• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• 풍력에너지저널
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• 제4권1호
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• pp.20-29
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• 2013

Load measurement, which is performed based on IEC 61400-13, consists of three stages: the stage of collecting huge amounts of load measurement data through a measurement campaign lasting for several months; the stage of processing the measured data, including data validation and classification; and the stage of analyzing the processed data through time series analysis, load statistics analysis, frequency analysis, load spectrum analysis, and equivalent load analysis. In this research, we pursued the development of an analysis software in MATLAB to save labor and to secure exact and consistent performance evaluation data in processing and analyzing load measurement data. The completed analysis software also includes the functions of processing and analyzing power performance measurement data in accordance with IEC 61400-12. The analysis software was effectively applied to process and analyse the load measurement data from a demonstration research for a 750 kW direct-drive wind turbine generator system (KBP-750D), performed at the Daegwanryeong Wind Turbine Demonstration Complex. This paper describes the details of the analysis software and its processing and analysis stages for load measurement data and presents the analysis results.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.351-356
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• 2011

Some materials show the character of rigid body in low frequency spectrum. The rigid body motions are consisted of translational and rotational motions. Especially, we can get the acceleration or displacement of a random point in the rigid body by analyzing rigid body transfer matrix at the car's engine and power train. Actually it is difficult to measure the acceleration by attaching the sensor inside of the engine and power train. So the hard to predict acceleration data can be achieved attaching the sensor on the outside of the engine and power train by analyzing the data of rigid body motion which the engine is operated using dynamo. Also this paper will show the change of predicted data and accuracy variation by not using all the measured data but a few exceptions of the point number.

• 한국콘텐츠학회논문지
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• 제13권2호
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• pp.211-219
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• 2013

빅 데이터를 활용한 분석 방법은 빅 데이터를 처리 할 수 있는 기술 기반으로 발전되어 오고 있다. 많은 IT 리서치 기관들이 빅 데이터를 통한 새로운 분석의 패러다임을 예견하고 있고, 또한 IT 벤더들을 중심으로 빅 데이터 처리를 위한 표준 기술들을 제시하고 있다. 빅 데이터는 IT 기기 및 환경의 발달과도 상호연관적이고 소셜 미디어를 주측으로 기존에 예측하지 못하는 비정형화된 데이터들을 정형화 하여, 이에 따른 다양한 분석, 예측 및 최적화에 초점이 맞추어 발달 하고 있다. 과거의 분석 기법은 정형화된 데이터를 기반으로 데이터 마이닝, OLAP, 통계 분석등을 통한 의사결정 도구로서 사용되어 왔다. 하지만 최근 빅데이터를 이용한 새로운 분석의 패러다임을 통해 분석기법의 다양화, 비정형 데이터 분석 등 새로운 형태의 기반 기술발전과 다양한 형태의 데이터를 통한 새로운 분석을 통해 통찰력을 높일 수 있다. 더욱이 고성능의 컴퓨팅 환경들의 발달과 표준화된 대용량 데이터 처리 기술 발달이 향후 조금 더 다양한 형태의 분석패턴을 만들어 갈 것이다. 따라서 본 논문은 빅 데이터를 통해 분석 가능한 다양한 기법을 알아보고, 기존의 데이터 마이닝 분석 기법을 통한 소셜 미디어의 분석 형태에 대한 활용 및 분석방안을 제시 하였다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.487-496
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• 2008

Recently survival analysis becomes popular in a variety of fields so that a number of statistical packages are developed for analyzing the survival model. In this paper, several types of survival models are introduced and considered briefly. In addition, widely used three packages(SAS, SPSS, and STATA) for survival data are reviewed and their characteristics are investigated.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1993년도 추계학술대회논문집
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• pp.133-144
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• 1993

Psychophysical data, in general, belong to one of the four scale categories : Nominal, Ordinal, Interval, and Ratio Scale. This paper introduces properties of the four scale categories and describes some psychophysical scales that attempt to measure subjective feeling or opinion of human. In addition, guidelines of analyzing and interpreting measured data are suggested. Some examples of analyzing and interpreting paychophysical data inappropriately are presented especially with category scales which have been used most widely in measuring subjective information.

• 한국측량학회지
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• 제34권6호
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• pp.569-578
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• 2016

With the recent advancement of surveying and technology, the spatial data acquisition rates and precision have been improved continually. As the updates of spatial data are rapid, and the size of data increases in line with the advancing technology, the LOD (Level of Detail) algorithm has been adopted to process data expressions in real time in a streaming format with spatial data divided precisely into separate steps. The existing GRID analysis utilizes the single DEM, as it is, in examining and analyzing all data outside the analysis area as well, which results in extending the analysis time in proportion to the quantity of data. Hence, this study suggests a method to reduce analysis time and data throughput by acquiring and analyzing DEM data necessary for GRID analysis in real time based on the area of analysis and the level of precision, specifically for streaming DEM data, which is utilized mostly for 3D geographic information service.

• 태양에너지
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• 제5권2호
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• pp.3-10
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• 1985

This paper is concerned with the characterized method of wind speed distribution for calculation of wind power density of regional group and wind potential in Korea. It is shown that the Rayleigh distribution, K = 2, is not suitable for analyzing wind data in Korea. Simple relationship, K = 0.21 V + 0.84, is derived from Weibull wind distribution by analyzing wind data obtained from 24 meteorological station and is a suitable tool for estimation of wind power density. Application of this result, the domestic ideal and actual wind potential are estimated as $3.16{\times}10^9$ KWH/year and $7.14{\times}$10^8 KWH/year respectively for the case of 10 meter height, $1m^2$ swept area and $0.1{\times}0.1Km^2$ land area. And for the case of 50 meter height, ideal and actual wind potential are increased as $7.56{\times}10^9$ KWH/year and $2.37{\times}10^9$ KWH/year respectively.

• 한국인터넷방송통신학회논문지
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• 제9권2호
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• pp.29-36
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• 2009

생명정보학 분야의 발전에 따라 방대한 양의 DNA서열 데이터를 효율적으로 분석하기 위해 분석도구가 사용되고 있다. 하지만 기존의 분석도구들은 분석하고자 하는 데이터를 찾고, 적용해야 하는 불편함이 있다. 본 논문에서는 이러한 문제점을 해결하기 위하여 웹2.0기반 RIA(Rich Internet Application) 방식으로 구현한 분석도구를 제안한다. RIA방식을 적용한 분석도구는 기존 웹 방식의 문제점을 보완한 웹2.0기반에서 DNA서열 데이터를 찾고, 실시간으로 분석내용을 보여준다. 개발된 웹 에플리케이션은 윈도우 시스템 상에서 Flex2를 이용하였다.