• Title/Summary/Keyword: Data Quality Model

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A Data Cleansing Strategy for Improving Data Quality of National R&D Information - Case Study of NTIS (데이터 품질을 고려한 국가R&D정보 데이터베이스의 통합 사례 연구 - NTIS 데이터베이스 통합 사례)

  • Shin, Sung-Ho;Yoon, Young-Jun;Yang, Myung-Suk;Kim, Jin-Man;Shon, Kang-Ryul
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.6
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    • pp.119-130
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    • 2011
  • On the point of data quality management, data quality is influenced by quality policy, quality organization, business process, and business rule. Business rules, guide of data manipulation, have effects on data quality directly. In case of building an integration database among distributed databases, defining business rule is more important because data integration needs to consider heterogeneous structure, code, and data standardization. Also data value has various figures depended on data type, unit, and transcription. Finally, database structure and data value problem have to be solved to improve data quality. For handling them, it is needed to draw database integration model and cleanse data in integrated database. NTIS(stands for National science and Technology Information Service) has an aim to serve users who need all information about national R&D by internet, and for that aim, it has a integrated database which has been made with several database sources. We prove that database integration model and data cleansing are needed to build a successful integrated database through NTIS case study.

Improvement in Stream Hydraulic Characteristics Estimation Method for Modeling Water Quality: Focusing on QualKo (수질모델링을 위한 하천수리특성 추정방법 개선: QualKo 모형을 중심으로)

  • Han, Suhee;Shin, Hyun-Suk;Kim, Sangdan
    • Journal of Wetlands Research
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    • v.10 no.1
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    • pp.11-20
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    • 2008
  • In this study the estimation method for stream hydraulic characteristics which is served as the input data set for running QualKo water quality model is investigated. The conventional approach for estimating such hydraulic parameters is to use the data set from the last cross section in each reach. However, it is shown that in order to represent correctly flow velocity profiles or the travel time in streams, hydraulic parameters of QualKo model should be estimated with all cross section data set within the corresponding reach. In addition, the unsuitable estimation of hydraulic parameters at some reaches has influence on the water quality predictions at the corresponding reaches, and the errors of water quality predictions are propagated toward the downstream without any error attenuation.

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Watershed Modeling Application for Receiving Water Quality Management in Nakdong River Basin (낙동강 유역의 수질관리를 위한 유역모델링 적용 연구)

  • Jang, Jae-Ho;Ahn, Jong-Ho
    • Journal of Korean Society on Water Environment
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    • v.28 no.3
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    • pp.409-417
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    • 2012
  • SWAT model was applied for the Nakdong River Basin to characterize water quality variability and assess the feasibility of using the load duration curve to water quality management. The basin was divided into 67 sub-basins considering various watershed environment, and rainfall runoff and pollutant loading were simulated based on 6 year measurements of meteo-hydrological data, discharge data of treatment plants, and water quality data (SS, T-N and T-P). The results demonstrate that non-point source loads during wet season increase by 80 ~ 95% of total loads. Although the rate of water flow governs the amount of SS that is transported to the main streams, nutrient concentrations are highly elevated during dry season by being concentrated. This phenomenon is more pronounced in the lower basin, receiving large amounts of urban point source discharges such as treated sewages. Also, the load duration curves (LDC) demonstrate dominant source problems based on the load exceedances, showing that SS concentrations are associated with the rainy season and nutrients, such as T-P, may be more concentrated at low flow and more diluted at higher flow. Overall, the LDC method could be used conveniently to assess watershed characteristics and pollutant loads in watershed scale.

The Influence of Brand Equity on Customer Purchase Decision: A Case Study of Retailers Distribution

  • NGUYEN, Van Thuy;TRAN, Thi Hong Dao;NGO, Thi Xuan Binh
    • Journal of Distribution Science
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    • v.20 no.2
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    • pp.11-18
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    • 2022
  • Purpose: The purpose of this paper is to investigate the influence of brand equity on customer purchase decision (CPD) of products for retailers distribution (RB) in Ho Chi Minh city, Vietnam. There are five elements in the brand equity model such as brand awareness, brand association, brand loyalty, perceived quality, and pricing policy. Research design, data and methodology: Qualitative methodology was used for exploring the research model and variables. The survey was conducted to collect data from 251 respondents who bought products at RB in Ho Chi Minh city, which is based on a Likert scale. The collected data were analyzed with the reliability of the scale, exploratory factor analysis, and research hypothesis testing by SPSS 22. Results: The results obtained revealed that brand awareness, brand association, perceived quality, and pricing policy have a significant impact on CPD for RB. Furthermore, the results showed that perceived quality is the most significant component in influencing CPD at retailers. Conclusions: From the research results, some management implications that RB should focus on are perceived quality, choice of pricing policies and strategies, brand building and development to attract more customers as well as enhance its image to improve customers' purchasing decisions of products at retail distributors chain.

Flood Simulation by using High Quality Geo-spatial Information (고품질 지형공간정보를 이용한 홍수 시뮬레이션)

  • Lee, Hyun-Jik;Hong, Sung-Hwan
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.3
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    • pp.97-104
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    • 2010
  • The important factors in a flood simulation are hydrologic data (such as the rainfall and intensity), a threedimensional terrain model, and the hydrologic inundation calculation matrix. Should any of these factors lack accuracy, flood prediction data becomes unreliable and imprecise. The three-dimensional terrain model is constructed based on existing digital maps, current map updates, and airborne LiDAR data. This research analyzes and offers ways to improve the model's accuracy by comparing flood weakness areas selected according to the existing data on flood locations and design frequency.

Analysis of mixture experimental data with process variables (공정변수를 갖는 혼합물 실험 자료의 분석)

  • Lim, Yong-B.
    • Journal of Korean Society for Quality Management
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    • v.40 no.3
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    • pp.347-358
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    • 2012
  • Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.

Proposal of diagnosis rule mapping model to support public data quality diagnosis (공공데이터 품질진단 지원을 위한 진단규칙 매핑모델 제안)

  • Jeong, Ha-Na;Kim, Jae-Woong;Lee, Yun-Yeol;Chae, Yi-Geun;Chung, Young-Suk
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.127-128
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    • 2022
  • 정부는 공공데이터 개방을 통해 신산업, 일자리 창출 등 경제 활성화를 위한 도구로 활용하는 것을 목표로 한다. 정부는 고품질의 공공데이터 보유를 위하여 품질 개선 활동을 통해 공공데이터 품질 향상을 진행하고 있다. 그러나 공공데이터 품질관리 수준 진단을 진행하는 담당자의 데이터에 대한 전문성과 이해도에 따라 품질진단 결과에 격차가 발생하여 진단 결과의 신뢰성을 보장하기 어렵다. 본 논문은 공공데이터의 원활한 품질진단 지원을 위해 품질진단규칙 매핑 모델을 제안하여 공공데이터 품질진단의 안정성과 신뢰성을 높인다.

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A Structural Model for Quality of Life in Women Having Hysterectomies (여성의 자궁절제술후 삶의 질 구조모형)

  • 김숙남
    • Journal of Korean Academy of Nursing
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    • v.29 no.1
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    • pp.161-173
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    • 1999
  • The purpose of this study was to develope and test the structural model for quality of life in women having hysterectomies. A hypothetical model was constructed on the basis of previous studies and a review of literature. The conceptual framework was built around eight constructs. Exogenous variables included in this model were marital intimacy, importance of uterus, professional support, positive coping behavior and pre-operative symptoms. Endogenous variables were spouse's support, sense of loss and quality of life. Empirical data for testing the hypothetical model was collected using a self-report questionnare from 203 women having hysterectomies at the outpatient clinics of four general hospitals and a mail survey in Pusan City. The Data was collected from December, 1997 to January, 1998. Reliability of the eight instruments was tested with Cronbach's alpha which ranged from 0.639-0.915. For the data analysis, SPSS 7.5 WIN Program and LISREL 8.12 WIN Program were used for descriptive statistics and covariance structural analysis. The results of covariance structure analysis were as follows : 1. Hypothetical model showed a good fit with the empirical data. [$\chi$$^2$=6.93(df=5, P=.23), GFI=.99, AGFI=.94, RMSR=.019, NNFI=.97, NFI=.98, CN=440, standardized residuals(-2.14-2.10)] 2. For the parsimony of model, a modified model was constructed by deleting 3 paths and adding 1 path according to the criteria of statistical significance and meaning. 3. The modified model also showed a good fit with the data. [$\chi$$^2$=5.26(df=7, P=.63), GFI=.99, AGFI=.97, RMSR=.014, NNFI=1.02, NFI=.99, CN=710, standardized residuals(-1.46-1.70)] Results of the testing of the hypothesis were as follows : 1. Marital intimacy(${\gamma}$11=.78, t=14.37) and professional support(${\gamma}$13=.12, t=2.12) had a significant direct effect on the spouse's support. 2. Pre-operative symptoms(${\gamma}$25=.32, t=3.12), importance of uterus(${\gamma}$22=.20, t=2.61) and spouse's support($\beta$2l=-.19, t=-2.43) had a significant direct effect on the sense of loss. 3. Sense of loss($\beta$32=-.66, t=-9.83) had a direct effect on the quality of life. Marital intimacy had a direct(${\gamma}$31=.19, t=3.33), indirect(${\gamma}$31=.14, t=2.52) and total effect(${\gamma}$31=.25, t=4.41) on the quality of life. Professional support had a direct effect(${\gamma}$33=.11, t=2.07) and total effect(${\gamma}$33=.13, t=2.31) on the quality of life. The direct effect of pre-operative symptoms(${\gamma}$35=-.36, t=4.02) and positive coping behavior(${\gamma}$34=.15, t=2.06) had the insignificant effect on the quality of life while, due to the idirect effect these variables had overall significant effect on the quality of life. The results of this study showed that the sense of loss had the most significant direct effect on the quality of life. Marital intimacy, pre -operative symptoms and spouse's support had a significant direct effect on this sense of loss. These four variables, the sense of loss, marital intimacy, pre-operative symptoms and spouse's support, were identified as relatively important variables. The results of this study suggested that there is needed to determine if nursing intervention would alleviate this sense of loss and promote a greater quality of life in women who have had hysterectomies.

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모바일 데이터 서비스 사용량 증감에 영향을 미치는 요인들에 관한 연구;이요인 이론(Two Factor Theory)을 바탕으로

  • Lee, Sang-Hun;Kim, Il-Gyeong;Lee, Ho-Geun;Park, Hyeon-Ji
    • 한국경영정보학회:학술대회논문집
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    • 2007.06a
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    • pp.885-890
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    • 2007
  • This study is to investigate factors that affect usage change in mobile data service (MDS). In the first, an exploratory study based on 378 survey responses was conducted to learn about important decision factors of MDS usage. It revealed discrepancy between the influencing forces of usage increase and those of usage decrease. Based on the findings from the exploratory study and the two-factor theory, we postulated information quality as the motivator and system quality as the de-motivator (or hygiene) of MDS. Then, a confirmative study was undertaken on their respective role in encouraging and discouraging the usage of mobile data service. A research model was proposed and subsequent hypotheses were empirically tested with partial least square (PLS) based on 478 responses from the users of mobile data service. It was learned that information quality (as a motivator) was positively associated with usage increase in mobile data service, but system quality (as a de-motivator) was not. Also, system quality was negatively associated with usage decrease, but information quality was not. Lastly, their association strength was partially moderated by the type of motivation for using MDS.

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Application of Zero-Inflated Poisson Distribution to Utilize Government Quality Assurance Activity Data (정부 품질보증활동 데이터 활용을 위한 Zero-Inflated 포아송 분포 적용)

  • Kim, JH;Lee, CW
    • Journal of Korean Society for Quality Management
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    • v.46 no.3
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    • pp.509-522
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    • 2018
  • Purpose: The purpose of this study was to propose more accurate mathematical model which can represent result of government quality assurance activity, especially corrective action and flaw. Methods: The collected data during government quality assurance activity was represented through histogram. To find out which distributions (Poisson distribution, Zero-Inflated Poisson distribution) could represent the histogram better, this study applied Pearson's correlation coefficient. Results: The result of this study is as follows; Histogram of corrective action during past 3 years and Zero-Inflated Poisson distribution had strong relationship that their correlation coefficients was over 0.94. Flaw data could not re-parameterize to Zero-Inflated Poisson distribution because its frequency of flaw occurrence was too small. However, histogram of flaw data during past 3 years and Poisson distribution showed strong relationship that their correlation coefficients was 0.99. Conclusion: Zero-Inflated Poisson distribution represented better than Poisson distribution to demonstrate corrective action histogram. However, in the case of flaw data histogram, Poisson distribution was more accurate than Zero-Inflated Poisson distribution.