• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• The Journal of Natural Sciences
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• v.7
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• pp.133-162
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• 1995

Paderborn's companies, Wameling and Cassau, produce the liturgical vestments, which have much traditional artistic merit. And Kevelaerer Fahnen + Paramenten GmbH, located in Kevelater which is a place of pilgrimage of the Virgin Mary, was known to Europe, Africa, America and the Scandinavia Peninsula as the "Hidden Company" of liturgical vesments maker up to now. Paderborn and Kevelaer were the place of the center of the religious world and the Catholic ceremony during a good few centries. The Catholic liturgical vestiments of these 3 companies use versatile design, color, shape and techniques. These have not only the symbolism of religion, but also can meet our's expectations of utilization of modern textile art, art clothing and wide-all division of design. These give the understanding of symbolic meanings and harmony according to liturgical vestments to the believers. And these have an influence on mental thinking and induction of religious belief to the non-believers as the recognition and concerns about the religious art. The liturgical vestments are clothes which churchmen put on at the all ceremonial function of a mass, a sacrament, performance and a parade according to rules of church. These show the represen-tation of "Holy God" in silence and distinguish between common people and churchmen. And these represent a status and dignity of churchmen and induce majesty and respect to churchmen. Common clothes of the beginning of the Greece and Rome was developed to Christian clothes with the tendency of religion. There were no special uniforms distinguished from commen people until the Christianity was recognized officially by the Roman Emperor Constantinus at A.D.313. The color of liturgical vestments was originally white and changed to special colors according to liturgical day and each time by the Pope Innocentius at 12th century. The color and symbolic meaning of the liturgical vestments of present day was originated by the Pope St. Pius(1566-1572). Wool and Linen was used as decorations and materials in the beginnings and the special materials like silk was used after 4th century and beautiful materials made of gold thread was used at 12th century. It is expected that there is no critical changes to the liturgical vestments of future. But the development of liturgical vestments will continues slowly by the command of conservative church and will change to simple and convenient formes according to the culture, the trend of the times and the fashion of clothes. The companies of liturgical vestments develop versatile design, embroidery technique and realization of creative design for distinction of the liturgical vestments of each company and artistic progress. The cooperation of companies, artists and church will make the bright future of these 3 companies. We expect that our country will be a famous producing center of the liturgical vestments through the research and development of companies, participation of artists in religeous arts and concerts of church.

• Tuberculosis and Respiratory Diseases
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• v.43 no.2
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• pp.190-200
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• 1996

Background : Mechanical ventilation constitutes the last therapeutic method for acute respiratory failure when oxygen therapy and medical treatment fail to improve the respiratory status of the patient. This invasive ventilation, classically administered by endotracheal intubation or by tracheostomy, is associated with significant mortality and morbidity. Consequently, any less invasive method able to avoid the use of endotracheal ventilation would appear to be useful in high risk patient. Over recent years, the efficacy of nasal mask ventilation has been demonstrated in the treatment of chronic restrictive respiratory failure, particularly in patients with neuromuscular diseases. More recently, this method has been successfully used in the treatment of acute respiratory failure due to parenchymal disease. Method : We assessed the efficacy of Bilevel positive airway pressure(BiPAP) in the treatment of acute exacerbation of chronic obstructive pulmonary disease(COPD). This study prospectively evaluated the clinical effectiveness of a treatment schedule with positive pressure ventilation via nasal mask(Respironics BiPAP device) in 22 patients with acute exacerbations of COPD. Eleven patients with acute exacerbations of COPD were treated with nasal pressure support ventilation delivered via a nasal ventilatory support system plus standard treatment for 3 consecutive days. An additional 11 control patients were treated only with standard treatment. The standard treatment consisted of medical and oxygen therapy. The nasal BiPAP was delivered by a pressure support ventilator in spontaneous timed mode and at an inspiratory positive airway pressure $6-8cmH_2O$ and an expiratory positive airway pressure $3-4cmH_2O$. Patients were evaluated with physical examination(respiratory rate), modified Borg scale and arterial blood gas before and after the acute therapeutic intervention. Results : Pretreatment and after 3 days of treatment, mean $PaO_2$ was 56.3mmHg and 79.1mmHg (p<0.05) in BiPAP group and 56.9mmHg and 70.2mmHg (p<0.05) in conventional treatment (CT) group and $PaCO_2$ was 63.9mmHg and 56.9mmHg (p<0.05) in BiPAP group and 53mmHg and 52.8mmHg in CT group respectively. pH was 7.36 and 7.41 (p<0.05) in BiPAP group and 7.37 and 7.38 in cr group respectively. Pretreatment and after treatment, mean respiratory rate was 28 and 23 beats/min in BiPAP group and 25 and 20 beats/min in CT group respectively. Borg scale was 7.6 and 4.7 in BiPAP group and 6.4 and 3.8 in CT group respectively. There were significant differences between the two groups in changes of mean $PaO_2$, $PaCO_2$ and pH respectively. Conclusion: We conclude that short-term nasal pressure-support ventilation delivered via nasal BiPAP in the treatment of acute exacerbation of COPD, is an efficient mode of assisted ventilation for improving blood gas values and dyspnea sensation and may reduce the need for endotracheal intubation with mechanical ventilation.

• Tuberculosis and Respiratory Diseases
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• v.42 no.6
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• pp.923-933
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• 1995

Background: Pleural abnormality is the the most common respiratory change caused by asbestos dust inhalation and also develop other asbestos related disease after cessation of asbestos exposure. So we conducted epidemiologic study to investigate if the pleural abnormality is associated with pulmonary function change and what factors are influenced on pulmonary function impairment. Methods: Two hundred and twenty two asbestos workers from 9 industries using asbestos in Korea were selected to measure the concentration of sectional asbestos fiber. Ouestionnaire, chest X-ray, PFT were also performed. All the data were analyzed by student t-test and chi-square test using SAS. Regressional analysis was performed to evaluate important factors, for example smoking, exposure concentration, period and the existence of pleural thickening, affecting to the change of pulmonary function. Results: 1) All nine industries except two, airborn asbestos fiber concentration was less than an average permissible concentration. PFT was performed on 222 workers and the percentage of male was 88.3%, their mean age was $41{\pm}9$ years old, and the duration of asbestos exposure was $10.6{\pm}7.8$ yrs. 2) The chest X-ray showed normal(89.19%), pulmonary Tb(inactive)(2.7%), pleral thickening (7.66%), suspected reticulonodular shadow(0.9%). 3) The mean values of height, smoking status, concentration of asbestos fiberwere not different between the subjects with pleural thickening and others, but age, cumulative pack-years, the duration of asbestos exposure were higher in subjects with pleural thickening. 4) All the PFT indices were lower in the subjects with pleural thickening than in the subjects without pleural thickening. 5) Simple regression analysis showed there was a significant correlation between $FEF_{75}$ which is sensitive in small airway obstruction and cumulative smoking pack-years, the duration of asbestos exposure and the concentration of asbestos fiber. 6) Multiple regression analysis showed all the pulmonary function indices were decreased as the increase of cumulative smoking pack-years and especially in the indices those are sensitive in small airway obstruction. Pleural thickening was associated with reduction in FVC, $FEV_1$, PEFR and $FEF_{25}$. Conclusion: The more concentration of asbestos fiber and the more duration of asbestos exposure, the greater reduction in $FEF_{50}$, $FEF_{75}$. Therefore PFT was important in the evaluation of early detection for small airway obstruction. Furthermore pleural thickening without asbesto-related parenchymal lung disease is associated with reduction in pulmonary function.

• Tuberculosis and Respiratory Diseases
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• v.45 no.5
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• pp.962-974
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• 1998

Background: Alteration of p53 tumor suppressor genes is most frequently identified in human neoplasms, including lung carcinoma. It is well known that bcl-2 oncoprotein protects cells from apoptosis. Recent studies have demonstrated that bcl-2 expression is associated with favorable prognosis for patients with non-small cell lung carcinoma. However, the precise biologic role of bcl-2 in the development of these tumors is still obscure. p53 and bcl-2 have important regulatory influence in the apoptotic pathway and thus their relationship is of interest in tumorigenesis, especially lung cancer. Purpose: The author investigated to know the prognostic significance of the expression of p53 and bcl-2 in radically resected non-small cell lung cancer. Method: 84 cases of formalin-fixed paraffin-embedded blocks from resected primary non-small cell lung cancer from 1980 to 1994 at Hanyang University Hospital were available for both clinical follow-up and immunohistochemical staining using monoclonal antibodies for p53 and bcl-2. Results : The histologic classification of the tumor was based on WHO criteria., and the specimens included 45 squamous cell carcinomas(53.6%), 28 adeonocarcinomas(33.3%) and 11 large cell carcinomas(13.1 %). p53 immunoreactivity was noted in 47 cases of 84 cases(56.0%). bcl-2 immunoreactivity was noted in 15 cases of 84 cases(17.9%). The mean survival duration was $64.23{\pm}10.73$ months in bcl-2 positive group and $35.28{\pm}4$. 39 months in bcl-2 negative group. The bcl-2 expression was significantly correlated with survival in radically resected non-small cell lung cancer patients(p=0.03). The mean survival duration was $34.71{\pm}6.12$ months in p53 positive group and $45.35{\pm}6.30$ months in p53 negative group(p=0.21). The p53 expression was not predictive for survival. There was no correlation between combination of the different status of p53 and bcl-2 expression in our study. Conclusions : The interaction and the regulation of new biologic markers, such as those involved in the apoptotic pathway, are complex. bcl-2 overexpression is a good prognostic factor in non-small cell lung cancer and p53 expression is not significantly associated with the prognostic factor in non-small cell lung cancer.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.3
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• pp.78-97
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• 2016

The objectives of this study are to examine the context of the establishment of Suhoe Gugok, Byeokgye Gugok Vally, and Nosan Palkyung, which have been established in Seojong-myeon of Yangpyeong-gun, by literature review and site investigations, and to determine the sceneries of Byeokgye scenic site as enjoyed and managed during the period of Hwaseo Lee, Hang-ro(華西 李恒老). The results of the study are as follows. First, Byeokgye Gugok Vally(黃蘗九曲) and Nosan Palkyung(蘆山八景), which have been established after the period of Hwaseo and theorized to have been established around key scenic areas associated with Hwaseo's activities, the analysis results showed that they were collecting sceneries of modern times. The extensive overlap between Byeokgye Gugok Vally and concentrated scenic elements of Suhoe Gugok(水回九曲), and the artificial configuration from the end point of Suhoe Gugok to the beginning point of Nosan Palkyung, reveal the pattern of space conflict and hegemony between Byeokgyes of Suip-ri and Nomun-ri. This is likely to be caused by the conflict between the historicity of the group that enjoyed Byeokgye prior to Hwaso's period and the strong territoriality of the space filled with the image of Hwaseo. Second, Byeokgye Gugok Vally was the secondary spatial system created by selecting the most scenic sites in Suip-ri while expanding the area of Nosan Palkyung. After establishment of Byeokgye Gugok Vally, the spatial identity of the entire Byeokgyecheon area was effectively established. This was a "Hwaseo-oriented" move, including the complete exclusion of the scenic sites from the pre-Hwaseo period such as Cheongseo Gujang and Suhoe Gugok's Letters Carved on the Rock. Consequently, the entire Byeokgyecheon area was reorganized into a cultural scenic site with Heoseo's influence. Third, Fifth, creations of Gugok(九曲) to determine the lineage of the Hwaseo School from Juja(朱子) to Yulgok(栗谷) to Uam(尤庵) to Hwaseo is likely to be an opportunity of birth and external motivation of the establishment of new Gugok Palkyung. In other words, Nosan Palkyung and Byeokgye Gugok Vally are likely to have been created as a reaction to the change of the center of the Hwaseo School to Okgyedong, and with strategic orientation based on the motivation and needs such as creation of the connecting space between Mui Gugok, Gosan Gugok, and Okgye Gugok, and the elevation of Hwaseo's status. Fourth, from the Hwaseo's Li-centric point of view, all revered sites in Beokwon(蘗園) that he managed existed as the spatial creative work to experience the existence of "li" through the objects in the landscape and the boundary of the spirit of emptiness of the aesthetic self. This clearly shows how Byeokgye Gugok Vally or Nosan Palkyung must be defined, and furthermore, appreciated and approached, prior to discussing it as the space associated with Hwaseo. Fifth, Nosan Palkyung was composed of cultural scenic landscapes of Gokjungkyung(曲中景) with eight scenic sites where Hwaseo gave his teachings and spend time around, in the Byeokgye of Nomun-ri area of Byeokgye Gugok Vally. The sceneries is, however, collected by depending on Hwaseo's Letters Carved on the Rock and poetry. Consequently, an inner exuberance of Nosan Palkyung is satisfied beside Byeokgye Gugok Vally, but its conceptual adequacy leaves room for questions.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.