• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.378-384
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• 2011

During the flight test of KSLV-I, various sensors are installed in the launch pad and the flame deflector to measure the flame characteristics and their influences on the launch complex when a launch vehicle lifts off. Parameter Measurement System is responsible for acquiring the above flight test data. The measurement methodology such as the configuration of measurement system, sensor locations and data acquisition procedures are presented. And this paper compares and explains the characteristics of data sets measured during two flight tests.

• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.97-105
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• 2013

In the e-business domain where data objects are quantitatively large, measuring similarity to find the same or similar objects is important. It basically requires comparing and computing the features of objects in pairs, and therefore takes longer time as the amount of data becomes bigger. Recent studies have shown various algorithms to efficiently perform it. Most of them show their performance superiority by empirical tests over some sets of data. In this paper, we introduce those data sets, present their characteristics and the meaningful threshold values that each of data sets contain in nature. The analysis on practical data sets with respect to their threshold values may serve as a referential baseline to the future experiments of newly developed algorithms.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.45-50
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• 2019

This study proposes a method to measure software reliability according to software reliability measurement model to measure software reliability. The model presented in this study uses the distribution of Non - Homogeneous Poisson Process and presents a measure of the software reliability of the presented model. As a method to select a suitable software reliability growth model according to the presented model, we have studied a method of proposing an appropriate software reliability function by calculating the mean square error according to the estimated value of the reliability function according to the software failure data. In this study, we propose a reliability function to measure the software quality and suggest a method to select the software reliability function from the viewpoint of minimizing the error of the estimation value by applying the failure data.

• Journal of Digital Convergence
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• v.6 no.3
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• pp.139-147
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• 2008

-Healthcare란 건강관련 정보를 시간과 공간의 제약 없이 수집, 처리, 전달, 관리할 수 있게 해줌으로써 원격지 의료서비스를 제공하는 것을 말한다. 본 논문은 USN을 활용하여 원격에서 측정된 의료정보를 수집하여 서버에 전달하는 미들웨어 시스템을 시뮬레이션 했다. 헬스 케어기기에서 측정된 데이터를 USN을 통해 원격지의 서버로 전송하는데, 데이터의 전송에는 근거리 무선통신기술인 Zigbee를 사용하였다. 이러한 과정에서 헬스 케어기기와 서버사이에 미들웨어를 두어 측정된 이진코드 데이터를 텍스트데이터로 변환하여 서버의 헬스케어 시스템에 저장한다. 서버에 저장된 환자들의 의료정보는 의료진이 활용할 수 있도록 했다. 또한, 미들웨어 시스템에서는 데이터의 필터링을 통해 불필요한 데이터를 삭제해 서버의 부하를 줄여서, 외부 어플리케이션의 질의에 대한 정보제공을 용이하게 했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.165-168
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• 2020

사용자 행위 기반 인증 기술은 다른 인증 기술들에 비해서 인증의 인식률을 높이는데 많은 데이터의 장기간 추출이 필요하다. 본 논문은 터치 센서와 자이로스코프를 이용하여 그동안의 행위 기반 인증 연구에서 사용 되었던 행위 특정 데이터들 중에서 핵심적인 최소한의 데이터들만을 사용하였다. 측정한 데이터들의 검증에는 그간 사용자 행위 기반 인증 연구에서 이용되지 않고 문서 검색의 유사도 측정에 사용되었던 코사인 유사도를 사용하였다. 이를 통해 최소한의 특정 데이터와 기준이 되는 데이터의 코사인 유사도 비교 검증만을 통해서도 인증 범위에 적용되는 임계값을 조절하는 방식을 동해서 최초 EER 37.637%에서 최종 EER 1.897%의 높은 검증 성능을 증명하는데 성공하였다.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.143-149
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• 2021

As the need to establish a big data system for rapid provision of big data and efficient management of resources has emerged due to rapid entry into the hyper-connected intelligence information society, public institutions are pushing to establish a big data system. Therefore, this study analyzed and combined the success factors of big data-related studies and the specific aspects of big data in public institutions based on the measurement of environmental factors for establishing an integrated information system for higher education institutions. In addition, 19 measurement items reflecting big data characteristics were derived from big data experts using brainstorming and Delphi methods, and a plan to successfully apply them to public institutions that want to build big data systems was proposed. We hope that this research results will be used as a foundation for the successful establishment of big data systems in public institutions.

• Information Systems Review
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• v.26 no.1
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• pp.57-71
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• 2024

There are several ways to assess the value of personal data, but there is no standard for evaluating data value. In the case of medical my data utilization platform services, it was found that when the platform company received the user's consent and received data for the purpose of data utilization, an average of about 4,000 credits was paid per user as compensation. As in the previous case, the value of personal information is mainly measured based on the value of each individual, not on specific items of personal information. However, as the number and type of personal information increases, the value of personal information must be measured by type. This study focuses on measuring the value of unstructured personal information, especially images, and proposes standards for unstructured personal information. By measuring the value of images, we will be able to help platform companies set credit standards for compensation per person when providing data and support objective and reasonable pricing when selling B2B data.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.218-230
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• 2007

Measured values of solar radiation data have a characteristic that they change almost by the minute, so original data can be massive. Therefore, we need to construct a database which stores and manages history data of solar radiation data systematically. A study of an estimation method of the future change trend is also required. In this paper, we present a data structure in order to store history data of solar radiation data and propose an estimation method for the change trend of solar radiation that applies to a time-series decomposition method. Also, we present the results of experiments based on measured data from 20 domestic cities in Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.19-21
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• 2022

Anomaly detection using self-supervised learning typically generates synthetic data to learn to classify normal and abnormal, and uses real abnormal data as test data to measure anomaly detection performance. In a study using this method to generate synthetic data similar to normal data, anomaly detection was carried out by generating synthetic data by cutting and pasting a specific patch from the original image. In this way, the degree of similarity to normal data depends on the number and size of patches, which affects anomaly detection performance. In this paper, synthetic data were generated by varying patch sizes and numbers, and then similarity and analysis with normal data were conducted using a pre-trained model, and anomaly detection performance was measured by learning the model.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.619-622
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• 2018

최근 데이터의 형태는 점점 다양화되고 증가하고 있기 때문에 데이터의 체계적 분류 및 관리의 필요성이 증대되고 있다. 이러한 목적을 위하여 데이터에 대한 품질 평가는 중요한 요소가 된다. 최근 데이터는 기존의 정형화된 데이터보다 비정형 데이터가 대부분을 차지하고 있다. 그러나 기존의 데이터 품질 평가는 정형 데이터에 편중되어 왔다. 따라서 다양한 형태와 의미를 가지고 있는 비정형 데이터는 기존의 평가 기술로는 품질을 측정하기 어렵다. 이와 같은 문제로 본 논문은 텍스트기반의 비정형 데이터에 적용 가능한 영역별 평가 지표를 구축하고, 신문기사와 커뮤니티(질의응답)데이터를 사용하여 각 요소별 품질을 측정하여 그 결과에 대해서 고찰하였다.