• The Journal of Engineering Geology
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• v.33 no.1
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• pp.85-103
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• 2023

The in-situ remediation of a solidified stratum containing a large amount of fine-texture material like clay or organic matter in contaminated soil faces limitations such as increased remediation cost resulting from decreased purification efficiency. Even if the soil conditions are good, remediation generally requires a long time to complete because of non-uniform soil properties and low permeability. This study assessed the remediation effect and evaluated the field applicability of a methodology that combines pneumatic fracturing, vacuum extraction, and plasma blasting (the PPV method) to improve the limitations facing existing underground remediation methods. For comparison, underground remediation was performed over 80 days using the experimental PPV method and chemical oxidation (the control method). The control group showed no decrease in the degree of contamination due to the poor delivery of the soil remediation agent, whereas the PPV method clearly reduced the degree of contamination during the remediation period. Remediation effect, as assessed by the reduction of the highest TPH (Total Petroleum Hydrocarbons) concentration by distance from the injection well, was uncleared in the control group, whereas the PPV method showed a remediation effect of 62.6% within a 1 m radius of the injection well radius, 90.1% within 1.1~2.0 m, and 92.1% within 2.1~3.0 m. When evaluating the remediation efficiency by considering the average rate of TPH concentration reduction by distance from the injection well, the control group was not clear; in contrast, the PPV method showed 53.6% remediation effect within 1 m of the injection well, 82.4% within 1.1~2.0 m, and 68.7% within 2.1~3.0 m. Both ways of considering purification efficiency (based on changes in TPH maximum and average contamination concentration) found the PPV method to increase the remediation effect by 149.0~184.8% compared with the control group; its average increase in remediation effect was ~167%. The time taken to reduce contamination by 80% of the initial concentration was evaluated by deriving a correlation equation through analysis of the TPH concentration: the PPV method could reduce the purification time by 184.4% compared with chemical oxidation. However, the present evaluation of a single site cannot be equally applied to all strata, so additional research is necessary to explore more clearly the proposed method's effect.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.131-148
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• 2023

The purpose of this study is to investigate the effects of entrepreneurial environment and entrepreneurial competency on entrepreneurial intention by setting degree of self-determination as a moderating variable for pre-entrepreneur of agriculture industry. The entrepreneurial environment was divided into perceived support and perceived barriers, and the sub-variables of entrepreneurial competence were set as creativity, problem solving, communication, marketing, and business plan. 253 questionnaires were used for empirical analysis. The results of the analysis using SPSS v25.0 and Process macro v4.2 are as follows. First, the perceived support and perceived barriers of the entrepreneurial environment have a significant effect on entrepreneurial intention. Creativity, problem solving, marketing and business plan of entrepreneurial competency have a significant effect on entrepreneurial intention, but the effect of communication was non-significant. Second, the degree of self-determination did not moderate the relationship between perceived support, barriers and entrepreneurial intention. This means that the level of self-determination may not have a significant effect on the relationship between entrepreneurial environment and entrepreneurial intention. Third, the degree of self-determination was found to moderate the relationship between creativity, problem solving, communication, marketing and business plan of entrepreneurial competency and entrepreneurial intention. Specifically, as the degree of self-determination increases, the size of the influence of creativity, problem solving, marketing, and business plan on entrepreneurial intention plays a role of strengthening in a positive direction. On the other hand, as the degree of self-determination increases, the degree of self-determination, which weakens the relationship between communication and entrepreneurial intention. Future research will require exploration of other factors that can explain entrepreneurial environment and entrepreneurial capacity, and follow-up studies are needed to analyze the moderated mediating effects through conditional process models that include new mediating and moderating variables.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.