• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.101-109
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• 2011

M&S in the field of national defense is a battle system has been highly spotlighted for obtaining weapon systems, analyzing and experimentation of battle effects to reduce costs, time, and risks. It is classified as Campaign, Mission, Engagement, and Engineering levels by detail of description. In engagements, many situations on the battle field which are really unpredictable are required to be considered on the view of diverse tactics. Thus, engagement simulation is in demand to use for forecasting real-world battle situations by inserting various components which consists of real engaging situations into virtual local battle field. While developing the engagement simulation, adopting the concept of agent-based simulation gives it benefits which are improved autonomy, composability, and reusability of entities. It means reducing the time, cost and effort to develop the simulations. This paper concentrates on the framework of multi-agent based engagement simulation using Cougaar Architecture.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.139-147
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• 2021

BIBFRAME, which is attracting attention as an alternative to the machine-readable catalog format (MARC) in the library world, presents a new bibliographic data model in the open web environment while maintaining compatibility with existing data. To convert KORMARC(Korean data model of MARC) records into BIBFRAME, we extract 25 key fields by analyzing the latest 5,000 bibliographic data from Nowon-gu Library in Seoul. The extracted core fields are classified into three types according to the compatibility of MARC 21, and define conversion rules for each type. In addition, implement an open source-based converter to perform KORMARC to BIBFRAME conversion. As a basic study on KORMARC to BIBFRAME conversion, this study is meaningful in that it analyzes the latest KORMARC information actually used, defines conversion rules, and attempts BIBFRAME conversion.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.17-24
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• 2018

This study attempted to analyze technology convergence structure and key technology research sectors in bio-health. For this, network analysis was performed based on the patent outcomes achieved through national R&Ds. Then, a patent network was analyzed to derive problems and collect data from the National Science & Technology Information Service. With the five groups obtained through the analysis of IPC network and national R&D patents in bio-health based on a research frame network, topics were chosen based on the bio-healthcare technology system. Then, the technology with the greatest ripple effects was derived and compared to other sectors, suggesting a direction for national R&D investments. It is anticipated that this study would make a contribution to a search for R&D investment direction by additionally analyzing overseas patent data and improving correlation analysis between technology convergence and government-led R&D expenses.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.427-435
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• 2019

Soundscape provides important resources to understand social and cultural aspects of our society, however, it is still its infancy to study on the research framework to record, conserve, categorize, and analyze soundscapes. Topic modeling is an automatic approach to discover hidden themes that are disperse in unstructured documents, thus topic modeling is robust enough to find latent topics such as research trends behind a collection of documents. The purpose of this paper is to discover topics on current soundscape research based on topic modeling, furthermore, to discuss the possibilities to design a metadata system for sound archives and to improve Soundscape Ontology which is currently developing.

• Journal of Navigation and Port Research
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• v.43 no.3
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• pp.160-165
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• 2019

The conduct of seafarer is major cause of marine accidents. This study models the behavior of the seafarer based on the Hidden Markov Model (HMM). Additionally, through the path analysis of the behavior estimated by the model, the kind of situations, procedures and errors that may have caused the marine accidents were interpreted. To successfully implement the model, the seafarer behaviors were observed by means of the summarized verdict reports issued by the Korean Maritime Safety Tribunal, and the observed results converted into behavior data suitable for HMM learning through the behavior classification framework based on the SRKBB (Skill-, Rule-, and Knowledge-Based Behavior). As a result of modeling the seafarer behaviors by the type of vessels, it was established that there was a difference between the models, and the possibility of identifying the preferred path of the seafarer behaviors. Through these results, it is expected that the model implementation technique proposed in this study can be applied to the prediction of the behavior of the seafarer as well as contribute to the prioritization of the behavior correction among seafarers, which is necessary for the prevention of marine accidents.

• The Korean Journal of Archival Studies
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• no.39
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• pp.3-43
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• 2014

This paper showed results of the risk management project in detail which was conducted by National Archives of Korea(NAK) in 2010. In the project NAK examined its long-term preservation business of electronic records using DRAMBORA(Digital Repository Audit Method Based on Risk Assessment). NAK has defined 44 different risk elements related to its business activities, assessed and classified them into several grades according to the severity calculated by risk probability score and risk potential impact score, and developed precise management plans for two of the most serious risks. This paper introduced the management plan for one of them. The risk was numbered with NR04 and described by 'Loss of integrity of records information'. This paper explained mitigation strategies, contingency organization, disaster control responsibilities, and personal mission cards for the NR04. This paper planned to give comprehensive understandings to Records Management Organizations about the risk management approaches as an effective way for business management through the case study.

• Journal of Korean Society of Rural Planning
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• v.27 no.2
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• pp.13-22
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• 2021

As the measures for solving problems of modern city and farming & fishing villages through mutual cooperation and complementation, this study aims to present an integrated rural area development model by changing the farming & fishing villages from a food production-focused space to a service space for the whole nation including urban residents, into the direction of creating new vitality and jobs in farming & fishing villages. In order to establish a service space that could increase the life quality and happiness of the people, this study presented the K-FARM framework types that would integrate and arrange total four themes such as rental farm, experience farm, stay farm, and management farm. In case when this K-FARM framework is applied to rural areas adjacent to cities, especially farming & fishing villages around innovative cities, there would be great effects such as expansion of exchanges between public institutions and local residents of innovative cities. Especially, the theme model classified into four types could be applied suitable for the characteristics of farming & fishing village development project district that is currently operated. Meanwhile, to realize the construction of K-FARM framework, on top of demand analysis of rental farm, it would be also necessary to additionally analyze the urban residents' demand for experience farm and management farm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.195-208
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• 2010

As information communication technologies have highly advanced, a large amount of user sensitive information can be easily collected and unexpectedly distributed. For user-friendly services, a service provider requires and processes more user information. However known privacy protection models take on a passive attitude toward user information protection and often involve serious weaknesses. In reality, information exposure by unauthorised access and mistakenly disclosure occurs frequently. In this paper, we study on the applicability of anonymous authentication services for fine-grained user privacy protection. We analyze authentication schemes and classify them according to the level of privacy newly defined in this paper. In addition, we identify security requirements that a privacy protection scheme based on anonymous authentication can achieve within legal boundary.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.77-88
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• 2021

The development history of China's big data is relatively short, and it has only been ten years so far. Although the application level of big data in real life is not high, some achievements have been made in the supply chain. Various kinds of data will be generated in the actual operation of the supply chain. If these data can be effectively classified and used, the "bullwhip effect" of the operation of the supply chain can be also effectively improved. Thus this paper proposes the development of a supply chain collaborative inventory management model and application framework using big data. In this study, we analyzed the supply chain of beer industry, which is the most prominent consumption industry with "bullwhip effect", and further established a big data collaborative inventory management model for the supply chain of beer industry based on system dynamics. We used the Vensim software for simulation and sensitivity test and after appling our model, we found that the inventory fluctuations of the participants in the beer industry supply chain became significantly smaller, which verified the effectiveness of the model. Our study can be also applied to the possible problems of the large data supply chain collaborative inventory management model, and gives certain countermeasures and suggestions.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.31-38
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• 2022

This paper applies an expert independent unsupervised neural network learning-based multivariate time series data analysis model, MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder), and to overcome the limitation, because the MCRED is based on Auto-encoder model, that train data must not to be contaminated, by using learning data sampling technique, called Subset Sampling Validation. By using the vibration data of power plant equipment that has been labeled, the classification performance of MSCRED is evaluated with the Anomaly Score in many cases, 1) the abnormal data is mixed with the training data 2) when the abnormal data is removed from the training data in case 1. Through this, this paper presents an expert-independent anomaly diagnosis framework that is strong against error data, and presents a concise and accurate solution in various fields of multivariate time series data.