• Tuberculosis and Respiratory Diseases
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• v.42 no.4
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• pp.569-583
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• 1995

Background: The expression of the adhesion molecules on the cell surface is important in the movement of cells and the modulation of immune response. DILD starts as an alveolitis and progresses to pulmonary fibrosis. So adhesion molecules in these patients is expected to be increased. There are several reports about adhesion molecules in DILD in terms of the percentage of positive cells in immuno-stain, in which the interpretation is subjective and the data were variable. Methods: So we measured the relative median fluorescence intensity(RMFI) which is the ratio of the FI emitted by bound primary monoclonal antibody to FI emitted by isotypic control antibody of the cells in BALF of 28 patients with DILD(IPF:10, collagen disease:7, sarcoidosis:9, hypersensitivity pneumonitis:2) and 9 healthy control. Results: RMFI of the ICAM-1 on AM($3.30{\pm}1.16$) and lymphocyte($5.39{\pm}.70$) of DILD were increased significantly than normal control($0.93{\pm}0.18$, $1.06{\pm}0.21$, respectively, p=0.001, P=0.003). RMFI of the CD18 on lymphocyte was also higher($24.9{\pm}14.9$) than normal($4.59{\pm}3.77$, p=0.0023). And there was a correlation between RMFI of ICAM on AM and the % of AM(r=-0.66, p=0.0001) and lymphocyte(r=0.447, p=0.0116) in BALF. Also RMFI of ICAM on lymphocyte had a significant (r=0.593, p=0.075) correlation with the % of IL-2R(+) lymphocyte in BALF. The soluble ICAM(sICAM) in serum was also significantly elevated in DILD($499.7{\pm}222.2\;ng/ml$) compred to normal($199.0{\pm}38.9$) (p=0.00097) and sICAM in BAL fluid was also significantly higher than normal control group($41.8{\pm}23.0\;ng/ml$ vs $20.1{\pm}13.6\;ng/ml$). There was a Significant correlation between sICAM level in serum and the expression of ICAM-l on AM(r=0.554, p=0.0259).Conclusion: These data suggest that in DILD the expression of adhesion molecules is increased in the AM and BAL lymphocytes with elevated serum sICAM, and these parameter may be useful in determining disease activity.

• Tuberculosis and Respiratory Diseases
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• v.49 no.6
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• pp.724-732
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• 2000

Background : In patients with severe chronic lung diseases even a small pneumothorax can result in life-threatening respiratory distress. It is important to treat the attack by chest tube drainage until the lung expands. Pneumothorax with a persistent air leak that does not resolve under prolonged tube thoracostomy suction is usually treated by open operation to excise or oversew a bulla or cluster of blebs to stop the air leak. Pleurodesis by the instillation of chemical agents is used for the patient who has persistent air leak and is not good candidate for surgical treatment. When the primary trial of pleurodesis with common agent fails, it is uncertain which agent should be used f or stopping the air leak by pleurodesis. It is well known that inappropriate drainage of hemothorax results in severe pleural adhesion and thickening. Based on this idea, some reports described a successful treatment with autologous blood instillation for pneumothorax patients with or without residual pleural space. We tried pleurodesis with autologous bood for pneumothorax with persistent air leak and then we evaluated the efficacy and safety. Methods : Fifteen patients who had persistent air leak in the pneumothorax complicated from the severe chronic lung disease were enrolled. They were not good candidates for surgical treatment and doxycycline pleurodesis failed to stop up their air leaks. We used a mixture of autologous blood and 50% dextrose for pleurodesis. Effect and complications were assessed by clinical out∞me, chest radiography and pulmonary function tests. Results : The mean duration of air leak was 18.4${\pm}$6.16 days before ABP (autologous blood and dextrose pleurodesis) and $5.2{\pm}1.68$ days after ABP. The mean severity of pain was $2.3{\pm}0.70$ for DP(doxycycline pleurodesis) and $1.7{\pm}0.59$ for ABDP (p<0.05). There was no other complication except mild fever. Pleural adhesion grade was a mean of $0.6{\pm}0.63$. The mean dyspnea scale was $1.7{\pm}0.46$ before pneumothrax and $2.0{\pm}0.59$ after ABDP (p>0.05). The mean $FEV_1$ was $1.47{\pm}1.01$ before pneumothorax and $1.44{\pm}1.00$ after ABDP (p>0.05). Except in 1 patient, 14 patients had no recurrent pneumothorax. Conclusion : Autologous blood pleurodesis (ABP) was successful for treatment of persistent air leak in the pneumothorax. It was easy and inexpensive and involved less pain than doxycycline pleurodesis. It did not cause complications and severe pleural adhesion. We report that ABP can be considered as a useful treatment for persistent air leak in the pneumothorax complicated from the severe chronic lung disease.

• Tuberculosis and Respiratory Diseases
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• v.55 no.3
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• pp.250-256
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• 2003

Background : Anthracofibrosis, a descriptive term for multiple black pigmentation with fibrosis on bronchoscopic examination, has a close relationship with active tuberculosis (TB). However, TB activity is determined in the later stage by the TB culture results in some cases of anthracofibrosis. Therefore, it is necessary to identify early markers of TB activity in anthracofibrosis. There have been several reports investigating the serum levels of IL-2 $sR{\alpha}$, IFN-${\gamma}$ and TBGL antibody for the evaluation of TB activity. In the present study, we tried to measure the above mentioned serologic markers for the evaluation of TB activity in patients with anthracofibrosis. Methods : Anthracofibrosis was defined when there was deep pigmentation (in more than two lobar bronchi) and fibrotic stenosis of the bronchi on bronchoscopic examination. The serum of patients with anthracofibrosis was collected and stored under refrigeration before the start of anti-TB medication. The serum of healthy volunteers (N=16), patients with active TB prior to (N=22), and after (N=13), 6 month-medication was also collected and stored. Serum IL-2 $sR{\alpha}$, IFN-${\gamma}$ were measured with ELISA kit (R&D system, USA) and serum TBGL antibody was measured with TBGL EIA kit (Kyowa Inc, Japan). Results : Serum levels of IL-2 $sR{\alpha}$ in healthy volunteers, active TB patients before and after medication, and patients with anthracofibrosis were $640{\pm}174$, $1,611{\pm}2,423$, $953{\pm}562$, and $863{\pm}401$ pg/ml, respectively. The Serum IFN-${\gamma}$ levels were 0, $8.16{\pm}17.34$, $0.70{\pm}2.53$, and $2.33{\pm}6.67$ pg/ml, and TBGL antibody levels were $0.83{\pm}0.80$, $5.91{\pm}6.71$, $6.86{\pm}6.85$, and $3.22{\pm}2.59$ U/ml, respectively. The serum level of TBGL antibody was lower than of other groups (p<0.05). There was no significant difference of serum IL-2 $sR{\alpha}$ and IFN-${\gamma}$ levels among the four groups. Conclusion : The serum levels of IL-2 $sR{\alpha}$, IFN-${\gamma}$ and TBGL antibody were not useful in the evaluation of TB activity in patients with anthracofibrosis. More useful ways need to be developed for the differentiation of active TB in patients with anthracofibrosis.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.492-497
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• 2004

Purpose: it is very important to differentiate breast cancer from benign mass. There are many reports to evaluate the differential diagnosis under the several diagnostic tools. We evaluated the usefulness of mammography and Tc-99m MIBI scintimammography in the differential diagnosis of breast mass and correlated with pathologic findings. Materials and Methods: This study included 80 patients (a8e: 24-72, mean: 48.4) who underwent mammography and Tc-99m MIBI scintimammography for breast masses. Scintimammographies (anterior-posterior and lateral projections) were acquired in 10 minutes and 2 hours after intravenous injection of Tc-99m MIBI. four specialists in diagnostic radioloay and nuclear medicine evaluated the findings of breast masses under the mammography and Tc-99m MIBI scintimammography, and calculated the tumor to background (T/B) ratio. The pathologic results were obtained and we statistically analyzed the correlations between pathologic results and imaging findings under the mammography and Tc-99m MIBI scintimammography by chi-square and correlation test. Results: The sensitivity, specificity, positive predictive value, and negative predictive value of mammography for detection of breast cancer were 87.5%, 56.3%, 75.0%), and 75.0% respectively. 45 cases of 80 patients were suspicious for breast cancer under the Tc-99m MIBI scintimammography. 41 cases of 45 patients were confirmed as breast cancer and the remaining 4 cases were confirmed as benign masses. The sensitivity, specificity, positive predictive value and negative predictive value of Tc-99m MIBI scintimammography for detection of breast cancer were 85.4%, 87.5%, 91.1%, and 80.8% respectively. The sensitivity of scintimammography was lower than that of mammography for detection of breast cancer, however the specificity, positive predictive value, and negative predictive value were higher. In the benign mass, the mean T/B ratio in 10 minutes was $1.409{\pm}0.30$, and that in 2 hours was $1.267{\pm}0.42$. The maximal T/B ratio of benign mass in 10 minutes was $1.604{\pm}0.42$, and that in 2 hours was $1.476{\pm}0.50$. In the malignant mass, the mean T/B ratio in 10 minutes was $2.220{\pm}1.07$, and that in 2 hours was $1.842{\pm}0.75$. The maximal T/B ratio of malignant mass was $2.993{\pm}1.94$, and that in 2 hours was $2.480{\pm}1.34$. And the T/B ratio under the early and delayed images were meaningful. Conclusion: The scintimammography is useful diagnostic tool to differentiate breast cancer from benign mass, although the sensitivity of mammography for detection of breast mass is high. Especially, the use of the T/B ratio is helpful to diagnose breast cancer.

• Journal of Sericultural and Entomological Science
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• v.52 no.2
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• pp.110-116
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• 2014

Recently the number of the butterflies, Mellicta ambigua, had been decreasing rapidly, and already disappeared at many habitat. In this studies, we investigated ecological environment of Mellicta ambigua for preparing of primary research data recovering habitat, and studied on bionomical characteristics. Two different habitat, Jindo and Inje, were selected for investigation of ecological environment. We investigated four times during 3-month, from June to August in 2012. In Jindo, we observed more than 100 butterflies and a lot of host plants, Melampyrum roseum var. japonicum. But only 5 butterflies and only a few host plants, Veronicastrum sibiricum were observed in Inje. We could not observe the eggs, the larva and pupa on the host plants at all. For finding of bionomical characteritics, we reared butterflies at natural conditions. Collected 3-female butterflies from Jindo laid 465 eggs on the leaves of 3-host plants, Veronicastrum sibiricum. 120 ~ 186 eggs per each female were laid in the shape of cluster. An egg was globular shape, 0.6 mm diameter and 0.7 mm height. The egg periods were $9.96{\pm}0.4days$ after ovipositioning, and the hatchability was 95.% at natural condition. The larval periods were $4.1{\pm}0.6days$ (1st instar), $2.1{\pm}1.0days$ (2nd), $8.1{\pm}0.7days$ (3rd), $239.2{\pm}10.9days$ (4th), $12.3{\pm}1.3days$ (5th), $17.1{\pm}1.1days$ (6th), $10.5{\pm}1.0days$ (7th) each other. The larva of 4th instar overwintered in the nest that had been made into the leaf of host plant with secreted thread as a group until early March next year. In the early March next year, overwintered larva went around their nest in search of host plants, and went to other host plants, Veronica persica and Plantago asiatica, sometimes. The overwintered larva of Mellicta ambigua could grow up on two other host plants normally. In the following experiment, the butterflies of Mellicta ambigua laid eggs on the leaves of Plantago asiatica, but the 1st instar larva from eggs died all. The headwidth of each developmental larval stage were $0.28{\pm}0.02mm$ (1st), $0.45{\pm}0.02mm$ (2nd), $0.58{\pm}0.02mm$ (3rd), $0.75{\pm}0.03mm$ (4th), $0.89{\pm}0.05mm$ (5th), $1.23{\pm}0.06mm$ (6th), $2.13{\pm}0.11mm$ (7th). The pupal ratio was 92.0%. The pupal period were $9.1{\pm}1.6days$, and the emergence rate was 88.6%. As a result we determined that Mellicta ambigua can rear at natural conditions. But indoor-rearing is considered to be difficult and not useful industrially, because they have long term larval stage and only one life cycle per an year.

• 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.

• The Korean Journal of Archival Studies
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• no.22
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• pp.157-199
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• 2009

The organization for managing records and archives did not emerge together with the founding of the Chinese Communist Party. Such management became active with the establishment of the Department of Documents (文書科) and its affiliated offices overseeing reading and safekeeping of official papers, after the formation of the Central Secretariat(中央秘書處) in 1926. Improving the work of the Secretariat's organization became the focus of critical discussions in the early 1930s. The main criticism was that the Secretariat had failed to be cognizant of its political role and degenerated into a mere "functional organization." The solution to this was the "politicization of the Secretariat's work." Moreover, influenced by the "Rectification Movement" in the 1940s, the party emphasized the responsibility of the Resources Department (材料科) that extended beyond managing documents to collecting, organizing and providing various kinds of important information data. In the mean time, maintaining security with regard to composing documents continued to be emphasized through such methods as using different names for figures and organizations or employing special inks for document production. In addition, communications between the central political organs and regional offices were emphasized through regular reports on work activities and situations of the local areas. The General Secretary not only composed the drafts of the major official documents but also handled the reading and examination of all documents, and thus played a central role in record processing. The records, called archives after undergoing document processing, were placed in safekeeping. This function was handled by the "Document Safekeeping Office(文件保管處)" of the Central Secretariat's Department of Documents. Although the Document Safekeeping Office, also called the "Central Repository(中央文庫)", could no longer accept, beginning in the early 1930s, additional archive transfers, the Resources Department continued to strengthen throughout the 1940s its role of safekeeping and providing documents and publication materials. In particular, collections of materials for research and study were carried out, and with the recovery of regions which had been under the Japanese rule, massive amounts of archive and document materials were collected. After being stipulated by rules in 1931, the archive classification and cataloguing methods became actively systematized, especially in the 1940s. Basically, "subject" classification methods and fundamental cataloguing techniques were adopted. The principle of assuming "importance" and "confidentiality" as the criteria of management emerged from a relatively early period, but the concept or process of evaluation that differentiated preservation and discarding of documents was not clear. While implementing a system of secure management and restricted access for confidential information, the critical view on providing use of archive materials was very strong, as can be seen in the slogan, "the unification of preservation and use." Even during the revolutionary movement and wars, the Chinese Communist Party continued their efforts to strengthen management and preservation of records & archives. The results were not always desirable nor were there any reasons for such experiences to lead to stable development. The historical conditions in which the Chinese Communist Party found itself probably made it inevitable. The most pronounced characteristics of this process can be found in the fact that they not only pursued efficiency of records & archives management at the functional level but, while strengthening their self-awareness of the political significance impacting the Chinese Communist Party's revolution movement, they also paid attention to the value possessed by archive materials as actual evidence for revolutionary policy research and as historical evidence of the Chinese Communist Party.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Journal of Bio-Environment Control
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• v.28 no.1
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• pp.78-85
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• 2019

This study was designed to examine the performance of an aspirated radiation shield(ARS), which was made at the investigator's lab and characterized by relatively easier making and lower costs based on survey data and reports on errors in its measurements of temperature and relative humidity. The findings were summarized as follows: the ARS and the Jinju weather station made measurements and recorded the range of maximum, average, and minimum temperature at $2.0{\sim}34.1^{\circ}C$, $-6.1{\sim}22.2^{\circ}C$, $-14.0{\sim}15.1^{\circ}C$ and $0.4{\sim}31.5^{\circ}C$, $-5.8{\sim}22.0^{\circ}C$, $-14.1{\sim}16.3^{\circ}C$, respectively. There were no big differences in temperature measurements between the two institutions except that the lowest and highest point of maximum temperature was higher on the campus by $1.6^{\circ}C$ and $2.6^{\circ}C$, respectively. The measurements of ARS were tested against those of a standard thermometer. The results show that the temperature measured by ARS was lower by $-2.0^{\circ}C$ or higher by $1.8^{\circ}C$ than the temperature measured by a standard thermometer. The analysis results of its correlations with a standard thermometer reveal that the coefficient of determination was 0.99. Temperature was compared between fans and no fans, and the results show that maximum, average, and minimum temperature was higher overall with no fans by $0.5{\sim}7.6^{\circ}C$, $0.3{\sim}4.6^{\circ}C$ and $0.5{\sim}3.9^{\circ}C$, respectively. The daily average relative humidity measurements were compared between ARS and the weather station of Jinju, and the results show that the measurements of ARS were a little bit higher than those of the Jinju weather station. The measurements on June 27, July 26 and 29, and August 20 were relatively higher by 5.7%, 5.2%, 9.1%, and 5.8%, respectively, but differences in the monthly average between the two institutions were trivial at 2.0~3.0%. Relative humidity was in the range of -3.98~+7.78% overall based on measurements with ARS and Assman's psychometer. The study analyzed correlations in relative humidity between the measurements of the Jinju weather station and those of Assman's psychometer and found high correlations between them with the coefficient of determination at 0.94 and 0.97, respectively.

• 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.