• Journal of the Korean earth science society
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• v.29 no.6
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• pp.495-505
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• 2008

The main purposes of this study are to: (1) to develop astronomy observation program based on a standardized coefficient decision program; and (2) to apply the developed program to after-school or club activities. As a first step, we analyzed activities related to astronomy in the authorized textbooks that are currently adopted in high schools. based on the analysis, we developed an astronomy observation program according to the standardized coefficient decision program, and the program was applied to students' astronomical observations as part of the club activities. Specifically, this program used a 102 mm refracting telescope and digital camera. we took into account the observation site's environment of the urban areas in which many school were located and then developed a the computer program for observation activities. The results of this study are as follows. First, the current astronomical education in schools was based off of the textbooks. Specifically, it was mostly about analyzing the materials and making simulated experiments. Second, most schools participated in this study were located in urban areas where students had more difficulty in observation than in rural areas. Third, an exemplary method was investigated in order to make an astronomical observation efficiently in urban areas with the existing devices. In addition, the standardized coefficient decision program was developed to standardize the magnitude of stars according to the observed value. Finally, based on the students' observations, we found that there was no difference between the magnitude of a star in urban sites and in rural sites. The current astronomical education in schools lacks an activity of practical experiments, and many schools have not good observational sites because they are located in urban areas. However, use of this program makes it possible to collect significant data after a series of standardized corrections. In conclusion, this program not only helps schools to create an active astronomy observation activity in fields, but also promotes students to be more interested in astronomical observation through a series of field-based activities.

• Korean Security Journal
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• no.11
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• pp.159-181
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• 2006

This study is concerned on Why The Certified Security certification is needed and How to control the security quality to get better service to the clients. Theses days are required The Certified Certificate in all the industry. And in this point of view, the certified certificate is a kind of confirmation by an authority to the person who has how much special knowledge and practice in a certain field. Moreover, in the functionalism society the certified certificate system would be very positive effect to the related industry and society as official measurement by an authority. The security is freedom from fear and anxiety. Which means the security can not be operated in isolation from citizen's safe-living expectation, and which is also dealing with valuable human being's life. For getting the better purpose the security industry employees should have more organized special training and education. As my understanding the certified certificate exam system is the confirmation by an authority, the certified certificate is only neutral evidence to get the confidence and credit from the clients. In this point of view the core point is How to control The Certified Certificate by a credied authority.

• Korean Journal of Psychosomatic Medicine
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• v.11 no.2
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• pp.97-117
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• 2003

Objective: This study is to examine the validity and reliability of Computerized Neurocognitive Function Test among normal children in elementary school. Methods: K-ABC, K-PIC, and Computerized Neurocognitive Function Test were performed to the 120 body of normal children(10 of each male and female) from June, 2002 to January, 2003. Those children had over the average of intelligence and passed the rule out criteria. To verify test-retest reliability for those 30 children who were randomly selected, Computerized Neurocognitive Function Test was carried out again 4 weeks later. Results: As a results of correlation analysis for validity test, four of continues performance tests matched with those on adults. In the memory tests, results presented the same as previous research with a difference between forward test and backward test in short-term memory. In higher cognitive function tests, tests were consist of those with different purpose respectively. After performing factor analysis on 43 variables out of 12 tests, 10 factors were raised and the total percent of variance was 75.5%. The reasons were such as: 'sustained attention, information processing speed, vigilance, verbal learning, allocation of attention and concept formation, flexibility, concept formation, visual learning, short-term memory, and selective attention' in order. In correlation with K-ABC to prepare explanatory criteria, selectively significant correlation(p<.0.5-001) was found in subscale of K-ABC. In the test-retest reliability test, the results reflecting practice effect were found and prominent especially in higher cognitive function tests. However, split-half reliability(r=0.548-0.7726, p<.05) and internal consistency(0.628-0.878, p<.05) of each examined group were significantly high. Conclusion: The performance of Computerized Neurocognitive Function Test in normal children represented differ developmental character than that in adult. And basal information for preparing the explanatory criteria could be acquired by searching for the relation with standardized intelligence test which contains neuropsycological background.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.3
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• pp.142-161
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• 2013

In order to enhance scientific interest and a sense of affinity about ocean, the programs of the oceanic camp 'oceanic summer school' were developed and applied to $4^{th}$ and $9^{th}$-grade elementary and middle school students for 9 years from 2004 to 2012. It was composed of oceanic training for snorkeling, a tour to oceanic institutes and museums near the camp academy place, experimental learning in oceanic-related field, field trips for ocean and earth sciences, and lectures on various subjects of ocean. We developed and implemented 9-kinds of inquiry surveys to evaluate changes in cognitive and affective characteristics, and ocean literacy of students participated at the present oceanic summer camp. Based on the statistical analysis, affective characteristics such as interest, inquisitiveness, passion, and so on, were enhanced. Analysis of ocean literacy revealed that cognitive characteristics of the students were increased by 40%. We presented parents' responses on the programs of oceanic summer school. Some students with less initial interest of ocean have positively changed to make up their minds to be a oceanographer in several years later. In light of this, the summer school can be evaluated to be successfully functioned as a long-term support system for potentially young-talented students in the field of ocean science. This study addresses that long-term implementation of the summer oceanic camp may trigger students with potential talent toward in-depth science in the near future even though it could not bring positive effect immediately. This addresses the necessity of policy supports in order that various programs like the scientific camp should be more constructively developed and executed for next-generation manpower in oceanographic fields.

• Journal of The Korean Association For Science Education
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• v.36 no.5
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• pp.739-756
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• 2016

The purpose of the study is to reflect on 'myself' as a teacher educator of college of education in depth and to improve my instruction through self-study with three critical collaborators. 17 pre-service science teachers and I have participated in this study of a teacher educator's course since March 2016 after the preliminary practice in 2015. The video recorded the course for 11 weeks with about 40 hours of lessons. The data source also included teacher educator's reflective journals, lecture evaluations, online boards and so on. Questionnaires were distributed and answered both at the beginning and at the end of the course and pre-service teachers wrote their reflective journals. Four of them were in the focus group interviews. During the course, the weekly group meeting of critical collaborators analyzed the emerging issues based on the lesson clips and teacher educator's reflective journals with discussion for the course innovation. Four phases were revealed in the process and for the purpose of the course such as exploration, conflicts, challenges, and changes. The results showed that first, we identified tensions among the teacher educator's multiple identities as a lecturer, a faculty member, and a researcher. Second, there were differences between goals of teacher educator and pre-service teachers in the course, and this obstructed the success of the course sometimes. Third, these practices led to explore balanced alternative views and interpretations of the problem by critical views and to expand and improve our teaching practice and thinking. In addition, the self-study with critical collaborators helped to bring conflicts and issues below my practice to light for collaborative reflection and it gave a chance to understand ourselves as teacher educators in different ways.

• Journal of Korean Home Economics Education Association
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• v.16 no.2
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• pp.37-53
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• 2004

The purpose of this study is to observe the developmental Process of interaction and attitude of children through instruction for “making fabric doll”. Based on the theory of “Waldorf Education”, instruction of 8 hours for 3 weeks exercised against 40 children(18 boys, 22 girls) of 6th grade, especially focused two group(10 children), in K elementary school in Chunchoen. The results of the study by qualitative research method through observing, recording, interpretation are as follows 1. The changes in interaction among children were observed in increase of quantity and quality of conversation among children, of reliability and dependence among children, of intimacy and cooperation among children, and of intimacy between teacher and children. 2. The changes in the attitude toward instruction were observed in increase of confidence and satisfaction, of active and attentive attitude to instruction via more interest about own fabric doll, of positive attitude through attachment to the doll. Therefore, the instruction of “making fabric doll” based on “Waldorf Education” seems to be efficient to child development and Practical Arts Education.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.3
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• pp.26-45
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• 2019

Objective : The purpose of this study is to develop educational goals, training content, and training methods for the intervention course of the Korean Academy of Sensory Integration (KASI) and to conduct competency-based intervention courses based on the competency model for sensory integration intervention. Methods : This study was conducted on work therapists who participated in the 2019 intervention course of KASI. In the first phase, educational needs were analyzed to set goals for the interventional course. In the second phase, a meeting of researchers drafted the intervention course education program and the methods of education, and the intervention course was conducted. In the third phase, the changes in educational satisfaction and performance level pre- and post-intervention course for each competency index were investigated. Results : The educational goals of "learning and applying the clinical reasoning process of sensory integration intervention" and "intervention by applying the principle of sensory integration intervention" were set after reflecting on the results of the analysis of the educational requirements. The length of the competency-based intervention course was 42 hours. The average education satisfaction level of participants in the arbitration process was 4.48±0.73, and the average education satisfaction level of the supervisor was 3.92±0.71. In both groups, the most satisfying curriculums were the data-driven decision-making process and the intervention goal-setting lecture. But the satisfaction level of was the lowest. Before and after the intervention course, there were significant changes in the performance of the two behavioral indicators of the analytic skills in the expertise competency cluster of the competency model. Conclusion : This study is meaningful in that it conducted a survey of educational needs, the development and implementation of an educational curriculum, and an education satisfaction survey through systematic courses necessary for education development.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.