• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.37-52
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• 2015

In this study, assessment items to examine geocognition on plate tectonics were developed and applied to middle and high school students and college students. Conceptual constructs on plate tectonics are Earth interior structure, specific geomorphology, and geologic phenomena at each plate boundary. Construct for geocognition included temporal reasoning, spatial reasoning, retrospective reasoning, and system thinking. Pictorial data in each item were all obtained from GeoMapApp. Students' responses to the items were analyzed and measured cross-sectionally by Rasch model, which distinguishes persons' ability levels based on their scores for all items and compared them with item difficulty. By Rasch model analysis, Wright maps for middle and high school students and college students were obtained and compared with each other. Differential Item Functioning analysis was also implemented to compare students' item responses across school grades. The results showed: 1) Geocognition on plate tectonics was an assessable construct for middle and high school students in current science curriculum, 2) The most distinguished geocognition factor was spatial reasoning based on cross sectional analysis across school grades, 3) Geocognition on plate tectonics could be developed towards more sophisticated level through scaffolding of relevant instruction and earth science content knowledge, and 4) Geocognition was not a general reasoning separated from a task content but a content-specific reasoning related to the content of an assessment item. We proposed several suggestions for learning progressions for plate tectonics and national curriculum development based on the results of the study.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.658-672
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• 2022

The unique teaching and learning difficulties of speed-related units in elementary school science are mainly due to the student's lack of mathematical thinking ability and procedural knowledge on speed measurement, and curriculums and textbooks must be constructed with these in mind. To identify the implications of composing a new science curriculum and relevant textbooks, this study reviewed the structure and contents of the speed-related units of three curriculums from the 2007 revised curriculum to the 2015 revised curriculum and the resulting textbooks and examined their relevance in light of the literature. Results showed that the current content carries the risk of making students calculate only the speed of an object through a mechanical algorithm by memorization rather than grasp the multifaceted relation between traveled distance, duration time, and speed. Findings also highlighted the need to reorganize the curriculum and textbooks to offer students the opportunity to learn the meaning of speed step-by-step by visualizing materials such as double number lines and dealing with simple numbers that are easy to calculate and understand intuitively. In addition, this paper discussed the urgency of improving inquiry performance such as process skills by observing and measuring an actual object's movement, displaying it as a graph, and interpreting it rather than conducting data interpretation through investigation. Lastly, although the current curriculum and textbooks emphasize the connection with daily life in their application aspects, they also deal with dynamics-related content somewhat differently from kinematics, which is the main learning content of the unit. Hence, it is necessary to reorganize the contents focusing on cases related to speed so that students can grasp the concept of speed and use it in their everyday lives. With regard to the new curriculum and textbooks, this study proposes that students be provided the opportunity to systematically and deeply study core topics rather than exclude content that is difficult to learn and challenging to teach so that students realize the value of science and enjoy learning it.

• Journal of The Korean Association For Science Education
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• v.41 no.6
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• pp.441-454
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• 2021

In this study, we propose the composition of contents on the area of astronomy for high school Earth Science elective courses for the 2022 revised curriculum based on high school students' perceptions of changes in Earth Science core concepts over the curriculum revisions, and analysis of learning elements in the area of astronomy for domestic and foreign Earth Science curriculum. Four Earth Science education experts compared and analyzed the astronomy contents presented in Korea, the US, British Columbia (BC) in Canada, Japan, and the International Baccalaureate Diploma Program (IBDP) curriculum. According to the survey results, high school students who answered that they were most interested in the core concepts of astronomy expressed a lot of regret that the contents related to astronomical observation were eliminated from the 2015 revised curriculum. As a result of comparing domestic and foreign curriculum, Korea and IBDP curriculum dealt with the largest amount of learning elements in astronomy. In the case of BC in Canada and IBDP, astronomy was offered as an independent subject, and the curriculums of Japan and Korea dealt with astronomy in the Earth Science subject. According to the results, it is necessary to develop general elective courses in Earth Science with astronomy-related contents with high discriminating power in order to strengthen astronomy education. Since astronomy requires background knowledge from various disciplines and inter-disciplinary learning was required, it is necessary to organize the career-related elective courses in Earth Science so that astronomy can be dealt with according to the knowledge structure of general Astronomy. Based on the research results, ways to organize astronomy contents for Earth Science elective courses were suggested.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.437-449
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• 2024

Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.121-130
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• 2024

As internet and communication technology (ICT) is improved exponentially, types and amount of available data also increase. Even though data analysis including statistics is significant to utilize this large amount of data, there are inevitable limits to process various and complex data in general way. Meanwhile, there are many attempts to apply machine learning (ML) in various fields to solve the problems according to the enhancement in computational performance and increase in demands for autonomous systems. Especially, data processing for the model input and designing the model to solve the objective function are critical to achieve the model performance. Data processing methods according to the type and property have been presented through many studies and the performance of ML highly varies depending on the methods. Nevertheless, there are difficulties in deciding which data processing method for data analysis since the types and characteristics of data have become more diverse. Specifically, multi-variate data processing is essential for solving non-linear problem based on ML. In this paper, we present a multi-variate tabular data processing scheme for ML-aided data analysis by using Titanic dataset from Kaggle including various kinds of data. We present the methods like input variable filtering applying statistical analysis and normalization according to the data property. In addition, we analyze the data structure using visualization. Lastly, we design an ML model and train the model by applying the proposed multi-variate data process. After that, we analyze the passenger's survival prediction performance of the trained model. We expect that the proposed multi-variate data processing and visualization can be extended to various environments for ML based analysis.

• The Journal of Korean Philosophical History
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• no.35
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• pp.223-248
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• 2012

This research is to investigate his creative perspective to Deahak through Seoktan Lee Shin-Ui's Daehakcharok. Lee Shin-Ui is a scholar and politician in the middle of Joseon Dynasty. His ancestral home is Jeonui. The honor name is Gyeongchik and pen name is Seoktan. The posthumous name is MunJeong. His Daehakcharok was written in the process of taking basic foundation as the politic leader. It was a record that he usually wrote down things realized after reading Deahakjanggu. Seoktan clearly classified the meaning of Jang (chapter) and Gu (phrase) as the structure of Deahakjanggu, and created new realm about the method of classified study. In the preface of Deahakjanggu, he emphasized that the core of Deahak is in Gyeong (敬, respect or honor), and clarified that Deahak deals with Sim (心, mind) and Seong (性, human nature). In the interpretation of Daehakdeajeon, he thought that the core of Samgangnyeong (三綱領, three doctrines or essential principles) depended on Myeong (明, realizing), Shin (新, taking re-newness), and Ji (止, achieving) as the meaning of 'realizing, taking re-newness, and achieving', and interpreted the context of Tao (道, the way), Myeong (明, realizing), and Deuk (德, virtue) in detail. In addition, he interpreted various concepts and meaning of Deahak with Myeongmyeongdeuk (明明德, realizing human nature) and Sinmin (新民, renewing people) as relationship with Ji(知, realization), Haeng(行, practice), Che(體, main structure), and Yong (用, dealing with), and developed Neo-Confucianism deeply. In case of the main interpretation of Deahakjanggu, he analytically reviewed 50 phrases one by one throughout 10 total chapters. In case of chapter five which includes Zhuzi's the theory of Gyeokmul (格物, approaching things or persons), he interpreted it in three parts and classified Gyeokmulchiji (格物致知, approaching things or persons and then realizing their nature) about researching deeply of principle and each thing, and Mulgyeokjiji (物格知至, approaching things or persons and then realizing them) about all things. He arranged in order of 'principle- researching-result' as well. In final, chapter ten showing the core of politic thought emphasized the way of Hyeolgu (?矩, considering others' situation through his/her own experience) intensively and informed that it is the best virtue for a governor.

• Journal of Service Research and Studies
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• v.11 no.4
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• pp.1-20
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• 2021

This study was conducted to derive a model of the legal system that is the basis for realizing the service economy, political administration, and social education system. Based on the experience of mankind's legal system operation in the historical era for the past 5,000 years, a legal system model that will make the future human society sustainable has been established. The problems of the current legal system were analyzed at the fundamental level. The root cause of injustice and unfairness was analyzed and a new legal system was designed. Through the legal systems of various national societies that have been attempted in the history of mankind, the structure of the legal system that is desirable for the modern society was designed. Human society, which has experienced how much good legal system has been and is being abused by human irrationality and nonsense, needs to make an effort to change the legal system paradigm itself by learning lessons from failure. This study derives the basis for a legal system that can realize justice and a fair society in the long term. It proposed a model for improving the legal system that allows human society to be happy for a long time. To this end, the fundamental role of the legal system was analyzed at the ideological level and the problems of the current legal system were presented. In addition, the problem of fundamental assumptions about human nature was analyzed and improved assumptions were presented. The structural system of the current legal system was analyzed and a new structure was proposed. In addition, a plan for the operation of a new legal system based on a new structure was suggested. The new legal system was named servicism system. This is because it is a model centered on thorough checks and balances between all opponents, not a simple linear one-dimensional legal system, but a multidimensional legal system, and because it is a viewpoint that clearly recognizes both human reason and desire. The new system is a model that reflects the confrontation between the rule of law and the non-law rule and the confrontation between the power people and the general public. A follow-up study is needed on a concrete plan for transitioning from the current legal system to a new legal system.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.91-116
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• 1991

Market liberalization progressing simultaneously with high and rapidly rising domestic wages has created an adverse business environment for domestic firms. Korean firms are losing their international competitiveness in comparison to firms from LDC(Less Developed Countries) in low-tech industries. In high-tech industries, domestic firms without government protection (which is impossible due to the liberalization policy and the current international status of the Korean economy) are in a disadvantaged position relative to firms from advanced countries. This paper examines the division of roles between the private sector and the government in order to achieve a successful structural adjustment, which has become the impending industrial policy issue caused by high domestic wages, on the one hand, and the opening of domestic markets, on the other. The micro foundation of the economy-wide structural adjustment is actually the restructuring of business portfolios at the firm level. The firm-level business restructuring means that firms in low-value-added businesses or with declining market niches establish new major businesses in higher value-added segments or growing market niches. The adjustment of the business structure at the firm level can only be accomplished by accumulating firm-specific managerial assets necessary to establish a new business structure. This can be done through learning-by-doing in the whole system of management, including research and development, manufacturing, and marketing. Therefore, the voluntary cooperation among the people in the company is essential for making the cost of the learning process lower than that at the competing companies. Hence, firms that attempt to restructure their major businesses need to induce corporate-wide participation through innovations in organization and management, encourage innovative corporate culture, and maintain cooperative labor unions. Policy discussions on structural adjustments usually regard firms as a black box behind a few macro variables. But in reality, firm activities are not flows of materials but relationships among human resources. The growth potential of companies are embodied in the human resources of the firm; the balance of interest among stockholders, managers, and workers of the company' brings the accumulation of the company's core competencies. Therefore, policymakers and economists shoud change their old concept of the firm as a technological black box which produces a marketable commodities. Firms should be regarded as coalitions of interest groups such as stockholders, managers, and workers. Consequently the discussion on the structural adjustment both at the macroeconomic level and the firm level should be based on this new paradigm of understanding firms. The government's role in reducing the cost of structural adjustment and supporting should the creation of new industries emphasize the following: First, government must promote the competition in domestic markets by revising laws related to antitrust policy, bankruptcy, and the promotion of small and medium-sized companies. General consensus on the limitations of government intervention and the merit of deregulation should be sought among policymakers and people in the business world. In the age of internationalization, nation-specific competitive advantages cannot be exclusively in favor of domestic firms. The international competitiveness of a domestic firm derives from the firm-specific core competencies which can be accumulated by internal investment and organization of the firm. Second, government must build up a solid infrastructure of production factors including capital, technology, manpower, and information. Structural adjustment often entails bankruptcies and partial waste of resources. However, it is desirable for the government not to try to sustain marginal businesses, but to support the diversification or restructuring of businesses by assisting in factor creation. Institutional support for venture businesses needs to be improved, especially in the financing system since many investment projects in venture businesses are highly risky, even though they are very promising. The proportion of low-value added production processes and declining industries should be reduced by promoting foreign direct investment and factory automation. Moreover, one cannot over-emphasize the importance of future-oriented labor policies to be based on the new paradigm of understanding firm activities. The old laws and instititutions related to labor unions need to be reformed. Third, government must improve the regimes related to money, banking, and the tax system to change business practices dependent on government protection or undesirable in view of the evolution of the Korean economy as a whole. To prevent rational business decisions from contradicting to the interest of the economy as a whole, government should influence the business environment, not the business itself.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.77-88
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• 2017

Recently, with the advent of knowledge based society where information and knowledge make values, patents which are the representative form of intellectual property have become important, and the number of the patents follows growing trends. Thus, it needs to classify the patents depending on the technological topic of the invention appropriately in order to use a vast amount of the patent information effectively. IPC (International Patent Classification) is widely used for this situation. Researches about IPC automatic classification have been studied using data mining and machine learning algorithms to improve current IPC classification task which categorizes patent documents by hand. However, most of the previous researches have focused on applying various existing machine learning methods to the patent documents rather than considering on the characteristics of the data or the structure of patent documents. In this paper, therefore, we propose to use two structural fields, technical field and background, considered as having impacts on the patent classification, where the two field are selected by applying of the characteristics of patent documents and the role of the structural fields. We also construct multi-label classification model to reflect what a patent document could have multiple IPCs. Furthermore, we propose a method to classify patent documents at the IPC subclass level comprised of 630 categories so that we investigate the possibility of applying the IPC multi-label classification model into the real field. The effect of structural fields of patent documents are examined using 564,793 registered patents in Korea, and 87.2% precision is obtained in the case of using title, abstract, claims, technical field and background. From this sequence, we verify that the technical field and background have an important role in improving the precision of IPC multi-label classification in IPC subclass level.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.