• Title/Summary/Keyword: 데이터품질관리

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A Study on Construction of High Quality Marine-Bodiversity Metadata DB (해양생물다양성 메타DB 고품질 구축 연구)

  • Yang, Sung-Young;Park, Dea-Woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.05a
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    • pp.459-462
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    • 2011
  • 해양생물다양성 자원에 대한 국가 주권을 인정하는 해양생물다양성협약의 발효로 생물다양성 자원을 확보하기 위한 세계 각국의 경쟁이 치열한 상황이다. 현재 우리나라 각 기관 및 대학들이 보관하고 있는 해양생물자원 정보가 산재되어 있고, DB에 대한 관리 미흡으로 인하여 학술적, 산업적 활용이 어려운 상황임을 인지하여, 통합적으로 관리할 수 있는 정보체계가 필요한 시점이다. 본 논문에서는 해양생물다양성 자원 중 고품질 해양생물자원에 대한 현황을 분석한다. 그리고 해양생물다양성 데이터 고품질 확보 방안을 위한 DB 품질 오류율 산정 기준을 적용하여 메타DB 구축 방안을 제시한다. 본 연구는 향후 해양생물자원에 대한 국가전략수립에 기여할 것으로 기대한다.

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Applications of python package for statistical engineering (통계공학을 위한 Python 패키지 응용)

  • Jang, Dae-Heung
    • The Korean Journal of Applied Statistics
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    • v.34 no.4
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    • pp.633-658
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    • 2021
  • Statistical engineering contains design of experiments, quality control/ management, and reliability engineering. Python is a free software environment for machine learning, data science, and graphics. Python package has many functions and libraries for statistical engineering. We can use Python package as a useful tool for statistical engineering. This paper shows applications of Python package for statistical engineering and suggests a total Python projects for statistical engineering.

Comparative analysis of wavelet transform and machine learning approaches for noise reduction in water level data (웨이블릿 변환과 기계 학습 접근법을 이용한 수위 데이터의 노이즈 제거 비교 분석)

  • Hwang, Yukwan;Lim, Kyoung Jae;Kim, Jonggun;Shin, Minhwan;Park, Youn Shik;Shin, Yongchul;Ji, Bongjun
    • Journal of Korea Water Resources Association
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    • v.57 no.3
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    • pp.209-223
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    • 2024
  • In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

An IPA-based Evaluation of 3D Scanning Technology Application for Quality Control in Modular Construction Projects (IPA 분석을 통한 3차원 스캐닝의 모듈러 건축 프로젝트 품질관리 적용에 관한 연구)

  • Lee, Jeong-Hoon
    • Journal of the Korea Institute of Building Construction
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    • v.24 no.4
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    • pp.471-482
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    • 2024
  • Modular construction, a prominent method in the evolving construction industry, necessitates robust quality control for successful implementation. This study investigates the potential of 3D scanning technology for enhancing quality control processes in modular building construction. Through an IPA analysis of major construction projects across factory production, transportation, and on-site stages, the study evaluates the current state of 3D scanning application in modular construction quality control. Results indicate a high demand for 3D scanning data across various quality control aspects. However, certain limitations in technology and practical application were identified. The findings of this research contribute to the advancement of 3D scanning technology in modular construction and inform future research on cutting-edge quality control strategies.

A Case Study on the Change of Sampling inspection method for the Small Depth Charge Fuze (소형폭뢰용 수압식 신관의 품질검사방법 전환사례 연구)

  • Jee, Jae-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.10
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    • pp.531-538
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    • 2017
  • In the case of hydraulic pressure type fuse, we accept or reject certain product lots by considering the number of defective products in the operating pressure test. Generally, this procedure, known as 'The inspection by attributes', has been most commonly used in the field of quality assurance of products. However, the method of inspection by attributes suffers because it tests more samples than inspection by variables. Even though the quality of the products has remained stable in the process condition, the same number of samples is required for every lot, which wastes time and money. This paper suggests that the lot acceptance procedure is changed from inspection by attributes to inspection by variables. We can calculate the statistical tolerance percent of defectives and compare this to the Acceptable Quality Level (AQL) in order to save money and time. It is also easier to monitor and control the quality of products by using the process capability index and x-bar charts. In conclusion, the procedure delivers mutual benefit to both the customer and the producer by securing high quality products and reference data.

Development of Data Management and Analysis Software for Autonomous Vehicle Driving Environment (자율주행 대응 기계학습 데이터를 관리하고 분석하는 소프트웨어의 개발)

  • Park, Jongbin;Lee, Han-Duck;Kim, Kyung-Won;Jung, Jong-Jin
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.87-88
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    • 2019
  • 최근 기계학습 기술의 급속한 발전에 힘입어 자율주행을 위한 객체 인식 및 처리 기술 역시 비약적으로 발전하고 있다. 그러나 이러한 기계학습의 성능은 모델의 구조와 학습용 데이터의 품질에 영향을 받는다. 특히 주행환경을 잘 표현하는 학습데이터가 중요한데 전혀 새로운 도로, 주행환경, 장애물, 정적 혹은 동적 객체 등을 마주하면 정확도와 안정성에서 부정적인 영향을 받을 수 있는 것이다. 해외의 주행 데이터들에 크게 의존하고 있는 우리나라의 현실에 비춰 볼 때 국내 환경에 맞는 학습데이터를 쉽고 효율적으로 확보/관리/분석할 수 있게 하는 환경의 구축이 시급하다. 따라서 본 논문에서는 자율주행을 위한 기계학습 데이터를 효과적으로 관리하고 분석하기 위한 소프트웨어를 설계하고 개발하였다. 구체적으로는 수집된 영상들을 관리하는 기능, 영상에 존재하는 노이즈 제거 및 화질 개선 처리 기능, 학습 및 검증을 위한 메타 정보 태깅 기능, 태깅 정보의 통계적 분석 기능들을 포함한다. 개발한 소프트웨어는 우리나라에서 자체 촬영한 자율주행 학습 영상들에 대해 딥러닝 모델들을 학습하고 검증하는데 활용할 예정이다.

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Development of Ubiquitous Sensor Network Quality Control Algorithm for Highland Cabbage (고랭지배추 생육을 위한 유비쿼터스 센서 네트워크 품질관리 알고리즘 개발)

  • Cho, Changje;Hwang, Guenbo;Yoon, Sanghoo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.20 no.4
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    • pp.337-347
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    • 2018
  • Weather causes much of the risk of agricultural activity. For efficient farming, we need to use weather information. Modern agriculture has been developed to create high added value through convergence with state-of-the-art Information and Communication Technology (ICT). This study deals with the quality control algorithms of weather monitoring equipment through Ubiquitous Sensor Network (USN) observational equipment for efficient cultivation of cabbage. Accurate weather observations are important. To achieve this goal, the Korea Meteorological Administration, for example, developed various quality control algorithms to determine regularity of the observation. The research data of this study were obtained from five USN stations, which were installed in Anbandegi and Gwinemi from 2015 to 2017. Quality control algorithms were developed for flat line check, temporal outliers check, time series consistency check and spatial outliers check. Finally, the quality control algorithms proposed in this study can also identify potential abnormal observations taking into account the temporal and spatial characteristics of weather data. It is expected to be useful for efficient management of highland cabbage production by providing quality-controlled weather data.

Design and Implementation of Medical Data Warehouse Architecture (의료용 데이터 웨어하우스 아키텍쳐의 설계 및 구현)

  • 김종호;김태훈;민성우;이희석
    • Proceedings of the Korea Database Society Conference
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    • 1999.06a
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    • pp.393-402
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    • 1999
  • 과거와 다르게 최근의 병원들은 정보화로 인해서 상당한 양의 의료 데이터가 저장되어 있어서 이의 효과적인 이용에 관심을 가지고 있다. 그러나 기존 통합병원정보시스템 (Integrated Hospital Information System)은 아직까지 일반관리와 원무관리 중심에서 벗어나지 못하고 있다. 품질 좋은 의료 서비스를 제공하기 위해서 환자 중심의 진료 및 진료지원, 임상연구 등을 종합적으로 지원하기 위한 데이터 웨어하우스 (Data Warehouse)의 필요성이 대두되기 시작했다. 이에 본 연구는 병원 전체 차원에서 데이터 웨어하우스의 아키텍쳐를 설계하고 개발하는 데 주안점을 두었다. 특히, 임상 데이터 웨어하우스 (Clinical Data Warehouse)에 초점을 두었으며 이에 대한 프로토타입은 J 병원에 적용되어서 개발되었다.

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Methodology for Evaluating Big Data Platforms Performance in the Domestic Electronic Power Industry (국내 전력산업에서의 빅데이터 플랫폼 성과 평가 방법론)

  • Cho, Chisun;Lee, Nangyu;Hahm, Yukun
    • The Journal of Bigdata
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    • v.5 no.1
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    • pp.97-108
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    • 2020
  • As the domestic electric power industry becomes a smart grid, big data platforms for demand management, facility management, and customer service have been deployed. However, due to the nature of the big data project, big data platforms take time to realize their value in the business processes. Therefore, it is not easy to evaluate the performance of the initial big data platforms using the known or theoretical evaluation methods. In this paper, we propose a methodology of big data platform performance evaluation based on specific information quality such as information completeness/sufficiency, information reliability, information relevancy, information comparability, information unbiasedness, timeliness of information, related to the volume, diversity, and velocity of big data.

A Study of BIM based estimation Modeling data reliability improvement (BIM기반 견적 모델링 데이터 신뢰성 향상을 위한 연구)

  • Kim, Yeong-Jin;Kim, Seong-Ah;Chin, Sang-Yoon
    • Korean Journal of Construction Engineering and Management
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    • v.13 no.3
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    • pp.43-55
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    • 2012
  • A methodology for BIM Quality Assurance in the construction industry is becoming increasingly an important issue to determine the reliability of BIM. However, the quality assurance of BIM is currently limited to check 3D models, such as clash detection and space layout while verification methods for disciplinary BIM results from structural engineering, mechanical engineering, and estimation do not exist yet. Particularly, in the BIM-based estimation mathematical equations to take off quantities are not clearly exposed so that the results are not quite accepted at practices. With the concept of reliability engineering defined in the manufacturing industry to improve reliability of outcomes of BIM-based quantity take-off, impacting factors that affect reliability of BIM-based quantity take-off were derived. It was found that the factors also include the modeling method and the features of a BIM tool. Therefore, this research aims to propose modeling and verification methods to improve reliability of BIM-based quantity take-off through the pilot test that was performed with commercial BIM tools and IFC-based BIM data.