• Journal of Environmental Impact Assessment
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• v.13 no.1
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• pp.9-19
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• 2004

This study is performed to examine the relationship between air pollution exposure and mortality in Daejeon for the years of 1998 - 2001. Daily counts of death were analyzed by general additive Poisson model, with adjustment for effects of seasonal trend, air temperature, humidity, and day of the week as confounders in a nonparametric approach. Daily death counts were associated with CO(4 day before), $O_3$(current day), $PM_10$(4 day before), $NO_2$(6 day before), $SO_2$(2 day before). Increase of $31.07{\mu}g/m^3$(interquartile range) in $PM_10$ was associated with 2.0 % (95% CI = 0.5 % - 3.5 %)) increase in the daily number of death. This effect was greater in children(less than 15 aged) and elderly(more than 65 aged). We concluded that Daejeon had 2 - 4 % increase in mortality in association with IQR in air pollutants. Daily variations in air pollution within the range currently occurring in Daejeon might have an adverse effect on daily mortality. These findings also support the hypothesis that air pollution at levels below the current ambient air quality standards of Korea except PM10, is harmful to sensitive subjects, such as children or elderly.

• Journal of environmental and Sanitary engineering
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• v.18 no.3 s.49
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• pp.89-99
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• 2003

This study is peformed to examine the relationship between air pollution exposure and mortality in Incheon for the years of 1998 - 2001. Daily counts of death were analyzed by general additive Poisson model, with adjustment for effects of seasonal trend, air temperature, humidity, and day of the week as confounders in a nonparametric approach. Daily death counts were associated with CO(1 day before), O$_3$(2 day before), PM$_{10}$(1 day before), NO$_2$(1day before), SO$_2$(1 day before). Increase of 32.21 ${\mu}$g/m$^3$(interquartile range) in PM$_{10}$ was associated with 1.9 % (95% CI = 0.8 % - 2.9 %) increase in the daily number of death. This effect was greater in children(less than 15 aged) and elderly(more than 65 aged). We concluded that Incheon had 2 - 4 % increase in mortality in association with IQR in air pollutants. Daily variations in air pollution within the range currently occurring in Incheon might have an adverse effect on daily mortality. These findings also support the hypothesis that air pollution, at levels below the current ambient air quality standards of Korea, is harmful to sensitive subjects, such as children or elderly.

• Journal of Environmental Science International
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• v.15 no.11
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• pp.1017-1025
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• 2006

This study was conducted to evaluate characteristic of water duality in coastal sea of Incheon using a multivariate analysis. The analysis data in coastal sea of Incheon was aquired by the NFRDI data which was surveyed from March 1997 to November 2003. Eleven water quality parameters were determined on each survey The results were summarized as follow : Water quality in Incheon coastal sea could be explained up to 64.62% by three factors which were included in loading of fresh water and nutrients by the land(36.98%), seasonal variation(16.19%), and internal metabolism (11.24%). The results of time series analysis by factor score, in case of factor 1, station 1 influenced by Han river was shown to high factor score and station 3 located by outer sea was shown to low factor score. In case of factor 2, station 1 was appeared to high variation and station 3 was appeared to low variation. The result of cluster analysis by station was classified into three group that has different water quality characteristics. Especially, station 1 which affected by Han river and station 4 which affected by sewage treatment plant was appeared to considerable water quality characteristics against other station. In yearly cluster analysis, three group was classified and water quality in 2003 years due to high precipitation was different to another year. It could be suggested from these results that it is important to control discharge of fresh water by Han rivet and sewage treatment plant for water quality management of coastal sea of Incheon.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.197-207
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• 2018

SMEs manufacturing Factory, which are small-scale production systems of various types, mass-produce and sell products in order to meet customer needs. This means that the company has an excessive amount of material supply to reduce the loss due to lack of inventory and high inventory maintenance cost. And the products that fail to respond to the demand are piled up in the management warehouse, which is the reality that the storage cost is incurred. To overcome this problem, this paper uses ARIMA model, a time series analysis technique, to predict demand in terms of seasonal factors. In this way, demand forecasting model based on economic order quantity model was developed to prevent stock shortage risk. Simulation is carried out to evaluate the effectiveness of the development model and to demonstrate the effectiveness of the development model as applied to SMEs in the future.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.47-54
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• 2015

In this study, we developed strategies for pre-processing GNSS data for the purpose of separating geodetic factors from crustal deformation due to the earthquakes. Before interpreting GNSS data analysis results, we removed false signals from GNSS coordinate time series. Because permanent GNSS stations are located on a large tectonic plate, GNSS position estimates should be affected by the tectonic velocity of the plate. Also, stations with surrounding trees have seasonal signals in their three-dimensional coordinate estimates. Thus, we have estimated the location of an Euler pole and angular velocities to deduce the plate tectonic velocity and verified with geological models. Also, annual amplitudes and initial phases were estimated to get rid of those false annual signals showing up in the time series. By considering the two effects, truly geodetic analysis was possible and the result was used as preliminary data for analyzing post-seismic deformation of the Korean peninsula due to the Tohoku-oki earthquake.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.451-454
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• 2004

The study aims to assess the quality of bank filtrate in relation to streamflow and physico-chemical properties of the stream. Turbidity, pH, temperature and dissolved oxygen (DO) of Nakdong River and riverbank filtrate were statistically analyzed. The physico-chemical properties of riverbank filtrate were measured from irregularly different seven pumping wells every day. Autocorrelation analyses were conducted to the qualities of stream water and bank filtrated water. Temperature, pH and DO of streamflow shows strong linearity and long memory effect, indicating the effect of seasonal air temperature and rainy season. Temperature of riverbank filtrate shows weak linearity and weak memory, indicating differently from the trend of stream temperature. Turbidity of steramflow shows strong linearity and long memory effect, while turbidity of riverbank filtrate indicates weak linearity and weak memory. Cross-correlation analysis shows low relation between turbidity, pH, temperature and DO of riverbank filtrate and those of streamflow. Turbidity of streamflow was largely affected by the streamflow rate, showing a similar trend with autocorrelation function of streamflow rate. The turbidity of riverbank filtrate has a lag time of 25 hours. This indicates that turbidity of streamflow in a dry season has very low effect on the turbidity of riverbank filtrate, and a high turbidity of the stream in a rainy season has a fairly low effect on the turbidity of riverbank filtrate.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.69-78
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• 1999

In this paper, a neural network approach to forecast Korean regional precipitation is presented. We first analyze the characteristics of the conventional models for time series prediction, and then propose a new model and its learning method for the precipitation forecast. The proposed model is a layered network in which the outputs of a layer are buffered within a given period time and then fed fully connected to the upper layer. This study adopted the dual connections between two layers for the model. The network behavior and learning algorithm for the model are also described. The dual connection structure plays the role of the bias of the ordinary Multi-Layer Perceptron(MLP), and reflects the relationships among the features effectively. From these advantageous features, the model provides the learning efficiency in comparison with the FIR network, which is the most popular model for time series prediction. We have applied the model to the monthly and seasonal forecast of precipitation. The precipitation data and SST(Sea Surface Temperature) data for several decades are used as the learning pattern for the neural network predictor. The experimental results have shown the validity of the proposed model.

• Journal of Environmental Health Sciences
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• v.33 no.4
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• pp.283-292
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• 2007

Atmospheric concentrations of radon had been continuously observed in Seoul, Korea since December 1999, as a tracer for long-range transport of air pollutants from China continent to Korea. In order to study radon as a tracer of long-range transport, it is important to know information about the atmospheric distribution and variation of radon concentration and its time variation. Atmospheric radon concentration are measured with electrostatic radon monitor(ERM) at Hanyang University located in Eastern area of Seoul. Air sample is taken into a vessel of ERM, and alpha particles emitted by radon daughters $Po^{218}$ are detected with ZnS(Ag) scintillation counter. Hourly mean concentrations and hourly alpha counts are recorded automatically. The major results obtained from time series observation of atmospheric radon were as follows : (1) The mean of airborne radon concentration in Seoul was found to be $7.62{\pm}4.11\;Bq/m^3$ during December $1999{\sim}January$ 2002. (2) The hourly variation of radon concentrations showed the highest in 8:00AM ($8.66{\pm}4.22\;Bq/m^3$) and the lowest in 3:00AM ($6.62{\pm}3.70\;Bq/m^3$) and 5:00AM ($6.62{\pm}3.39\;Bq/m^3$). (3) the seasonal variation of radon concentrations showed higher during winter-to-fall and lower during summer-to-spring. (4) Correlation between airborne radon concentration and the meteorological factors were -0.21 for temperature, 0.09 for humidity, -0.20 for wind speed, and 0.04 for pressure. (5) The mean difference of airborne radon concentration between Asian dust ($5.36{\pm}1.28\;Bq/m^3$) and non-Asian dust ($4.95{\pm}1.49\;Bq/m^3$) phenomenon was significant (p=0.08). We could identify time series distribution of radon concentration related meteorological factors. In addition, radon can be considered a good natural tracer of vertical dispersion and long-range transport.

• Journal of Korean Society of Forest Science
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• v.73 no.1
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• pp.70-75
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• 1986

The secular trend and seasonal variation of chestnut prices have been analyzed, and the production and price for the next two decades (1985-2004) have been forecasted by the derived equation model. The results of the study can be summarized as follows; 1) The chestnut prices went up at the rate of 10.95% per annum during 1965-1972, but, due to excessive supply of chestnuts, went down at the rate of 7.25% during 1973-1984. 2) In a year, the prices were lowest at the harvesting season, especially on October, and highest on July. Such a seasonal fluctuations of chestnut prices tend to be even with the passage of time, but the range of fluctuation is still wide. 3) It was forecasted under certain premises that the annual chestnut production will be increased by 99,000 tons in 1992, but the amount will fall rapidly to about 23,000 tons in 2004. The prices will be similar to the present level or have slightly upward Tendency until 1992, but this will be rapidly raised thereafter.