• The Korean Journal of Archival Studies
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• no.79
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• pp.305-341
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• 2024

This study explored the possibilities of a new approach to developing the provenance concept to electronic records in the data-driven digital environments by reviewing and adopting data provenance concepts and models. It then conducted basic literature review to develop a ground for a model representing the provenance of data-driven electronic records. In particular, it proposed to embrace to the concepts of retrospective and prospective provenance, and to develop a different model for representing provenance from records management metadata. If the model can be developed that can represent provenance independently while maintaining a dynamic relationship with records, it can be ensure the fluidity of records and even support to secure the record's attributes and play the roles of provenance. Eventually, it proposed the direction to develop the provenance model which can support the fixity of records, the reproducibility of activities, and the trustworthiness of representations. It is expected to be a fit provenance model in the data-driven digital environment.

• The Korean Journal of Archival Studies
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• no.80
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• pp.5-41
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• 2024

This study was conducted to develop a provenance representation model for data-type electronic records. It supports the distinction between provenance and context for the creation and management of data-type electronic records. To express both, it aims to design an extensible provenance model. For this purpose, W3C PROV is utilized as a basic model, with P-Plan and ProvONE for designing prospective provenance area. Afterward, the provenance model was extended by mapping the record management requirements. The provenance model proposed in this study is designed to represent and connect both retrospective and prospective provenance of data-type electronic records. Based on this study, it is expected to discussing the concept of provenance in the records management and archival studies area and to extending the model in the future.

• Convergence Security Journal
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• v.24 no.3
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• pp.23-31
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• 2024

The anonymity and decentralized nature of cryptocurrencies make them highly susceptible to criminal exploitation, requiring the development of effective tracking techniques. By analyzing various open source intelligence(OSINT), such as public data, social media, and online forums, open source intelligence can provide useful information for identifying criminals and tracking the flow of cryptocurrency funds. In this study, we present a comprehensive proposal for the utilization of open source intelligence. We will discuss the current status and trends of cryptocurrency and related crimes, and introduce the concept and methodology of open source intelligence. The paper then focuses on five methods and seven frameworks of open source intelligence for tracking and analyzing cryptocurrency-related crimes, and presents techniques for the integrated application of open source intelligence methods and frameworks.

• Journal of Korean Society of Archives and Records Management
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• v.2 no.2
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• pp.69-92
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• 2002

The objective of this study is to examine the re cent trend of the interpretation of the Principle of the Provenance in today s new environment of Archives Management and to identify the effective way of the application of the Principle of Provenance to Archives Management. Because of the continued change and the flexibility of the administrative organization and the development of information network, the traditional concept of the Principle of Provenance which put emphasis on a single creator and the physical entity of the archives has been gradually modified to a rather conceptual, abstract and realistic one. A method to apply the recent concept of the Principle of Provenance is to separate the descriptions of the record entity, the creators and the context and use the organic linkage of the separated description areas. Also we can control the provenance from the current stage or even from the pre-current stage by utilizing the classification scheme and the retention schedule. In case of the electronic records, we can manage the provenance and the context by using metadata inherent in the computerized information system. Above all it is critical that we need to structure and control the provenance by building the Korean rules for archival description corresponding to the international standards. And it is another an essential point that we have to develop a guideline for constructing the fond and maintaining its consistency.

• TTA Journal
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• s.107
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• pp.24-29
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• 2006

차세대 인프라인 광대역통합망(BcN)은 이미 음성과 데이터 통합, 통신과 방송 융합, 유무선 통합이 가능한 AII-IP 망을 구축함으로써 컨버전스를 완성하는 비전을 제시하고 있다. 음성과 데이터 통합은 통합서비스나 네트워크 구축 측면에서 활발하게 진행되고 유무선 통합도 와이브로와 3세대 이동통신(WCDMA) 등 올 IP기반 무선망이 등장하면서 관심이 높아지고 있다. 이 가운데 가장 주목을 받는 것이 IPTV(인터넷 방송)이다. IPTV의 잠재력은 2012년까지 국내 생산유발 효과가 12조9천억원으로 고용창출 효과도 7만여 명에 달하며(출처 : ETRI) 세계 IPTV 서비스 가입자 수는 2013년 5천 300만 명에 다다를 것(출처 : Dittberner Associates)이라고 한다. 이번 호에는 BcN + IPTV 컨버전스 표준화 특집과 연동하여 TTA 표준화위원회 전문가와의 인터뷰를 통해 향후 기술전망과 함께 국제표준화 대응전략에 대하여 들어본다.

• Bulletin of Food Technology
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• v.10 no.1
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• pp.94-101
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• 1997

NIR(근적외) 분광분석법이 녹차의 원산국을 판별하는데 이용할 수 있는지를 알아보기 위하여 분쇄한 47종의 한국산 및 일본산 녹차에 대하여 NIR 분석을 실시한 후, 그 분광 데이터에 대하여 principal component analysis(주성분 분석 )와 canonical variate analysis(정준판별분석)을 실시하였다. 15개의 주성분과 1100~2500nm에서의 first derivative log(1/R) 데이터를 이용할 경우, 제1 및 제2 정준판별함수는 한국산 녹차 및 일본산 녹차를 판별하는데 가장 효과적이었다. 사용된 canonical variate analysis는 녹차 시료를 97.87%의 정확도로 그 지리적 출처를 판별하였다. 한편 first derivative log(1/R) spectra상의 파장범위 1674~1686, 1950~1992, 2014~2030및 2118~2158 nm에서 일본산 녹차와 3종의 한국산 녹차 그룹간에 현저한 차이가 발견되었다. 이 차이는 polyphenols, caffeine 및 amino acids와 같은 녹차의 주요성분과 관련되어 있지 않으며 주로 지리적 출처상의 차이에 기인한 것으로 판단되었다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.111-119
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• 2024

In this paper, we propose a big data platform that can collect information from various sources collected at ocean. Currently operating ocean-related big data platforms are focused on storing and sharing created data, and each data provider is responsible for data collection and preprocessing. There are high costs and inefficiencies in collecting and integrating data in a marine environment using communication networks that are poor compared to those on land, making it difficult to implement related infrastructure. In particular, in fields that require real-time data collection and analysis, such as weather information, radar and sensor data, a number of issues must be considered compared to land-based systems, such as data security, characteristics of organizations and ships, and data collection costs, in addition to communication network issues. First, this paper defines these problems and presents solutions. In order to design a big data platform that reflects this, we first propose a data source, hierarchical MEC, and data flow structure, and then present an overall platform structure that integrates them all.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1128-1134
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• 2014

Web based simulation service is actively utilized to computably analyze various kinds of phenomena in real world according to progress of computing technology and spread of Network. However it is hard to share data and information among users on the services, because most of web based simulation services do not share and open simulation processing information and results. In this paper, we design a simulation provenance data sharing service on EDISON_CFD (EDucation-research Integration Simulation On the Net for Computational Fluid Dynamics) to share the calculated simulation performance information. To store and share the simulation processing information, we define the simulation processing step as "Problem ${\rightarrow}$ Plan, Design ${\rightarrow}$ Mesh ${\rightarrow}$ Simulation performance ${\rightarrow}$ Result ${\rightarrow}$ Report." Users can understand a problem solving method through a computer simulation by searching the simulation performance information with Search/Share API of the store. Besides, this opened simulation information can reduce the waste of calculation resource to process same simulation jobs.

• Smart Media Journal
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• v.12 no.5
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• pp.65-72
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• 2023

Smart Farm means creating new value in various fields related to agriculture, including not only agricultural production but also distribution and consumption through the convergence of agriculture and ICT. In Korea, a rental smart farm is created to spread smart agriculture, and a smart farm big data platform is established to promote data collection and utilization. It is pushing for digital transformation of agricultural products distribution from production areas to consumption areas, such as expanding smart APCs, operating online exchanges, and digitizing wholesale market transaction information. As such, although agricultural data is generated according to characteristics from various sources, it is only used as a service using statistics and standardized data. This is because there are limitations due to distributed data collection from agriculture to production, distribution, and consumption, and it is difficult to collect and process various types of data from various sources. Therefore, in this paper, we analyze the current state of domestic agricultural data collection and sharing for digital agriculture and propose a data collection and linkage method for artificial intelligence services. And, using the proposed data, we propose a deep learning-based environmental factor recommendation method.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.486-500
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• 2013

This study is conducted to examine how epistemic reasoning and argument structures of students vary according to data sources used in the process of argumentation implemented in the context of inquiry. To this end, three argument tasks using first-hand data and three argument tasks using second-hand data were developed and applied to the unit on 'Nutrition of Plants' for first year middle school students. According to the results of this study, epistemic reasoning of students manifested during the process of argumentation and varied according to data sources. While most students composed explanations with phenomenon-based or relation-based reasoning in argumentation using first-hand data, all the small groups composed explanations that included model-based reasoning in argumentation using second-hand data. In the case of arguments including phenomenon-based or relation-based reasoning, students described only observable characteristics, with warrants omitted from arguments in many cases. On the other hand, in the case of arguments that included model-based reasoning, explanations were composed by combining the results of observations with theoretical knowledge, with warrants more apparent in their arguments.