• Journal of the Korean Institute of Landscape Architecture
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• 제39권6호
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• pp.67-75
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• 2011

This study was carried out to investigate the changes in citizen satisfaction with parks and green spaces in Daegu. Three surveys were conducted using the same measurement tools in 1986, 2001, and 2010. Major results are as follows: 1. The overall satisfaction level with parks and green spaces increased remarkably over the last25years. Satisfaction levels with city spaces overall were higher than that of nearby surrounding areas. 2. Diversity of green spaces was the most distinguished indicator in increasing level of satisfaction while the management level of green space facilities showed the lowest improvement. 3. The factor analysis for individual variables for satisfaction resulted in two factors: functions and physical conditions were categorized as one factor, and indicators for the planning of green spaces were the other. Using a regression model, the major variables found for satisfaction were diversity, management level of woods, quantitative level, function of static recreation, and management level of facilities, respectively. 4. Regarding satisfaction level by the type of green spaces, green spaces by streets showed a remarkable increase while green spaces in industrial areas showed the lowest improvement. A factor analysis for each type of green space resulted in 3 factors: green spaces of urban parks, green spaces of urban recreational facilities, and green spaces of each district including residential areas and industrial areas.

• Journal of the Korea Concrete Institute
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• 제18권3호
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• pp.389-395
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• 2006

For the assessment of exsiting concrete structures, it is important to get the real strength of concrete. The load test or core test has many problems due to cost time, easiness, structural damage, and reliability and so on. Thus, various non-destructive test and statistical analysis techniques for strength assessment have been developed. As a result the real strength of concrete can be obtained by both direct and indirect test. In this study, a series of experimental tests of core strength and Schmidt hammer tests on 3, 7, 14, 28, 90, 180, 365, and 730 days' were done for predicting the compressive strength of high strength concrete with 65.0MPa of 28-days' strength. Each experimental results was analyzed by simple regression analysis. Then, reliability level and error rate between the proposed equations and the existing ones was examined. However, the application of the exsisting equations was inadequate to high strength concrete, because they were conducted under normal strength concrete. Therefore, the following compressive strength equations were proposed for predicting the compressive strength of high strength concrete by Schmidt hammer test. The proposed equations by Schmidt hammer test are as follows.

• Journal of Distribution Science
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• 제13권5호
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• pp.53-60
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• 2015

Purpose - The purpose of this paper is to shed light on the importance of the slope and curvature of the volatility curve implied in option prices in the KOSPI 200 options index. A number of studies examine the implied volatility curve, however, these usually focus on cross-sectional characteristics such as the volatility smile. Contrary to previous studies, we focus on time-series characteristics; we investigate correlation dynamics among slope, curvature, and level of the implied volatility curve to capture market information embodied therein. Our study may provide useful implications for investors to utilize current market expectations in managing portfolios dynamically and efficiently. Research design, data, and methodology - For our empirical purpose, we gathered daily KOSPI200 index option prices executed at 2:50 pm in the Korean Exchange distribution market during the period of January 2, 2004 and January 31, 2012. In order to measure slope and curvature of the volatility curve, we use approximated delta distance; the slope is defined as the difference of implied volatilities between 15 delta call options and 15 delta put options; the curvature is defined as the difference between out-of-the-money (OTM) options and at-the-money (ATM) options. We use generalized method of moments (GMM) and the seemingly unrelated regression (SUR) method to verify correlations among level, slope, and curvature of the implied volatility curve with statistical support. Results - We find that slope as well as curvature is positively correlated with volatility level, implying that put option prices increase in a downward market. Further, we find that curvature and slope are positively correlated; however, the relation is weakened at deep moneyness. The results lead us to examine whether slope decreases monotonically as the delta increases, and it is verified with statistical significance that the deeper the moneyness, the lower the slope. It enables us to infer that when volatility surges above a certain level due to any tail risk, investors would rather take long positions in OTM call options, expecting market recovery in the near future. Conclusions - Our results are the evidence of the investor's increasing hedging demand for put options when downside market risks are expected. Adding to this, the slope and curvature of the volatility curve may provide important information regarding the timing of market recovery from a nosedive. For financial product distributors, using the dynamic relation among the three key indicators of the implied volatility curve might be helpful in enhancing profit and gaining trust and loyalty. However, it should be noted that our implications are limited since we do not provide rigorous evidence for the predictability power of volatility curves. Meaning, we need to verify whether the slope and curvature of the volatility curve have statistical significance in predicting the market trough. As one of the verifications, for instance, the performance of trading strategy based on information of slope and curvature could be tested. We reserve this for the future research.

• Korean Journal of Remote Sensing
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• 제36권6_1호
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of Navigation and Port Research
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• 제48권1호
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• pp.34-48
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• 2024

As global supply chain risks proliferate unpredictably, the high interdependence of port and logistics industry intensifies the risk burden. This study conducted fundamental research to explore diverse safety issues in domestic ports. Utilizing news article data about Busan Port, we employed LDA topic modeling and time-series linear regression to understand key safety trends. Over the past 30 years, Busan Port faced nine major safety issues-maritime safety, import cargo inspection, labor strikes, and natural disasters emerged cyclically. Major port safety issues in Busan Port are primarily characterized by an unpredictable nature, falling under socio-environmental and natural phenomena types, indicating a significant impact of global uncertainty. Therefore, systematic policies need to be formulated based on identified port safety issues to enhance port safety in Busan Port. Additionally, there is a need to strengthen the resilience of port safety for unpredictable risk situations. In conclusion, advanced research activities are necessary to promote port safety enhancement in response to dynamically changing social conditions.

• The Journal of the Convergence on Culture Technology
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• 제10권1호
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• pp.183-192
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• 2024

The purpose of this study is to empirically analyze the determining factors (economy, security, domestic politics, administration, and international politics) that affect the ROK-US defense cost sharing decision. Through this, we will gain a deeper understanding of the defense cost sharing decision process and improve the efficiency of defense cost sharing calculation and execution. The scope of the study is ROK-US defense cost sharing from 1991 to 2021. The data used in the empirical analysis were various secondary data such as Ministry of National Defense, government statistical data, SIPRI, and media reports. As an empirical analysis method, multiple regression analysis using time series was used and the data was analyzed using an autoregressive model. As a result of empirical research through multiple regression analysis, we derived the following results. It was analyzed that the size of Korea's economy, that is, GDP, the previous year's defense cost share, and the number of U.S. troops stationed in Korea had a positive influence on the decision on defense cost sharing. This indicates that Korea's economic growth is a major factor influencing the increase in defense cost sharing, and that the gradual increase in the budget and the negotiation method of the Special Agreement (SMA) for cost sharing of stationing US troops in Korea play an important role. On the other hand, the political tendencies of the ruling party, North Korea's military threats, and China's defense budget were found to have no statistically significant influence on the decision to share defense costs.

• Journal of Intelligence and Information Systems
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• 제18권3호
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Digital Convergence
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• 제15권11호
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• pp.567-579
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• 2017

The purpose of this study was conducted to clarify physical activity university students on time perspective in leisure constraints and leisure flow. To achieve this purpose, subjects of this study were sampled 295 Physical Activity University Students participant using purposeful sampling method for 2 months from May to June of 2017. Using questionnaires stratified cluster random sampling in university students in D city and C city. The analysis method was used t-test, one-way ANOVA, multiple regression analysis, correlation analysis methods in order to solve problems of the study. According to the study Result, First, studies show that female have high levels of leisure constraints than males. Males have higher levels of leisure flow than females. The first grader show high level of individual constraints and past negation were also high. In the series of majors, natural affiliates and humanities are high in the past negation, present destiny, the service major currently high in pleasure and of leisure, autotelic experience of leisure flow. In the rhythmic type of Activity type, the past negation, present destiny and leisure constraints are highly likely to be higher. In the competitive have shown that is high. Second, leisure constraints on students' participation in physical activities have been found to have negative influence on their students. Third, leisure flow have shown that they have a positive effect on past affirmation and present pleasure.

• Journal of Korea Water Resources Association
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• 제45권11호
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• pp.1157-1168
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• 2012

In this study, we assess changes in water quality trends over time based on certain control measurements in order to identify and analyze the cause of the trend in water quality. The current water pollution in the Nakdong River was analyzed, as it suggests that the significant changes in water quality have occurred in between 2006 and 2010. Based on monthly average data, we have examined for trends of the Nakdong River watershed in water temperature, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP). Moreover, we have investigated seasonal variation of water quality of sites within the Nakdong River Basin by implementing further analyses such as, Correlation Coefficient, Regression Analysis, Hierarchical Clustering Method, and Time Series Analysis on SPSS. Geology and topography of the watershed, controlled by various conditions such as, climate, vegetation, topography, soil, and rain medium, have been affected by the non-homogeneity. Our study suggests that such variables could possibly cause eutrophication problems in the river. One possible way to overcome this particular problem is to lay up a ship on the river by increasing the nasal flow measurement of the Nakdong River during rainy season. Moreover, the water management requires arranging the measurement of the flow in order to secure the river while the numerous construction projects need to be continuously observed. However, the water is not flowing tributary of the reason for the timing to be flowing in a natural state of river water and industrial water intake because agriculture. Therefore, ongoing research is needed in addition to configuration of all observations.

• Journal of the Korean Society for Marine Environment & Energy
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• 제13권4호
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• pp.279-287
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• 2010

To identify characteristics of the water quality at Goseong bay, we analyzed long term monitoring data collected at surface and bottom water which was accumulated during the period of 1987~2009. The result showed that the waters of Goseong bay represented mesotrophic level that is based on chlorophyll-a, DIP and DIN and seasonal average of COD that indicates level by the COD criteria. This analysis can be translated that the waters is comparatively clean even though the waters is in the closed bay that slowly diffuses influx mass. We also did the time series analysis, correlation analysis and regression analysis on the moving average of the water parameter at Goseong bay. According to the results, DIP showed a increasing trend as time passed while DIN was on a decreasing trend under the same condition. In the waters of Goseong bay, the phyto-plankton growth was shown to be limited by DIN concentration. The chlrophyll-a was at the peak in August, at $4.60{\mu}g/L$. As the seasonal average and index were the highest in November, it was understood that the balance of nutrient at Goseong bay was dependent more on inner factors, ie, mass farming of aquatic species and release of bottom sediment rather than on inflow of fresh water. Accordingly, it is needed to consider the balance of nutrient like DIP and DIN to manage the water quality or estuaries at Goseong bay.