• Title/Summary/Keyword: Data Quality Model

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A Study on the Model Improvement of Korean Industrial Standards-Quality Excellence Index(KS-QEI) (KS제품 품질우수성지수 모델 개선 방안에 관한 연구)

  • Kim, Tai-Kyoo;Kim, Myung Joon
    • Journal of Korean Society for Quality Management
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    • v.41 no.3
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    • pp.327-335
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    • 2013
  • Purpose: The purpose of this study is to suggest the modified 'Korean Standard-Quality Excellence Index' model and analyze the improvement effect with survey data by comparing the properness between current and suggested model result. Methods: The collected data through the survey were analyzed using paired t-test and unbalanced ANOVA method for testing the consistency of two customer satisfaction evaluating categories and comparing the current model to suggested model for confirming the improvement of performance. Results: The statistical analysis result shows that adjusted model using prior information improves the consistency between two customer satisfaction in case of short life-cycle product. Also long life-cycle product case, the result shows difference gap decreasing with same direction. Conclusion: Considering statistical model for QEI reflecting the characteristic of product group such as life cycle seems to be meaningful. Since index may be compared yearly base for checking the trend, careful approaching without big change should be considered for application.

Market Segmentation With Price-Dependent Quality Evaluation in Denim Jeans Market ; Based on Conjoin analysis and mixture model (청바지제품 세분시장 내 가격-품질 평가집단 추출에 관한 연구: 결합분석과 mixture model를 이용하여)

  • 곽영식;이진화
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.11
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    • pp.1605-1614
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    • 2002
  • The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

Effects of Emission from Seoul Metropolitan Area on Air Quality of Surrounding Area Using MESOPUFF II Model (MESOPUFF II모델을 이용한 서울시 $SO_2$배출량이 주변지역 대기질에 미치는 영향 분석)

  • 조창래;이종범
    • Journal of Korean Society for Atmospheric Environment
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    • v.14 no.6
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    • pp.563-576
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    • 1998
  • To study the influences of the emission sources during lune 13∼15 1997 in Seoul, MESOPVFF II model has been used. The MESOPVFF II model includes terrain effects, chemical transformation and removal processes. Data of 20 surface meteorological stations and the upper air station on mid-west area in Korea were used as a DWM (Diagnostic Wind Model) input data. This model is likely to be applicable because the predicted SO2 concentration was well matched with measured 502 concentration in Seoul and Kyonggido. In generally air pollutants in Seoul have major influence on the other cities but the result of modeling appeared also air pollutants of the other cities influence on Seoul. Finally, in the case of calculating the air quality by diffusion model, the influences of air pollutants emitted in metropolitan area as well as the emission rate in modeling area should be considered.

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Parameter Estimation and Comparison for SRGMs and ARIMA Model in Software Failure Data

  • Song, Kwang Yoon;Chang, In Hong;Lee, Dong Su
    • Journal of Integrative Natural Science
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    • v.7 no.3
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    • pp.193-199
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    • 2014
  • As the requirement on the quality of the system has increased, the reliability is very important part in terms of enhance stability and to provide high quality services to customers. Many statistical models have been developed in the past years for the estimation of software reliability. We consider the functions for NHPP software reliability model and time series model in software failure data. We estimate parameters for the proposed models from three data sets. The values of SSE and MSE is presented from three data sets. We compare the predicted number of faults with the actual three data sets using the NHPP software reliability model and time series model.

The Social Networking Application Success Model: An Empirical Study of Facebook and Twitter

  • Ou, Carol X.J.;Davison, Robert M.;Huang, Vivian Q.
    • International Journal of Knowledge Content Development & Technology
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    • v.6 no.1
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    • pp.5-39
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    • 2016
  • Social networking applications (SNAs) are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean's updated information systems (IS) success model. In addition to their original three dimensions of quality, i.e., system quality, information quality and service quality, we propose that a fourth dimension - networking quality - contributes to SNA success. We empirically examined the proposed research model with a survey of 168 Facebook and 149 Twitter users. The data validates the significant role of networking quality in determining the focal SNA's success. The theoretical and practical implications are discussed.

The Analysis of Casual Model of Quality of Life for Employed Wives and Unemployed Wives (취업주부와 비취업 주부의 삶의 질에 대한 인과모형분석)

  • 고정자
    • Journal of the Korean Home Economics Association
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    • v.35 no.1
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    • pp.429-442
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    • 1997
  • This study present s and tests a casual model of cohesion adaptability the level of stress recognition coping starategies and quality of life for employed wives and unemployed wives. For the data set 205 employed wives and 200 unemployed wives living in Pusan were chosen. The data were analyzed using M, SD, t-test multiple regression and path analysis. The findings of this study are as follows; First There level of stress recognition and quality of life are higher for employes wives than unemployed wives. Cohesion is higher for employed wives. Whereas adaptability is higher for unemployed wives than employed wives. Employes wives are greater use of coping starategies than unemployed wives. Second For employes wives adaptability the level of stress recognition and coping starategies have significant direct effect on quality of life. Besides wife's level of education age of the youngest child working hours employment motivation and cohesion have significant indirect effect on quality of life. For unemployed wives cohesion adaptability and level of stress recognition have signficant direct effect on quality of life. Besides wife's level of education number of children religion and husband's housework participation are indirectly associated with quality of life. From these results the proposed model is generally supported by the data.

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A Study on Product Data Quality Assurance for Automotive Industry (자동차산업에서 제품데이터품질 향상을 위한 연구)

  • Yang Jeongsam;Han Soonhung;Kang Hyejeong;Kim Junki
    • Transactions of the Korean Society of Automotive Engineers
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    • v.13 no.1
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    • pp.184-193
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    • 2005
  • Digital representations of products and parts have largely replaced physical drawings as the form in which product data are stored, analyzed, and communicated among the people contributing to the design of an automobile. Many individuals and companies participate in the design of an increasingly complex automobile; hence, the design process depends critically on team members' ability to share information about essential design elements. These trends have elevated the importance of the quality of product data and its efficient exchange. In this paper, we show state-of-the-art on Product Data Quality(PDQ), and activities of PDQ assurance. And we propose a novel design history-based approach for diagnosis and healing of a CAD model.

Forecasting of Water Quality in Chinyang Reservoir Using ARIMA Model (ARIMA 모형을 이용한 진양호 수질의 장래예측)

  • Kim, Jong-oh;Yoo, Hwan-Hee;Kim, Ok-Sun;Park, Jung-Seok
    • Journal of Wetlands Research
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    • v.1 no.1
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    • pp.17-28
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    • 1999
  • The purpose of this study was to analysis water quality monitoring data and to estimate future trends using ARIMA model of time series analysis. Water quality data in Chin yang reservoir were used with monthly monitoring interval during past 7 years. The variations of water quality parameters with periodicity and trend could be estimated by multiplicative ARIMA models and the statistical tests showed a good agreement with the observed data. Therefore, the monthly values of water quality parameters could be forecasted using these models.

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On the applications of AWS into the Four-Dimensional Data Assimllation Technique for 3 Dimensional Air Quality Model in Use of Atmospheric Environmental Assessment (환경영향평가용 대기질 모델을 위한 AWS자료의 4 차원 동화 기법에 관한 고찰)

  • Kim, Cheol-Hee
    • Journal of Environmental Impact Assessment
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    • v.11 no.2
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    • pp.109-116
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    • 2002
  • The diagnostic and prognostic methods for generating 3 dimensional wind field were comparatively analyzed and 4 dimensional data assimilation (FDDA) technique by incorporating Automatic Weather System (AWS) into the prognostic methods was discussed for the urban scale air quality model. The A WS covered the urban scale grid distance of 10.6 km and 4.3 km in South Korea and Kyong-in region, respectively. This is representing that AWS for FDDA could be fairly well accommodated in prognostic model with the meso${\gamma}$~ microa scale (~5 km), indicating that the 3 dimensional wind field by FDDA technique could be a useful interpretative tool in urban area for the atmospheric environmental impact assessment.

Automatic Validation of the Geometric Quality of Crowdsourcing Drone Imagery (크라우드소싱 드론 영상의 기하학적 품질 자동 검증)

  • Dongho Lee ;Kyoungah Choi
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.577-587
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    • 2023
  • The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.