• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.487-499
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• 2021

Purpose:The purpose of the paper is to review the problems of performance enhancement of safety certification standards and to suggest directions for improvement in order to rationalize safety certification standards for future industrial development and environmental changes. Method: The problems and limitations of the safety certification system are summarized through literature review and interview with manager, and the status of safety certification standards is classified into design standards, performance standards, and detailed standards, and the status analysis is performed. In addition, by synthesizing the results of the investigation and analysis, improvements are suggested to improve the performance of the safety certification standards. Result: Through the survey, the problems and limitations of safety certification could be grouped into six categories: government-led certification system operation, standardized certification standards, long time required to improve certification, poor certification standards preparation system, and lack of reflection of industry opinions. And, as a result of analyzing the certification standards by dividing them into performance and design standards, in the case of machinery, equipment, and protection devices, the design standards were high at 69.7% and 64.9%, whereas in the case of protective equipment, the performance standards were high at 61.1%. In order to improve the performance of safety certification standards centered on design standards, it is necessary to determine the possibility of performance enhancement of the certification standards and determine the feasibility of the inspection test method. In order to improve performance, it was reviewed that it was necessary to establish a systemic foundation and infrastructure, such as strengthening the Product Liability Act, systematizing market monitoring, etc., distributing certification test tasks, and participating in the preparation of certification standards by the private sector. Conclusion: Through this study, the problems and limitations of Korea's safety certification system were summarized and the necessity for performance improvement was reviewed. Performance improvement of safety certification standards is a matter that requires preparatory work, such as legislative revision and infrastructure construction, and requires mid-to-long-term promotion. In addition, rather than improving the overall safety certification standards, the performance requirements for each item subject to certification should be reviewed and promoted, and details should be specified through additional research.

• Korean Journal of Environmental Biology
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• v.38 no.4
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• pp.634-649
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• 2020

Recently, stream longitudinal connectivity has been a topic of investigation due to the frequent disconnections and the impact of aquatic ecosystems caused by the construction of small and medium-sized weirs and various artificial structures (fishways) directly influencing the stream ecosystem health. In this study, the international and domestic research trends of the longitudinal connectivity in aquatic ecosystems were evaluated and the applicability of fish-based longitudinal connectivity models used in developed countries was analyzed. For these purposes, we analyzed the current status of research on longitudinal connectivity and structural problems, fish monitoring methodology, monitoring approaches, longitudinal disconnectivity of fish movement, and biodiversity. In addition, we analyzed the current status and some technical limitations of physical habitat suitability evaluation, ecology-based water flow, eco-hydrological modeling for fish habitat connectivity, and the s/w program development for agent-based model. Numerous references, data, and various reports were examined to identify worldwide longitudinal stream connectivity evaluation models in European and non-European countries. The international approaches to longitudinal connectivity evaluations were categorized into five phases including 1) an approach integrating fish community and artificial structure surveys (two types input variables), 2) field monitoring approaches, 3) a stream geomorphological approach, 4) an artificial structure-based DB analytical approach, and 5) other approaches. the overall evaluation of survey methodologies and applicability for longitudinal stream connectivity suggested that the ICE model (Information sur la Continuite Ecologique) and the ICF model (Index de Connectivitat Fluvial), widely used in European countries, were appropriate for the application of longitudinal connectivity evaluations in Korean streams.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.265-280
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• 2022

Hwangnyongsa Temple was the large Buddhist monastery of Silla that has existed for about 685 years. The temple underwent a series of excavations from 1976 to 1983, during which it was discovered that its layout consisted of one pagoda and three main dharma halls. This discovery also led to the production of four artistic depictions of the temple at various times from its foundation to its final phase. Previous studies on the architectural layout of Hwangnyongsa Temple are largely focused on the inner sanctuary ("Buddha's Land"). The studies on the temple's main architectural structures may be natural for those who are interested in the origins of and background to its establishment, but the studies on its outer sanctuary ("Sangha's Land") have to come first to acquire a deeper knowledge of the architectural layout of the temple as a whole. To gain a comprehensive understanding of the entire layout of Buddhist monasteries of the Silla dynasty, including both their inner and outer sanctuaries, the studies on Hwangnyongsa Temple are essential as it was once the kingdom's most highly honored temple. The studies on Korean Buddhist monasteries of the Three Kingdoms Period have produced only a limited amount of information concerning the outer sanctuary, resulting in little evidence about the exact scope of the temple's sanctuary. Meanwhile, the excavations of the Hwangnyongsa Temple site have revealed the archaeological features of the walls that divided the monastery and its neighboring facilities, thus helping to delineate the size of the temple site. The excavations have revealed the boundaries between the inner and outer sanctuaries of Hwangnyongsa Temple, as well as the entire temple precincts and the exterior, providing valuable information about the changes made to the layout of the temple. In this study, the main discussion focuses on the changes made to the sanctuary of Hwangnyongsa Temple during the Unified Silla and Goryeo Periods, particularly in relation to the architectural layout of the temple. The discussion is based on a review of the periods in which the Nammunji(South Gate site) was built, which provides tangible evidence about the expansion of the temple to the south, and the walls enclosing the temple precincts on the four sides and the changes that occurred afterwards. As a result, the study concludes that both the inner and outer sanctuaries of the temple probably changed through the 1 st and 3rd. It also concludes that the changes made to the architectural layout of Hwangnyongsa Temple were intended not only to alter the scope of the temple but were also closely associated with the politico-geographical significance of its location at the center of the royal capital of Silla and the urban archaeological remains around it.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1463-1478
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• 2022

Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

• Journal of the Speleological Society of Korea
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• no.68
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• pp.23-73
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• 2005

Purpose of study; The purpose of this study is specifically classified as two parts. The one is to attempt the chronological annals of Quaternary topographic surface through the study over the formation process of alluvial surfaces in our country, setting forth the alluvial surfaces lower-parts of Han River area, as the basic deposit, and comparing it to the marginal landform surfaces. The other is to attempt the classification of micro morphology based on the and condition premising the land use as a link for the regional development in the lower-parts of Han river area. Reasons why selected the Lower-parts of Han river area as study objects: 1. The change of river course in this area is very serve both in vertical and horizontal sides. With a situation it is very easy to know about the old geography related to the formation process of topography. 2. The component materials of gravel, sand, silt and clay are deposited in this area. Making it the available data, it is possible to consider about not oかy the formation process of topography but alsoon the development history to some extent. 3. The earthen vessel, a fossil shell fish, bone, cnarcoal and sea-weed are included in the alluvial deposition in this area. These can be also valuable data related to the chronological annals. 4. The bottom set conglometate beds is also included in the alluvial deposits. This can be also valuable data related to the research of geomorphological development. 5. Around of this area the medium landform surface, lower landform surface, pediment and basin, are existed, and these enable the comparison between the erosion surfaces and the alluvial surfaces. Approach : 1. Referring to the change of river beds, I have calculated the vertical and horizontal differences comparing the topographic map published in 1916 with that published in 1966 and through the field work 2. In classifying the landform, I have applied the method of micro morphological classification in accordance with the synthetic index based upon the land conditions, and furthermore used the classification method comparing the topographic map published in 1916 and in that of 1966. 3. I have accorded this classification with the classification by mapping through appliying the method of classification in the development history for the field work making the component materials as the available data. 4. I have used the component materials, which were picked up form the outcrop of 10 places and bored at 5 places, as the available data. 5. I have referred to Hydrological survey data of the ministry of Construction (since 1916) on the overflow of Han-river, and used geologic map of Seoul metropolitan area. Survey Data, and general map published in 1916 by the Japanese Army Survbey Dept., and map published in 1966 by the Construction Research Laboratory and ROK Army Survey Dept., respectively. Conclusion: 1. Classification of Morphology: I have added the historical consideration for development, making the component materials and fossil as the data, to the typical consideration in accordance with the map of summit level, reliefe and slope distribution. In connection with the erosion surface, I have divided into three classification such as high, medium and low-,level landform surfaces which were classified as high and low level landform surfaces in past. furthermore I have divided the low level landform surface two parts, namely upper-parts(200-300m) and bellow-parts(${\pm}100m$). Accordingly, we can recognize the three-parts of erosion surface including the medium level landform surface (500-600m) in this area. (see table 22). In condition with the alluvial surfaces I have classified as two landform surfaces (old and new) which was regarded as one face in past. Meamwhile, under the premise of land use, the synthetic, micro morphological classification based upon the land condition is as per the draw No. 19-1. This is the quite new method of classification which was at first attempted in this country. 2. I have learned that the change of river was most severe at seeing the river meandering rate from Dangjung-ni to Nanjido. As you seee the table and the vertical and horizontal change of river beds is justly proportionable to the river meandering rate. 3. It can be learned at seeing the analysis of component materials of alluvial deposits that the component from each other by areas, however, in the deposits relationship upper stream, and between upper parts and below parts I couldn't always find out the regular ones. 4. Having earthern vessel, shell bone, fossil charcoal and and seaweeds includen in the component materials such as gravel, clay, sand and silt in Dukso and Songpa deposits area. I have become to attempt the compilation of chronicle as yon see in the table 22. 5. In according to hearing of basemen excavation, the bottom set conglomerate beds of Dukso beds of Dukso-beds is 7m and Songpa-beds is 10m. In according to information of dredger it is approx. 20m in the down stream. 6. Making these two beds as the standard beds, I have compared it to other beds. 7 The coarse sand beds which is covering the clay-beds of Dukso-beds and Nanjidobeds is shown the existence of so-called erosion period which formed the gap among the alluvial deposits of stratum. The former has been proved by the sorting, bedding and roundness which was supplied by the main stream and later by the branch stream, respectively. 8. If the clay-beds of Dukeo-bed and Songpa-bed is called as being transgressive overlap, by the Eustatic movement after glacial age, the bottom set conglomerate beds shall be called as being regressive overlap at the holocene. This has the closest relationship with the basin formation movement of Seoul besides the Eustatic movement. 9. The silt-beds which is the main component of deposits of flood plain, is regarded as being deposited at the Holocene in the comb ceramic and plain pottery ages. This has the closest relationship with the change of river course and river beds.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• 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.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• International Commerce and Information Review
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• v.10 no.4
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• pp.457-491
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• 2008

As stage equipment export markets along with special lighting service lack the attraction for already globally established businesses, such markets can be viewed as an advantageous opportunity for SMEs as in general. In reality, global businesses tend to focus on large construction projects and this indicates relatively less substantial markets such as stage equipment and special lighting service export are more suitable for SME businesses. However, possible problems may be recognized as following; doubtful capabilities by such businesses to join in the vast and competitive global market and pursue manufacturing and service based export. This point is also supported by the fact that such in general SME businesses have substantially less experience in exporting products and services abroad. Realizing the distinctive features of the Korean economy, it is unarguable that every sector and area of global market must be regarded and monitored closely. Hence, it can be argued that there is an imminent need for establishment of supportive institution to assist export process of combination of stage equipments and special lighting service. This study emphasizes the need to improve export process of stage equipments, special lighting services as well as other related products and services which have been focused in domestic market only until now. Further, it also analyzed the potential prospect of such direction reconciling current crisis our manufacturing industry is facing. Even though it maybe regarded as one of the niche market for export of Korea in the short term view, stage equipment and special lighting service industry may rapidly grow as the global cultural industries have grown along with the increase of national income earnings overall. Due to such advantageous features, it can be expected that such industries will show strong growth in the near future. After analyzing the fact that Korea's plants (eg. powerplants) export sector is at its boom, there is a need to transform stage equipment and special lighting service export market into a primary market from a secondary(niche) market for SMEs. This study is viewed from the Korean economic and export sector aspect in the aim of seeking a solution to conquest our realistic limit in our export sector by developing a suitable export model. There have been cases of very few attempts to expand abroad by SMEs who have failed miserably due to their failure to adapt to foreign culture, practice and languages as well as substantial lack in experience in export marketing. Despite this, neglecting our manufacturing industry as it is which is showing its limit and problems is out of option therefore, it is imminent that we come up with an effective measure to address this problem and service export can be suggested as one of them. This study reveals manufacturing-service export model of stage equipment and special lighting service and its related areas is recognized as a field with a very strong future and furthermore, it is expected to bring synergy effects in manufacturing and services sector as well. Further, the operation strategy contains combination, composition and fusion(convergence) of manufacturing and service sectors which could derive various of export products which displays greater success probability or this export model. The outcome of this research is expected to become a useful source for enterprises related to such industry which are seeking a possible global expansion. Furthermore, it is also expected to become a catalyst which fastens the process of global expansion and not only that, we are firmly assured that this study will become an opportunity to improve our current policies and institutions related to this area's export market.

• 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.