• Journal of KIISE:Databases
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• v.35 no.2
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• pp.132-142
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• 2008

In biological domain, there exist a variety of protein analysis databases which have their own meaning toward the same target of protein. If we integrate these scattered heterogeneous data efficiently, we can obtain useful information which otherwise cannot be found from each original source. Reflecting the characteristics of biological data, each data source has its own syntax and semantics. If we describe these data through RDF(S) models, one of the Semantic Web standards, we can achieve not only syntactic but also semantic integration. In this paper, we propose a new concept of integration layer based on the RDF unified schema. As a conceptual model, we construct a unified schema focusing on the protein information; as a representational model, we propose a technique for the wrappers to aggregate necessary information from the relevant sources and dynamically generate RDF instances. Two example queries show that our integration layer succeeds in processing the integrated requests from users and displaying the appropriate results.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.119-131
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• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.

• Journal of Korean Library and Information Science Society
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• v.41 no.2
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• pp.251-272
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• 2010

Resource Description and Access(RDA) was published in 2008, reflecting IFLA IME ICC's International Cataloguing Principles(ICP), conceptual model for cataloging of Functional Requirement for Bibliographic Records(FRBR), and conceptual model for authority data of Functional Requirement for Authority Data(FRAD). Therefore, new tags and fields have been added to MARC21 format, and researches about the prototype have been studied to implement FRBR as envisioned by the new RDA standard. According to the innovative international cataloging environments, KCR and KORMARC must be revised to accommodate RDA description. This study was to grasp occurrence rate of work and expression element of FRBR and RDA among MARC field of Hansung University library and to analyze limitation of MARC data for RDA. Based on this limitations, cataloging rules and tags and fields of KORMARC were suggested to accommodate RDA in national cataloging environment. This study reviewed cataloging rules such like representation, main entry and rule of three, preferred title, types of content, media and carrier. This study is to suggest the consideration of KCR and KORMARC for RDA in Korea.

• Journal of Environmental Impact Assessment
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• v.29 no.2
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• pp.144-155
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• 2020

This research developed an approach to identify ecologically important areas at local scales and explained how the results of this approach could contribute to extend the protected areas in the Republic of Korea (ROK). While most developed countries have considered various biotic and abiotic factors, ecological processes, migration routes, habitat connectivity, ecosystem services, and etc. to determine the protected areas, ROK has considered a few factors focusing on biodiversity, landscape, and the habitats of endangered organisms. However, for sustainable management of our nature, we need comprehensive understanding of various ecosystem factors and interactions among them at local scales in designating protected areas. Forthis, we developed a conceptual model based on the ecological engineering approach and then explained how the results of this approach could contribute to extend the protected areas. In particular, we considered future land-use and climate change in determining the priority areas for novel protected areas. Our research suggested an effective methodology 1) to include various ecosystem factors and 2) to consider future environmental changes as well as current environmental conditions in finding the ecologically important areas and prioritizing these areas. However, our approach has limitations on the real-world applications due to the lack of fundamental information and data on our ecosystems. To improve the effectiveness of our approach in the real-world applications, we need various long-term ecological research results, environmental and ecological monitoring data, and both current and future spatial environmental data.

• Journal of Distribution Science
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• v.17 no.10
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• pp.61-71
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• 2019

Purpose - This study aims to explore the impact of factors on Korean consumer goods purchase decision of Vietnam's Generation Z. Research design, data, and methodology - A mixed research method was utilized in this study including focus group, in-depth interview, pilot study, and official study. The conceptual model and hypothesis were tested using data collected cross-sectional by questionnaire, from a sample of 439 respondents, by both electronic and paper surveys with non-probability and convenience sampling. The SPSS 20 and AMOS 20 software were employed to analyze the data. Results - Results showed that Vietnam's Generation Z was strongly impacted by social media, Hallyu, country of origin, social norms, and perceived usefulness. Besides, Korean consumer goods purchase decision of Vietnam's Generation Z also were impacted by intermediary factors such as trust, social norms, product involvement, perceived quality, perceived usefulness, attitude, and buying intention. There were differences in factors affecting the purchase decision of the boy and girl Generation Z group. Conclusions - The factors impacting on Korean consumer goods decision of Vietnam's Generation Z are very important for Korean firms and government. The findings provide Korean firms opportunity for appropriate to be carried out factors impacting Korean consumer goods to generation Z in Vietnam successful.

• Child Health Nursing Research
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• v.10 no.4
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• pp.383-394
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• 2004

Purpose: This study was conducted to identify resiliency factor, to test causal relationship and effect of resiliency factors on adaptation in families of children with cancer. A conceptual framework was constructed based on McCubbin's resiliency model. Hypotheses were tested with empirical data. Method: Data were collected using self-report questionnaire from 232 families of children with cancer. The collected data were analyzed using the SAS program and LISREL program for covariance structural analysis. Result: Family hardiness and problem-solving coping had significant direct effects on adaptation in families of children with cancer. Social support had significant indirect and total effect on adaptation. Family Schema had significant direct effect on family hardiness and problem-solving coping. Problem-solving communication had a significant direct effect on family hardiness and an indirect effect on family functioning and problem-solving coping. Among the resiliency factors, family hardiness had the greatest effect on adaptation in family of children with cancer. Conclusion: The findings suggest that nursing interventions to enhance family hardiness, problem-solving coping and social support would result in an increase in adaptation in families of children with cancer. An integrated intervention that emphasizes and promotes resiliency factors should be developed and established for families of children with cancer.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2262-2273
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• 2020

Digital twin technology can provide significant value for the prognostics and health management (PHM) of critical plant components by improving insight into system design and operating conditions. Digital twinning of systems can be utilized for anomaly detection, diagnosis and the estimation of the system's remaining useful life in order to optimize operations and maintenance processes in a nuclear plant. In this regard, a conceptual framework for the application of digital twin technology for the prognosis of Control Element Drive Mechanism (CEDM), and a data-driven approach to anomaly detection using coil current profile are presented in this study. Health management of plant components can capitalize on the data and signals that are already recorded as part of the monitored parameters of the plant's instrumentation and control systems. This work is focused on the development of machine learning algorithm and workflow for the analysis of the CEDM using the recorded coil current data. The workflow involves features extraction from the coil-current profile and consequently performing both clustering and classification algorithms. This approach provides an opportunity for health monitoring in support of condition-based predictive maintenance optimization and in the development of the CEDM digital twin model for improved plant safety and availability.

• Journal of Distribution Science
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• v.21 no.2
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• pp.35-43
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• 2023

Purpose: As Thailand seeks to become a regional startup hub, Thai startups have been acquiring growth and scalability in the last ten years. Hence, this paper examines influential factors in Thailand's growth of logistics tech startups. The conceptual framework incorporates sensing user needs, sensing technological options, conceptualizing, scaling, and stretching, co-producing, and orchestrating, business strategy, strategic flexibility, and startup growth. Research design, data, and methodology: The quantitative method was applied to distribute the questionnaire to 500 managers and above in logistics tech startups in Thailand. The sampling techniques involve judgmental, convenience, and snowball samplings. Before the data collection, The Item Objective Congruence (IOC) Index and pilot test (n=45) were employed for content validity and reliability. The data were mainly analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The findings revealed that sensing technological options, scaling, and stretching, co-producing, and orchestrating, and business strategy significantly influence the growth of startups in Thailand. Nevertheless, sensing user needs, conceptualizing, and strategic flexibility have no significant relationship with startup growth. Conclusions: For Thailand to accelerate its digital economy driven by tech startups, firms must emphasize influential factors to accelerate growth by providing the right tech solutions for people's lives.

• Journal of Distribution Science
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• v.21 no.3
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• pp.61-69
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• 2023

Purpose: This study's purpose is to conduct empirical research on online comments affect Vietnamese consumers' impulsive buying in e-distribution. This study also considers affecting of browsing toward the urge to buy, and the urge to buy toward impulse buying in e-distribution. Research design, data and methodology: This study used the non-probability method to assemble data from 273 customers' online buying experiences via a Google Forms online survey. By using SmartPLS, the data were examined for reliability, convergent validity, discriminant validity of the variables, and proposed hypothesis testing. Results: The empirical study discovered that internet comments with utilitarian and hedonistic values had a positive effect on browsing, the urge to buy, and impulse purchases in e-distribution. Additionally, the result revealed that browsing had a positive influence on the urge to purchase. Likewise, the findings also disclosed that the urge to buy had a favorable effect on impulse buying. Conclusions: This study offered a thorough conceptual model of internet feedback influencing browsing, urge to buy, and impulsive purchases in e-distribution. Also, to increase impulsive buying, this study will assist e-distribution managers in concentrating on developing innovative marketing strategies and action plans that take into consideration consumers' internet reviews, browsing, and urge to buy.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.150-156
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• 2004

Though the concept of Life-Cycle Cost (LCC) itself is not new, its effectiveness for planning, design, rehabilitation and maintenance/management of civil infrastructures is becoming increasingly recognized. For the decision problems as in the case of the LCC of plant facilities, equipments, bridge decks, pavements, etc., the Life-Cycle Cost Analysis (LCCA) is relatively simple, and thus its practical implementation is rather straightforward. However, when it comes to major infrastructures such as bridge, tunnels, underground facilities, etc., the LCCA problem becomes extremely complex because lack of cost data associated with various direct and indirect losses, and the absence of uncertainty data available for the assessment as well. As a result, the LCC studies have been largely limited only to those relatively simple LCCA problems of planning or conceptual design for making decisions. Accordingly, in the recent years, the researchers have pursued extensive studies on the LCC effectiveness mostly related to LCC models and frameworks for civil infrastructures. Moreover, recently the demand on the practical application of LCC effective decisions in design and maintenance is rapidly growing unprecedently in civil engineering practice. Indirction cost is very important on LCC formulation. But that is very difficult and complicate the estimation every LCC. The objective of this paper is to suggest efficient regression model for the estimation of indirect cost approach to the practical application of LCC for the design and rehabilitation of civil. infrastructures considering traffic, traffic network, detour condition, and workzone condition. In this paper, it performed the sensitivity analysis and correlation analysis of parameter for development of regression model of inflection cost.