• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.86-92
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• 2022

Recently, the bio-healthcare market is enlarging worldwide due to various reasons such as the COVID-19 pandemic. Among them, biometric measurement and analysis technology are expected to bring about future technological innovation and socio-economic ripple effect. Existing systems require a large-capacity battery to drive signal processing, wireless transmission part, and an operating system in the process. However, due to the limitation of the battery capacity, it causes a spatio-temporal limitation on the use of the device. This limitation can act as a cause for the disconnection of data required for the user's health care monitoring, so it is one of the major obstacles of the health care device. In this study, we report the concept of a standalone healthcare monitoring module, which is based on both triboelectric effects and electromagnetic effects, by converting biomechanical energy into suitable electric energy. The proposed system can be operated independently without an external power source. In particular, the wireless foot pressure measurement monitoring system, which is rationally designed triboelectric sensor (TES), can recognize the user's walking habits through foot pressure measurement. By applying the triboelectric effects to the contact-separation behavior that occurs during walking, an effective foot pressure sensor was made, the performance of the sensor was verified through an electrical output signal according to the pressure, and its dynamic behavior is measured through a signal processing circuit using a capacitor. In addition, the biomechanical energy dissipated during walking is harvested as electrical energy by using the electromagnetic induction effect to be used as a power source for wireless transmission and signal processing. Therefore, the proposed system has a great potential to reduce the inconvenience of charging caused by limited battery capacity and to overcome the problem of data disconnection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.1-7
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• 2022

The purpose of this study is to discuss the impact of unmanned aerial vehicle service and how to activate it. The discussion on the impact of the introduction of the unmanned aerial vehicle service was examined in terms of economic, environmental, and social acceptance, and a plan to revitalize the industry was presented. In terms of economic impact, if transportation services are increased using unmanned aerial vehicles in the future, road-based transportation cargo may decrease and road movement speed may increase due to reduced road congestion. This can have a positive effect on the increase in the value of land or real estate assets, and it also provides an impact on smart city design. In terms of environmental impact, unmanned aerial vehicles (UAVs) generally move through electricity, so they emit less exhaust gas compared to other existing devices, such as vehicles and railroads, and thus have less environmental impact. However, noise can have a negative impact on the habitat in the presence of wild animals along their migration routes. In terms of social acceptability of unmanned aerial vehicles (UAV) technology, areas that are declining due to the emergence of new services may appear, and at the same time, organizations that create profits may appear, causing conflicts between industries. Therefore, it is essential to form a social consensus on the acceptance of emerging industries. The government should come up with various countermeasures to minimize the negative impact that reflects the characteristics of the unmanned aerial vehicle use service. Just as various systems such as road signs were introduced so that vehicles can be operated on the ground to secure air routes in the mid- to long-term for revitalization of unmanned-based industries, development and establishment of services that should be introduced and applied prior to constructing air routes I need this. In addition, the design and implementation of information collection and operation plans for unmanned air traffic management in Korea and a plan to secure a control system for each region should also be made. This study can contribute to providing ideas for mid- to long-term research on new areas with the development of the unmanned aerial vehicle industry.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.361-381
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• 2023

Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.95-110
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• 2011

As global economic conditions are getting uneasy and polarization of our economy is intensified, the economic sentiment of small businesses is still low and unstable. The collapse of worldwide banking systems due to sub prime crisis in 2007 became the catalyst that shakes financial industries in each country in the world; the most sentiment people, small businesspersons, also have hard time facing survival way out, facing a great crisis. All organizing powers including manufactures, wholesales and retails are being gradually greater in mutual relations and dependence, and unstable factors about risks are also increasing. For exterior environmental and physical risk factors which cannot make small businesses survive themselves by developing ways out are eventually increasing, those who cannot cope with these factors face a great crisis. Although the government tries hard to overcome this situation conducting many ways, the effect does not continue. It is the real state that independent business markets including overall employment and establishing business have vicious cycle that they cannot be improved, due to increase of employment centered on short-term labors which lack durability in creation of employment and decline of household income. Recently, growth shows indication of slowdown because of multinational risk factors including financial crisis in each country in Europe, the death of Kim Jung-il, relationship with North Korea, and unstability of war situation in the Middle East Asia. Experts expect that growth rate will be about 4%, and independent business that ordinary people feel is still gloomy. It's reality that there is no adequate alternative for lack of jobs, unstable employment and a means of living after retirement. Also, the fact that large companies enter the market which is narrow and in the excessive competition should be an environmental factor that makes the situation worse. The business concept, a franchise, is the part we should think about whether it is the institutional solution that can guarantee independent businessmen stable life. Major companies are frightfully entering the market today, breaking the barrier to entry and shouting of a win-win with independent businesses. It's the small businesspersons who go through painful domestic recession, cannot predict the future and manage confusing and unstable independent business. It's very important to restore the domestic economy through wisely boosting consumption as soon as possible. It's also important to lead the situation by gathering powers of the government and related organizations, agonizing, suggesting solutions, and establishing accurate directions. The purpose of this study, therefore, is to suggest ways to strengthen competitiveness of small businesspersons by examining small business support policies which are currently implemented.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• KDI Journal of Economic Policy
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• v.12 no.1
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• pp.31-68
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• 1990

The concentration of economic power takes the form of one or a few firms controlling a substantial portion of the economic resources and means in a certain economic area. At the same time, to the extent that these firms are owned by a few individuals, resource allocation can be manipulated by them rather than by the impersonal market mechanism. This will impair allocative efficiency, run counter to a decentralized market system and hamper the equitable distribution of wealth. Viewed from the historical evolution of Western capitalism in general, the concentration of economic power is a paradox in that it is a product of the free market system itself. The economic principle of natural discrimination works so that a few big firms preempt scarce resources and market opportunities. Prominent historical examples include trusts in America, Konzern in Germany and Zaibatsu in Japan in the early twentieth century. In other words, the concentration of economic power is the outcome as well as the antithesis of free competition. As long as judgment of the economic system at large depends upon the value systems of individuals, therefore, the issue of how to evaluate the concentration of economic power will inevitably be tinged with ideology. We have witnessed several different approaches to this problem such as communism, fascism and revised capitalism, and the last one seems to be the only surviving alternative. The concentration of economic power in Korea can be summarily represented by the "jaebol," namely, the conglomerate business group, the majority of whose member firms are monopolistic or oligopolistic in their respective markets and are owned by particular individuals. The jaebol has many dimensions in its size, but to sketch its magnitude, the share of the jaebol in the manufacturing sector reached 37.3% in shipment and 17.6% in employment as of 1989. The concentration of economic power can be ascribed to a number of causes. In the early stages of economic development, when the market system is immature, entrepreneurship must fill the gap inherent in the market in addition to performing its customary managerial function. Entrepreneurship of this sort is a scarce resource and becomes even more valuable as the target rate of economic growth gets higher. Entrepreneurship can neither be readily obtained in the market nor exhausted despite repeated use. Because of these peculiarities, economic power is bound to be concentrated in the hands of a few entrepreneurs and their business groups. It goes without saying, however, that the issue of whether the full exercise of money-making entrepreneurship is compatible with social mores is a different matter entirely. The rapidity of the concentration of economic power can also be traced to the diversification of business groups. The transplantation of advanced technology oriented toward mass production tends to saturate the small domestic market quite early and allows a firm to expand into new markets by making use of excess capacity and of monopoly profits. One of the reasons why the jaebol issue has become so acute in Korea lies in the nature of the government-business relationship. The Korean government has set economic development as its foremost national goal and, since then, has intervened profoundly in the private sector. Since most strategic industries promoted by the government required a huge capacity in technology, capital and manpower, big firms were favored over smaller firms, and the benefits of industrial policy naturally accrued to large business groups. The concentration of economic power which occured along the way was, therefore, not necessarily a product of the market system. At the same time, the concentration of ownership in business groups has been left largely intact as they have customarily met capital requirements by means of debt. The real advantage enjoyed by large business groups lies in synergy due to multiplant and multiproduct production. Even these effects, however, cannot always be considered socially optimal, as they offer disadvantages to other independent firms-for example, by foreclosing their markets. Moreover their fictitious or artificial advantages only aggravate the popular perception that most business groups have accumulated their wealth at the expense of the general public and under the behest of the government. Since Korea stands now at the threshold of establishing a full-fledged market economy along with political democracy, the phenomenon called the concentration of economic power must be correctly understood and the roles of business groups must be accordingly redefined. In doing so, we would do better to take a closer look at Japan which has experienced a demise of family-controlled Zaibatsu and a success with business groups(Kigyoshudan) whose ownership is dispersed among many firms and ultimately among the general public. The Japanese case cannot be an ideal model, but at least it gives us a good point of departure in that the issue of ownership is at the heart of the matter. In setting the basic direction of public policy aimed at controlling the concentration of economic power, one must harmonize efficiency and equity. Firm size in itself is not a problem, if it is dictated by efficiency considerations and if the firm behaves competitively in the market. As long as entrepreneurship is required for continuous economic growth and there is a discrepancy in entrepreneurial capacity among individuals, a concentration of economic power is bound to take place to some degree. Hence, the most effective way of reducing the inefficiency of business groups may be to impose competitive pressure on their activities. Concurrently, unless the concentration of ownership in business groups is scaled down, the seed of social discontent will still remain. Nevertheless, the dispersion of ownership requires a number of preconditions and, consequently, we must make consistent, long-term efforts on many fronts. We can suggest a long list of policy measures specifically designed to control the concentration of economic power. Whatever the policy may be, however, its intended effects will not be fully realized unless business groups abide by the moral code expected of socially responsible entrepreneurs. This is especially true, since the root of the problem of the excessive concentration of economic power lies outside the issue of efficiency, in problems concerning distribution, equity, and social justice.

• Economic and Environmental Geology
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• v.39 no.4 s.179
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• pp.369-384
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• 2006

Korean Peninsula, located on the southeastern part of Eurasian plate, belongs to the intraplate region. The characteristics of intraplate earthquake show the low and rare seismicity and the sparse and irregular distribution of epicenters comparing to interplate earthquake. To evaluate the exact seismic activity in intraplate region, long-term seismic data including historical earthquake data should be archived. Fortunately the long-term historical earthquake records about 2,000 years are available in Korea Peninsula. By the analysis of this historical and instrumental earthquake data, seismic activity was very high in 16-18 centuries and is more active at the Yellow sea area than East sea area. Comparing to the high seismic activity of the north-eastern China in 16-18 centuries, it is inferred that seismic activity in two regions shows close relationship. Also general trend of epicenter distribution shows the SE-NW direction. In Korea Peninsula, the first seismic station was installed at Incheon in 1905 and 5 additional seismic stations were installed till 1943. There was no seismic station from 1945 to 1962, but a World Wide Standardized Seismograph was installed at Seoul in 1963. In 1990, Korean Meteorological Adminstration(KMA) had established centralized modem seismic network in real-time, consisted of 12 stations. After that time, many institutes tried to expand their own seismic networks in Korea Peninsula. Now KMA operates 35 velocity-type seismic stations and 75 accelerometers and Korea Institute of Geoscience and Mineral Resources operates 32 and 16 stations, respectively. Korea Institute of Nuclear Safety and Korea Electric Power Research Institute operate 4 and 13 stations, consisted of velocity-type and accelerometer. In and around the Korean Peninsula, 27 intraplate earthquake mechanisms since 1936 were analyzed to understand the regional stress orientation and tectonics. These earthquakes are largest ones in this century and may represent the characteristics of earthquake in this region. Focal mechanism of these earthquakes show predominant strike-slip faulting with small amount of thrust components. The average P-axis is almost horizontal ENE-WSW. In north-eastern China, strike-slip faulting is dominant and nearly horizontal average P-axis in ENE-WSW is very similar with the Korean Peninsula. On the other hand, in the eastern part of East Sea, thrust faulting is dominant and average P-axis is horizontal with ESE-WNW. This indicate that not only the subducting Pacific Plate in east but also the indenting Indian Plate controls earthquake mechanism in the far east of the Eurasian Plate. Crustal velocity model is very important to determine the hypocenters of the local earthquakes. But the crust model in and around Korean Peninsula is not clear till now, because the sufficient seismic data could not accumulated. To solve this problem, reflection and refraction seismic survey and seismic wave analysis method were simultaneously applied to two long cross-section traversing the southern Korean Peninsula since 2002. This survey should be continuously conducted.

• Journal of Ginseng Research
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• v.26 no.3
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• pp.111-131
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• 2002

Korean ginseng (Panax ginseng C.A. Meyer) received a great deal of attention from the Orient and West as a tonic agent, health food and/or alternative herbal therapeutic agent. However, controversy with respect to scientific evidence on pharmacological effects especially, evaluation of clinical efficacy and the methodological approach still remains to be solved. Author reviewed those articles published since 1980 when pharmacodynamic studies on ginseng have intensively started. Special concern was paid on metabolic disorders including diabetes mellitus, circulatory disorders, malignant tumor, sexual dysfunction, and physical and mental performance to give clear information to those who are interested in pharmacological study of ginseng and to promote its clinical use. With respect to chronic diseases such as diabetes mellitus, atherosclerosis, high blood pressure, malignant disorders, and sexual disorders, it seems that ginseng plays preventive and restorative role rather than therapeutics. Particularly, ginseng plays a significant role in ameliorating subjective symptoms and preventing quality of life from deteriorating by long term exposure of chemical therapeutic agents. Also it seems that the potency of ginseng is mild, therefore it could be more effective when used concomitantly with conventional therapy. Clinical studies on the tonic effect of ginseng on work performance demonstrated that physical and mental dysfunction induced by various stresses are improved by increasing adaptability of physical condition. However, the results obtained from clinical studies cannot be mentioned in the indication, which are variable upon the scientist who performed those studies. In this respect, standardized ginseng product and providing planning of the systematic clinical research in double-blind randomized controlled trials are needed to assess the real efficacy for proposing ginseng indication. Pharmacological mode of action of ginseng has not yet been fully elucidated. Pharmacodynamic and pharmacokinetic researches reveal that the role of ginseng not seem to be confined to a given single organ. It has been known that ginseng plays a beneficial role in such general organs as central nervous, endocrine, metabolic, immune systems, which means ginseng improves general physical and mental conditons. Such multivalent effect of ginseng can be attributed to the main active component of ginseng,ginsenosides or non-saponin compounds which are also recently suggested to be another active ingredients. As is generally the similar case with other herbal medicines, effects of ginseng cannot be attributed as a given single compound or group of components. Diversified ingredients play synergistic or antagonistic role each other and act in harmonized manner. A few cases of adverse effect in clinical uses are reported, however, it is not observed when standardized ginseng products are used and recommended dose was administered. Unfavorable interaction with other drugs has also been suggested, which the information on the products and administered dosage are not available. However, efficacy, safety, interaction or contraindication with other medicines has to be more intensively investigated in order to promote clinical application of ginseng. For example, daily recommended doses per day are not agreement as 1-2g in the West and 3-6 g in the Orient. Duration of administration also seems variable according to the purpose. Two to three months are generally recommended to feel the benefit but time- and dose-dependent effects of ginseng still need to be solved from now on. Furthermore, the effect of ginsenosides transformed by the intestinal microflora, and differential effect associated with ginsenosides content and its composition also should be clinically evaluated in the future. In conclusion, the more wide-spread use of ginseng as a herbal medicine or nutraceutical supplement warrants the more rigorous investigations to assess its effacy and safety. In addition, a careful quality control of ginseng preparations should be done to ensure an acceptable standardization of commercial products.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• 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.