• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.559-563
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• 2015

Identification of energy use patterns in buildings has a great opportunity for energy saving. To find what energy use patterns exist, clustering analysis has been commonly used such as K-means and hierarchical clustering method. In case of high dimensional data such as energy use time-series, data reduction should be considered to avoid the curse of dimensionality. Principle Component Analysis, Autocorrelation Function, Discrete Fourier Transform and Discrete Wavelet Transform have been widely used to map the original data into the lower dimensional spaces. However, there still remains an ongoing issue since the performance of clustering analysis is dependent on data type, purpose and application. Therefore, we need to understand which data reduction techniques are suitable for energy use management. This research aims find the best clustering method using energy use data obtained from Seoul National University campus. The results of this research show that most experiments with data reduction techniques have a better performance. Also, the results obtained helps facility managers optimally control energy systems such as HVAC to reduce energy use in buildings.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1221-1223
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• 2003

With speediness of economy, the structure of land use has taken lots of change. How can we quickly and exactly obtain detailed land use/cover change information, and then we know land resource amount, quality, distributing and change direction. More and more high resolution satellite systems are under development. So we can make good use of RS data, existed GIS data and GPS data to extract change information and update map. In this paper a fully automated approach for detecting land use/cover change using remote sensing data with object-oriented classification based on GIS data, GPS data is presented (referring to Fig.1). At same time, I realize integrating raster with vector methods of updating the basic land use/land cover map based on 3S technology and this is becoming one of the most important developing direction in 3S application fields; land-use and cover change fields over the world. It has been successful applied in two tasks of The Ministry of Land and Resources P.R.C and taken some of benefit.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.426-428
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• 2003

Optical and microwave remote sensing data have been widely used in land cover and land use classification. Thanks to the spectral absorption characteristics of ground object in visible and near infrared region, optical data enables to extract different land cover types according to their material composition like water body, vegetation cover or bare land. On the other hand, microwave sensor receives backscatter radiance which contains information on surface roughness, object density and their 3-D structure that are very important complementary information to interpret land use and land cover. Separate use of these data have brought many successful results in practice. However, the accuracy of the land use / land cover established by this methodology still has some problems. One of the way to improve accuracy of the land use / land cover classification is just combination of both optical and microwave data in analysis. In this paper for the research, the author used LANDSAT TM scene 127/45 acquired on October 21, 1992, JERS-1 SAR scene 119/265 acquired on October 27, 1992 and aerial photographs taken on October 21, 1992. The study area has been selected in Hanoi City and surrounding area, Vietnam. This is a flat agricultural area with various land use types as water rice, secondary crops like maize, cassava, vegetables cultivation as cucumber, tomato etc. mixed with human settlement and some manufacture facilities as brick and ceramic factories. The use of only optical or microwave data could result in misclassification among some land use features as settlement and vegetables cultivation using frame stages. By combination of multitemporal JERS-1 SAR and TM data these errors have been eliminated so that accuracy of the final land use / land cover map has been improved. The paper describes a methodology for data combination and presents results achieved by the proposed approach.

• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.737-749
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• 2003

This Paper analyzed simultaneous activities of the time use survey by Korea National Statistical Office to use data mining's association rule. The survey of National Statistical Office in 1999 considered general analysis for main activities like that personal care(eating), employment and study, leisure, travel by purpose. But if we use the association rule, we can found the ratio of simultaneous activities at the same time. And also we can found the probability that another activities practise if we act one particular activity. Using this association rule of data mining we can do more developed and analytical sociological study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.587-608
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• 2022

The European Union recently established the General Data Protection Regulation (GDPR) for secure data use and personal information protection. Inspired by this, South Korea revised their Personal Information Protection Act, the Act on Promotion of Information and Communications Network Utilization and Information Protection, and the Credit Information Use and Protection Act, collectively known as the "Three Data Bills," which prescribe safe personal information use based on pseudonymous data processing. Based on these bills, the personal data store (PDS) has received attention because it utilizes the MyData service, which actively manages and controls personal information based on the approval of individuals, and it practically ensures their rights to informational self-determination. Various types of PDS models have been developed by several countries (e.g., the US, Europe, and Japan) and global platform firms. The South Korean government has now initiated MyData service projects for personal information use in the financial field, focusing on personal credit information management. There is also a need to verify the efficacy of this service in diverse fields (e.g., medical). However, despite the increased attention, existing MyData models and frameworks do not satisfy security requirements of ensured traceability, transparency, and distributed authentication for personal information use. This study analyzes primary PDS models and compares them to an internationally standardized framework for personal information security with guidelines on MyData so that a proper PDS model can be proposed for South Korea.

• 한국산학기술학회논문지
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• 제20권10호
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• pp.478-485
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• 2019

본 연구는 공공데이터 활용 여부에 따른 국내 기업체들의 빅데이터 기술사용 및 서비스 이용 의도에 미치는 영향요인을 파악하기 위한 탐색적 연구이다. 2017년 13,136개 국내 기업의 전산담당자와 총무담당자를 대상으로 정보화 통계 설문조사 데이터를 R 3.5.3 프로그램을 이용하여 연구 모형에 따른 가설검정을 시행하였다. 먼저 빅데이터 기술 및 서비스 이용의도에 영향을 미치는 요인에 대한 로지스틱 회귀분석 결과, 공공데이터를 활용하는 업체에서는 비용 절감이 빅데이터 이용의도에 긍정적 영향을 미치는 요인으로 나타났고, 공공데이터를 활용하지 않는 기업의 경우 고객만족은 긍정적 영향, 의사결정 지원은 빅데이터 이용에 부정적인 영향을 미치는 요인으로 나타났다. 최근 들어 우리 정부는 기업 지원에 있어 4차 산업 혁명의 동력 중 공공데이터 개방과 더불어 빅데이터 활용 부분에 중점을 두고 있다. 그러나 본 연구결과, 아직까지 국내 기업 전반에 공공데이터 및 빅데이터 활용이 미진한 것으로 밝혀졌다. 단, 본 연구를 위한 정보화 통계 데이터가 2017년도 데이터임을 감안할 때 정부의 빅데이터 지원 정책 등 실효적 성과를 분석하기 위해서는 지속적인 빅데이터 활용 및 이에 따른 성과에 대한 연구도 필요하다 하겠다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.1256-1263
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• 2022

With the advent of the Fourth Industrial Revolution, the amount of energy used in buildings has been increasing due to changes in the energy use structure caused by the massive spread of information-oriented equipment, climate change and greenhouse gas emissions. For the efficient use of energy, it is necessary to have a plan that can predict and reduce the amount of energy use according to the type of energy source and the use of buildings. To address such issues, this study presents a model embedded in a digital twin that predicts energy use in buildings. The digital twin is a system that can support a solution of urban problems through the process of simulations and analyses based on the data collected via sensors in real-time. To develop the energy use prediction model, energy-related data such as actual room use, power use and gas use were collected. Factors that significantly affect energy use were identified through a correlation analysis and multiple regression analysis based on the collected data. The proof-of-concept prototype was developed with an exhibition facility for performance evaluation and validation. The test results confirm that the error rate of the energy consumption prediction model decreases, and the prediction performance improves as the data is accumulated by comparing the error rates of the model. The energy use prediction model thus predicts future energy use and supports formulating a systematic energy management plan in consideration of characteristics of building spaces such as the purpose and the occupancy time of each room. It is suggested to collect and analyze data from other facilities in the future to develop a general-purpose energy use prediction model.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 춘계학술대회
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• pp.159-170
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• 2003

This Paper analyzed simultaneous activities of the time use survey by Korea National Statistical Office to use data mining‘s association rule. The survey of National Statistical Office in 1999 considered general analysis for simultaneous activities. But if we use the association rule, we can found the ratio of particular activities at the same time. And we found the probability that another activities practise if we act one particular activity. Using this association rule of data mining we can do more developed and analytical sociological study.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.267-270
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• 1999

Use of coherence data from operational satellite based SAR sensors has been experimented both on C and L band to identify landcover in tropics. While coherence data proved useful to improve accuracy in landcover identification, such data are not readily available. On the other hand, integrated use of backcatter data by multiple satellites is readily feasible. The very question to be asked is whether integration of backscatter data on multiple bands (e.g. C and L band) is either inferior or superior to use of coherence data. We therefore still do not have a solid clue to answer to the very question. The aim of this study is to evaluate the performance of "integrated use" of backscatter data on C and L band (by ERS and JERS respectively) to identify landcover, vis-a-vis the same by combination of backscatter and coherence data by single satellite. The study was carried out for an area in the southern part of the Sumatra Island, Indonesia. The area has been intensively converted from natural forest into plantation. Five categories of landcover exist in this study area. By ERS-1, only 2 or 3 classes may be identified with the backscatter data alone, while adding the coherence data could delineate 4 classes. By JERS-1, only 3 to 4 classes may be identified with the backscatter data alone, while 4 classes could be clearly delineated by adding the coherence data. By integrating backscatter data on two bands, 4 to 5 classes may be identified. It represents the best results among cases examined. The outcome of the study suggests that integrated use of backscatter data on two bands by ERS and JERS is as powerful as use of backscatter and coherence data on single band by one of these satellite.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 가을 학술발표회 논문집(II)
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• pp.1291-1296
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• 2000

A basis for the direct use of data from nondestructive evaluation methods in bridge management systems is presented. Bridge management systems use integer-valued condition ratings to recognize conditions of bridge elements, to model progression of deterioration, and to determine repair needs. Data from nondestructive evaluation methods can inform management systems on the extent of damage, on the initiation of deterioration processes, and on the exposure of bridge elements to aggressive agents. In addition, data obtained through nondestructive evaluation methods allow the formation of models of specific deterioration process. The use of these data in bridge management systems requires redefinition of condition ratings together with the creation of procedures for automated interpretation of data. By these action, nondestructive evaluation methods are directly used to assign condition ratings, and condition ratings are made into terse form of NDE data that are compatible with present day bridge management systems. This paper reports work in progress to strategic use of nondestructive evaluation methods in bridge management system.