• 천문학회보
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• 제42권1호
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• pp.57.2-57.2
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• 2017

Remote and robotic telescopes are the most effective instrument for astronomical survey projects. The system is based on the dynamic operation of all astronomical instruments such as dome and telescope control system (TCS), focuser, filter wheel and data taking camera. We adopt the ASCOM driver platform to control the instruments through the integrated software. It can convert different interface libraries from various manufacturers into a uniform standard library. This allows us to effectively control astronomical instruments without modifying codes. We suggest a conceptual design of software for automation of a small telescope such as the new wide-field 0.25m telescope at McDonald Observatory. It can also be applied to operation of multi-telescopes in future projects.

• 인터넷정보학회논문지
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• 제20권6호
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• pp.47-54
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• 2019

현재 건설되고 있는 댐이나 농업용 저수지와 같은 하천 시설의 준설은 안정적인 저수량을 확보하기 위해 이루어져야 한다. 그러나, 저수지나 댐의 정확한 담수량을 실시간으로 알려 주는 시스템을 찾기는 어렵다. 이러한 측정을 위해서는 매우 정확한 데이터를 실시간으로 수집하고 분석하기 위한 자동화된 시스템이 필요하다. 본 연구에서는 드론을 이용한 다중분할체적 계산을 통해 저수지의 담수량을 실시간으로 측정하는 방법을 제안하고 있으며, 이 방법을 이용하면 침전물 상태를 실시간으로 감지하고 정확한 준설 시기와 규모를 파악할 수 있다.

• 시스템엔지니어링학술지
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• 제1권1호
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• pp.14-19
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• 2005

High temperature vacuum furnaces or high standard electric furnaces demand high technology level and high production cost. Therefore, an iterative design process and the optimization approach under integrated computing environment are required to reduce the development risk. Moreover, it also required to develop an integrated design software that can manage the centralized database system between factory and design department, and the automated furnace design and analysis. The developed software is dedicated to the development of the vacuum (electric) furnaces. Based on the distribute middleware system, the GUI module, the CAD module, the thermal analysis module and the optimization module are integrated. For the DBMS, Microsoft Access is employed, the GUI is developed using Visual Basic language, and AutoCAD is utilized for the configuration design. By investigating the analysis code interface, the analysis and optimization process, and the data communication method, the overall system architecture, the method to integrate the optimizer and ana lysis codes, and the method to manage the data flow are proposed and verified through the optimal furnace design.

• 한국콘텐츠학회논문지
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• 제19권12호
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• pp.407-415
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• 2019

클라우드 컴퓨팅, 스마트워크 등으로 IT 환경 변화가 진행됨에 따라 기존의 경계 보안 모델이 한계를 보이고 있으며, 소프트웨어 정의 경계(Software Defined Perimeter)가 그 대안으로 논의되고 있다. 하지만, SDP Spec 1.0에서는 장치등록 절차와 정책 배포 과정 및 인증 키의 생성과 공유 과정이 명시되어 있지 않다. 이에 본 논문에서는 단일패킷인증(Single Packet Authentication)의 동작 절차를 개선하여 기존의 SDP 접근통제의 문제점을 보완하는 방법을 제안한다. 개선된 제안 방법을 통하여 기존 접근통제 방법에 비하여 일관되고 자동화된 통합 접근 통제 정책을 구현할 수 있음을 보이고자 한다.

• 융합보안논문지
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• 제22권1호
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• pp.3-9
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• 2022

개발 프로젝트의 소프트웨어 개발에 있어서 통합 개발환경의 역할은 매우 중요하다. 다수의 개발자가 각기 다른 모듈을 개발하면 컴파일과 디버깅, 그리고 통합과 테스트, 배포 등의 과정을 거치면서 제품이 완성된다. 하지만, 개발 과정에서의 버그나 각종 이슈 등은 소프트웨어 제품의 품질저하 및 요구사항 불만족 등의 문제를 발생시키게 되었고, 해당 문제를 회피하고 품질 향상을 위해 자동화 테스트의 필요성이 증가되었다. 본 연구에서는 통합 개발환경에서의 테스트 자동화를 통해 개발 프로세스 전 과정에서의 품질향상을 위한 4가지 관점의 테스트 자동화 모듈을 제안한다. 각 자동화 모듈은 데브옵스(DEVOPS) 방법으로 구현된 통합빌드프레임워크의 툴 체인 형태로 연결되어 구동된다.

• Genomics & Informatics
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• 제15권4호
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• pp.178-182
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• 2017

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

• 정보기술응용연구
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• 제1권
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제5권4호
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• pp.165-170
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• 2016

안드로이드 어플리케이션은 인텐트를 이용하여 다른 어플리케이션의 컴포넌트를 호출하여 실행시킬 수 있다. 하지만 컴포넌트들 사이의 상호작용이 정상적으로 처리되지 않으면 잘못된 컴포넌트가 실행되거나 전화 수신과 같은 시스템 브로드캐스트를 처리하지 못하는 문제점이 발생할 수 있다. 본 논문에서는 이와 같은 상호작용 문제점을 검사하기 위해 서로 연동하여 동작하는 어플리케이션들로부터 컴포넌트 기반의 다이어그램들을 생성하고 이를 하나의 병합된 다이어그램으로 변환하여 테스트 시나리오를 생성하는 방법을 제안한다. 제안된 방식은 기존의 테스팅 기법에서 고려하지 못한 어플리케이션간의 상호작용 검사를 효율적으로 수행할 수 있다.

• 한국CDE학회논문집
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• 제11권2호
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• pp.128-137
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• 2006

In this paper, a CAD/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares for a complex model in which the modeling by parametric feature is not easy to apply. Unigraphics is used for CAD modeling, in which the process is automated by using UG/Knowledge Fusion for modeling itself and UG/Open API function for the other functions respectively. Structural analyses are also carried out automatically by ANSYS using the imported parasolid model. The developed system is applied for the PLS(Plasma Lighting System) consisting of more than 20 components, which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The analyses include responses by static, wind and impact loads. As a result of analyses, tilt assembly, which is a link between upper and lower body, is found to be the most critical component bearing higher stresses. Experiment is conducted using MTS to validate the analysis result. Optimization is carried out using the software Visual DOC for the tilt assembly to minimize material volume while maintaining allowable stress level. As a result of optimization, the maximum stress is reduced by 57% from the existing design, though the material volume has increased by 21%.

• Mass Spectrometry Letters
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• 제4권2호
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• pp.25-29
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• 2013

Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution) method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.