• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.4
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• pp.425-434
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• 2022

Objectives: This study analyzes TVOC concentrations in root industry workplaces in order to prevent probable occupational disease among workers. Root industry includes all the infrastructure of manufacturing, such as casting and molding. Methods: Real-time TVOC sensors were deployed in three root industry workplaces. We measured TVOC concentrations with these sensors and analyzed the results using a data-analysis tool developed with Python 3.9. Results: During the study period, the mean of the TVOC concentrations remained in an acceptable range, 0.30, 2.15, and 1.63 ppm across three workplaces. However, TVOC concentrations increased significantly at specific times, with respective maximum values of 4.98, 28.35, and 26.65 ppm for the three workplaces. Moreover, the analysis of hourly TVOC concentrations showed that during working hours or night shifts TVOC concentrations increased significantly to higher than twice the daily mean values. These results were scrutinized through classical decomposition results and autocorrelation indices, where seasonal graphs of the corresponding classical decomposition results showed that TVOC concentrations increased at a specific time. Trend graphs showed that TVOC concentrations vary by day. Conclusions: Deploying a real-time TVOC sensor should be considered to reflect irregularly high TVOC concentrations in workplaces in the root industry. It is expected that the real-time TVOC sensor with the presented data analysis methodology can eradicate probable occupational diseases caused by detrimental gases.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.65-73
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• 2001

Until recently, we use only weekly and monthly adjustment factors in order to estimate the AADT. By the way. we can suppose that the traffic is time series data related to flow of time. So we tried to analyse traffic patterns using time series analysis and apply them to estimate the AADT. We could divide traffic patterns into trend, cyclic variation, seasonal variation and irregular variation like as time series data. Also, in order to reduce random error components, we have looked for the weather conditions as an influential factor. There are many weather conditions such as rainfalls, but, temperatures, and sunshine hours among others but we selected rainfalls and lowest temperatures. And then, we have estimated the AADT using time series factors. To compare the results of, we have applied both irregular variation joined to weather factors and that not joined to. RMSE and U-test were opted at methods to appreciate results of AADT estimation.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.7 no.3
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• pp.171-180
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• 2002

The temporal and spatial distributions of phosphorus have been investigated in the Gomso Bay, Korea. TP, PIP, TOP and DIP in sediment were found 548.8mg P kg$^{-1}$ , 426.1mg P kg$^{-1}$ , 122.6mg P kg$^{-1}$ , and 0.217mg P kg$^{-1}$ , respectively with a decreasing order of PIP>TOP>DIP. Any temporal or spatial trend has not been found on the distribution of TP in the sediment, except the high TP values near the mouth of Julpo-chun. We found seasonal patterns high TOP(28.90% of TP) and low TIP(71.10% of TP) in August, but low TOP(15.63% of TP) and high TIP(84.38% of TP) in November. There were three times higher DIP concentration in August than in November. Such case is probably not only due to the enhanced supply of DIP directly from the decomposition of organic matter from overlying water in summer, but also the released phosphate from the adsorbed particulate matter such as PIP under the low pH and Eh conditions at the subsurface layers of the sediment induced by the active microbial respiration of increased organic materials in summer. Primarily, the source of phosphorous from municipal sewage strongly influenced the early stage of the distribution of all the phosphorous in the Gomso tidal flat. Notwithstanding, through the processes of diagenesis in sediment, water temperature and organic contents probably functioned as the key parameters to control the temporal distributions of TOP, TIP and DIP in the Gomso tidal flat.

• Korean Security Journal
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• no.61
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• pp.109-135
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• 2019

The purpose of this study is to investigate the occupational diseases(the number of medical treatment) of fire officials by using time-series analysis. The results of the study are as follows. First, the average rates of the occupational diseases of fire officials were as follows: ① internal diseases were the highest at 9.24% in December, the lowest at 7.76% in February, ② otolaryngologic diseases were the highest at 9.29% in December, the lowest at 6.74% in August, ③ dermatological diseases were the highest at 10.03% in July, the lowest at 7.35% in January and February, ④ surgical diseases were the highest at 10.38% in November, the lowest at 5.62% in February, ⑤ orthopedic diseases were the highest at 9.69% in March, the lowest at 7.52% in November, ⑥ neurosurgical diseases were the highest at 9.33% in April, the lowest at 6.82% in February, ⑦ neurological diseases were the highest at 9.47% in December, the lowest at 7.06% in October, and ⑧ mental health diseases were the highest at 9.93% in December, the lowest at 6.51% in May. Second, the seasonal decomposition of the disease occurrence of fire officials were described by assigning seasonal factor(S), trend factor(T), circulation factor(C) and irregular factor(R): ① internal diseases were 1.075(S) × 189.355(T·C) × 1.174(R) = 238.975(F), ② otolaryngologic diseases were 1.023(S) × 69.605(T·C) × 1.040(R) = 74.000(F), ③ dermatological diseases were 1.002(S) × 73.088(T·C) × 0.874(R) = 64.000(F), ④ surgical diseases were 1.099(S) × 27.229(T·C) × 0.669(R) = 20.000(F), ⑤ orthopedic diseases were 1.115(S) × 73.182(T·C) × 1.213(R) = 99.000(F), ⑥ neurosurgical diseases were 0.993(S) × 27.836(T·C) × 1.303(R) = 36.000(F), ⑦ neurological diseases were 1.029(S) × 62.417(T·C) × 1.152(R) = 74.000(F), and ⑧ mental health diseases were 1.210(S) × 8.781(T·C) × 1.035(R) = 11.000(F).