• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.25-38
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• 2021

The aim of this study is to protect workers and pedestrians from accidents at night or bad weather by attaching optical fiber to existing safety clothing that is made only with fluorescent fabrics and retroreflective materials. A safety vest was designed and manufactured by applying optical fiber, and energy-harvesting technology was developed. The safety vest was designed to emit light using the automatic flashing of optical fibers attached to the film, and an energy harvester was manufactured and attached to drive the light emission of the optical fiber more continuously. As a result, first, the vest wearer' body was recognized from a distance through the optical fiber and retroreflection, which helped prevent accidents. Thus, this concept helps in saving lives by preventing accidents during night-time work on the roadside or activities of rescue crew and sports activities, or by quickly finding the point of an accident with a signal that changes the optical fiber light emission. Second, to use the wasted energy, a piezoelectric-element power generation system was developed and the piezoelectric-harvesting device was mounted. Potentially, energy was efficiently produced by activating the effective charging amount of the battery part and charging it auxiliary. In the existing safety vest, detecting the person wearing the vest is almost impossible in the absence of ambient light. However, in this study, the wearer could be found within 100 m by the light emission from the safety vest even with no ambient light. Therefore, in this study, we will help in preventing and reducing accidents by developing smart safety clothing using optical fiber and energy harvester attached to save lives.

• 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.

• Journal of Oral Medicine and Pain
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• v.32 no.2
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• pp.157-175
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• 2007

This study was conducted through an interview process in which questionnaires were administered to 293 people. The questionnaires related to the behaviors of oral hygiene care, and disease history related to halitosis, and status of halitosis, halitosis measurement, oral examination, and caries activity tests such as the snyder test, Salivary flow rate test, and Salivary buffering capacity test. Our sample was taken from 293 rural residents within the period from 4th to 21st of January 2006. This was done in order to provide basic data to prepare both policies of halitosis prevention and a device to efficiently measure halitosis status and investigate the factors related therein. The major findings of this study results are as follows: 1. As for frequency of tooth brushing, twice a day occupied the greatest portion at 46.1 % Women exceeded men in frequency of tooth brushing. Tongue brushing everyday produced a 25.6 % result among subjects and The use of auxiliary oral hygiene devices occupied 9.2 %. 2. As for degree of usual self-awareness of halitosis: 62.5 %. This result also demonstrate that the severest time of self-awareness in regards to halitosis is wake up time in the morning. The time period produced the highest portion of 72.7 % in times of self-awareness. In terms of the area in which halitosis was observed, gum resulted in 23.0 %. As for types of halitosis, fetid smell was the most frequent at 37.2 %. 3. As for the result of halitosis measurement, values of OG less than 50 ppm occupied 54.3 % and $50{\sim}100ppm$ occupied 41.6 %. As for $NH_3$ values, $20{\sim}60ppm$ showed the highest value range of 52.6 %. 4. As for OG per disease history related to halitosis, values of OG were significantly high in the ranges of $50{\sim}100ppm$ within family history groups of food impaction by dental caries, diabetes mellitus and halitosis. As for values of $NH_3$, there showed a significant difference in respiratory system disease groups. 5 Value range of OG per ordinary halitosis self-awareness degree: values ranging less than 50 ppm were recorded at 55.9 % from the group realizing not aware of smell. 57.5 % from groups only realizing sometimes, while values range of $50{\sim}100ppm$ were recorded at 52.0 % from groups always aware of smell. 63.6 % from groups always strongly aware of smell. Meanwhile as for the values ranges of $NH_3$, $20{\sim}60ppm$. they occupied high portions for all groups of exams. 6. Values of OG per oral examination: the more pulp-exposed teeth and food impaction and the higher the tongue plaque index, values of OG increased within the range of $50{\sim}100ppm$. As for values of $NH_3$, the more prosthetic teeth and the higher the tongue plaque index, this value increased significantly, and the values increased up to no less than 60 ppm for groups of mandibular partial denture. 7. Within the realm of caries activity test: as for the Snyder test, high activity was highest by 43.0 % wherewith the higher the activity of acidogenic bacteria the higher the OG values. As for the salivary flow rate test, the number of cases below 8.0 ml showed the highest tendency by 62.5 %. The larger the salivary flow rate the more decreased OG values distribution. As for the salivary buffering capacity test, $6{\sim}10$ drops of 0.1N lactic acid showed the overwhelming trend by 58.7 % whereby the higher the salivary buffering capacity the greater distribution occupancy ratio of OG values below 50 ppm which is scentless to on ordinary person. 8. As for the correlation between oral environment and halitosis, OG showed the positive correlation with pulp exposed teeth, filled teeth, present teeth, tongue plaque index, and food impaction, while the negative correlation with salivary flow rate and prosthetic teeth. $NH_3$ showed a positive correlation with prosthetic teeth and frequency of tooth brushing, while decayed teeth was negative correlation. 9. As for the multiple regression analysis result, there have been selected female, pulp exposed teeth, prosthetic teeth, food impaction, salivary flow rate, tongue plaque index and severe activities in the Snyder test as factors affecting OG wherein explanatory power on it was 45.1 %. There have been selected females, pulp exposed teeth, tongue plaque index, and prosthetic teeth as factors affecting on $NH_3$ wherein explanatory power on it was 6.6 %. With the aforementioned results in mind, the status of halitosis among rural residents is considered to bare a close relation with oral environments and other factors related to halitosis such as the Snyder test from caries activity test, and salivary flow rate test. For the prevention of halitosis of residents in rural areas, we have to focus on correct tooth brushing methods and tongue brushing, with using auxiliary oral hygiene devices to remove fur of tongue plaque and food impaction. Also, when the cause and ingredients of halitosis are diverse and complex, in order to analyze exactly the factors of individual halitosis development, we need continuous and systematic study in order to provide rural residents with programs of oral hygiene education and encourage the use of dental hygienists in public health centers.