• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1172-1184
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• 2003

At present, new techniques based on different component reference models for the integration of component and system of different platforms, such as EJB and COM+, are introduced. The operation between the components in the identical component platform is realized by the composition at the source level. In case of the different component platform, however, it is impossible to use combined components in real condition although they are components of similar domain. In this paper we proposed a solution for the composition problem by using component transformation methodology based on model between EJB and COM+ components which are different components. For the composition between EJB and COM+ components, we compared and analyzed each reference model, then proposed the Virtual Component Model which is implementation independent and the Implementation Table for the mutual conversion. Reffering to the Virtual Component Model and the Implementation Table, we can generalize each Implementation model to the Virtual Component Model, make the Virtual Component Model which is implementation independent through the virtual component modeling, transform EJB and COM+ components selectively. Proposing the effective Model Transformation method to the different component platform, we can combine EJB and COM+ components.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.427-436
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• 2022

Korea Trade-Investment Promotion Agency (KOTRA) annually publishes the trade data in South Korea under the guidance of the Ministry of Trade, Industry and Energy in South Korea. The trade data usually contains Gross domestic product (GDP), a custom tariff, business score, and the price of export items in previous and this year, with regards to the trading items and the countries. However, it is challenging to figure out the meaningful insight so as to predict the future price on trading items every year due to the significantly large amount of data accumulated over the several years under the limited human/computing resources. Within this context, this paper proposes a multi layer perception that can predict the future price of potential trading items in the next year by training large amounts of past year's data with a low computational and human cost.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.301-307
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• 2024

This study introduces a novel cascade fusion architecture aimed at enhancing thermal images across various scale conditions. The processing of thermal images at multiple scales has been challenging due to the limitations of existing methods that are designed for specific scales. To overcome these limitations, this paper proposes a unified framework that utilizes cascade feature fusion to effectively learn multi-scale representations. Confidence maps from different image scales are fused in a cascaded manner, enabling scale-invariant learning. The architecture comprises end-to-end trained convolutional neural networks to enhance image quality by reinforcing mutual scale dependencies. Experimental results indicate that the proposed technique outperforms existing methods in multi-scale thermal image enhancement. Performance evaluation results are provided, demonstrating consistent improvements in image quality metrics. The cascade fusion design facilitates robust generalization across scales and efficient learning of cross-scale representations.

• The Journal of Sustainable Design and Educational Environment Research
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• v.16 no.1
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• pp.20-29
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• 2017

In order to prove the hypothesis that the element of school location planning - the density of development, availability of various private institutes, the location of school, the type of school district, the distance to nearby schools, the existence of communal areas, the pedestrian street, the number of road lanes - affects the increase and decrease of the number of students in the long term, we examined the tendency of the number of long-term (24 years). The results of the analysis are as follows: First, the development factors such as development density, location of school, type of school district, distance from neighboring schools, separation of pedestrians and cars are clearly related. Second, the planning factors such as location of private school and installation of pedestrian-only street seem to be related to each other. Third, the number of road lanes and element of "communal area" is irrelevant. This study is limited to generalization of five new metropolitan cities in the metropolitan area, and it is necessary to further elaborate the analysis factors and evaluation criteria.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.109-122
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• 2018

The composite lognormal-generalized Pareto distribution (LN-GPD) is a mixture of right-truncated lognormal and GPD for a given threshold value. Scollnik (Scandinavian Actuarial Journal, 2007, 20-33, 2007) shows that the composite LN-GPD is adequate to describe body distribution and heavy-tailedness. This paper considers time-varying modeling of the LN-GPD based on local polynomial maximum likelihood estimation. Time-varying model provides significant detailed information of time dependent data, hence it can be applied to disciplines such as service engineering for staffing and resources management. Our work also extends to Beirlant and Goegebeur (Journal of Multivariate Analysis, 89, 97-118, 2004) in the sense of losing no data by including truncated lognormal distribution. Our proposed method is shown to perform adequately in simulation. Real data application to the service time of the Israel bank call center shows interesting findings on the staffing policy.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.602-617
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• 2020

The aim of this study is to evaluate the effects of income-led growth path induced by government and consumption expenditures. Six of Nordic countries, Latin American countries and South Korea are selected for this purpose due to the fact that these countries have been pursuing income-led growth policy for more than the last decade except South Korea. The structural equation is formulated based on the government and consumption expenditures with lagged variable, and the GLMs estimation is employed for empirical analysis. Although the impacts are not overwhelmingly effective, empirical evidence suggests that income-led growth path contributes to stimulate economic activities which are associated with increasing in national income in Nordic countries and South Korea. However, the income-led growth path is quite weakly operated. Furthermore, it is even unstable in Latin American countries. In addition to this, the policy target would rather be focused on middle consumption group than low consumption group. Overall, it would be concluded that the income-led growth policy should be implemented for complementary purpose. And, it also has to be mentioned that sustainable growth may not be achievable by this policy.

• Journal of the Korean Geotechnical Society
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• v.19 no.4
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• pp.299-310
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• 2003

In the evaluation of the subgrade stiffness structure by the SASW method, the calculation of the phase velocities is the important task controlling the reliability of the result. The interpretation of the phase spectrum should precede the phase-velocity calculation in the current practice of the SASW method. The difficulty involved in the interpretation prohibited the SASW method from being spread over to the industry. This study proposed a new method called the frequency-wave number technique, which is based on the frequency-wave number relationship of the surface wave in the multi-layered system. The frequency-wave number technique eliminates the expertise in the interpretation of the phase spectrum, automates the phase-velocity calculation and expedites the determination of the phase-velocity dispersion curve. To verify the validity of the proposed frequency-wave number method, the transfer function determined from the numerical simulation of the SASW measurements was used fir the calculation of the automatic calculation of the phase velocities and compared with the phase velocities by WinSASW employing the phase-unwrapping method. Also, the proposed method was applied to the real SASW measurements performed at$\bigcirc$$\bigcirc$area in GyeongGi-Do to see how the proposed method works with the real measurements.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.731-746
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• 1997

The usage of object models for the development of software has been frowung due to the prevalence of the ob-ject oriented paradigm.The object moedels produced as results of requirments analysis and design activities are vety veneficial to the implementation phase.It is even possible for source code to be genrated automatically if object models are concrete enough.Therefore system analyzers and desingners should make an dffort to refine theabstrace ogject model defined at.an early stage in order to achieve a more conrete object model.In general,re-fining an abstrace object model into a concrete model depends too much on the desigver's infromal experience.In this paper,we persent the refinement techniques required for concreting an abstract object model bassed on OMT(Object Modeling Technique)'s notation,We will discuss the definition of the abstraction level of an object model and the transformational rules of refinement.These transformational rules are currently applied to the design of a software tool,named Process Modeler,which is a major component of the software development process modeling system for ICS(Information Communication Service). Finally we can achieve a concrete object model which can easily be translated into C++ source code.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.274-274
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• 2019

최근 하천에서 실시간 유량측정을 위하여 유수에 접촉 또는 비접촉 유속측정방식을 이용한 자동유량측정시스템이 설치 운영되고 있으며, 주로 지표유속법(index velocity method)이 적용되고 있다. 지표유속법 적용을 위해서는 다양한 범위에서 측정된 지표유속과 평균유속관계를 분석해야한다. 그러나 유속계 설치초기에는 측정된 유속이 없기 때문에 측정된 유량을 신뢰하기가 어렵다. 본 연구에서는 비접촉 유속계인 전자파표면유속계(MU2720)로 측정된 표면유속과 지표유속법을 이용하여 일반적인 하천에서 비접촉(레이다 또는 전자파표면유속계 등) 방식에 의한 자동유량측정 시스템 운영초기에 적용 가능한 경험적 지표-평균유속 관계식을 개발하여 검토하였다. 연구 대상지점은 한탄강(1개소), 홍천강(3개소), 내린천(2개소), 북천(1개소), 탄천(1개소), 섬강(1개소) 등 6개 하천 9개 지점이며, 2016~2018년에 지점별로 측정된 총 103개(6~26개)의 측정자료를 이용하여 분석하였다. 지점별 최대유속이 발생하는 지표유속과 평균유속과의 관계를 분석한 결과 결정계수(R2)가 0.8848(원주시(문막교))~0.9874(서울시(대곡교))로 평균 0.9626를 보여 매우 높은 상관성을 보였다. 또한 9개 지점의 모든 유속자료를 통합하여 지표-평균유속 관계식을 개발하였다. 그 결과 결정계수는 0.9247를 보였으며, 유속분포가 일반적이지 않은 홍천강의 홍천군(반곡교), 섬강의 원주시(문막교) 지점 자료를 제외한 7개 지점의 자료만으로 지표-평균유속 관계식을 개발한 결과 결정계수가 0.9603으로 매우 높은 상관성을 보였다. 이러한 결과를 볼 때 일반적인 유속분포(포물선형태)를 가진 하천은 본 연구에서 7개 지점으로 개발된 지표-평균유속 관계식을 운영초기에 활용할 수 있을 것으로 판단된다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.