• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.209-212
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• 2007

A very detail instruction of a m-Business application case for small scale company is given. Two results are proved. The one is that m-business application can reduce system building and maintaining fee. The other is that m-business application should running on the mobile machine with caching some application data on it.

• The Journal of Society for e-Business Studies
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• v.6 no.2
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• pp.127-142
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• 2001

For the B2B e-commerce and SCM (Supply Chain Management), standardization of electronic catalogue that contains product and business data is important. Especially, standardization of hierarchies that is required for categorization, and standardization of product properties are difficult and costly to maintain. The ability of searching for items and data in databases is critical for successful e-commerce system. This paper introduces the data dictionary of PUB (ISO 13584) part 42 which can establish the standard of product data. The method is applied to develop the data dictionary of automotive parts.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.386-395
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• 2009

Business entities with which most service components interact are kind of cross-cutting concerns in a multi-layered distributed application architecture. When business entities are modified, service components related to them should also be modified, even though they implement common functions of the application framework. This paper proposes what we call DTT (Data Type-Tolerant) component model to process the variability of business entities, or externalized data, which feature modern application architectures. The DTT component model expresses the data variability of product lines at the implementation level by means of SCDTs (Self-Contained Data Types) and variation point interfaces. The model improves the efficiency of application engineering through data type converters which support type conversion between SCDTs and business entities of particular applications. The value of this model lies in that data and functions are coupled locally in each component again by allowing service components to deal with SCDTs only instead of externalized business eutities.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.175-180
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• 2022

Data is an important resource to expect new value as 21st-century crude oil. In the shipping industry, despite the existence of numerous maritime data accumulated through ship operations, it was negligent in developing a business model with the data. This paper identified major demand sources and demand types based on the type and availability of maritime data surveyed through interviews with experts in the shipping industry and academia. Considering the characteristics and demands of these maritime data, this paper presented a private-type and public-interest business model. In the case of the private-type model, it creates additional added value by using maritime data and uses mainly ship internal data. The public-type model is to seek public safety and social benefits and mainly uses external data. A great synergy effect can be expected when combined with public services such as maritime survey, vessel traffic service, maritime environment management, and meteorological service. This study is expected to contribute greatly to the spread of the proposed business models throughout the shipping industry.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.1-9
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• 2014

This research describes strategies to promote the growth of the Big Data industry and the companies within the ecosystem. In doing so, we identify the roles and responsibilities of various objects of this ecosystem and Big Data concepts. We describe the five components of the Big Data ecosystem: governance, data holders, service users, service providers and infrastructure providers. Related to the Big Data industry, the paper discusses 13 business strategies between the five components in the ecosystem. These strategies directly respond to areas of research by the Big Data industry leading experts on its early development. These strategies focus on how companies can gain competitive advantages in a growing new business environment of Big Data. The strategy topics are as follows: 1) the government's long term policy, 2) building Big Data support centers, 3) policy support and improving the legal system, 4) improving the Privacy Act, 5) increasing the understanding of Big Data, 6) Big Data support excavation projects, 7) professional manpower education, 8) infrastructure system support, 9) data distribution and leverage support, 10) data quality management, 11) business support services development, 12) technology research and excavation, 13) strengthening the foundation of Big Data technology. Of the proposed strategies, establishing supportive government policies is essential to the successful growth of thee Big Data industry. This study fosters a better understanding of the Big Data ecosystem and its potential to increases the competitive advantage of companies.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.83-107
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• 2020

Selecting business charts based on the nature of the data and the purpose of the visualization is useful in business analysis. However, current visualization tools lack the ability to help choose the right business chart for the context. Also, soliciting expert help about visualization methods for every analysis is inefficient. Therefore, the purpose of this study is to propose an accessible method to improve business chart productivity by creating rules for selecting business charts from online published documents. To this end, Korean, English, and Chinese unstructured data describing business charts were collected from the Internet, and the relationships between the contexts and the business charts were calculated using TF-IDF. We also used a Galois lattice to create rules for business chart selection. In order to evaluate the adequacy of the rules generated by the proposed method, experiments were conducted on experimental and control groups. The results confirmed that meaningful rules were extracted by the proposed method. To the best of our knowledge, this is the first study to recommend customizing business charts through open unstructured data analysis and to propose a method that enables efficient selection of business charts for office workers without expert assistance. This method should be useful for staff training by recommending business charts based on the document that he/she is working on.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.242-248
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• 2003

◎ Uncover the hidden pattern from massive data(data warehouse) -Builds a reasonable model to predict the future for business advantage -Decision Making based on the learned models(omitted)

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.18-19
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• 2014

As issued the development of energy resources, EPC work process through the IT technology is essential for efficient business management, and systematic management of data generated in this process is needed. In domestic, the research related to system development for the collection and management of construction data detected in the field has been done continuously, but pipeline business target the long-distance in extreme cold weather, almost no cases have been studied up to now. Therefore, this research is aimed to derive the data item for efficient management in EPC Stage of pipeline business in extreme cold weather. WBS system of EPC work are classified easily at two levels, data items can be divided based on the type of document. In the future I will be expected to be the foundation of the systematic management of data generated in the EPC step-by-step of pipeline business.

• East Asian Journal of Business Economics (EAJBE)
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• v.6 no.1
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• pp.31-41
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• 2018

Purpose - The main target to do this analysis is to find out the competitiveness between 2 countries (China and USA) in the aircraft business industry. The main target about mentioned research is to find out how a certain country takes more advantage against the other partner country in the country's trade structure. Research design, data, and methodology - Mentioned research period ranges from 1995 to 2016. Research basic data are coming from UN COMTRADE database which is top of top in the world statistical data and Research methods are used 3 types of international trade related theory for credible data outcomes. Results - Even though general data about aircraft industry are open to world society, detailed classified data are not easy to get them. Generally, Both China & USA are not easy to obtain data especially, in the overseas production field as a business secret which is one of research limitation in every research scopes. Conclusions - Even though Chinese aircraft industry looks like strong and more advantage against those of other countries based on competitive labor work wages and low price of raw material and resources, Actually, USA has overwhelmingly dominant advantage against that of China in the field of aircraft industry because USA has abundant capitals and up-to-date advanced high-technology as top of world economic communities. Additionally, even if USA aircraft industries hold a dominant position so far, if USA proposes sound competition relationship with China about aircraft industry, both 2 countries' future will be bright as their cooperation will make synergy effects for mutual benefits under current circumstances in 2 countries.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.319-320
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• 2023

본 논문에서는 합성곱 신경망이 적용된 네트워크를 활용해 전이 학습의 과정을 거친 멸종위기종 철새들의 이미지를 분류하는 시스템의 설계과정과 결과를 제시한다. 연구 방법으로 한국 영랑호를 찾아오는 멸종위기종, 천연기념물인 철새들의 이미지를 학습시켜 "가창오리", "노랑부리백로", "물총새" 이 세 종의 철새들을 매우 정확하게 분류하는 것을 확인하였다. 데이터 예비학습과정에서 train data의 개수를 40개로 진행했을때 약 92%의 정확도를 확인 후, train data의 이미지 개수를 50장으로 늘려 더 높은 정확도를 얻을 수 있었다. 이 시스템은 한국을 방문하는 멸종위기종 철새들을 무분별하게 포획하지 않도록 철새 이미지 분류시 활용 가능하다고 사료된다.