Jo, Deok-Jun;Kim, Myoung-Su;Lee, Jung-Ho;Park, Moo-Jong;Kim, Joong-Hoon
Proceedings of the Korea Water Resources Association Conference
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2005.05b
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pp.1199-1203
/
2005
Combined sewer overflows(CSOs) are themselves a significant source of water pollution. Therefore, the control of urban drainage for CSOs reduction and receiving water quality protection is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as stormwater detention storage is highly dependant on the temporal variability of storage capacity available(which is influenced by the duration of interevent dry periods) as well as the infiltration capacity of soil and recovery of depression storage. As a result, a contiunous approach is required to adequately size such facilities. This study for the continuous long-term analysis of urban dranage system used analytical Probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model have evolved that offer much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics or the subject area using analytical Probabilistic model. Runoff characteristics manifasted the unique characteristics of the subject area with the infiltration capacity of soil and recovery of depression storage and was examined appropriately by sensitivity analysis. This study presented the average annual COSs and number of COSs when the interceptor capacity is in the range 3xDWF(dry weather flow). Also, calculated the average annual mass of pollutant lost in CSOs using Event Mean Concentration. Finally, this study presented a dicision of storage volume for CSOs reduction and water quality protection.
From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.
Balun, Bilal;Nemutlu, Omer Faruk;Benli, Ahmet;Sari, Ali
Earthquakes and Structures
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v.18
no.2
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pp.223-231
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2020
Due to the fact that Bingöl province is at the intersection of the North Anatolian Fault and the Eastern Anatolian Fault, the seismicity of the region is important. In this study, probabilistic seismic hazard analyzes (PSHA) were conducted to cover the boundaries of Bingöl province. It occurred since 1900, the seismicity of the region was obtained statistically by considering the earthquake records with a magnitude greater than 4 and the Gutenberg-Richter correlation. In the study, magnitude-frequency relationship, seismic hazard and repetition periods were obtained for certain time periods (10, 20, 30, 40, 50, 75 and 100 years). Once a project area determined in this study, which may affect the peak ground acceleration according to various attenuation relationships are calculated and using the Turkey Earthquake Hazard Map, average acceleration value for Bingöl province were determined. As a result of the probabilistic seismic hazard analysis, the project earthquakes with a probability of exceeding 50 years indicate that the magnitude of the project earthquake is 7.4 and that the province is in a risky area in terms of seismicity. The repetition periods of earthquakes of 6.0, 6.5, 7.0 and 7.5 are 42, 105, 266 and 670 years respectively. Within the province of Bingöl; the probability of exceeding 50 years is 2%, 10% and 50%, while the peak ground acceleration values are 1.03 g, 0.58 g and 0.24 g. As a result, probabilistic seismic hazard analysis shows that the seismicity of the region is high and the importance of considering the earthquake effect during construction is emphasized for this region.
Ground Motion Prediction Equations (GMPEs) are essential tools in seismic hazard analysis. With the introduction of probabilistic approaches for the estimation of seismic response of structures, also known as, performance based earthquake engineering framework; new tasks are defined for response spectrum such as the reference criterion for effective structure-specific selection of ground motions for nonlinear time history analysis. One of the recent efforts to introduce a high quality databank of ground motions besides the corresponding selection scheme based on the broadband spectral consistency is the development of SIMBAD (Selected Input Motions for displacement-Based Assessment and Design), which is designed to improve the reliability of spectral values at all natural periods by removing noise with modern proposed approaches. In this paper, a new global GMPE is proposed by using selected ground motions from SIMBAD to improve the reliability of computed spectral shape indicators. To determine regression coefficients, 204 pairs of horizontal components from 35 earthquakes with magnitude ranging from Mw 5 to Mw 7.1 and epicentral distances lower than 40 km selected from SIMBAD are used. The proposed equation is compared with similar models both qualitatively and quantitatively. After the verification of model by several goodness-of-fit measures, the epsilon values as the spectral shape indicator are computed and the validity of available prediction equations for correlation of the pairs of epsilon values is examined. General consistency between predictions by new model and others, especially, in short periods is confirmed, while, at longer periods, there are meaningful differences between normalized residuals and correlation coefficients between pairs of them estimated by new model and those are computed by other empirical equations. A simple collapse assessment example indicate possible improvement in the correlation between collapse capacity and spectral shape indicators (${\varepsilon}$) up to 20% by selection of a more applicable GMPE for calculation of ${\varepsilon}$.
Journal of the Korean Regional Science Association
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v.8
no.1
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pp.31-50
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1992
The aim of this paper is to define major factors influencing land development of each of major uses (residential, commercial, industrial) in the process of rapid urban expansion. The main hypothesis of this study is that land use changing patterns are directed by supply side of land managed to public policies rather than demand side. The graphic analysis is applied to relationships between urban growth and land development process of each use and between land development project managed to public policies and land development process. Public and land development projects and zonning protection seem to be major roles of land supply and main determinants of urban spatial structure. Location factors for land development of each uses are selected in 23 variables. Factor analysis is applied to test correlation between variables in 1971 and 1981. Factor structure between two years is similar, but progressive processing of functional separation is derived such as intensive land use is grouped, different location between residential and industrial use is deep. Dependent variables are standardized to logarithm of land development of each use per unit vacant land in two periods, between 1971 and 1980 year and between 1981 year. Correlation analysis between 6 dependent variables and 23 location factors in each years are applied. Major factors of each use are selected in criteria such as high correlation with dependent variables, low correlation between independent variables and common application in two periods. As the result, major factors for residential land development are Land Readjustment Project (LRP), percent of total zoned area in residential zone, residential floor space density per available area, percent of total area in industrial use; for commercial development is distance to CBD, percent of total area in commercial use, residential floor space density per available area in each year, and volumn rate of industrial use; for industrial use is percent of total area of industrial use is percent of total area of industrial use, Industrial Estate Project (IES), LRP, and distance from CBD. Land development pattern of each use between two periods are slightly different. So 6 equation is derived from appling backward method of regession. Adjusted multiple R squares of all is more than 0.5 and those equation is statistically significant and valuable to assist urban land use forecasting.
This paper conducts a Structural Dcomposition Analysis on the structure of factors contributing to the output growth of Korean Maritime and Port Industry during year 2000~ year 2017. Some of results are as follows. The output growth rates of the industry (yearly average 4.3%) was far lower than the average growth rates of Service as well as of Manufacturing Industries (yearly average 9% and 6.8%, respectively) due to the lower output growth of Maritime Industry. Among the growth contributing factors, change in domestic demand for final goods is the first contributing factor, and then change in technology, change in export and import substitution for intermediate goods are followed in order, but import substitution for final goods decreased its output. However, in each respective sub-periods of pre-global financial crisis and post-global financial crisis, change in the export, especially change in the export of Maritime Industry is the dominant determinant of output change in the Maritime and Port Industry in opposite ways. In the periods of the former the increase in the export of Maritime Industry overwhelmingly led the output growth of the Maritime and Port industry, but in the periods of the latter the decrease in its export was the culprit of lower output growth of the industry. On the other hand, among all industries of service and manufacturing sectors, Wholesale and Retail industry is the leading industry in contributing to the output growth of the Maritime and Port Industry, and Transportation Equipment industry is the leading industry among all manufacturing industries.
International Journal of Advanced Culture Technology
/
v.12
no.2
/
pp.221-226
/
2024
This study used text mining, a big data analysis technique, to explore XR trends in South Korea. For this research, I utilized a big data platform called BigKinds. I collected data focusing on the keyword 'XR', spanning approximately 14 years from 2010 to 2024. The gathered data underwent a cleansing process and was analyzed in three ways: keyword trend analysis, relational analysis, and word cloud. The analysis identified the emergence and most active discussion periods of XR, with XR devices and manufacturers emerging as key keywords.
The price relationship between the futures market and the underlying spot market has attracted the attention of academics, practitioners, and regulators due to their roles during periods of turbulence in financial markets. The purpose of this paper is to investigate the dynamic of price relationship(or lead-lag relationship) between Korean Treasury Bond futures market and spot market. To examine the nature of the price relationship, descriptive statistics, serial correlation, and cross-correlation are used as a preliminary statistics in the Korean Treasury Bond spot and futures market. Next, following Stoll-Whaley(1990) and Chan(1992), the multiple regression method is used to examine the lead-lag patterns between the two markets. The empirical results are summarized as follows. The mean returns of spot markets and future markets are positive(+) and negative(-) respectively and the standard deviation of both stock and futures returns increase through the sub-periods. For the most periods, there is negative skewness in the both markets. The zero excess kurtosis due to the heavy tails of the distribution are relatively large. The autocorrelations in the spot returns for the sample periods are positive in time lag 1, but the autocorrelations in the future returns shows no significant evidence. The results of the daily cross-correlations between the KTB spot and futures returns indicate that a lead-lag relationship don't exist for price changes of futures and spot markets as a preliminary analysis. Finally, empirical results of regression analysis for both market indicate that there is no evidence that the KTB futures lead the KTB spot market, or the KTB spot market lead the KTB futures market. These results are robust for all sub-periods.
The concentrations of gaseous mercury (Hg) determined between two different time periods of the late 1980s and the late 1990s were compared to account for the effects of changes between source/sink relationships of atmospheric Hg in an urban area. The Hg concentration levels were different remarkably between the two time periods due possibly to changes in source/sink relationships. The results showed that the Hg levels in the former period were measured to be 14.4${\pm}$9.56ngm$^{-3}$ (N = 2714), whereas those of the latter period were characterized by approximately three-fold decreased values of 5.34${\pm}$3.92 ngm$^{-3}$ (N=2576). Using two independent measurement data sets, we examined the patterns of Hg distribution at different time scales. When analyzed over 24 hour scale, these data sets exhibited two distinctive distribution patterns. The former period showed enhanced concentration levels during daytime, while the latter period showed relative depletion during daytime. The patterns of the two data sets were also examined over seasonal scale. The results of two different time periods consistently showed the occurrences of maximum seasonal values during winter. The former period was characterized by seasonal patterns of fuel consumption with excessive Hg levels during winter. Conversely, no distinctive trend was apparent for the latter period with slight changes in concentration levels across seasons. In order to analyze the factors affecting Hg distributions between two different periods, we conducted both correlation and factor analysis on both all data sets and on seasonally divided data groups. The results of these analyses consistently indicate that the Hg concentration levels for two different time periods are regulated by distinctive source processes that are characteristic of each period.
Using a method suggested by Yanovskaya, we obtained Rayleigh wave group velocities with a resolution of $1.0^{\circ}{\times}1.0^{\circ}$ in a period range between 10 and 80 s in and around the Korean peninsula. Both regional and distant earthquake data sets were used together in analysis of group velocities. The resolution of the group velocity maps has been remarkably enhanced by the method, especially in the sparse/non-station region in the northern Korean peninsula. Some qualitative geophysical information was inferred from the group velocity maps. In the East Sea, the slow group velocities at periods longer than 40 s suggest the existence of an oceanic lithosphere at depths of 50-70 km, assuming 4 km/s of S wave velocity at a period of 40 s. On the other hand, a thick lithosphere can be inferred in the continental area from the fast group velocities at periods longer than 50 s. For most periods, the group velocities change rapidly over a short distance of about 200 km across the eastern coast of Korean peninsula, which may suggest a rapid change in the thickness of lithosphere in this area.
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