• 디지털콘텐츠학회 논문지
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• 제8권4호
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• pp.541-546
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• 2007

많은 양의 연속적인 스트림 데이터를 대상으로 하는 연속적인 질의처리의 경우는 전통적 방식의 요구구동형 질의처리 방식이 적합하지 않다. 본 논문에서는 자료구동형 방식을 도입하여 질의를 처리함으로써 스트림 데이터에 알맞은 질의처리 기법을 제안하고 질의계획의 구조와 질의실행 방식을 설명하였다. 제안된 질의처리 기법은 다중질의 처리가 가능하며, 질의 간에 공유가 가능하게 한다. 또한 부분질의의 실행결과가 저장됨으로써 실행시간을 단축할 수 있다. 본 질의처리 모델에 XML 데이터와 XQuery 질의를 적용하였다.

• 한국산학기술학회논문지
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• 제14권5호
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• pp.2481-2486
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• 2013

GPS에 대한 이해가 부족한 일반사용자가 정상적으로 GPS 자료를 처리하기 위해서는 많은 시간과 노력이 필요하다. 하지만 GPS 자료처리 분야는 외산 소프트웨어에 크게 의존하고 있으며, 사용자 위주의 기술 개발은 거의 이루어지지 않고 있다. 이에 본 연구에서는 비전문가도 상대측위 방법으로 고정밀 GPS 자료처리가 가능한 전문가 서비스를 구축하고자 하였다. 연구결과, GPS 자료처리에 필요한 최소 정보만을 입력함으로써 사용자의 편의성을 극대화시킬 수 있는 전문가 서비스를 개발하였으며, 국토지리정보원에서 제공하는 위성기준점의 관측자료와 실제 GPS측량으로 취득한 관측자료의 처리를 통해 전문가 서비스를 검증하였다. 전문가 서비스는 GPS 자료처리에 소요되는 노력과 시간을 크게 단축시킴으로써 정밀위치결정은 물론 다양한 학술연구에 기여할 것이다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

• 한국측량학회지
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• 제35권5호
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• pp.405-414
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• 2017

Spatial data processing often poses challenges due to the unique characteristics of spatial data and this becomes more complex in spatial big data processing. Some tools have been developed and provided to users; however, they are not common for a regular user. This paper presents a benchmark test between two notable tools of spatial big data processing: GIS Tools for Hadoop and SpatialHadoop. At the same time, a MapReduce application is introduced to be used as a baseline to evaluate the effectiveness of two tools and to derive the impact of number of maps/reduces on the performance. By using these tools and New York taxi trajectory data, we perform a spatial data processing related to filtering the drop-off locations within Manhattan area. Thereby, the performance of these tools is observed with respect to increasing of data size and changing number of worker nodes. The results of this study are as follows 1) GIS Tools for Hadoop automatically creates a Quadtree index in each spatial processing. Therefore, the performance is improved significantly. However, users should be familiar with Java to handle this tool conveniently. 2) SpatialHadoop does not automatically create a spatial index for the data. As a result, its performance is much lower than GIS Tool for Hadoop on a same spatial processing. However, SpatialHadoop achieved the best result in terms of performing a range query. 3) The performance of our MapReduce application has increased four times after changing the number of reduces from 1 to 12.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.285-304
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• 2017

Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.

• 항공우주기술
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• 제6권1호
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• pp.245-254
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• 2007

KSLV-l의 탑재 시스템은 발사 전부터 발사 후 임무 종료 시까지 발사체 및 탑재위성에 대한 각종동작상태 및 특성에 관한 제반자료를 원격측정 지상국시스템으로 전송한다. 원격측정 지상국시스템의 안테나시스템은 이러한 원격측정신호를 실시간으로 획득한 후 자료 처리시스템으로 공급하고, 자료처리시스템은 수신한 텔레메트리 데이터를 처리.저장한 후 임무진행자들에게 분배하여 발사 진행시 발사임무진행을 위한 판단자료로 활용하도록 한다. 본 논문에서는 KSLV-1 으로부터 텔레메트리 신호를 수신한 후 효율적이고 안정적인 데이터처리과정을 위한 최적의 자료처리시스템의 구성 및 기능을 제시하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.95-97
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• 2005

Communication, Ocean, and Meteorological Satellite (COMS) to be launched in year 2008 will be the first Korean multi-purpose geostationary satellite aiming at three major missions, i.e.: communication, ocean, and meteorological applications. The development of systems for the meteorological mission sponsored by the Korea Meteorological Administration (KMA) consists of payloads, ground system, and data processing system. The program called COMS Meteorological Data Processing System (CMDPS) has been initiated for the development of data processing system. The primary objective ofCMDPS is to derive the level-2 environmental products from geo-Iocated and calibrated level 1.5 COMS data. Preliminary design for the level-2 data processing system consists of 16 baseline products and will be refined by end of 3rd project year. Also considered for the development are the necessary initial information such as land use and digital elevation map, algorithms for the vicarious calibration and procedures for the calibration monitoring, and radiative transfer model. Here, we briefly introduce the overall development strategy, flow chart for the intended baseline products, a few preliminary algorithm results and future plans.

• ETRI Journal
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• 제39권1호
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• pp.41-50
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• 2017

In connection-oriented data transport services, data loss can occur when a service experiences a problem in its end-to-end path. To resolve the problem promptly, the data transport systems providing the service must quickly modify their internal configurations, which are distributed among different locations within each system. The configurations are modified through a series of problem (event) handling procedures, which are carried out by multiple control processors in the system. This paper proposes a provisioning-to-signaling method for inter-control-processor messaging to improve the time efficiency of event processing. This method simplifies the sharing of the runtime event, and minimizes the time variability caused by the amount of event data, which results in a decrease in the latency time and an increase in the time determinacy when processing global events. The proposed method was tested for an event that required 4,000 internal path changes, and was found to lessen the latency time of global event processing by about 50% compared with the time required for general methods to do the same; in addition, it reduced the impact of the event data on the event processing time to about 30%.

• Mass Spectrometry Letters
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• 제11권1호
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• pp.1-5
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• 2020

In this study, some of the recently reported data processing strategies were evaluated and modified based on their capabilities and a brief workflow for data mining was redefined for Q-TOF LC-MS based untargeted metabolomics. Commercial pooled human plasma samples were used for this purpose. An ultrafiltration procedure was applied on sample preparation. Sample set was analyzed through Q-TOF LC/MS. A C18 column (Agilent Zorbax 1.8 µM, 50 × 2.1 mm) was used for chromatographic separation. Raw chromatograms were processed using XCMS - R programming language edition and Isotopologue Parameter Optimization (IPO) was used to optimize XCMS parameters. The raw XCMS table was processed using MS Excel to find reliable and reproducible peaks. Totally 1650 reliable and reproducible potential metabolite peaks were found based on the data processing procedures given in this paper. The redefined dataset was upload into MetaboAnalyst platform and the identified metabolites were matched with 86 metabolic pathways. Thus, two list were obtained and presented in this study as supplement files. The first list is to present the retention times and m/z values of detected metabolite peaks. The second list is the metabolic pathways related with the identified metabolites. The briefly described data processing strategies and dataset presented in this study could be beneficial for the researchers working on untargeted metabolomics for processing their data and validating their results.

• 지구물리와물리탐사
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• 제13권2호
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• pp.159-168
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• 2010

석유/가스 물리탐사 분야에서의 최근 추세는 3D 탄성파 탐사라 할 수 있다. 기존의 2D 자료처리와는 달리, 3D탄성파 탐사 자료처리는 고가의 상용 소프트웨어 시스템과 고성능 컴퓨터가 필요한 것으로 인식되어 왔다. 본 논문에서는 일반 개인용 컴퓨터(PC)를 기반으로 일반에게 공개되어 있는 비상업용의 공유 소프트웨어 시스템들인 "SU, SEPlib, SEPlib3D"들을 선택적으로 조합하여 적용하는 3D 탄성파 자료처리 방법론을 제시하고, 이를 실제 자료에 매우 근접한3D 합성 탄성파 자료인 SEG/EAGE 3D 합성 자료에 적용하여 실질적인 적용성을 시험해 보았다.