• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.161-165
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• 2008

This paper introduces three continuous sampling plans by attribute. Revised KS standards for acceptance samplings such as KSA ISO 2859-3, 4 : 2001 and 21247 : 2007 are presented. These plans are based on skip-lot, DQL(Declared Quality Level) and VL (Verification Level).

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.394-405
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• 2001

Since most real-world application data involve continuous-valued attributes, properly addressing the discretization process for constructing a decision tree is an important problem. A continuous-valued attribute is typically discretized during decision tree generation by partitioning its range into two intervals recursively. In this paper, by removing the restriction to the binary discretization, we present a hybrid multi-interval discretization algorithm for discretizing the range of continuous-valued attribute into multiple intervals. On the basis of experiment using semiconductor etching machine, it has been verified that our discretization algorithm constructs a more efficient incremental decision tree compared to previously proposed discretization algorithms.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.459-470
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.879-894
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• 2003

We evaluated the efficiencies of applying attribute selection methods and prior discretization to supervised learning, modelled by C4.5 and Naive Bayes. Three databases were obtained from UCI data archive, which consisted of continuous attributes except for one decision attribute. Four methods were used for attribute selection : MDI, ReliefF, Gain Ratio and Consistency-based method. MDI and ReliefF can be used for both continuous and discrete attributes, but the other two methods can be used only for discrete attributes. Discretization was performed using the Fayyad and Irani method. To investigate the effect of noise included in the database, noises were introduced into the data sets up to the extents of 10 or 20%, and then the data, including those either containing the noises or not, were processed through the steps of attribute selection, discretization and classification. The results of this study indicate that classification of the data based on selected attributes yields higher accuracy than in the case of classifying the full data set, and prior discretization does not lower the accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.463-468
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• 2011

Context prediction methods have been developed in two ways - one is a prediction for discrete context and the other is for continuous context. As most of the prediction methods have been used with prediction algorithms in specific domains suitable to the environment and characteristics of contexts, it is difficult to conduct a prediction for a user's context which is based on various environments and characteristics. This study suggests a context prediction method available for both discrete and continuous contexts without being limited to the characteristics of a specific domain or context. For this, we conducted a context prediction based on sequence matching by generating sequences from contexts in consideration of association rules between context attributes and by applying variable weights according to each context attribute. Simulations for discrete and continuous contexts were conducted to evaluate proposed methods and the results showed that the methods produced a similar performance to existing prediction methods with a prediction accuracy of 80.12% in discrete context and 81.43% in continuous context.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.397-401
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• 2007

Recent applications on continuous queries on moving objects are extended quickly to various parts. These applications need not only 2-dimensional space data but also high-dimensional space data. If we use previous index for overlapped continuous range queries on high-dimensional space data, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We focus on stationary queries, non-exponential increase of storage cost and efficient processing time for large data sets. In this paper, to solve these problems, we present a novel query indexing method, denoted as PAB(Projected Attribute Bit)-based query index. We transfer information of high-dimensional continuous range query on each axis into one-dimensional bit lists by projecting technique. Also proposed query index supports incremental update for efficient query processing. Through various experiments, we show that our method outperforms the CES(containment-encoded squares)-based indexing method which is one of the most recent research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.1-7
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• 2005

Data mining is widely used for turning huge amounts of data into useful information and knowledge in the information industry in recent years. When analyzing data set with continuous values in order to gain knowledge utilizing data mining, we often undergo a process called discretization, which divides the attribute's value into intervals. Such intervals from new values for the attribute allow to reduce the size of the data set. In addition, discretization based on rough set theory has the advantage of being easily applied. In this paper, we suggest a discretization algorithm based on Rough Set theory and SOM(Self-Organizing Map) as a means of extracting valuable information from large data set, which can be employed even in the case where there lacks of professional knowledge for the field.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.768-773
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• 2007

Standardization to information attribute of construction material is continuous demanded through the life cycle of a construction project, and the productivity elevation is derived of contribution effect in construction market. This study surveyed the means of acquisition and attribute of information to a staff in purchase, which are effected on the revitalization of information circulation to the construction material Proposed the standardization to information attribute of construction material that is based on improvement and application to the information attribute. And information attribute is classified with construction process through analysis on test list of quality certification. This study also suggested representative attribute of quality information, for the elevation of safety and quality in construction industry. Therefore, logicality of common information is based by analysis of mathematical statistics, systemicity of quality information is applied by MasterFormat(2004)

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.157-162
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• 2000

Discriminant analysis is a method to relate whether the objects have a specific characteristic or not with their 'continuous' attribute values and, for given objects, to estimate whether they have a specific characteristic or not by their values of discriminant scores gotten from their attribute values. The author developed the new 'computational' method of discriminant analysis without specific hypotheses or assumptions and, by this new method, we can find 'feasible' solutions under the conditions required by our actual problems. In this paper, the author tried to apply this new method to the discrimination of logical relations. If this trial could be a success, we can apply this new method of discriminant analysis to the problems about relating the specific characteristic of the objects with their 'discrete' attribute values. The result was successful and the applicability of discriminant analysis could be expanded as a method for constructing the models for "estimating impressions".

• Journal of the Korean Applied Science and Technology
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• v.39 no.2
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• pp.340-347
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• 2022

This study aimed to provide basic data on how to strengthen competitiveness and operate efficiently by differentiated selection attributes by identifying the influence between satisfaction and continuous participation intention, focusing on the selection attributes of Taekwondo studio perceived by parents. Therefore, parents who had registered at a Taekwondo studio located in the metropolitan area and participated in their children were selected as samples and surveyed from February 1 to 26, 2021, and a total of 386 copies of data were used for the final analysis. Data processing used the SPSS (ver.21.0) program to conduct frequency analysis, exploratory factor analysis, internal consistency, correlation analysis, simple and multiple regression analysis. The main results of this study are as follows. First, the selection attributes of Taekwondo studio has been shown to influence the satisfaction in the order of facilities and environment, master, cost and program. Second, the satisfaction has been shown to influence the continuous participation intention. Third, the selection attributes of Taekwondo studio has been shown to influence the continuous participation intention in the order of accessibility, facilities and environment, master and program.