• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.39-44
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• 2012

This paper propose a transmission method for "Transportation system" that can decide precise position under wide area road traffic environment. For precise position detecting, central station collect multiple receiver station's satellite navigation data and generate correction information. In this process, we need efficient real time transmission method for satellite navigation message that has variable data size. We propose real time data transmission method. This real time transmission method offer efficient processing structure for multiple receiver station's satellite navigation message. This paper explains proposed real time transmission method and proofs this transmission method.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.305-308
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• 2005

The COMS, Korea's first geostationary multipurpose satellite program will accommodate 3 kind of payloads; Ka-Band communication transponder, GOCI (Geostationary Ocean Color Imager), and MI (Meteorological Imager). MI raw data will be transferred to ground station via L-band link. The ground station will perform image data processing for raw data, generate them into the LRIT/HRIT format, the user dissemination data recommended by the CGMS. The LRIT/HRIT are disseminated via satellite to user stations. This paper shows the COMS LRIT data generation procedure based on COMS LRIT specification and its verification results using the LRIT user station.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.29-43
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• 1996

This paper identifies these data by the data diagnosis in lognormal distribution and presents the method to obtain exact parameter estimates and confidence intervals of regression line. The life-stress relationship uses Arrhenius model and life data generate Class-H insulation complete data by simulation. Also, the method to estimate parameters uses least squares estimation and externally Studentized residuals can be used as test statistics for identifing outliers. And influential cases are identified by Cook's distance. This research is intended to obtain the useful information for the life of products and test method, to save time and costs, and to help optimum accelerated life test plans.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1159-1166
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• 2010

To improve prediction quality of a nonlinear prediction system, the system's capability for uncertainty of nonlinear data should be satisfactory. This paper presents a TSK fuzzy prediction system that can consider and deal with the uncertainty of nonlinear data sufficiently. In the design procedures of the proposed system, HCBKA(Hierarchical Correlationship-Based K-means clustering Algorithm) was used to generate the accurate fuzzy rule base that can control output according to input efficiently, and the first-order difference method was applied to reflect various characteristics of the nonlinear data. Also, multiple prediction systems were designed to analyze the prediction tendencies of each difference data generated by the difference method. In addition, to enhance the prediction quality of the proposed system, an error compensation method was proposed and it compensated the prediction error of the systems suitably. Finally, the prediction performance of the proposed system was verified by simulating two typical time series examples.

• Proceedings of the KSRS Conference
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• v.2
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• pp.619-622
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• 2006

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral data. In this study, we attempted to generate the water vapor contents image from hyperspectral data itself and developed the atmospheric correction algorithm for EO-1 Hyperion data using pre-calculated atmospheric look-up-table (LUT) for fast processing. To apply the new atmospheric correction algorithm, Hyperion data acquired June 3, 2001 over Seoul area is used. Reflectance spectrums of various targets on atmospheric corrected Hyperion reflectance images showed the general spectral pattern although there must be further development to reduce the spectral noise.

• The Journal of Bigdata
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• v.2 no.1
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• pp.71-75
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• 2017

The topic of big data has gained attention from the industry and the academics, because of the revitalization of social network services. The purpose of this study is to analyze the application cases of big data according to the categories of U-City services. The result from this study is that inside and unstructured information is more applied than outside and structured information in order to generate big data.

• Journal of Mechanical Science and Technology
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• v.18 no.5
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• pp.753-761
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• 2004

In this paper, an efficient method for generating 5-axis cutting data for a turbine blade is presented. The interference elimination of 5-axis cutting currently is very complicated, and it takes up a lot of time. The proposed method can generate an interference-free tool path, within an allowance range. Generating the cutting data just point to the cutting process and using it to obtain NC data by calculating the feed rate, allows us to maintain the proper feed rate of the 5-axis machine. This paper includes the algorithms for: (1) CL data generation by detecting an interference-free heel angle, (2) finding the optimal tool path interval considering the cusp-height, (3) finding the adaptive feed rate values for each cutter path, and (4) the inverse kinematics depending on the structure of the 5-axis machine, for generating the NC data.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.11
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• pp.897-906
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• 2002

Standard temperature and absolute humidity weather correlations of Seoul for dynamic energy simulation have been developed regressing the measured data compiled by the Korea Meteorological Adminstration during a 10-year period from 1991 to 2000. The mathematical equations can generate the daily and yearly variations of outdoor weather data with consistency unlike the measured data which may show abnormal behavior, Considering that each hour of the day follows a certain yearly pattern, the correlations are developed for each hour. The derived 24 simple mathematical equations can be used for estimating outdoor temperature and humidity conditions for any arbitrary time of the year.

• Genomics & Informatics
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• v.11 no.2
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• pp.60-67
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• 2013

A decade-long project, led by several international research groups, called the Encyclopedia of DNA Elements (ENCODE), recently released an unprecedented amount of data. The ambitious project covers transcriptome, cistrome, epigenome, and interactome data from more than 1,600 sets of experiments in human. To make use of this valuable resource, it is important to understand the information it represents and the techniques that were used to generate these data. In this review, we introduce the data that ENCODE generated, summarize the observations from the data analysis, and revisit a computational approach that ENCODE used to predict gene expression, with a focus on the human transcriptome and its association with chromatin modifications.