• Journal of Korean Society of Archives and Records Management
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• v.21 no.3
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• pp.139-162
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• 2021

As the demand for finding clearer information amid vast information acquisition increases, the enhancement of academic research services is highly important. In 2019, the Presidential Archives opened the only academic research services among the permanent archives management institutions. This study aims to identify the status of the insufficient use of academic research services implemented in the Presidential Archives, analyze problems and requirements through interviews with users who have used the Presidential Archives for academic purposes and conducted research, suggest a plan to upgrade the research services of the Presidential Archives, and offer a plan to improve the services of archives institutions accordingly. Researchers mostly sought information through an online search, but the information gap was large depending on the background knowledge, and the research scope was reduced because of insufficient information. Moreover, problems occurred regarding search tools, records management, and records disclosure, and most users were unaware of the academic research services. Therefore, the advancement plans entailed reducing the information gap among researchers, improving the search tool functions, creating more detailed descriptions of records, resolving geographic constraints, promoting academic research services and developing content, nurturing subject-specialized archivists, and providing online chatting services.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.471-492
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• 2017

The demand and interest in big data analytics are increasing rapidly. The concepts around big data include not only existing structured data, but also various kinds of unstructured data such as text, images, videos, and logs. Among the various types of unstructured data, text data have gained particular attention because it is the most representative method to describe and deliver information. Text analysis is generally performed in the following order: document collection, parsing and filtering, structuring, frequency analysis, and similarity analysis. The results of the analysis can be displayed through word cloud, word network, topic modeling, document classification, and semantic analysis. Notably, there is an increasing demand to identify trending topics from the rapidly increasing text data generated through various social media. Thus, research on and applications of topic modeling have been actively carried out in various fields since topic modeling is able to extract the core topics from a huge amount of unstructured text documents and provide the document groups for each different topic. In this paper, we review the major techniques and research trends of text analysis. Further, we also introduce some cases of applications that solve the problems in various fields by using topic modeling.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.11-16
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• 2015

Data center, not only the development of globally of cloud-based IT solutions, As the big data, education, use of development electronic equipment of communication means is increased, Demand of domestic and international data center has increased steadily. Due to the increase of data center demand, heat generation of server rack due to the development of IT equipment is also increasing continuously. Calculating heat value of the data center, because more than 99% of the power usage of IT server is converted into heat, the calorific value as the size and capacity of the server is larger will increase. In this paper, to center the cooling system of air-cooled, and research and development of air conditioning systems for energy reduction of data center, through performance analysis and simulation, it has been analyzed that there is energy savings.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.422-431
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• 2004

In recent years, different models in data delivery have been explored in mobile computing systems. Particularly, there were a lot of research efforts in the periodic push model where the server repetitively disseminates information without explicit request. However, average waiting time per data operation highly depends on the length of a broadcast cycle and different access pattern among clients may deteriorate the response time considerably. In this case, clients are preferably willing to send a data request to the server explicitly through backchannel in order to obtain optimal response time. We call the broadcast model supporting backchannel as hybrid broadcast. In this paper, we devise a new transaction processing algorithm(O-PreH) in hybrid broadcast environments. The data objects which the server maintains are divided into Push_Data for periodic broadcasting and Pull_Data for on-demand processing. Clients tune in broadcast channel or demand the data of interests according to the data type. Periodic invalidation reports from the server support maintaining transactional consistency. If one or more conflicts are found, conflict orders are determined not to violate the consistency(pre-reordering) and then the remaining operations have to be executed pessimistically. Through extensive simulations, we demonstrate the improved throughput of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.251-258
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• 2022

In this paper, we propose a standard AI developer job training track based on industry needs. The characteristic of this curriculum is that it can minimize the mismatch of AI developer job competency between industries and universities. To develop an AI developer job training track, a survey will be conducted for AI developers working in industrial fields. In this survey, among the five NCS-based AI developer jobs, job analysis is conducted by deriving AI developer jobs with high demand for manpower in industrial fields. In job analysis, the core competency unit elements of the job are selected, and knowledge, skills, tools, etc. necessary to perform the core competency unit elements are derived. In addition, a standard AI developer job curriculum is developed by deriving core subjects and road-map that can educate knowledge, skills, tools, etc. In addition, we present an efficient AI developer job training method using the standard AI developer job training course proposed in this paper.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.257-269
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• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.221-224
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• 2005

According as marine leisure industry has developed and the demand of leisure culture has increased rapidly, a desire about service which supply marine safety and connect marine information is enlarging. We wish tc develop contents of download form that supply geographic information of Electronic Navigational Chart(ENC) in the marine that is digitalized to carrying along terminal of WIPI base and various informations for marine leisure. For this, DB that offer ENC and additional information should be constructed. Also, we need server (CPS; Contents provider Server) that offer required contents. In this paper, we design web retrieval component which store request information to database. When consumer required necessary information through personal mobile device, CPS can inform that. So, we wish to develop web retrieval agent component that parse informations in various World Wide Webs, and store to database.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.18-32
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• 2021

Social media has become a popular source of information around the world. Previous studies explored different trends of social media news consumption. However, no studies have focused on Bangladesh to date, where social media penetration is very high in recent years. To fill this gap, this research aimed to understand its popularity trends during the period. For that reason, this work analyzes 97.67 million page likes and 3.48 billion interaction data collected from nine Bangladeshi news media's Facebook pages between December 2016 to November 2020. The analysis shows that the growth rates of page likes and interaction rates declined during this period. It suggests that the media's Facebook pages are gradually losing their popularity among Facebook users, which may have two more interpretations: Facebook's aggregate appeal as a news source is decreasing to users, or Bangladeshi media's appeal is eroding to Facebook users. These findings challenge the previous results, i.e., Facebook's demand as a news source is increasing with time. We offer four explanations of the decreased popularity of Facebook's news: information overload, exposure to incidental news, users' selective exposure and different aims of using Facebook, and conflict between media agendas and users' interests. Some theoretical and practical significance of the results has been discussed as well.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.953-963
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.71-86
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• 2023

The rapid change in industry and the technological gap give rise to social demand for upskilling and reskilling and spread of alternative education. Against this backdrop, digital certification and career management tools can be used to manage various types of learning activities comprehensively. Digital badges provide various kinds of history information related to individual learning, and the reliability and transparency of the issued information can be strengthened by applying blockchain technology. There have been various discussions about digital badges for a long time, but due to the lack of standards to support the issuance and distribution of digital badges, they have been partially used in some areas. However, interest in digital badges is increasing due to the development of related technologies, establishment of standards, paradigm changes in higher education, and government policies related to nurturing digital talent. This paper deals with the use of digital badges for efficient and transparent learning management and career management in an online learning environment. The researcher analyzes the technical characteristics and use cases of digital badges, and proposes a plan for use in online higher education based on them.