically significantly higher than that of middle school students in 'science-related career aspiration.' In the 'science-related self-concept', 'science learning motivation,' and 'science-related attitude,' the differences in scores according to grade and school level were not statistically significant. The main causes of the decline in each sub-components of PES were somewhat different depending on the school level. Based on these results, the ways to improve students' PES were sought according to grade and school level.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.69-75
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• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).

• Journal of Korean Home Economics Education Association
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• v.19 no.1 s.43
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• pp.47-64
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• 2007

The purpose of this study was to develop, apply and evaluate the teaching learning plan for disabled experimental activity to evaluate the accessibility of middle school experimental facilities. Three main resources such as 2 hours teaching learning plan for disabled activity, recording sheets and evaluation sheets had been developed. The process plan had been applied 214 senior students in 7 middle schools purposely selected by areas, constructed years, number of stories of school during November to December, 2005. General accessible levels of middle school facilities was somewhat inadequate especially exterior slops, toilets, bowls were the most unaccessible ones. Most of all students had accidents and/or injuries in school environments from minor to major ones. Male Students were more likely than female Students to get injuries. Students experience of accidents and injuries and awareness of inconvenience, danger, needed facilities supported. the result of the accessibility levels evaluated by disabled activities. Students were generally satisfied with and positive to the teaching learning process plan developed and applied in this study. Students had improved critical Perspectives as well as awareness of inaccessible chances in the school facilities through the experimental process. The evaluation as differed by school characteristics and students' interests in disability.

• Analytical Science and Technology
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• v.28 no.3
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• pp.187-195
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• 2015

The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.229-237
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• 2007

In this study, an artificial neural network (ANN)-based damage detection algorithm using acceleration signals is developed for real-time alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed tot damage detection in real time. The cross-covariance of two acceleration-signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained lot potential loading Patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.287-297
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• 2012

In order to prepare for the introduction of the E-Discovery system from the United States and to cope with some causable changes of legal systems, we propose a general E-Discovery process and essential tasks of the each phase. The proposed process model is designed by the analysis of well-known projects such as EDRM, The Sedona Conference, which are advanced research for the standardization of E-Discovery task procedures and for the supply of guidelines to hands-on workers. In addition, Machine Learning Algorithms, Open-source libraries for the Information Retrieval and Distributed Processing technologies based on the Hadoop for big data are introduced and its application methods on the E-Discovery work scenario are proposed. All this information will be useful to vendors or people willing to develop the E-Discovery service solution. Also, it is very helpful to company owners willing to rebuild their business process and it enables people who are about to face a major lawsuit to handle a situation effectively.