• Food Science and Industry
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• v.52 no.1
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• pp.20-31
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• 2019

Sensory perception of food/beverage products is one of the most important quality factors to determine consumer acceptability and thus sensory discrimination methodology has been a vital tool for quality management. Signal detection theory(SDT) and Thurstonian modeling provide the most advanced psychometric approach to modeling various discrimination methods. In these theories, perceptual and cognitive decisional factors are considered so that, a fundamental measure of sensory difference (d') can be computed, independent of test methods used. In this paper, sensory discrimination analysis based on SDT and Thurstonian modeling is introduced for more accurate and systematic applications of sensory and hedonic quality management in industry. Ways to realize the statistical power and relative sensitivity of sensory discrimination methods theorized in SDT and Thurstonian modeling in practice, are also discussed by using a case study of the Nongshim quality management program for drinking water in which SDT A-Not A test methodology was further optimized.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.47-54
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• 2004

A hydraulically and hydrologically based estimation method of pollutant delivery load for water quality modeling is proposed. The proposed method works on grid basis and routes overland flows from one cell to the next following the maximum downslope directions. The method is able to consider spatially-varied data of source pollutant, topography, land slopes, soil characteristics, land use and aspects, which can be extracted from geographic information systems (GIS) and from digital elevation models (DEMs). Because of this feature, the proposed method can be expected to be used for evaluating the impacts of various practices on watershed management for water quality.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.3
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• pp.151-164
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• 2013

Multidimensional dynamic water quality model of organic matter and trophic state was applied to the Han River system. The model was calibrated using field measurement data obtained during the year of 2007. The model results showed reasonable performance in predicting temporal variations of TN, TP, Chl-a and BOD concentrations. The applied integrated modeling system can be effectively used to simulate water quality as well as hydrodynamic and water temperature for river-lake continuous system in the Han River. Utilizing the calibrated model, we analyzed the spatial and temporal distributions of TN, TP, Chl-a and BOD concentrations in the Han River system. The temporal variations of water quality at each river reach and lake were effectively simulated with the developed model and spatial distribution of water qualities in the Han River system could be compared. The multidimensional dynamic modeling system can simulate the water qualities of entire waterbody where Lake Paldang and the incoming flows are included using single modeling system. So it can be effectively used for integrated water quality management of the Han River system.

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.703-708
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• 2000

• Water for future
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• v.30 no.4
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• pp.28-34
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• 1997

• Proceedings of the Korea Water Resources Association Conference
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• 1993.07a
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• pp.125-132
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• 1993

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.703-708
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• 2000

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1053-1060
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• 2021

Current water quality monitoring systems in Korea carried based on in-situ grab sample analysis. It is difficult to improve the current water quality monitoring system, i.e. shorter sampling period or increasing sampling points, because the current systems are both cost- and labor-intensive. One possible way to improve the current water quality monitoring system is to adopt a modeling approach. In this study, a modeling technique was introduced to support the current water quality monitoring system, and an artificial neural network model, the computational tool which mimics the biological processes of human brain, was applied to predict water quality of the river. The approach tried to predict concentrations of Total coliform at the outlet of the river and this showed, somewhat, poor estimations since concentrations of Total coliform were rapidly fluctuated. The approach, however, could forecast whether concentrations of Total coliform would exceed the water quality standard or not. As results, modeling approaches is expected to assist the current water quality monitoring system if the approach is applied to judge whether water quality factors could exceed the water quality standards or not and this would help proper water resource managements.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.84-93
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• 2012

The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.

• Journal of Environmental Impact Assessment
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• v.3 no.2
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• pp.25-32
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• 1994

This study was carried out as the Anyang creek water quality management using Geographic Information System (GIS) is the purpose of this pilot project to apply a GIS to environmental management field. Analysis of water quality data has been investigated using GIS with modeling of water quality management for the Anyang creek. The results of this study are summarized as follows: 1. The concentration of Mercury in sediment was increased rapidly nearby A26(Nightsoil Treatment Plant) and maximum was showed at A18 (Imgok bridge). Cadmium was increased rapidly at A35(Chulsan bridge). 2. River water quality management using visible computer system as GIS is effective to make decision for water quality management plan and database of environmental factors should be completed before applying GIS. 3. When water pollution accident is occurred in the river water system, pollutant source can be traced and analysed systematically using GIS to manage pollutants discharged into the river water system.