• Korean Journal of Child Studies
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• v.15 no.1
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• pp.55-69
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• 1994

The purpose of this study was to investigate methodological and theoretical problems in measuring the acquisition of national identity of in-country and over-seas Korean adolescents. The subjects consisted of 574 incountry and overseas (Chinese, Russia and Japan) Korean adolescents (total 509), 15 to 25 years of age. Data were collected with the use of a questionaire, the Scale of National Identity. The results were that (1) the concept of national identity was organized on two dimensions (cognitive vs. sociocultural). The former consisted of 6 cognitive characteristics (uniqueness, sameness, continuity, acceptability, respectability and royalty). The sociocultural dimension consisted of the cognition of 7 sociocultural characteristics (history, norm, fraternity, symbol, consanguinity, Korean language and nationality). Except for consanguinity, there was a close relationship within each and between the 6 cognitive characteristics. Also there was a close relationship within each and between the 7 sociocultural characteristics of national identity. (2) Some demographic variables, such as age of respondents, place of birth and level of understanding of Korean language contributed to acquisition of national identity. (3) Among several demographic variables, nationality was the most explainable.

• Journal of Magnetics
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• v.16 no.4
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• pp.403-407
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• 2011

Metal-insulator type, nano-granular soft magnetic films have been reviewed from the viewpoint of high frequency magnetic materials. The formation of nano-granular structure is related to the magnitude of heat of formation of intergranule materials. Variation of the ratio of granule phase to intergranule phase in the film is found to produce various characteristics in the magnetic properties of the film. The HRTEM observation reveals that neighboring granules in the film with above 60 at.% Co, contact at considerable points and the films show soft magnetic properties which are explainable in terms of the random anisotropy model for nano-crystalline materials. Addition of Ni group elements in Co-O based films enhances their anisotropy field up to 400 Oe and they exhibit excellent frequency response of permeability. Also, large electromagnetic noise suppression effect is demonstrated as one of their potential applications.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.359-364
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• 1999

Providing the reasonable construction cost at the initial stage of the rural development project, is a kety factor of the each step of project , such as propriety analysis , cost planning , design, and planning the progress of work. The explainable construction cost can be estimated at the early stage using the actual cost data by statistical analysis. In this study, the influence factors are extracted by factor analysis with the actual cost data of rural development project, object cost model is developed by multiple regression analysis, and verify the developed cost model by Monte-Carlo simulation .

• ETRI Journal
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• v.13 no.4
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• pp.25-34
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• 1991

The stability and the electronic structure of $In_0.5$.$Ga_0.5$P-based superlattices are examined through self-consistent ab initio pseudopotential calculations. A chalcopyrite-like structure is found to be the lowest energy state over (001) and (111) monolayer superlattices (MLS). Our calculations indicate that all the ordered structures in bulk form are unstable against phase segregation into binary constituents at T = 0 while for epitaxial growth, the chalcopyrite phase is stabilized. The fundamental band gaps of the ordered structures are found to be direct and smaller than that of disordered alloys. The lowering of the band gap is explainable by band folding and pushing effects. We find the reduction of the band gap to be largest for the (111) MLS.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.9-16
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• 2017

In an English multiple Wh-construction with two wh-words, only a higher-located wh-word in a sentence structure is allowed to pre-pose to the Spec of CP, which has been known as a Superiority Effect(SE). Contrary to English, Korean and Japanese have been known not to respect SE, and this phenomenon has been called an Anti-Superiority Effect(ASE). Recent studies including Takita et al(2007) and Harada(2015) among others, however, have suggested exceptional cases to ASE in Japanese, and attempted to explain them through a feature checking mechanism within the Minimalist Program(MP) by Chomsky(1995, 1998). Such explanations of MP, which are based on the abstract feature checking system, have recently been considered just as a kind of technicalia and should be backed up with further empirical evidence. In this paper, I show that there are also exceptions to ASE in Korean, and the exceptional cases to ASE both in Korean and Japanese can be well explainable based on the empirical evidence of Korean/Japanese morpho-syntax.

• Proceeding of KASS Symposium
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• 2006.05a
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• pp.73-80
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• 2006

In this paper, we work with steel circular tubes and propose analysis model which can consider local buckling that it has an effect on failure of steel structures and induce the relation between loading and deformation. First of all, in respect to axial symmetry local buckling, which is simplest case, elasto-plastic behavior acting only axial loads is object. Therefore, it suggests analysis model for axial symmetry local buckling. And that is explainable the process from increasing internal force to decreasing passing maximum internal force. Besides, we induce the relation between the axial force and axial deformation.

• Electronics and Telecommunications Trends
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• v.34 no.1
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• pp.98-110
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• 2019

Machine learning has been applied to medical imaging and has shown an excellent recognition rate. Recently, there has been much interest in preventive medicine. If data are accessible, machine learning packages can be used easily in digital healthcare fields. However, it is necessary to prepare the data in advance, and model evaluation and tuning are required to construct a reliable model. On average, these processes take more than 80% of the total effort required. In this study, we describe the basic concepts of machine learning, pre-processing and visualization of datasets, feature engineering for reliable models, model evaluation and tuning, and the latest trends in popular machine learning frameworks. Finally, we survey a explainable machine learning analysis tool and will discuss the future direction of machine learning.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.64-70
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• 2021

The future society will be changed through an artificial intelligence (AI) based intelligent revolution. To prepare for the future and strengthen industrial competitiveness, countries around the world are implementing various policies and strategies to utilize AI in the manufacturing industry, which is the basis of the national economy. Manufacturing AI technology should ensure accuracy and reliability in industry and should be explainable, unlike general-purpose AI that targets human intelligence. This paper presents the future shape of the "autonomous factory" through the convergence of manufacturing and AI. In addition, it examines technological issues and research status to realize the autonomous factory during the stages of recognition, planning, execution, and control of manufacturing work.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1122-1137
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• 2021

PM_2.5 concentration in Seoul could be predicted by deep neural network model. In this paper, the contribution of input factors to the model's prediction results is analyzed using the LRP(Layer-wise Relevance Propagation) technique. LRP analysis is performed by dividing the input data by time and PM concentration, respectively. As a result of the analysis by time, the contribution of the measurement factors is high in the forecast for the day, and those of the forecast factors are high in the forecast for the tomorrow and the day after tomorrow. In the case of the PM concentration analysis, the contribution of the weather factors is high in the low-concentration pattern, and that of the air quality factors is high in the high-concentration pattern. In addition, the date and the temperature factors contribute significantly regardless of time and concentration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.1022-1034
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• 2023

Various aspects of artificial intelligence (AI) have become of significant interest to academia and industry in recent times. To satisfy these academic and industrial interests, it is necessary to comprehensively investigate trends in AI-related changes of diverse areas. In this study, we identified and predicted emerging convergences with the help of AI-associated research abstracts collected from the SCOPUS database. The bidirectional encoder representations obtained via the transformers-based topic discovery technique were subsequently deployed to identify emerging topics related to AI. The topics discovered concern edge computing, biomedical algorithms, predictive defect maintenance, medical applications, fake news detection with block chain, explainable AI and COVID-19 applications. Their convergences were further analyzed based on the shortest path between topics to predict emerging convergences. Our findings indicated emerging AI convergences towards healthcare, manufacturing, legal applications, and marketing. These findings are expected to have policy implications for facilitating the convergences in diverse industries. Potentially, this study could contribute to the exploitation and adoption of AI-enabled convergences from a practical perspective.