• Journal of Korea Society of Industrial Information Systems
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• v.15 no.4
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• pp.47-52
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• 2010

This paper describes a visualization technique that animates geometrical defect data that are extracted using a magnetic flux leakage (MFL) operating system on nondestructive evaluation (NDE). Since data are collected from different locations and often not regular, the data must be converted to the standard format that is used within the pipeline in visualization procedures. In order to navigate inside of the pipeline, 3D virtual objects are generated and are able to explore the pipeline continuously. The major objectives of this paper are to characterize, generate general shape of defects, and enable computer interaction in virtual environment. Pipeline navigation system (PNS) has introduced the framework for interactive visual applications based upon the principles of modeling 3D objects. PNS presents some preliminary efforts to enable the user to interact human and computer with each other.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.125-129
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• 2023

In this paper, we propose a method to design and implement a smart pipeline information management system that can provide visualization information linked to GIS and roadmap based on the construction of precise pipeline buried information. The smart pipeline information management system consists of a positioning device for high-precision pipeline location measurement and surround view image data recording, a database for data storage and management, and a mobile app for remote monitoring and management. It connects surrounding image data and location data with GIS and roadmap. Convenience and accessibility of management can be improved.

• Publications of The Korean Astronomical Society
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• v.28 no.1
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• pp.1-6
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• 2013

Real-time data reduction pipeline for the Korea Microlensing Telescope Network (KMTNet) was developed by Korea Astronomy and Space Science Institute (KASI). The main goal of the data reduction pipeline is to find variable objects and to record their light variation from the large amount of observation data of about 200 GB per night per site. To achieve the goal we adopt three strategic implementations: precision pointing of telescope using the cross correlation correction for target fields, realtime data transferring using kernel-level file handling and high speed network, and segment data processing architecture using the Sun-Grid engine. We tested performance of the pipeline using simulated data which represent the similar circumstance to CTIO (Cerro Tololo Inter-American Observatory), and we have found that it takes about eight hours for whole processing of one-night data. Therefore we conclude that the pipeline works without problem in real-time if the network speed is high enough, e.g., as high as in CTIO.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.403-416
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• 2003

There are common features, in both imaging surveys and image processing, between astronomical observations and remote sensing. Handling large amounts of data, in an easy and fast way, has become a common issue. Implementing pipeline software can be a solution to the problem, one which allows the processing of various kinds of data automatically. As a case study, the development of pipeline software for the EIS (European Southern Observatory Imaging Survey) is introduced. The EIS team has been conducting a sky survey to provide candidate targets to the 250 VLTs (Very Large Telescopes) observations. The survey data have been processed in a sequence of five major data corrections and reductions, i.e. preprocessing, flat fielding, photometric and astrometric corrections, source extraction, and coaddition. The processed data are eventually distributed to the users. In order to provide automatic processing of the vast volume of observed data, pipeline software has been developed. Because of the complexity of objects and different characteristic of each process, it was necessary to analyze the whole works of the EIS survey program. The overall tasks of the EIS are identified, and the scheme of the EIS pipeline software is defined. The system structure and the processes are presented, and in-depth flow charts are analyzed. During the analyses, it was revealed that handling the data flow and managing the database are important for the data processing. These analyses may also be applied to many other fields which require image processing.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.60-66
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• 2014

In this study, the overseas failure frequency data of the high-pressure gas pipeline were investigated to apply QRA of high-pressure gas pipeline. The typical overseas failure frequency data of high-pressure gas pipeline are DOT of United States, EGIG of Europe, and UKOPA of United Kingdom (UK). Comparative analysis of these data was shown that EGIG data was suitable for the situation in Korea. In order to apply QRA of high-pressure gas pipeline, non-linear regression analysis using the failure frequency data in the report of EGIG 8th was performed. In the future, intensive researches are required for the external interference because about 50% of the failure frequency of all incidents is the external interference, and for combining of domestic and overseas data.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.214-215
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• 2014

Recently, Russia decided to export an annual 7.5 million tons of natural gas to Korea over 30 years from 2015, as also deal with China, planed to build a pipeline connecting Siberia to Shandong Peninsula about 4000km. Risk management is required depending on the project in extreme cold weather, because it is concerned about the behavior of the seasonal changes in soil temperature and the strain of pipe according to the long-distance pipeline construction. The plan of data management shall be prepared in parallel for a sophisticated risk management, because a data is massive scale and it is generated/accumulated in real time. Therefore, this research is aimed to classify a data items in engineering stage of pipeline by previous studies for managing a generated data depending on the detail works in extreme cold weather. We expect to be provided the foundation of an efficient classification system of a generated data from the pipeline project life cycle.

• Genomics & Informatics
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• v.16 no.4
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• pp.29.1-29.5
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• 2018

Hybrid capture-based targeted sequencing is being used increasingly for genomic variant profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing polymerase chain reaction biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various study groups for their own purposes. Due to this provincial usage of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared and pooled together, and an 8-plexed capture library was processed to the enrichment step before 150-bp paired-end sequencing with Illumina HiSeq series. For the analysis, we evaluated several published tools. We focused mainly on the compatibility of the input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of the quality and efficiency of conducted experiments.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.18-19
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• 2014

As issued the development of energy resources, EPC work process through the IT technology is essential for efficient business management, and systematic management of data generated in this process is needed. In domestic, the research related to system development for the collection and management of construction data detected in the field has been done continuously, but pipeline business target the long-distance in extreme cold weather, almost no cases have been studied up to now. Therefore, this research is aimed to derive the data item for efficient management in EPC Stage of pipeline business in extreme cold weather. WBS system of EPC work are classified easily at two levels, data items can be divided based on the type of document. In the future I will be expected to be the foundation of the systematic management of data generated in the EPC step-by-step of pipeline business.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.196-208
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• 2017

This study presents an experimental work in a petrochemical company for scanning a buried pipeline using $Tc^{99m}$ radiotracer based on the measured velocity changes, in order to determine the flow reduction along a pipeline. In this work, $Tc^{99m}$ radiotracer was injected into the pipeline and monitored by sodium iodide scintillation detectors located at several positions along the pipeline. The flow velocity has been calculated between every two consecutive detectors along the pipeline. Practically, six experiments have been carried out using two different data acquisition systems, each of them being connected to four detectors. During the fifth experiment, a bypass was discovered between the scanned pipeline and another buried parallel pipeline connected after the injection point. The results indicate that the bypass had a bad effect on the volumetric flow rate in the scanned pipeline.

• Journal of the Korean Institute of Gas
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• v.5 no.2 s.14
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• pp.43-51
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• 2001

ln this study, a natural gas pipeline network model was established using STONER. First a map of natural gas pipeline network was drawn on STONER and then the length and diameter of the pipe were inputted. And as the specific gravity of gas flowing in the pipeline which is the value of natural gas was inputted. Finally in order to decide the pipeline variables and gas temperature, through the verification with observed real data, the possible error was minimized. For the verification, the pipeline variables and gas temperature were assumed and the pipeline network analysis was accomplished with real demand data. The square deviation of analysed pressure from observed pressure was calculated and the minimum case was selected for the optimum pipeline variables and gas temperature. Thus a proper natural gas pipeline network model for real network was established.