• Journal of Korean Society on Water Environment
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• v.20 no.6
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• pp.685-691
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• 2004

Water quality forecasting with long term flow is important for management and operation of river environment. However, it is difficult to set up and operate a physical model for water quality forecasting due to large uncertainty in the data required for model setting. Therefore, relatively simpler stochastic approaches are adopted for this problem. In this study we try several multivariate time series models such as ARMAX models for the possible substitute for water quality forecasting. Those models are applied to the BOD and COD levels at Noryangin station, Han river, and also evaluated the effect of release from Paldang dam on them. Monthly BOD and COD data from 1985 to 1991 (7 years) are used for model building and another two year data for model testing. As a result of the study, the effect of improvement on water quality is much more effective combining with the water quality improvement of dam release than considering only increment of dam release in the downstream Han river.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2000.11a
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• pp.265-283
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• 2000

Factors influencing the success or failure of information systems(IS) have been discussed in many literature. However, little theoretical development or empirical research has examined effectiveness of hospital information systems(HIS) This study set the research model of influencing factors and consequences of HIS through theoretical studies based on Management Information Systems, and then empirically tested several hypotheses related to this model. Based on a sample of 274 respondents who participated in dealing with the HIS, this research used a multiple regression analysis to test the research model. The results of this study are as follows: system quality, information quality and support of top management are statistically significant influence on user satisfaction. Service quality is a partially significant influence on user satisfaction. Hypothesis 5, proposing that computer self-efficacy would relate positively to user satisfaction, was not supported by the questionnaire results. Based on these results, system quality, information quality and support of top management are very important variables for IS success. And the study's findings indicate DeLone and McLean's model is correct in proposing that the indirect relationship between influencing factors and organizational effectiveness, mediated by user satisfaction, is an important one.

• Environmental Engineering Research
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• v.16 no.3
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• pp.121-129
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• 2011

The completely mixed flow and plug flow (CAP) water quality model was developed for streams with discontinuous flows, a condition that often occurs in low base flow streams with in-stream hydraulic structures, especially during dry seasons. To consider the distinct physical properties of each reach effectively, the CAP model stream network can include both plug flow (PF) segments and completely mixed flow (CMF) segments. Many existing water quality models are capable of simulating various constituents and their interactions in surface water bodies. More complicated models do not necessarily produce more accurate results because of problems in data availability and uncertainties. Due to the complicated and even random nature of environmental forcing functions, it is not possible to construct an ideal model for every situation. Therefore, at present, many governmental level water quality standards and decisions are still based on lumped constituents, such as the carbonaceous biochemical oxygen demand (CBOD), the total nitrogen (TN) or the total phosphorus (TP). In these cases, a model dedicated to predicting the target concentration based on available data may provide as equally accurate results as a general purpose model. The CAP model assumes that its water quality constituents are independent of each other and thus can be applied for any constituent in waters that follow first order reaction kinetics. The CAP model was applied to the Geum River in Korea and tested for CBOD, TN, and TP concentrations. A trial and error method was used for parameter calibration using the field data. The results agreed well with QUAL2EU model predictions.

• Journal of Korean Academy of Nursing
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• v.39 no.4
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• pp.518-527
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• 2009

Purpose: The purpose of this study was to identify factors influencing quality of life in kidney transplant recipients and to understand the concrete pathway of influence and the power of each variable, so that integrated prediction model to promote the quality of life of kidney transplant recipients could be developed. Methods: The sample was composed of 218 patients in follow-up care after a kidney transplant in one of 4 university hospitals in the Honam area. A structured questionnaire was used and the collected data were analyzed for fitness, using the LISREL program. Results: This model was concise and extensive in predicting the quality of life of kidney transplant recipients. Conclusion: The research verified the factors influencing quality of life for kidney transplant recipients and it verified that direct factors such as perception of health state, compliance, self-efficacy, stress and indirect factors such as self-efficacy and social support can be important factors to predict the quality of life for recipients. Moreover, those variables represent 87% of variance in explaining quality of life in a prediction model so that the variables can be utilized to predict quality of life for kidney transplant recipients.

• Knowledge Management Research
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• v.15 no.2
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• pp.67-88
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• 2014

This study aims to investigate on measuring the success of e-Learning. For this purpose, we proposed a research model that consists of e-Learning contents quality, e-Learning system quality, e-Lecturing quality, sense of e-Learning community factors as independent factors and e-Learning and e-Learning satisfaction as mediators and tested it empirically based on the structural equation model. The empirical results showed that e-Learning contents quality, e-Learning system quality, sense of e-Learning community factors directly lead to e-Learning. The study also found that e-Learning contents quality, e-Lecturing quality, sense of e-Learning community factors bring about higher e-Learning satisfaction and that e-Learning satisfaction has a positive impact on e-Learning. Furthermore, the research discovered that both e-Learning and e-Learning satisfaction have a significant relationship with e-Learning net benefits. This research renders its theoretical contribution to analyzing a positive influence of sense of e-Learning community, a newly suggested variable added to the existing IS success model in this study, on e-Learning. From a practical view, the findings of this study can lead to improving the quality of e-Learning in today's era where the growth of e-Learning industry is quite noticeable.

• Information Systems Review
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• v.3 no.1
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• pp.19-30
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• 2001

With the e-business paradigm emerging, the website became a critical resource for most corporations. However, the amount of value creation through internet is still in question. This paper shows the result of an exploratory study on website assessment, following the tradition of Technology Acceptance Model (TAM). We viewed the intended usage as the value of the website and added such factors as playfulness, commitment, system quality, and information security as external variables of the model. Website types, visiting purposes, and the user system quality were included as moderators. The website value could differ depending on website types, purposes of the use and system quality. In the case of internet shopping malls, playfulness, compatibility, website quality were identified as key influencers, while for stock trading users, however, commitment and security factors are more important. In terms of user purposes, information search requires both the compatibility and the website quality. Also the website quality was strongly affected by the user system quality. In other words, any investment of upgrading the website system quality can be meaningless unless the user system quality is improved as well. For each variable considered, empirical results are discussed and practical implications are provided.

• Journal of KIBIM
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• v.12 no.1
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• pp.23-34
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• 2022

In the current 2D-based design, design reliability is lowered due to interference and inconsistency between plans, errors in drawings and quantities, etc. At the time of transition to BIM-based 3D design, it is necessary to expand the reliability and usability of BIM by eliminating these errors from the design stage through securing the quality of the BIM digital model. Therefore, in the railway infrastructure design stage, the quality management process and standards of the BIM digital model were defined and quality management index were developed. Based on the rule extracted from the quality management index, a pilot quality management was conducted in connection with the commercial Model-Checker rule, problems and improvement plans were derived, and a rule-based automated quality management plan was prepared.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.1
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• pp.1-15
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• 2024

Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.219-229
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• 2017

A watershed-river linked modeling system was developed to forecast the water quality, particularly weekly changes in chlorophyll-a concentration, of the Yeongsan River, Korea. Hydrological Simulation Program-Fortran (HSPF) and Environmental Fluid Dynamics Code (EFDC) were adopted as the basic model framework. In this study, the EFDC model was modified to effectively simulate the operational condition and flow of multi-functional weirs constructed in the main channel of rivers. The model was tested against hydrologic, water quality and algal data collected at the right upstream sites of two weirs in 2014. The mean absolute errors (MAEs) of the model calibration on the annual variations of river stage, TN, TP, and algal concentration are 0.03 ~ 0.10 m, 0.65 ~ 0.67 mg/L, 0.03 ~ 0.04 mg/L, and $9.7{\sim}10.8mg/m^3$, respectively. On the other hand, the MAE values of forecasting results for chlorophyll-a level at the same sites in 2015 range from 18.7 to $22.4mg/m^3$, which are higher than those of model calibration. The increased errors in forecasting are mainly attributed to the higher uncertainties of weather forecasting data compared to the observed data used in model calibration.

• Journal of Korean Society for Quality Management
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• v.29 no.1
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• pp.101-112
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• 2001

In supply chain, the quality level of assembly factory depends on the quality levels of suppliers and it is very important to integrate efforts improving the quality levels between producer and suppliers, In this paper, we consider an integrated determination problem of quality specification levels of suppliers. The cost model is developed and the optimal policy under a specific model assumption is obtained. A numerical example is studied.