• Environmental Engineering Research
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• v.10 no.2
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• pp.62-70
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• 2005

Pollution loading of Combined Sewer Overflows (CSOs) is frequently over the capacity of a wastewater treatment plant (WWTP) receiving the water. The objectives of this study are to investigate water quality of CSOs in Anmyun-ueup, Tean province and to apply Storm Water Management Model to predict flow rate and water quality of the CSOs. The capacity of a local WWTP was also estimated according to rainfall duration and intensity. Eleven water quality parameters were analyzed to characterize overflows. SWMM model was applied to predict the flow rate and pollutant load of CSOs during rain event. Overall, profile of the flow and pollutant load predicted by the model well followed the observed data. Based on model prediction and observed data, CSOs frequently occurs in the study area, even with light precipitation or short rainfall duration. Model analysis also indicated that the local WWTP’s capacity was short to cover the CSOs.

• Korea Journal of Hospital Management
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• v.13 no.3
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• pp.69-93
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• 2008

Rising healthcare cost is a global phenomenon that justifies governments' introduction of 'incentive regulation' plan for the improvement of hospital efficiency. A number of previous studies tried to evaluate the efficiency of healthcare organization by using Data Envelopment Analysis(DEA), a common efficiency benchmarking method. However, there is a concern that this kind of efficiency evaluation could induce "quantity-quality trade-off". Moreover, as quality aspect is especially important in terms of 'effectiveness' of health care, it should be considered in efficiency evaluation of healthcare organization. A number of different models were tried so far to incorporate quality aspect into DEA, however, none is universally recognized as a standard. Thus, in this study, previous quality-incorporating DEA models were categorized into 6 types according to the way of incorporating quality aspect, and strengths and limitations of each type were reviewed with a set of artificial data as an example. Based on this review, a new quality-incorporating efficiency evaluation model, named Quality-adjusted output DEA(QAO-DEA), was suggested. As an exploratory empirical analysis, technical efficiency of human resource were measured with different quality-incorporating DEA models, using 2004 data from National University Hospitals. In conclusion, Quality-adjusted output DEA(QAO-DEA) model seems to be one of the most desirable alternatives to incorporate quality aspect in efficiency evaluation of hospital, and deserves the consideration as a policy tool to induce simultaneous improvement of both efficiency and quality.

• Journal of Applied Reliability
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• v.17 no.2
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• pp.83-91
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• 2017

Purpose: The purpose of this study is to develop a quality assurance model and to determine appropriate warranty period for a guided missile using its field data. Methods: 10 years of actual firing data is collected from the defense industry company and military. Parametric maximum likelihood estimation for a reliability function is determined with the data. Results: The reliability function estimates average lifetime of the missile. That function shows a user requirement, 80% reliability (lifetime) is come up when 8 years have passed, which is longer than the estimates in the missile's development phase. Conclusion: Quality assurance warranty for a guided missile must be established with actual test data. It is necessary to update and modify the reliability prediction and the warranty period with actual field test data.

• Journal of Korean Society on Water Environment
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• v.32 no.6
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• pp.570-581
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• 2016

A watershed model was constructed using the Hydrological Simulation Program Fortran to predict the water quality, especially chlorophyll-a concentraion, at major tributaries of the Nakdong River basin, Korea. The BOD export loads for each land use in HSPF model were estimated at $1.47{\sim}8.64kg/km^2/day$; these values were similar to the domestic monitoring export loads. The T-N and T-P export loads were estimated at $0.618{\sim}3.942kg/km^2/day$ and $0.047{\sim}0.246kg/km^2/day$, slightly less than the domestic monitoring data but within the range of foreign literature values. The model was calibrated at major tributaries for a three-year period (2008 to 2010). The deviation values ranged from -31.5~1.6% of chlorophyll-a, -24.0~2.2% of T-N, and -5.7~34.8% of T-P. The root mean square error (RMSE) ranged from 4.3~44.4 ug/L for chlorophyll-a, -0.6~1.5 mg/L for T-N, and 0.04~0.18 mg/L for T-P, which indicates good calibration results. The operational water quality forecasting results for chlorophyll-a presented in this study were in good agreement with measured data and had an accuracy similar with model calibration results.

• Journal of Distribution Science
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• v.22 no.10
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• pp.43-54
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• 2024

Purpose: Market competition in the fashion industry is intensifying, pushing brands to strive for consumer preference and market leadership. Mobile fashion applications have emerged as key distribution channels, with live streaming being a common feature for product distribution and consumer loyalty. Therefore, this study will analyze the loyalty model in live streaming on mobile fashion applications by integrating the quality loyalty model, parasocial relationships, and uses and gratifications (U&G) theory. Research design, data and methodology: Data were collected from a survey of 427 respondents who are customers of a fashion product that had been purchased through live streaming on a mobile fashion application and processed using the PLS-SEM method Results: The results of the study show that the live streamer and product quality significantly influence satisfaction and loyalty. Conversely, AR content and live streaming content do not directly influence loyalty but have an indirect effect through satisfaction Conclusions: this study is the first to model loyalty in mobile fashion applications by integrating the quality loyalty model, parasocial relationship, and U&G theory. Practically, fashion companies are advised to conduct live streaming by considering aspects of content, live streamer, and product quality to enhance satisfaction and loyalty.

• The Journal of Information Systems
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• v.32 no.1
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• pp.109-146
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• 2023

Purpose With Intelligent public service (IPS), it is possible to automate the quality of civil affairs, provide customized services for citizens, and provide timely public services. However, empirical studies on factors for the successful use of IPS are still insufficient. Hence, the purpose of this study is to empirically analyze the factors that affect the success of IPS with classification function. ISSM (Information System Success Model) is considered as the underlying research model, and how the algorithm quality, data quality, and environmental quality of the discrimination system affect the relationship between utilization intentions is analyzed. Design/methodology/approach In this study, a survey was conducted targeting users using IPS. After giving them a preliminary explanation of the intelligent public service centered on the discrimination system, they briefly experienced two types of IPS currently being used in the public sector. Structural model analysis was conducted using Smart-PLS 4.0 with a total of 415 valid samples. Findings First, it was confirmed that algorithm quality and data quality had a significant positive (+) effect on information quality and system quality. Second, it was confirmed that information quality, system quality, and environmental quality had a positive (+) effect on the use of IPS. Thirdly, it was confirmed that the use of IPS had a positive (+) effect on the net profit for the use of IPS. In addition, the moderating effect of the degree of knowledge on AI, the perceived accuracy of discriminative experience and IPS, and the user was analyzed. The results suggest that ISSM and TOE framework can expand the understanding of the success of IPS.

• International Journal of Contents
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• v.6 no.4
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• pp.62-68
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• 2010

More and more researchers and practitioners in the field of e-commerce are paying attentions to the retention of online customers. However, only a few researches can be addressed in the context of internet shopping mall repurchase intention. This study aims at investigating and delineating the important characteristic factors which affect consumers' repurchase intentions by conducting an empirical analysis. In order to fulfill this purpose effectively, a comprehensive review of previous studies regarding information system success model was performed in order to render a stronger theoretical foundation for our study. Finally, based on the DeLone and McLean (2003) IS success model, information quality, system quality, service quality, customer satisfaction and repurchase intention were employed as five constructs in the research model and hypotheses on mutual relationships between these constructs were established accordingly. Structural equation modeling was employed to analyze the data collected from 204 internet shopping mall consumers in China. Our theoretical model exhibited a good fit with the observed data. The empirical results showed particularly strong support for the effects of information quality, service quality and user satisfaction. The findings of this research contributed to the extension of repurchase intention study in the context of Internet shopping malls. Our research also offered implications for practitioners in regards to devising internet shopping malls so as to increase consumers' repurchase intention to use these services.

• Food Science and Preservation
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• v.30 no.2
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• pp.224-234
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• 2023

We analyzed the major quality characteristics of red pepper powders from various regions and predicted these characteristics nondestructively using shortwave infrared hyperspectral imaging (HSI) technology. We conducted partial least squares regression analysis on 70% (n=71) of the acquired hyperspectral data of the red pepper powders to examine the major quality characteristics. R_c² values of ≥0.8 were obtained for the ASTA color value (0.9263) and capsaicinoid content (0.8310). The developed quality prediction model was validated using the remaining 30% (n=35) of the hyperspectral data; the highest accuracy was achieved for the ASTA color value (R_p²=0.8488), and similar validity levels were achieved for the capsaicinoid and moisture contents. To increase the accuracy of the quality prediction model, we conducted spectrum preprocessing using SNV, MSC, SG-1, and SG-2, and the model's accuracy was verified. The results indicated that the accuracy of the model was most significantly improved by the MSC method, and the prediction accuracy for the ASTA color value was the highest for all the spectrum preprocessing methods. Our findings suggest that the quality characteristics of red pepper powders, even powders that do not conform to specific variables such as particle size and moisture content, can be predicted via HSI.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.264-274
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• 2009

Concentration of Air Quality Models (CMAQ) has a deep connection with emissions and wind fields. In particular the wind field is highly affected by local topography and plays an important role in transport and dispersion of contaminants from the pollution sources. The purpose of this study is to examine the impact of interpolation on Air quality model. This study was designed to evaluate enhancement of MM5 and CMAQ predictions by using Four Dimensional Data Assimilation (FDDA), the SONDE data and the national meteorological station and the MODerate resolution Imaging Spectroradiometer (MODIS). The alternative meteorological fields predicted with and without MODIS data were used to simulate spatial and temporal variations of ozone in combined with CMAQ on June 2006. The result of this study indicated that data assimilation using MODIS data provided an attractive method for generating realistic meteorological fields and dispersion fields of ozone in the Korea peninsular, because MODIS data in 10 km domain are grid horizontally and vertically. In order to ensure the success of Air quality model, it is necessary to FDDA using MODIS data.

• The Journal of Information Technology
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• v.8 no.3
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• pp.83-103
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• 2005

The IT implementation literature suggests that various implementation factors play critical roles in the success of an information system; however, there is little empirical research about the implementation of data warehousing has unique characteristics that may impact the importance of factors that apply to it. in this study, a cross-sectional survey investigated a model of data warehousing success. Data warehousing managers and data suppliers from 51 organizations completed paired mail questionnaires on implementation factors and the success of the warehouse. The results from a regression analysis of the data identified relationships between the system quality and data quality factors and perceived net benefits. It was found that management support and resources help to address organizational issues that arise during warehouse implementations, resources, user participation, and highly-skilled project team members increase the likelihood that warehousing projects will finish on-time, on-budget, with the right functionality; and diverse, unstandardized source systems and poor development technology will increase the technical issues that project teams must overcome. The implementation's success with organizational and project issues, in turn, influence the system quality of the data warehouse; however, data quality is best explained by factors not included in the research model.