• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.19-22
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• 2006

최근 들어, 모든 장소에 컴퓨터가 있고 그것을 누구나 자유롭게 사용할 수 있는 인간 중심 유비쿼터스 환경에 대한 연구가 활발하게 진행되고 있다. 그러나 이러한 컴퓨팅 환경에서의 센서 미들웨어들은 연속적인 스트림 데이터 처리에 대한 막대한 비용을 줄이기 위해서 분석이 끝난 스트림 데이터를 삭제한다. 따라서 사용자의 서비스에 삭제된 스트림 데이터가 요구될 경우, 또는 과거 데이터들에 대한 확률 통계 정보가 요구될 경우, 이에 대한 서비스를 사용자에게 제공할 수 없다. 본 논문에서는 이러한 미들웨어에서의 스트림 데이터 재사용 문제를 해결하기 위해서 스냅샷을 가지는 다중 레벨 공간 DBMS를 기반으로 하는 효율적인 센서 데이터 미들웨어 구조를 설계하였다. 본 시스템은 사용자에게 재사용될 가치가 높은 스트림 데이터들을 다중 레벨 공간 DBMS 의 디스크 데이터베이스에서 관리한다. 또한 빈번한 서비스를 가지는 스트림 데이터의 경우 해당 스트림 데이터를 메모리 데이터베이스에 관리함으로서 사용자에게 신속한 서비스를 제공한다. 본 시스템은 기존의 미들웨어에서 지원할 수 없었던 동일한 스트림 데이터에 대한 빈번한 요청, 또는 확률이나 통계 자료와 같은 데이터 서비스 요청 문제들을 해결하였다. 그리고 메인 메모리 데이터베이스에 스냅샷 형태로 저장되는 스트림 데이터의 높은 데이터 재사용성을 유지함으로서, 사용자에게 지속적으로 정확하고 신속한 데이터 서비스를 제공한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.737-751
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• 2023

The importance of digital forensics in the cloud environment is increasing as businesses and individuals move their data from On-premise to the cloud. Cloud data can be stored on various devices, including mobile devices and desktops, and encompasses a variety of user behavior artifacts, such as information generated from linked accounts and cloud services. However, there are limitations in securing and analyzing digital evidence due to environmental constraints of the cloud, such as distributed storage of data and lack of artifact linkage. One solution to address this is archiving services, and Google's Takeout is prime example. In this paper, user behavior data is analyzed for cloud forensics based on archiving data and necessary items are selected from an investigation perspective. Additionally, we propose the process of analyzing selectively collected data based on time information and utilizing web-based visualization to meaningfully assess artifact associations and multi-behaviors. Through this, we aim to demonstrate the value of utilizing archiving data in response to the increasing significance of evidence collection for cloud data.

• Journal of Global Scholars of Marketing Science
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• v.17 no.1
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• pp.77-100
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• 2007

This study investigates the relationship between restaurants' environments and customer voluntary performance, and examines how restaurant value, quality and overall satisfaction play a mediating role between restaurants' environments and customer voluntary performance. In addition, this study investigates the structural relationships among restaurant's value, quality and overall satisfaction. For these purposes authors developed a structural model, which consists of several variables. The data were collected from 723 respondents and was analyzed with SPSS!PC+ 12.0 and LISREL 8.5. The findings are as follows. First, the menu characteristics have a significant positive influence on the value and quality of restaurants. Second, the employee service characteristics have a significant positive influence on the quality through mediating role of value variables. Third, the facilities/atmospheres have a significant positive effect on the value and quality of restaurants. Fourth, in-restaurant promotions have a significant positive effect on the value and quality of restaurants. Fifth, the customer value has a significant effect on the restaurant quality and overall satisfaction, and the restaurant quality has a significant effect on the overall satisfaction. Finally, the overall satisfaction has a significant effect on the customer loyalty, participation, and cooperation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.875-883
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• 2023

In Korea, the number of preservation and management entities to connect the traditional cultural heritage to next generations is rapidly decreasing. Building an infrastructure to pass on traditional cultural heritage to the next generation and to pay attention to the preservation and management of the next generation is important including the 'Seowon', a World Cultural Heritage listed by UNESCO. This study is based on the laws that regulates the preservation and support of traditional cultural assets and 'Seowon, through Big Data analysis techniques. The main keywords in each law were extracted, schematized, and a mutual Word Network was constructed and policy advice was derived. As policy advice, it is necessary to establish and implement policies to nurture and support businesses specialized in the region for the preservation·utilization, preservation·management and preservation·support of Seowons.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2083-2087
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• 2009

본 연구에서는 대전에 위치한 갑천을 대상으로, 하도 내 생물서식처를 10개의 유형으로 분류하였고, 다음 단계로 2차원 수리모형인 RIVER2D를 이용하여 10개 유형의 생물서식처 중 '개방형하도 습지'를 대상으로 수생 물리 서식처의 잠재적 가치를 분석하였다. 본 연구를 통하여 2차원 수리모델인 RIVER2D는 특정 복원 목표 어류 종의 수생물리서식처 조건 평가에 적용하기에 적합한 것으로 나타났다. 개방형 하도습지는 어류 서식처로서 평균이상의 잠재적 가치를 가지고 있었으며 이는 목표 종인 피라미를 통해 검증하였다. 또한 이 모델을 보다 유용하게 운용하기 위해서는 다양한 어류에 대한 풍부한 현장 데이터 자료의 수집 및 확립을 통해 각각의 HSI 수립이 필요하다. 또한 계절적 영향에 의한 수위변화, 지역적인 여건의 차이 등이 반드시 고려되어야 할 것이다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.433-436
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• 2000

경제가 고도로 성장하던 단계에서는 기업은 사업규모도 크지 않고, 경쟁환경도 치열하지 않았을 뿐 아니라 내·외부적인 환경도 안정적이기 때문에 양적 확대에만 집중하더라도 그것이 기업가치를 크게 하는 역할을 할 수 있었다. 그러나 내·외부적인 무수한 환경변화와 경쟁격화로 인하여 수익성의 악화가 반복되는 현실에서는 종전과 같은 경영사고나 전략으로는 새로운 환경에서 살아남을 수 없을 것이다. 따라서 본 논문은 기업들의 환경변화에 따른 대처능력과 의사결정을 원활히 하기 위해 기존의 단순 수치의 변환에 의해서 결과를 도출하는 회계 시뮬레이션에서 벗어나 회귀분석과 신뢰구간을 사용하여 기업의 의사결정에 있어서 보다 기업의 현실에 근접한 데이터를 추출하여 의사결정의 원활화를 도모하고자 하였으며 최종 시뮬레이션 결과를 EVA 에 둠으로써 기업의 수익성, 자본효율도 등의 기업가치를 여러 방면으로 추정할 수 있도록 하였다.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.9-15
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• 2013

Big data has a key engine of the new value creation and troubleshooting are becoming more data-centric era begins in earnest. This paper takes advantage of the big data, big data in order to secure the quality of the quality elements for ensuring the quality of Justice and quality per-element strategy argue against. To achieve this, big data, case studies, resources of the big data plan and the elements of knowledge, analytical skills and big data processing technology, and more. This defines the quality of big data and quality, quality strategy. The quality of the data is secured by big companies from the large amounts of data through the data reinterpreted in big corporate competitiveness and to extract data for various strategies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.157-158
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• 2021

Big data in the supply chain mainly comes from four aspects. One is the relevant data inevitably generated in the process of product value transfer of enterprises in the supply chain, such as production equipment quality data, planned procurement data, product data, etc; On the other hand, it is derived from the ERP data of various companies in the supply chain; The third is e-commerce data from the customer, and the last is data from external or manually entered data. A third-party data service center analysis and mining the data to predict and control the inventory in the process of supply chain operation. It brings innovation and change of management technology and way of thinking to the whole supply chain in many aspects, and finally achieves the goal of coordinated inventory and zero inventory of the whole supply chain.

• Knowledge Management Research
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• v.25 no.2
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• pp.193-218
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• 2024

The current study investigated the factors influencing the buyer's repurchase intention for second-hand products. This study first identified perceived risk and purchase value as the two primary influencing variables. Additionally, some exogenous variables influencing these two variables were examined. Statistical analysis using Partial Least Squares (PLS) revealed that product uncertainty, seller uncertainty, and site trust had statistically significant relationships with perceived transaction risk. However, while economic benefit showed a significant impact on purchase value, product scarcity and resale value did not exhibit a significant relationship with purchase value. Perceived transaction risk was found to have an insignificant relationship with repurchase intention, but indirectly influenced repurchase intention through purchase value. Purchase value was identified as having a significant influence on repurchase intention. Therefore, it was concluded that purchase value is the most important factor influencing repurchase intention in the purchase of second-hand products, while transaction risk indirectly influences repurchase intention through purchase value. The study indicates that product uncertainty and economic benefit are the most significant exogenous factors influencing transaction risk and purchase value, respectively.

• Journal of the Korean Society for information Management
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• v.37 no.2
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• pp.23-45
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• 2020

The world is paying attention to the South Korean government's aggressive COVID-19 response, key of which is transparency and openness in sharing information. Opening up government information is essential to enhancing its social and economic value through increased awareness and accessibility. The purpose of this study is to investigate the current status of SNS operated by national open data portals in which government-collected and -disclosed data is available and to suggest improvements for the use of open data portals. To do this, the study compared 3 national open data portals, each from India, U.S.A, and Korea, by performing quantitative analysis, user feedback analysis, time-series analysis, and information type analysis. Based on the identified information types and user needs, the study suggests concrete ways to facilitate the use of open data portals.