• 품질경영학회지
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• 제43권4호
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• pp.499-510
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• 2015

Purpose: This paper treats the improvement of the quality and reliability of military weapon systems based on the maintenance data. Methods: The proposed method of the data integration and refinement are used to obtain the component reliability information and to find the frequently failed components based on the Pareto analysis. Based on the reliability information and the number of failed component frequencies, the target components of quality improvement are determined and improved by multiple methods such as engineering changes, special meetings, additional training and revising maintenance manuals. Results: Based on the proposed process, we find some components which need to be improved in order to enhance the quality and reliability. Conclusion: A process is developed for improving the quality and reliability of weapon systems. This process will be adopted by various weapon systems to enhance the quality and reliability, as well as reduce military spending.

• 한국전자거래학회지
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• 제15권4호
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• pp.79-99
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• 2010

e-비즈니스의 활성화로 기업과 조직에서 이해당사자 간의 데이터 교환이 활발해 짐에 따라, 신뢰성 있는 데이터의 확보 및 관리가 시급한 과제로 떠오르고 있다. 이러한 문제를 해결하기 위해, 본 논문은 데이터의 품질을 체계적으로 관리할 수 있는 프레임워크를 시나리오와 함께 제시한다. 데이터 품질 관리 프레임워크는 데이터 품질 모니터링, 데이터 품질 개선, 데이터 활용의 3단계로 구분되어 있으며 각 단계마다 3개씩, 총 9개의 프로세스로 구성되어 있다. 각 프로세스에는 필요성, 기능, 역할, 프로세스간의 관계가 명시되어 있다. 또한, 본 프레임워크를 현장에 직접 적용할 수 있도록, e-비즈니스에서 많이 사용되는 상품식별 및 분류 코드체계의 사례를 이용하여 업무 시나리오를 제시하였다.

• 산업기술연구
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• 제18권
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• pp.17-25
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• 1998

Recently, there are a lot of studies to use a satellite image data in order to investigate a simultaneous change of a wide range area as a lake. However, many cases of a water quality research occur as problem when we try to extract the water quality factors from the satellite image data, because of the atmosphere scattering exert as bad influence on a result of analysis. In this study, and attempt was made to select the relative atmospheric correction method for the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors was performed by using the multi-temporal image data.

• 상하수도학회지
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• 제19권6호
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.

• 한국항공운항학회지
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• 제31권2호
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• pp.72-80
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• 2023

Line Operations Safety Audit (LOSA) is a well known preventive aviation safety program for Threat and Error management (TEM). High quality LOSA data suitable for safety management is obtained when a flight crew flies at the same level of attention as ordinary flight. Factors contributing to LOSA data quality may include flight crew's understanding on LOSA purpose, observer's career, and characteristics of the organization responsible for LOSA operations. This study explored purposes of TEM and LOSA, as well as their relationship. Previous studies mentioned quality of LOSA data can be influenced by heuristic judgment, hawthorne effect, and priming effect. This study recognized the importance of LOSA data quality to be effectively used for preventive safety management. It was confirmed that the level of understanding on LOSA concept, experience of the observer, and the characteristics of the department in charge of LOSA operation could affect the quality of LOSA data.

• 한국토양비료학회지
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• 제37권3호
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• pp.192-198
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• 2004

The heavy dependence of modern science-based agriculture on chemicals such as fertilizers and pesticides, and heavy machinery gave rise to questions about long-term sustainability of agriculture in relation to degradation of soil quality. The research achievements and trends in developing soil quality indicators were introduced and discussed in this report. Organization for Economic Cooperation and Development (OECD) established 13 agri-environment indicators including soil quality indicator in 1994, collected the soil data and methodologies for development of soil quality indicators in OECD member countries responded to OECD questionnaires and published the OECD reports, Environmental Indicators for Agriculture Volume 1, 2, and 3. Leading countries such as USA, Canada and New Zealand collected national data and evaluated the data in aspect of soil quality. They developed the various methods for selecting a minimum data set (MDS), scoring the soil properties and calculating soil quality index integrating the score of each soil property.

• 한국공간정보시스템학회 논문지
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• 제10권4호
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• pp.89-95
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• 2008

본 논문에서는 교통데이터 웨어 하우스에서 데이터 품질 관리를 위한 통합기법을 제안한다. 고속도로 교통관리시스템(FTMS)과 우회도로 교통정보시스템(ARTIS) 으로부터 대용량 교통데이터를 수집하여 데이터 웨어하우스를 구축하기 위한 방안을 기술하고, 다양한 분석을 위한 고품질 교통데이터를 제공하기 위한 통합 데이터 품질관리 기법을 제안하고 구현 평가한다. 제안된 통합 데이터 품질관리 기법을 활용하면 연구자들에게 검증된 고품질 교통데이터를 제공할 수 있고, 데이터처리와 평가를 위한 별도의 비용을 절감할 수 있을 것으로 기대된다.

• 한국콘텐츠학회논문지
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• 제20권9호
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• pp.439-447
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• 2020

공공데이터는 공공기관이 전자적으로 생성 또는 취득하여 관리하고 있는 모든 정보와 전자화된 파일이다. 공공데이터는 인공지능, 스마트 시티 등 차세대 신산업을 견인하는 중요한 요소로 인식되고 있다. 한국은 공공데이터 개방과 관련된 국제 평가에서 연속적으로 높은 순위에 위치하고 있다. 그럼에도 불구하고 공공데이터의 활용과 산업적 영향은 미흡하다. 공공데이터의 활용이 미흡한 이유는 다양할 수 있지만, 데이터 품질은 지속적으로 논의되는 주요 이슈이다. 본 논문은 공공데이터 품질 평가를 위한 지표를 검토하고, 개방된 공공데이터를 대상으로 정량적 품질 평가를 수행한다. 특히, 공공데이터 관리지침을 기준으로 구축 및 개방된 개방표준 데이터의 품질을 진단하여 정부의 가이드라인이 적합한지 검토한다. 데이터 품질평가는 개방표준 데이터의 메타데이터와 데이터값을 포함하고, 완전성과 정확성 지표를 기준으로 검토한다. 데이터 분석결과를 바탕으로 품질 개선을 위한 정책적·기술적 방안을 제안한다.

• Water Engineering Research
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• 제3권2호
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• pp.143-153
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• 2002

As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2007년도 International Conference
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• pp.582-587
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• 2007

ERP system is a good one because it provides required data to the Board of Directors at the right time, but needs to collect many data in this system. Nevertheless, increase in data leads to the system's quality deterioration which makes companies to carry out quality improvement. In order to solve quality deterioration problem, a company's quality improvement director must execute under acknowledgement of the relationships between sectors to be improved, which are DBMS, Application, System, Data Management, Archiving, and Reorganization. But in many cases, these relationships are ignored due to massive size of each of the sectors, resulting fragmental quality improvement operation. This case paper proposes a solution to effectively solve quality deterioration problem created by the massive data produced while operating ERP System(constructed by SAP package and web). First, it defines the sectors where quality improvements are vital, and lists out things to be considered. Then, by analysing the working process of these sectors, proposes the most efficient order of the improvement process. This case will eventually help the company's quality improvement director to execute quality improvement most effectively without trials and errors, which is this paper's ultimate goal.