• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1660-1661
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• 2007

수 처리 분야의 통합시스템을 구현함에 있어 이기종 장비 간의 데이터 연계는 프로그래머의 통신 프로그래밍 작업으로 매번 개발을 하여하는 문제점을 가지고 있다. 이로 인해 시스템의 안정화에 많은 시간 및 인력이 투입되고 있다. 본 연구는 인터프리터 엔진을 활용하여 엔지니어가 엔지니어링 한 데이터 (통신 스크립트)를 번역, 해석, 자동동작 시켜 별도의 프로그래밍 작업(개발)없이 엔지니어링으로만 통합 시스템의 감시 및 제어를 구축 가능케 프로토콜 편집기를 개발 하여 신뢰성 높은 시스템을 구축키 위한 내용이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.290-293
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• 2017

최근 IoT 기술발달로 인한 스마트폰 및 대용량 미디어기기 사용증가로 인터넷 네트워크 사용량이 폭발적으로 증가되고 있고, 이러한 데이터 사용량 급증으로 대량의 데이터를 지칭하는 빅데이터 수집 및 분석에 많은 기업과 정부가 주목하고 있다. 빅데이터는 기존에 없던 새로운 데이터의 구축이 아니며, 그동안 축적된 다방면의 방대한 데이터의 집합이라 할 수 있다. 빅데이터의 이용 및 분석에 대한 기업 정부 학계의 수요는 증가하고 있지만, 고난도의 빅데이터 분석을 위한 인프라 구축이 선결과제이어서, 이러한 인프라구축 비용 때문에 빅데이터 분석이 일선 산업분야에 바로 적용하는데 많은 장애요인이 되어 데이터 분석가들의 빅데이터 분석에 애로사항으로 존재하고 있다. 이러한 어려움을 해소하기 위한 방안으로 새로운 인프라 구축 없이 Google Analytics API를 연동한 R 프로그래밍의 데이터 시각화를 활용한 데이터 분석 방안을 제시하고자 한다. 본 연구에서는 구글 애널리틱스 API를 연동하여 사용자 웹사이트의 사용자접속, 사이트운영, 이벤트 발생 등의 데이터를 R 프로그램을 활용하여 사이트 현황을 데이터 시각화로 분석하고 운영중인 웹사이트에 적용 가능한 콘텐츠 개발 방안에 대해 연구하였다.

• Annual Conference of KIPS
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• 2003.11a
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• pp.189-192
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• 2003

이 논문에서는 그리드환경에서 Remote Procedure Call(RPC) 프로그래밍 인터페이스를 위한 메커니즘인 GridRPC 의 성능향상을 위해 DAG 기반의 Co-scheduling API 를 제안한다. 네트워크 상의 통신횟수를 줄임으로써 GridRPC call 의 최적화를 도모하기 위한 프로그래밍 인터페이스와 이를 가능하게 하는 서버구조를 제안한다. DAG 기반의 co-scheduling 은 서버-클라이언트간의 연산에 사용되는 입력값과 출력값들의 흐름을 분석하여 사용자로 하여금 DAG(Directed Acyclic Graph)로 GridRPC call 들을 구성하고 이를 기반으로 GridRPC call 들을 최적화하는 방법이다. 또한, GridRPC가 Client Interface 이기 때문에 생기는 문제점인 서버간의 지원의 문제점을 SOAP 서버의 Wrapping 을 통해 해결한다.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.73-117
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• 2004

Software 기술의 변화: 다중프로그래밍, 다중 사용자(multiuser), 실시간처리/데이터베이스, 제품소프트웨어 출현, 강력한 데스크-탑 시스템, 객체지향 시스템, 전문가 시스템, 인공지능(중략)

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.151-160
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• 2016

The purpose of this research is to investigate Korean popular attitudes and social perceptions of 'sharing economy' terminology at the current moment from a creative or socio-economic point of view. In Korea, this study discovers and interprets the objective and tangible annual changes and patterns of sociocultural collective intelligence that have taken place over the last five years by applying text mining in the big data analysis approach. By crawling and Googling, this study collected a significant amount of time series web meta-data with regard to the theme of the sharing economy on the world wide web from 2010 to 2014. Consequently, huge amounts of raw data concerning sharing economy are processed into the value-added meaningful 'word clouding' form of graphs or figures by using the function of word clouding with R programming. Till now, the lack of accumulated data or collective intelligence about sharing economy notwithstanding, it is worth nothing that this study carried out preliminary research on conducting a time-series big data analysis from the perspective of knowledge management and processing. Thus, the results of this study can be utilized as fundamental data to help understand the academic and industrial aspects of future sharing economy-related markets or consumer behavior.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.219-227
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• 2019

The educational method of physical computing, where students can experience software programming principles and practices while making concrete objects beyond outputs residing just inside of computer monitors, are drawing attentions. This current research sought an instructional method for pre-service teachers that they can experience 3D printing and modeling and at the same time they can understand programming principles in the 3D modeling processes. To achieve this aim, the TinkerCAD $Codeblocks^{(R)}$ was analyzed based on the computational thinking framework and a course utilizing the $Codeblocks^{(R)}$ to 3D modeling was devised. The designed class was applied to pre-service teachers and the students' perceptions of the class were collected by using a semi-structured survey. This study provides implications to software education for pre-service teachers as an instructional case that 3D printing is used to connecting computational thinking skills.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.4
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• pp.113-118
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• 2017

As the demand for industrial robots and Automated Guided Vehicles (AGVs) increases, higher performance is also required from them. Fuzzy controllers, as part of an intelligent control system, are a direct control method that leverages human knowledge and experience to easily control highly nonlinear, uncertain, and complex systems. This paper uses a $LabVIEW^{(R)}-based$ fuzzy controller with gain scheduling to demonstrate better performance than one could obtain with a fuzzy controller alone. First, the work area was set based on forward kinematics and inverse kinematics programs. Next, $LabVIEW^{(R)}$ was used to configure the fuzzy controller and perform the gain scheduling. Finally, the proposed fuzzy gain scheduling controller was compared with to controllers without gain scheduling.

• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.42-51
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• 2013

The R language is an open source programming language and a software environment for statistical computing and data visualization. The R language is widely used among a lot of statisticians and data scientists to develop statistical software and data analysis. The R language provides a variety of statistical and graphical techniques, including basic descriptive statistics, linear or nonlinear modeling, conventional or advanced statistical tests, time series analysis, clustering, simulation, and others. In this paper, we first introduce the R language and investigate its features as a data analytics tool. As results, we may explore the application possibility of the R language in the field of data analytics.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.651-669
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• 2018

This study suggests the prediction model to estimate the specific energy of a pick cutter using a gene expression programming (GEP) and particle swarm optimization (PSO). Estimating the performance of mechanical excavators is of crucial importance in early design stage of tunnelling projects, and the specific energy (SE) based approach serves as a standard performance prediction procedure that is applicable to all excavation machines. The purpose of this research, is to investigate the relationship between UCS and BTS, penetration depth, cut spacing, and SE. A total of 46 full-scale linear cutting test results using pick cutters and different values of depth of cut and cut spacing on various rock types was collected from the previous study for the analysis. The Mean Squared Error (MSE) associated with the conventional Multiple Linear Regression (MLR) method is more than two times larger than the MSE generated by GEP-PSO algorithm. The $R^2$ value associated with the GEP-PSO algorithm, is about 0.13 higher than the $R^2$ associated with MLR.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.1-8
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• 2012

The horizontal alignment of road is deeply related with the stability of the road and traffic capacity. It is necessary to analyze horizontal alignment of road accurately for efficient maintenance of the road and relevance judgment about the standard. Recently the study on horizontal alignment of road using Lidar data and GPS was concluded, but they were many problem analyzing horizontal alignment radius of curvature in wide area. In this study, the tool which the radius of curvature can evaluate the suitability about "Rules about the Road Structure & Facilities Standards" by using center lines of the road of the digital map tries to implement on GIS. The interface was designed and implemented which can automatically estimate the Road Centerline Horizontal Alignment by using $ESRI^{(R)}$ $ArcObject^{TM}$.