• Korean Journal of Comparative Education
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• v.24 no.3
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• pp.179-198
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• 2014

The purpose of this study is to find some implications for improving diversities of the senior high school system in Korea, by examining those of Australian high school system. Based on the literature review, school diversification can be defined as providing students or their parents with some range of alternative programs from which they can choose a school or program they believe are best suitable for them. In this point, the concept is very similar to that of school choice. The finding of this study can be summarized as follows. First, the programs of within-school diversification at Australian senior secondary schools include subject selecting, extension programs and vocational education and training courses(VET). Second, selective schools, independent schools and specialist schools are the types of between-schools diversity programs in Australia. Third, the characteristic of Australian school diversification was traditionally between-schools diversification, of which the purpose is to provide excellent learning opportunities for some talented students. However, the policy trend has, recently, been extended to within-school diversity programs. The conclusions of this study are as follows. First, the policy of high school diversification 300 in Korea can be seen as a suitable one because one of its aims was to overcome some limitations of the school equalization policy. Second, well defined within-school diversity programs should be considered in order to avoid educational disadvantage issues in education that can be inevitably risen from between-school diversification policies. Lastly, the possibilities of implementing VET programs at general high schools should also be urgently considered.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.1-11
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• 2021

Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.

• 재활복지
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• v.21 no.4
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• pp.177-193
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• 2017

The purpose of this study was to examine the factors that affect the awareness of disabled in undergraduate students. A sample of 1,998 respondents was surveyed. Of these, a total of 1,957 questionnaires were analysed excluding the 41 questionnaires that did not agree with the survey or had a missing data. The questionnaire consists of the general characteristics, experience related to disability and disability awareness and we used a 4-point Likert scale. Collected data was analyzed using the SPSS 24.0 program and descriptive statistics, t-test, variance analysis and multiple regression analysis were used. According to the results of the study, the disability awareness score of our respondents was average 40.52. Second, female students had more positive about disability awareness than male ones, and senior students had more positive awareness than other grade students. Third, non-rehabilitation department students' disability awareness was more positive than rehabilitation students. Fourth, the disability awareness of people who have a acquaintance member with disability or health worker were significantly positive. Finally, the awareness of people who experienced at the disability related institution were significantly positive. Therefore, to improve the awareness of undergraduate students about disabilities, it is required to activate positive contact experiences with people with disabilities rather than theoretical learning.

• Korean Journal of Heritage: History & Science
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• v.52 no.1
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• pp.170-189
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• 2019

Sochi Heo Ryun (小癡 許鍊, 1808-1893) was a literary artist of Chinese paintings of the Southern School during the late Joseon dynasty and the founder of paintings in the literary artist's style of Jindo County in South Jeolla Province. He was also a professional literary artist who acquired both learning and painting techniques under Choui (a Zen priest) and Kim Jeong-hee's teachings. Heo Ryun's landscape paintings were influenced by Kim Jung -hee. However, his ink orchid paintings, which he began producing in his later years, were not related to the 'Ink Orchid Paintings of Chusa (秋史蘭)'. His ink orchid paintings as a whole drew attention as he followed the old methods but still used rough brush strokes . Ordinary orchids were drawn based on Confucian content. However, his Jebal (題跋) and seal (印章) contain not only Confucian characters but also Taoist and Buddhist meanings. Therefore, it is possible to guess his direction of life and his private world of suffering. Ryun's ink orchid paintings reflected a variety of philosophies and aesthetic sensibilities. He went through a process of stylistic change over time and formed an 'Ink Orchid Painted Thought' in later life. The main characteristic of Sochi's ink orchid paintings is that he formed his own special methods for orchid paintings by mimicking the Manuals of Paintings. He drew orchids with his fingers in the beginning. Then, Jeongseop, Lee Ha-eung, Cho Hee-ryong, and others developed an organic relationship with the painting style of ink orchid paintings. Then in later years, orchid paintings reached the point of 'Picture Painted Thought (寫意畵)'. The above consideration shows that ink orchid paintings, which he produced until the end of his life, were the beginning of his mental vision and will to realize the image of a literal artist.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.28-34
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• 2022

This study analyzes the impact that accidents and near misses have on clients' and contractors' awareness of safety culture. Due to the unique characteristic of employment structure in Korea, the occurrence of accidents differs by company size, which has relevant implications for the establishment of safety culture. Attention has been drawn to the importance of the management of accidents and near misses, with safety awareness acting as a core factor. A positive effect on the prevention of accidents could be achieved by noting the difference in safety awareness between clients and contractors and suggesting an associated suitable safety management system. In support of this study, a survey was distributed to workers in the automobile manufacturing industry (May-August 2020), and data from a total of 574 workers was collected and analyzed, including 399 clients' worksers and 175 contractors' workers. The questionnaire addressed participants' experiences of accidents and near misses as well as 50 items from the Nordic Occupational Safety Climate Questionnaire. Analysis of the responses was conducted using the methods of frequency analysis, Fisher's exact test, t-test, correlation analysis, and regression analysis. The results demonstrated that clients had more experiences with accidents and near misses compared to contractors. Additional differences between clients and contractors were noted in terms of the safety culture factors of learning, communication, and trust. A correlation was observed between the experience of accidents and safety justice management: for clients and contractors who experienced accidents, safety justice management was 9.4 times higher. Furthermore, clients' and contractors' awareness of employees' commitment to safety was determined to be 28.5 times higher in those who had experienced near misses This study concludes that, in order to improve accident prevention through the management of accidents and near misses, clients must focus on overseeing safety justice management and aspects of safety culture factors, while contractors must focus efforts on managing employees' commitment to safety. In further applications, this study could provide baseline data for health and safety activities in terms of the safety culture of clients and contractors. Further study on the establishment of safety culture as related to employment structure is proposed for future research.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.133-142
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• 2023

In this paper, we built a data-driven artificial intelligence model using RNN-LSTM (Recurrent Neural Networks-Long Short-Term Memory) to predict the Lorenz system, and examined the possibility of whether this model can replace chaotic dynamic models. We confirmed that the data-driven model reflects the chaotic nature of the Lorenz system, where a small error in the initial conditions produces fundamentally different results, and the system moves around two stable poles, repeating the transition process, the characteristic of "deterministic non-periodic flow", and simulates the bifurcation phenomenon. We also demonstrated the advantage of adjusting integration time intervals to reduce computational resources in data-driven models. Thus, we anticipate expanding the applicability of data-driven artificial intelligence models through future research on refining data-driven models and data assimilation techniques for data-driven models.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.173-191
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• 2024

Typhoons are significant meteorological phenomena that cause interactions among the ocean, atmosphere, and land within Earth's system. In particular, wind speed, a key characteristic of typhoons, is influenced by various factors such as central pressure, trajectory, and sea surface temperature. Therefore, a comprehensive understanding based on actual observational data is essential. In the 2015 revised secondary school textbooks, typhoon wind speed is presented through text and illustrations; hence, exploratory activities that promote a deeper understanding of wind speed are necessary. In this study, we developed a data visualization program with a graphical user interface (GUI) to facilitate the understanding of typhoon wind speeds with simple operations during the teaching-learning process. The program utilizes red-green-blue (RGB) image data of Typhoons Mawar, Guchol, and Bolaven -which occurred in 2023- from the Korean geostationary satellite GEO-KOMPSAT-2A (GK-2A) as the input data. The program is designed to calculate typhoon wind speeds by inputting cloud movement coordinates around the typhoon and visualizes the wind speed distribution by inputting parameters such as central pressure, storm radius, and maximum wind speed. The GUI-based program developed in this study can be applied to typhoons observed by GK-2A without errors and enables scientific exploration based on actual observations beyond the limitations of textbooks. This allows students and teachers to collect, process, analyze, and visualize real observational data without needing a paid program or professional coding knowledge. This approach is expected to foster digital literacy, an essential competency for the future.