• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.85-93
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• 2021

The seventy percentage of Korean Peninsular is covered by the mountainous area, and the depth of west sea and south sea is relatively shallow. Therefore, a large scale land reclamation from the sea has been implemented for the construction of industrial complex, residental area, and port and airport facilities. The common problem of reclaimed land is consisted of soft ground, and hence it has low load bearing capacity as well as excessive settlement upon loading on the ground surface. The hollow concrete block has been used to reinforce the loose and soft foundation soil where the medium-high apartment or one-story industrial building is being planned to be built. Recently the earthquakes with the magnitude of 4.0~5.0 have been occurred in the west coastal and southeast coastal areas. Lee (2019) reported the advantages of hollow concrete block reinforced shallow foundation through the static laboratory bearing capacity tests. In this study, the dynamic behavior of hollow concrete block reinforced sandy ground with filling the crushed stone in the hollow space has been investigated by the means of shaking table test with the size of shaking table 1000 mm × 1000 mm. Three types of seismic wave, that is, Ofunato, Hachinohe, Artificial, and two different accelerations (0.154 g, 0.22 g) were applied in the shaking table tests. The horizontal displacement of structure which is situated right above the hollow concrete block reinforced ground was measured by using the LVDT. The relative density of soil ground are varied with 45%, 65%, and 85%, respectively, to investigate the effectiveness of reinforcement by hollow block and measured the magnitude of lateral movement, and compared with the limit value of 0.015h (Building Earthquake Code, 2019). Based on the results of shaking table test for hollow concrete block reinforced sandy ground, honeycell type hollow block gives a large interlocking force due to the filling of crushed stone in the hollow space as well as a great interface friction force by the confining pressure and punching resistance along the inside and outside of hollow concrete block. All these factors are contributed to reduce the great amount of horizontal displacement during the shaking table test. Finally, hollow concrete block reinforced sandy ground for shallow foundation is provided an outstanding reinforced method for medium-high building irrespective of seismic wave and moderate accelerations.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.