• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1797-1807
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• 2013

Dams always have the possibility of failure due to unexpected natural phenomena. In particular, dam failure can cause huge damage including damage for humans and properties when dam downstream regions are densely populated or have important national facilities. Although many studies have been conducted on the analysis of flood waves about single dam failure thus far, studies on the analysis of flood waves about the sequential failure of dams are lacking. Therefore, the purpose of this study was to calculate the peak discharge of sequential failure of dams through flood wave analysis of sequential failure of dams and this analysis techniques to predict flood wave propagation situation in downstream regions. To this end, failure flood wave analysis were conducted for Lawn Lake Dam which is a case of sequential failure of dams among actual failure cases using DAMBRK to test the suitability of the dam failure flood wave analysis model. Based on the results, flood wave analysis of sequential failure of dams were conducted for A dam in Korea assuming a virtual extreme flood to predict flood wave propagation situations and 2-dimensional flood wave analysis were conducted for major flooding points. Then, the 1, 2-dimensional flood wave analysis were compared and analyzed. The results showed goodness-of-fit values exceeding 90% and thus the accuracy of the 1-dimensional sequential failure of dams simulation could be identified. The results of this study are considered to be able to contribute to the provision of basic data for the establishment of disaster prevention measures for rivers related to sequential failure of dams.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.151-157
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• 2020

This study is to find out the effectiveness by Infant CPR method of a single rescuer. It was conducted for 51 general public. And typical infant CPR method by a single rescuer and a new method, CPR with two thumb chest compressions wrapped in both hands over the head were compared. SPSS 22.0 was used as an analysis method and to compare the both CPR methods, Paired t-test was used. As a result of the study, the average chest compression depth(39.38±1.07 mm) by CPR with two thumb chest compressions wrapped in both hands over the head was significantly high(p<0.001). Ease of mouth-to-mouth resuscitation(p<0.001), convenience of CPR method(p<0.001), and finger pain level(p<0.001) had a significant difference. As for the preference of the CPR method, 80.4%(41 people) preferred CPR with two thumb chest compressions wrapped in both hands over the head. In this study, CPR with two thumb chest compressions wrapped in both hands over the head showed more effective results than typical CPR method. However, as a virtual study using mannequins, further research is needed to apply high-quality CPR methods to field.

• The Journal of Korean Academy of Prosthodontics
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• v.54 no.1
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• pp.1-7
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• 2016

Purpose: The aim of this study was to evaluate the effect of increased vertical dimension of occlusion on lower facial changes by facial type. Materials and methods: Lateral cephalograms from 261 patients were obtained and classified by sagittal (Class I, II, and III) and vertical (hypodivergent, normodivergent, and hyperdivergent) facial patterns. Retrusive displacement of soft tissue Pogonion and downward displacement of soft tissue Menton were measured in each group after 2 mm of vertical dimension of occlusion was increased at the lower central incisor using a virtual simulation program. The ratio of both displacements was calculated in all groups. The statistical analysis was done by 2-way ANOVA and Post hoc was done by Tukey test (5% level of significance). Results: Retrusive displacement of soft tissue Pogonion in Class III group was statistically different compared to Class I and II, and in vertical facial groups all 3 groups were significantly different (P<.05). Downward displacement of soft tissue Menton showed statistically significant difference between all sagittal groups and vertical groups (P<.05). The ratio of both displacements showed statistically significant difference in all sagittal groups and vertical groups (P<.05), and Class II hyperdivergent group had the highest value. Conclusion: Lower facial change was statically significant according to the facial type when vertical dimension of occlusion increased. Class II hyperdivergent facial type showed the highest ratio after increase in vertical dimension of occlusion.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.