• Journal of KIISE:Databases
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• v.28 no.3
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• pp.301-314
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• 2001

Data mining refers to a set of techniques for discovering implicit and useful knowledge from large database. Many studies on data mining have been pursued and some of them have involved issues of temporal data mining for discovering knowledge from temporal database, such as sequential pattern, similar time sequence, cyclic and temporal association rules, etc. However, all of the works treat problems for discovering temporal pattern from data which are stamped with time points and do not consider problems for discovering knowledge from temporal interval data. For example, there are many examples of temporal interval data that it can discover useful knowledge from. These include patient histories, purchaser histories, web log, and so on. Allen introduces relationships between intervals and operators for reasoning about relations between intervals. We present a new data mining technique that can discover temporal relation rules in temporal interval data by using the Allen's theory. In this paper, we present two new algorithms for discovering algorithm for generating temporal relation rules, discovers rules from temporal interval data. This technique can discover more useful knowledge in compared with conventional data mining techniques.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.49-54
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• 2021

With the recent development of smart healthcare technology, interest in daily diseases is increasing. However, healthcare data has an imbalance between positive and negative data. This is caused by the difficulty of collecting data because there are relatively many people who are not patients compared to patients with certain diseases. Data imbalances need to be adjusted because they affect performance in ongoing learning during disease prediction and analysis. Therefore, in this paper, We replace missing values through multiple imputation in detection models to determine whether they are prevalent or not, and resolve data imbalances through over-sampling. Based on AutoML using preprocessed data, We generate several models and select top 3 models to generate ensemble models.

• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.167-190
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• 2023

This study is a literature study that analyzed the research data curation models using activity theory as a theoretical framework. Based on the factors of the activity used in the activity theory, this study analyzed various research data curation models, as well as issues that needed discussion in the library field in carrying out research data curation activities. And based on this, a new research data curation conceptual model was proposed. This study analyzed how the five previously proposed digital curation lifecycle models are configured, and analyzed the actions presented sporadically in each model. A new research data curation conceptual model was proposed by analyzing factors, extracting common factors and integrating them into a new model. In addition, six issues to be considered in carrying out research data curation activities in libraries and repositories were analyzed and discussed. The research data curation conceptual model proposed in this study consists of a total of 10 steps, and it contains practical issues and contradictions to consider at each stage of activity.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.195-217
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• 2022

SIARD_KR is an administrative information dataset preservation tool. It is a partially modified version of SIARD, technology used for long-term preservation of relational databases developed by the Swiss Federal Archives, to suit Korea's situation better. Previous studies have focused on how SIARD is able to effectively extract all data contained in the relational database without loss. However, not all data contained in the database is meaningful information, that is, an administrative information dataset. This paper began, therefore, with the awareness of the problem of whether SIARD_KR reflects the characteristics of the administrative information dataset. SIARD_KR is not only a tool for extracting data stored in the DB. We want to see if it is capable of identifying and extracting only meaningful information, and maintaining meaningful information, even if it is separated from the original system. The purpose of this paper is to analyze the structure of SIARD_KR, identify expected problems, and suggest improvement measures for them.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.571-581
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• 2020

Vegetation affects water level change and flow resistance in rivers and impacts waterway ecosystems as a whole. Therefore, it is important to have accurate information about the species, shape, and size of any river vegetation. However, it is not easy to collect full vegetation data on-site, so recent studies have attempted to obtain large amounts of vegetation data using terrestrial laser scanning (TLS). Also, due to the complex shape of vegetation, it is not easy to obtain accurate information about the canopy area, and there are limitations due to a complex range of variables. Therefore, the physical structure of vegetation was analyzed in this study by reconfiguring high-resolution point cloud data collected through 3-dimensional terrestrial laser scanning (3D TLS) in a voxel. Each physical structure was analyzed under three different conditions: a simple vegetation formation without leaves, a complete formation with leaves, and a patch-scale vegetation formation. In the raw data, the outlier and unnecessary data were filtered and removed by Statistical Outlier Removal (SOR), resulting in 17%, 26%, and 25% of data being removed, respectively. Also, vegetation volume by voxel size was reconfigured from post-processed point clouds and compared with vegetation volume; the analysis showed that the margin of error was 8%, 25%, and 63% for each condition, respectively. The larger the size of the target sample, the larger the error. The vegetation surface looked visually similar when resizing the voxel; however, the volume of the entire vegetation was susceptible to error.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.85.1-85.1
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• 2016

현대 과학기술에는 표면/계면 및 나노물질의 구조와 물성을 분석하는 다양한 방법들이 존재한다. 이들 분석장비들의 분해능과 감도의 향상으로 이전에는 보지 못한 물성들이 속속 발견되고 있다. 이러한 흐름 속에서 분석장비들의 다기능 시대가 열리고 있다. 예전에는 성분, 형태, 구조, 전자구조 등을 분석하기 위해 각각에 해당하는 분석장비들이 동원되었다. 하지만 21세기에 접어들어 분석장비들이 두 종류 이상의 분석이 가능하도록 개발되었다. 예를 들면, TEM으로 형태를 보는 것 외에도 TED와 EELS로 구조와 성분을 동시에 확인할 수 있게 되었다. 전통적인 성분 및 전자구조 분석법의 하나인 광전자분광법도 microscopy 기능을 탑재하는 변신이 있었다. 본 발표에서는 빛과 전자를 시료에 조사하여 물질의 성분, 형태, 구조, 전자구조 등을 동시에 분석이 가능한 분석법들에 대해 소개하고자 한다. 그 중, SPEM(Scanning Photoelectron Emission Microscopy)은 포항가속기연구소에 설치되어 있으며, PEEM(Photoelectron Microscopy)과 LEEM(Low Energy Electron Microscopy)은 수차보정장치를 갖춘 사양으로 최근 한국기초과학지원연구원에 설치되었다. 위에 언급한 장비를 활용하여 얻은 데이터를 바탕으로 나노물질의 표면 및 계면의 특성을 분석하는 방법 및 최근 연구 결과를 소개하고자 한다.

• Annual Conference of KIPS
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• 2004.05a
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• pp.1299-1302
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• 2004

본 연구에서는 MANET(Mobile Ad Hoc Network)에서 분산 PKI(Public Key Infrastructure) 메커니즘을 라우팅 프로토콜에 적용하기 위한 방법을 제안한다. 이를 위해 MANET이 사용하는 라우팅 프로토콜로 CBRP(Cluster Based Routing Protocol)를 고려한다. 제안하는 프로토콜은 CBRP의 기능과 분산 PKI 메커니즘을 활용하여 효율적으로 인증서 체인을 찾을 수 있고, 이를 통해 통신노드 상호간의 세션키 설정과 송수신하고자 하는 데이터에 대한 암호화를 지원한다. 또한, 라우팅 프로토콜의 안전한 동작을 위해 제안하는 프로토콜은 전자서명된 HELLO 메시지를 교환하여 악의적인 공격자들에 대해 신뢰성을 제공하고, 안전한 라우팅을 가능하게 한다.

• Annual Conference of KIPS
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• 2010.11a
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• pp.883-885
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• 2010

최근 무선통신기술의 발전으로 3G, WIFI, 그리고 블루투스와 같은 다양한 통신 인터페이스를 지닌 스마트폰이 등장하고 있다. 이러한 다양한 인터페이스를 동시에 활용하게 되면 보다 더 빠른 속도로 데이터를 송수신할 수 있다. 이러한 시스템의 대표적인 특징은 서버로 집중되는 트래픽을 분산시킬 수 있다는 것이다. 이러한 특징 때문에 최근 모바일 P2P 와 스트리밍 서버를 통한 동영상 스트리밍에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 다양한 네트워크 인터페이스를 활용한 P2P 스트리밍 시스템을 제안한다. 제안하는 시스템은 모바일 피어들로 P2P 네트워크를 구성하고 3G 망을 이용하여 서버에 접속을 한다. 본 논문에서는 간단한 시나리오를 통하여 제안한 시스템의 성능을 분석하였다. 실험 결과, 시스템의 버퍼링은 44.0% 감소하였고, 에너지는 30.2% 적게 소모하였으며, 그리고 서버의 트래픽 사용량도 50.0% 감소시켰다.

• Annual Conference of KIPS
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• 2011.11a
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• pp.261-264
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• 2011

최근 들어 스마트폰 보급의 확산과 더불어 일상생활에서 스마트폰 사용자들이 편리하게 이용할 수 있는 모바일 편의 서비스들의 개발도 활발하게 진행되고 있다. 본 논문에서는 안드로이드 스마트폰 환경에서 개발된 일정 안내 서비스의 설계와 구현에 대해 소개한다. 이 서비스는 선행 연구를 통해 개발된 인공지능 자동 계획 기술 기반의 모바일 퍼스널 어시스턴트 개발 도구인 스마트 스크립트 시스템을 이용하여 구현되었으며, 한 번의 버턴이나 아이콘 터치만으로 간단히 구글 캘린더에 저장중인 스마트폰 사용자의 일정 데이터를 기초로 음성 발화를 통해 그 날의 일정과 날씨를 알려주는 서비스이다. 본 논문에서는 실험을 통해 스마트 스크립트 시스템 및 일정 안내 서비스의 편리성과 효율성을 분석해본다.

• The Journal of Korean Academy of Prosthodontics
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• v.62 no.4
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• pp.375-385
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• 2024

In esthetic prosthetic treatment, color, shape, texture of teeth, and harmony with the facial appearance are considered very important. The virtual patient is formed by integrating data from intraoral and facial scans and mandibular movement records, making fabricating more aesthetic and functional prostheses possible in digital dentistry. In this case report, the patient with the tilted occlusal plane and facial asymmetry was restored with an anterior maxillary implant and a tooth-supported fixed prosthesis using the virtual patient. By using a virtual patient, it was possible to communicate between the dentist and patient or the dental technician during the design process, and we report this case because the results showed satisfactory aesthetic and functional results after treatment.