• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.525-543
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• 2008

Recently, the scope of user interface is increasing the relative importance in software development dramatically. As a result, there are various relative technologies like as SWING, MFC, Web 2.0, and etc. However, most current software developments are progressed in separate development process with user interface part and business part respectively. This causes the problems, like as a difficulty in the integration process, an development period's delay, and a poor reusability for the constructed models. That is, the extendability and reusability of the created models is being decreased because UI modeling is not systematic and hierarchical, and the consistent integration technique between UI modeling and business modeling does not supported. To solve these problems, this paper proposes an unified and systematic UI modeling process based on UML, using the hierarchical metamodel according to the abstraction levels of development phase. We suggest an UI metamodel, which contains a hierarchy by layering the modeling elements in PIM and PSM based on maturity degree of the development. An hierarchical modeling process combined UI modeling and business modeling is built by applying the UI and business metamodel in terms of three modeling phases(concept/specification/concrete). The effectiveness of the modeling process is shown by applying the proposed process into an Internet Shopping Mall System. Through the exploratory results, the hierarchical UI metamodel and process can produce systematic and layered UI models. This can improve the quality and reusability of models.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.4
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• pp.299-308
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• 2004

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance probability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a Protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated for the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as teaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.357-364
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• 2014

The first mission for the IoT based hyper-connectivity communication is developing a device-to-device communication technique in infra-less low-power and lossy networks. In a low-power and lossy wireless network, IoT devices and routers cannot keep the original path toward the destination since they have the limited memory. Different from the previous light-weight routing protocols focusing on the reduction of the control messages, the proposed scheme provides the light-weight IPv6 address auto-configuration, IPv6 neighbor discovery and routing protocol in a IoT capable infra-less wireless networks with the bloom filer and enhanced rank concepts. And for the first time we evaluate our proposed scheme based on the modeling of various probability distributions in the IoT environments with the lossy wireless link. Specifically, the proposed enhanced RPL based light-weight routing protocol improves the robustness with the multi-paths locally established based on the enhanced rank concepts even though lossy wireless links are existed. We showed the improvements of the proposed scheme up to 40% than the RPL based protocol.

• 한국노년학
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• v.38 no.2
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• pp.291-308
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• 2018

The purpose of this study is to analyze the factors influencing financial preparedness for retirement of the middle-aged North Korean defectors (resettling in South Korea) using concepts of 'financial literacy' and 'financial inclusion'. Those questioned were 100 North Korean defectors of 40-60 years-old residing in Seoul and Gyeonggi-do Province selected by convenience sampling, one of the non-probability sampling. Path analysis is used as a main analysis method. The results of the study show a direct effect in which increased financial literacy resulted in better financial preparedness for retirement among middle-aged North Korean defectors at a statistically significant level. In addition, by boost-trapping method, financial inclusion has its mediating effect on the relationship between financial literacy and financial preparedness for retirement. However, this study shows that influence of financial literacy on financial preparedness for retirement is different across economic statues. The mediating effect of financial inclusion on the relationship between financial literacy and financial preparedness is statistically significant only for the low-income group. Meanwhile, for the above average income group, financial literacy has a direct effect on the financial preparedness after retirement at a statistically significant level. Based on these results, this study suggests practical and policy implementation such as necessity of customized financial education suited to their economic status, development of financial instruments for retirement, introduction of financial social workers to prepare stable old age of North Korean defectors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.169-183
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• 2019

Should a startup file for a patent subject to imitation in its quest to attract venture capital(VC) investors? Considering the US pharmaceutical biotechnology industry context, this paper attempts to answer this question by investigating the relations between the number of applied patents of startups, patent imitability, and the total amount of money the startups received as their first VC funding round. Data of 157 US-based pharmaceutical biotechnology startups founded in between 1995 and 2005 are analyzed. Empirical results from this study show that the number of applied patents is positively related to the total amount of money received at the time of the first funding round, and patent imitability is negatively related to the total amount of money received as first VC funding round. Nonetheless, the interaction term between the number of applied patents of startups and patent imitability came out as positive, raising interesting questions and implications for innovation-oriented startup entrepreneurs. The current study's empirical findings suggest that, in the pharmaceutical biotechnology sector, VC investors pay attention to the quantity and quality of the patents possessed by startups when they decide the level of funding. In particular, imitability of applied patents may not be a one-sided concept related to negative features such as the weak protectability of an invention. Rather, patent imitability may be a multi-facet element which also contains positive attractiveness of the startup's invention. Furthermore, it seems that the positive side of imitability can be augmented by the number of applied patents.

• International Area Studies Review
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• v.20 no.2
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• pp.25-46
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• 2016

In order to newly expand and define the concept of "strategic servitization" based on Industry 4.0, this study tried to evaluate the existing status of domestic and foreign servitized manufacturing and investigated the servitization cases of some leading overseas companies. In addition, we chose 250 samples of manufacturing firms listed on KOSDAQ and collected a vast amount of data regarding servitized manufacturing, such as the current status about new businesses, profit model, and financial fluctuations of each company. Based on these data, we classified the main types of manufacturing-service convergence into a $2{\times}2$ framework and derived a new strategic servitization model for each type of signature. Furthermore, we divided the sample corporations into three groups, which are pure manufacturer, servitized firm, and strategic servitized firm, and through the mutual comparison of the real sales amounts and the estimated sales amounts by time-series extrapolation analysis, we statistically proved that the service sales of strategic servitized firms give positive impacts on ROA when compared with those of the other two groups. Finally, we selected 12 leading domestic strategic-servitized firms, interviewed them in depth, and not only organized the issues during this process and their solutions by categories but also suggested the policy demands for strategic servitization.

• Management & Information Systems Review
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• v.37 no.4
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• pp.41-62
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• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.454-464
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• 2021

Purpose: There is a need to construct an evacuation passageway for the 2-Arch tunnel, which has been constructed and is in operation. Therefore, it aims to analyze tunnel and center wall behaviour and stability due to excavation of the center wall. Method: We describe the theoretical background of 2-Arch tunnel and evacuation passageway, and focused on analyzing the behaviour of tunnel and wall using 3-dimensional finite element analysis. Parametric analysis according to rock rating was performed with various ground conditions, and the displacement and stress of the center wall were intensively analyzed. Result: With the center wall excavation, the largest amount of settlement was shown in the center of the opening, and the stress was greatest during the first excavation. In addition, it was shown that stress concentration occurred at the top of both openings, and stability reviews considering the concept of allowable stress showed that it exceeded the allowable stress. Conclusion: Although the displacement of the tunnel has secured stability within the allowable standard, the generated stress is found to exceed the allowable standard, so it is necessary to prevent sudden stress release by applying appropriate reinforcement methods during construction.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.19-28
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• 2021

Corrosion is the degradation of metals by reaction with the environment. It is difficult to completely remove. Corrosion proceeds rapidly after the protective barrier is destroyed, and several reactions occur that alter the composition and properties of the metal surface and local environments, such as diffusion of metal cations into the matrix, the formation of oxides, and local pH changes. The study of corrosion of steel and iron is of theoretical and practical interest and is receiving considerable attention. Acid solutions, which are widely used in industrial pickling, acid descaling, cleaning and acidification of oil wells, require the use of corrosion inhibitors to suppress corrosion attacks on metallic materials. Physical removal of rust requires expensive special equipment, and chemical removal of it can cause corrosion or shorten the life of the metal. In this study, an eco-friendly rust cleaner was developed using cosmetics and food materials by applying the concept of perm reducing agent and chelate, and applied to remove rust from industrial and hot water pipes and various industrial devices. As a result, it was found that rust cleaners remove rust more effectively and safely compared to conventional treatment methods. At the same time, the rust removal efficiency was 1.75 to 2.5 times better for industrial piping and 1.56 to 2.2 times better for boiler hot water than conventional methods.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.113-130
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• 2021

Recently, ground-penetrating radar (GPR) surveys have been actively employed to obtain a large amount of data on occurrences such as ground subsidence and road safety. However, considering the cost and time efficiency, more intuitive and accurate interpretation methods are required, as interpreting a whole survey data set is a cost-intensive process. For this purpose, GPR data can be subjected to attribute analysis, which allows quantitative interpretation. Among the seismic attributes that have been widely used in the field of exploration, complex trace analysis and similarity are the most suitable methods for analyzing GPR data. Further, recently proposed attributes such as edge detecting and texture attributes are also effective for GPR data analysis because of the advances in image processing. In this paper, as a reference for research on the attribute analysis of GPR data, we introduce the useful attributes for GPR data and describe their concepts. Further, we present an analysis of the interpretation methods based on the attribute analysis and past cases.