• 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 the Korean Data and Information Science Society
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• v.14 no.4
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• pp.845-852
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• 2003

Forecasting exchange rate movements is a challenging task since exchange rates impact world economy and determine value of international investments. In particular, Korean-U.S. exchange rate behavior is very important because of strong Korean and U.S. trading relationship. Neural networks models have been used for short-term prediction of exchange rate movements. Least squares support vector machine (LS-SVM) is used widely in real-world regression tasks. This paper describes the use of LS-SVM for short-term and long-term prediction of Korean-U.S. exchange rate.

• Journal of the Korean Society of Costume
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• v.21
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• pp.19-30
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• 1993

There are record that ancient Korean WOOl fabrics male from sheep, camel, rabbit. bear, horse. calile, raccoon dog, fox and so on. Wool fiber fabriher were also reported Kye, Gal, China, Tap Dung, Kuyu anul ram. These wool fabrics wre named amongling to their fineness and weaving method in the fabric. Technology of wool fabric weaving was developed and from Sam Kuk dynasties to to Koryo Dynasty wool fabrics were reported to weave and trade to China, Japan and Arabia. These fabrics were mainly used as clothes, rugs or blankets. In Koryo Dynasty, especially Kye Kurn was used for trading goods to China. There is another record that two thousand sheep, camels offord Koryo by Yo and Kum Dynasty. In this study, the characteristics of Korean wool fabrics will be disscussed from the literature survey of the relevant references.

• Physical Therapy Korea
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• v.9 no.1
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• pp.53-61
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• 2002

The purpose of this study was to compare the body alignment during standing on level and wedge board. Twenty healthy college students (8 females, 12 males) were evaluated in this study. Diagnostic contourline potographic imaging system (Model JTC-1, Jodang Trading Co.) was used to measure body alignment. Sagittal and frontal plane images were used to analyze the body alignment. The result showed that the cervical and lumbar lordotic curve significantly decreased during standing on wedge board when compared with standing on level. On the other hand, thoracic kyphosis significantly increased during standing on wedge board. There was no significant difference in body alignment according to gender, weight, and height. Clinically, patients with low back pain and severe lordosis may be affected by heel wedge. Further study is needed to identify whether the standing on wedge board can change the body alignment in patients with low back pain and spinal deformity.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.249-250
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• 2016

Korean government has announced declared prices of apartment reflecting market condition each year. Therefore, on that basis, apartment owners have used as basic data trading apartments and the government has been used to calculate the tax. However, the sales prices and declared prices of apartment has occurred difference depending on the region and the brand. This study has analyzed and compared regional differences in sales price of apartments. The results of this study, we have known that sales price of apartments was a big difference depending on the region and the gross area. Especially, Seoul and Gyeonggi Province are the highest. And sales price of Southeast and urban area are the highest in Seoul. In the future, it is necessary that gap analysis between sales price and declared prices of apartment. And It is needed to develop apartment index considering the region and the gross area.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.65-71
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• 2019

IAs smart device penetration rate is more than 90%, mobile transaction ratio using smart device is increasing. Smart contracts are used in various areas of real life including smart trading. By applying smart contracts to the platform for smart transactions through block-chain technology, the threat of hacking or forgery can be reduced. However, various threats to devices in smart transactions can pose a threat to the use of block chain Etherium, an important element in privilege and personal information management. Smart contract used in block chain Ethereum includes important information or transaction details of users. Therefore, in case of an attack of privilege elevation, it is very likely to exploit transaction details or forge or tamper with personal information inquiry. In this paper, we propose a detection and countermeasure method for privilege escalation attack, which is especially important for block chain for secure smart transaction using block chain Ethereum. When comparing the results of this study with the results of similar applications and researches, we showed about 12~13% improvement in performance and suggested the future countermeasures through packet analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.23-32
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• 2023

Since NFTs can be used like certificates due to the nature of blockchain, their use in various digital asset trading markets is expanding. This is because NFTs are expected to be actively used as a core technology of the metaverse virtual economy as non-transferable NFTs are developed. However, concerns about NFT security threats are also growing. Therefore, the purpose of this study is to investigate and analyze NFT-related infringement cases and to clearly understand the current security status and risks. As a research method, we determined NFT security areas based on previous studies and analyzed infringement cases and threat types for each area. The analysis results were systematically mapped in the form of domain, case, and threat, and the meaning of the comprehensive results was presented. As a result of the research, we want to help researchers clearly understand the current state of NFT security and seek the right research direction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.712-714
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• 2018

The system of this paper designs and implements a used trading system that is commonly used on the Internet. In order to pursue local transactions based on location, we designed the system by dividing the region in consideration of the general characteristics of used transactions that are restricted by transactions through distance and location. To do this, I used MySQL as the database engine and I used PHP, an Internet server-based scripting language, for database interworking. Due to the characteristics of secondary transactions, information security and design of each product are considered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.353-355
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• 2018

The system of this paper designs and implements a used trading system that is commonly used on the Internet. In order to pursue local transactions based on location, we designed the system by dividing the region in consideration of the general characteristics of used transactions that are restricted by transactions through distance and location. To do this, I used MySQL as the database engine and I used PHP, an Internet server-based scripting language, for database interworking. Due to the characteristics of secondary transactions, information security and design of each product are considered.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.785-815
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• 2013

This paper analyzes the three issues related to the effect of environmental regulations on the Korean trades with gravity equation model: the effect on the Korean exports, the bilateral trade flows between the Korea and the trade partners, and the Korean international competitiveness. For all three issues we carried the empirical tests with fixed effect estimation methods for total industries, non-pollution industries, pollution industries, and also 16 individual pollution industries. We use industry panel data for the 120 largest trading countries with Korea for the years 2000-2010. The Environmental Performance Index (EPI) is used as the proxy variable for the environmental regulation. The empirical result shows that while GDPs of both Korea and its trading partners are very important factors affecting positively the Korean trades for all industries, the environmental regulation of the importing country would be a definite trade barrier to the Korean pollution industries, but not a definite one for the non-pollution industries. In addition, the stricter environmental regulations of Korea's trade partners would weaken the Korean international competitiveness of Korean pollution industries. In this regard, the Porter Hypothesis would have not appeared in the Korean trades of pollution industries during the period observed in this study.