• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.292-299
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• 2021

A form of data mining software, based on manufacturing-based IIoT environment with the development of IT technologies are increasingly growing. However, it is difficult to evaluate the software quality in the same form as general software due to the characteristics of the software of a manufacturing company that has a large amount of data that needs to be carried out with big data and data mining. In addition, in a manufacturing-based environment where heterogeneous equipment and software are mixed, it is difficult to perform quality judgment on software used by applying existing quality characteristics. Therefore, in this paper, the characteristics of the manufacturing base are investigated, and a software quality evaluation model suitable for it is developed and evaluated.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.813-831
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• 2016

Purpose: The purpose of this study is to assess the service quality attributes of Korean airlines service for Chinese passengers and suggest revised model to count potential improvement. Methods: Using the Kano and Timko models based on survey questionnaire to classify the quality attributes and to calculate the customer satisfaction index for each service attributes. And the revised potential customers satisfaction index(R-PCSI) are used to access the improvement possibilities by Kano model's attributes. Results: The attributes by Kano model, the relative importance, and the priorities for improvement for 30 airline service quality characteristics are identified. The most important item for improvement is 'Loses and delays compensations service'. Conclusion: According to the PCSI calculation results, this paper can help for Korean Airlines to improve customer satisfaction for Chinese passengers. And R-PCSI model suggested by this paper can be used for other service quality analysis.

• Journal of Environmental Impact Assessment
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• v.18 no.2
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• pp.99-109
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• 2009

In general, manual calibration is commonly used for the stream water quality modelling. Because the manual calibration depends upon the subjectivity and experience of the researcher, it has a problem with the objectivity of the modelling. Thus, the interest about the automatic calibration by the optimization technique is deeply increased. In this study, Influence coefficient algorithm and Genetic algorithm are introduced to develop an automatic calibration model for the QUAL2K that are the latest version of the QUAL2E. Genetic algorithm, used in this study, is very simple and easy to understand but also applicable to any complicated mathematical problem, and it can find out the global optimum solution effectively. The developed automatic calibration model is applied to the Gangneung Namdaecheon. The calibration results about the 11 water quality variables show the good correspondence between the calculated and observed water quality values.

• Journal of Environmental Impact Assessment
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• v.14 no.2
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• pp.55-62
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• 2005

This study applied the Neural Network and Fuzzy theory to show water-purity control and preventive measure in water quality forecasting of the future river. This study picked out NAJU and HAMPYUNG as the subject of investigation and used monthly the water quality and the outflow data of KWANGJU2, NAJU, YOUNGSANNPO and HAMPYUNG from 1995 to 1999 to forecast BOD, COD, T-N, T-P water density. The datum from 1995 to 1999 are used for study and that of 2000 are used for verification. To develop model of water quality forecasting, firstly, this research formed Neural Network model and divided Neural Network model into two case - the case of considering lag and not considering. And this study selected optimal Neural Network model through changing the number of hidden layer based on input layer(n) from n to 3n. Through forecasting result, the case without considering lag showed more precise simulated result. Accordingly, this study intended to compare, analyse that Fuzzy model using the method without considering lag with Neural Network model. As a result, this study found that the model without considering lag in Neural Network Network shows the most excellent outcome. Thus this study examined a forecasting accuracy, analyzed result and verified propriety through appling the method of water quality forecasting using Neural Network and Fuzzy Algorithms to the actual case.

• Journal of Korean Society on Water Environment
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• v.30 no.4
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• pp.409-417
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• 2014

Spatial prediction methods have been useful to determine the variability of water quality in space and time due to difficulties in collecting spatial data across extensive spaces such as watershed. This study compares two kriging methods in predicting BOD concentration on the unmonitored sites in the Geum River Watershed and to assess its predictive performance by leave-one-out cross validation. This study has shown that cokriging method can make better predictions of BOD concentration than ordinary kriging method across the Geum River Watershed. Challenges for the application of cokriging on the spatial prediction of surface water quality involve the comparison of network-distance-based relationship and euclidean-distance-based relationship for the improvement in the predictive performance.

• Korean Journal of Environment and Ecology
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• v.38 no.1
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• pp.67-78
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• 2024

The term ecosystem services refers to natural ecosystems' benefits to humans. Various models have been developed and applied to quantify ecosystem services. Habitat quality assessment is a widely used leading InVEST ecosystem service model. In Korea, habitat quality assessment is conducted for national parks. For habitat quality assessment, the initial value of habitat quality must be used to assess the sensitivity to threats, which varies depending on the country and application field. Therefore, an expert survey (AHP) was conducted based on previous habitat quality assessments in national parks to adjust the sensitivity, the initial value for the habit quality assessment. As a result of the AHP, 18 items were adjusted, including 10 items, such as natural grassland and unarranged fields, upward and 8 items, such as rivers and ponds, downward. Based on the adjusted sensitivity results, the habitat quality of Bukhansan National Park and Gyeryongsan National Park (urban type), Gyeongju National Park (historic type), Hallyeohaesang National Park (ocean type), and Jirisan National Park and Seoraksan National Park (mountain type) were adjusted. The results of the analysis showed that the habitat quality of urban dry areas and water bodies distributed in the national parks was reflected in the habitat quality assessment. In the future, it will be possible to evaluate the habitat quality of natural parks using this standard.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.618-641
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• 2003

Various quality models using quality factor, quality criteria and metrics have been proposed in order to evaluate quality of software products. However, a customized quality model which is specific to the characteristics of software component is required. In this paper, we propose external quality prediction techniques enable us to predict what external quality the final software product will have by using metrics as with internal attributes of software in development. We also propose a model not only for measuring quality by using metrics but also for applying internal attributes of ISO 9126 into artifacts of software component development.

• Journal of Korean Academy of Nursing
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• v.43 no.3
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• pp.312-320
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• 2013

Purpose: The purpose of this study was to test a model for quality of life among infertile women. This model was based primarily on the concept of the Fertility Quality of Life by Boivin et al. (2011) and the Infertility Resilience Model by Rindenour (2009). Methods: Fifteen measurable variables were used to estimate quality of life. They included endogenous variables such as fertility quality of life and resilience, and exogenous variables such as infertility related stress, depression, marital adjustment, and family support. Data sets (n=203) used for analysis were collected in a general hospital which had, on average, 400 assisted reproductive technologies per month. Results: The assessment of the modified model indicated acceptable fit, with $x^2/d.f$=2.07, GFI=.90, AGFI=.89, NFI=.89, CFI=.91, RMSEA=.07. Depression, infertility related stress, marital adjustment, resilience, and family support had direct influences on quality of life. Conclusion: The results of this study should contribute to the development of nursing intervention programs to enhance quality of life using factors that affect fertiQol (fertility quality of life) of infertile women.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.277-296
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• 2016

Purpose: Propose model to diagnose and assess National Defense Industry and quality management by investigating and analyzing established standard model. Methods: Research on established internal model including MB, EQA and JQA model and make standard index for quality index extraction and quantitative index to test objectively for internal state. Results: Extract advantage and disadvantage by performance of National Defense Industry level diagnose and build foundation for quality management policy and road map. Conclusion: Due to result of diagnostic assesment of quality management of national defense industry, dependability, SCQM and safety part shows vulnerability and require improvement and support.

• Journal of Environmental Impact Assessment
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• v.8 no.4
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• pp.1-12
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• 1999

The purpose of this study is to develop a Water Quality Management System(WQMS), which calculates pollutant discharge and forecasts water quality with a water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView 3.1 was used to enter or edit geographic data and attribute data, and Avenue Script was used to customize the user interface. PCI, a remote sensing software, was used to derive land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, database subsystem and modelling subsystem. The database subsystem consisted of watershed data from digital maps, remote sensing data, government reports, census data and so on. The modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model) and SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. These two subsystems were connected through a graphic display module. This system has been calibrated for and applied to Mokhyun Stream watershed.