• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.4
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• pp.177-190
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• 2016

In case of the seabed around and under gravity structures such as submerged breakwater is exposed to a large wave action long period, the excess pore pressure will be generated significantly due to pore volume change associated with rearrangement soil grains. This effect will lead a seabed liquefaction around and under structures as a result from decrease in the effective stress. Under the seabed liquefaction occurred and developed, the possibility of structure failure will be increased eventually. Lee et al.(2016) studied for regular waves, and this study considered for irregular waves with the same numerical analysis method used for regular waves. Under the condition of the irregular wave field, the time and spatial series of the deformation of submerged breakwater, the pore water pressure (oscillatory and residual components) and pore water pressure ratio in the seabed were estimated and their results were compared with those of the regular wave field to evaluate the liquefaction potential on the seabed quantitatively. Although present results are based on a limited number of numerical simulations, one of the study's most important findings is that a more safe design can be obtainable when analyzing case with a regular wave condition corresponding to a significant wave of irregular wave.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.341-351
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• 2008

Since the damage from the torrential rain increases recently due to climate change and global warming, the significance of flood forecasting and warning becomes important in medium and small streams as well as large river. Through the preprocess and main processes for estimating runoff, diverse errors occur and are accumulated, so that the outcome contains the errors in the existing flood forecasting and warning method. And estimating the parameters needed for runoff models requires a lot of data and the processes contain various uncertainty. In order to overcome the difficulties of the existing flood forecasting and warning system and the uncertainty problem, ANFIS(Adaptive Neuro-Fuzzy Inference System) technique has been presented in this study. ANFIS, a data driven model using the fuzzy inference theory with neural network, can forecast stream level only by using the precipitation and stream level data in catchment without using a lot of physical data that are necessary in existing physical model. Time series data for precipitation and stream level are used as input, and stream levels for t+1, t+2, and t+3 are forecasted with this model. The applicability and the appropriateness of the model is examined by actual rainfall and stream level data from 2003 to 2005 in the Tancheon catchment area. The results of applying ANFIS to the Tancheon catchment area for the actual data show that the stream level can be simulated without large error.

• Journal of the Korean GEO-environmental Society
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• v.11 no.6
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• pp.5-20
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• 2010

One-dimensional equivalent linear site response analysis is widely used in practice due to its simplicity, requiring only few input parameters, and low computational cost. The main limitation of the procedure is that it is essentially a linear method, in which the time dependent change in the soil properties cannot be modeled and constant values of shear modulus and damping is used throughout the duration of the analysis. Various forms of modified equivalent linear analyses have been developed to enhance the accuracy of the equivalent linear method by incorporating the dependence of the shear strain with the loading frequency. The methods are identical in that it uses the shear strain Fourier spectrum as the backbone of the analysis, but differ in the method in which the strain Fourier spectrum is smoothed. This study used two domestically measured soil profiles to perform a series of nonlinear, equivalent linear, and modified equivalent linear site response analyses to verify the accuracy of two modified procedures. The results of the analyses indicate that the modified equivalent linear analysis can highly overestimate the amplification of the high frequency components of the ground motion. The degree of overestimation is dependent on the characteristics of the input ground motion. Use of a motion rich in high frequency contents can result in unrealistic response.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.7
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• pp.898-905
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• 2019

As the positive feedback between the absorption of chromophoric dissolved organic matter (CDOM) and acceleration of ice melt can impact the aquatic biota and dynamic heat budget, long-term monitoring of the CDOM variation in the polar ocean is necessary. However, the monitoring of CDOM is not easy because of harsh weather and difficult access, especially in the Antarctic Ocean. Therefore, the purpose of this study was to find a suitable long-term monitoring site for CDOM variation; we selected Maxwell Bay and Marian Cove at Sejong Base and horizontal and vertical distributions of CDOM were measured. After a 72 hr time-series measurement test of the CDOM variation at Sejong Dock and Sejong Cape in Maxwell Bay, Sejong Dock was selected, as it does not haveland discharge effects. The seasonal variation of CDOM was evident and the average CDOM concentration of Maxwell Bay was comparable with the adjacent sea. The CDOM at Sejong Dock from February to November 2010 was the highest in the fall and winter and the lowest during spring and summer. Thus, based on our one-year CDOM data, we suggest that Sejong Dock in Maxwell Bay is suitable for long-term monitoring of CDOM as an indicator of photochemical and biological environmental change and an important factor in determining the heating budget in the Antarctic Ocean.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.197-205
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• 2020

Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

• Journal of the Korean association of regional geographers
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• v.21 no.1
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• pp.98-113
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• 2015

In this study, spatial and temporal patterns and changes in seasonal multi-day cumulative extreme precipitation events defined by maximum 1~5 days cumulative extreme precipitation observed at 61 weather stations in the Republic of Korea for the recent 40 years(1973~2012) are examined. It is demonstrated that the magnitude of multi-day cumulative extreme precipitation events is greatest in summer, while their sensitivity relative to the variations of seasonal total precipitation is greatest in fall. According to analyses of linear trends in the time series data, the most noticeable increases in the magnitude of multi-day cumulative extreme precipitation events are observable in summer with coherences amongst 1~5 days cumulative extreme precipitation events. In particular, the regions with significant increases include Gyeonggi province, western Gangwon province and Chungcheong province, and as the period for the accumulation of extreme precipitation increases from 1 day to 5 days, the regions with significantly-increasing trends are extended to the Sobaek mountain ridge. It is notable that at several scattered stations, the increases of 1~2 days cumulative extreme precipitation events are observed even in winter. It is also observed that most distinct increasing tendency of the ratio of these multi-day cumulative extreme precipitation to seasonal total precipitation appears in winter. These results indicate that proactive actions are needed for spatial and temporal changes in not only summer but also other seasonal multi-day cumulative extreme precipitation events in Korea.

• Journal of the Korean association of regional geographers
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• v.22 no.4
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• pp.792-808
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• 2016

Due to the high importance of foreign trade in the national economy, Korea has a lot of ports designated as trade ports compared to the small land size. However, because of the poor utilization results, some small trade ports have been criticized for wasteful financing due to redundant investment in SOC. This is because the characteristics and comparative advantage of foreign trade in trade ports have not been analyzed in detail by region. Therefore, this study analyzes the patterns and types of change in the size of trade, number of cargo items handled, and the number of trade target countries in the past 20 years for 19 domestic small trade ports using the time-series cluster analysis technique. As a result of analysis, Korean small trade ports were classified into five growth pattern types according to the analysis index, and characteristics and implications for each type could be derived. Today, as the foreign trade environment changes drastically and the importance of balanced regional development is emphasized, it is very important to study the growth types and implications of small trade ports and the results of this study are expected to provide meaningful implications for regional port development and operation in the future.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.245-249
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• 2013

This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.101-113
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• 2021

This paper inquires the macro-economic factors that may affect the corporate venture capital (CVC) from an industrial organization theory perspective. Unlike existing studies focusing CVC investments related to parent corporates' strategic intention, we identified CVC firm as an independent financial investor affected by macro environment and industrial structure. Specifically, we empirically investigate whether and how industry's boom, exogenous crisis, economic growth, and competition intensity affect the CVC investment for a data set of investment in the U.S. based corporate venture capital industry, 1996-2017. The empirical data analyzed in the study contained a total of 84 U.S. based CVC firms and their 2,306 investments from 1996 until 2017. After conducting a time-series negative binomial analysis, our empirical analyses suggest that the CVC investments are affected negatively by exogenous crisis and competition intensity, and positively by industrial boom and economic growth. we found the significance and direction of our independent variables strongly supported all of our four hypotheses in a highly robust manner. The results of this study are expected to contribute the literatures of corporate venture capital and venture investment by illustrating which macro-economic and industrial structure factors affect CVC investment decision to adapt to dynamic environmental change beside strategic intention of CVC firm's parent corporates.