• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.413-413
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• 2010

In semiconductor manufacturing field, all equipments have various sensors to diagnosis the situations of processes. For increasing the accuracy of diagnosis, hundreds of sensors are emplyed. As sensors provide millions of data, the process diagnosis from them are unrealistic. Besides, in some cases, the results from some data which have same conditions are different. We want to find some information, such as data and knowledge, from the data. Nowadays, fault detection and classification (FDC) has been concerned to increasing the yield. Certain faults and no-faults can be classified by various FDC tools. The uncertainty in semiconductor manufacturing, no-faulty in faulty and faulty in no-faulty, has been caused the productivity to decreased. From the uncertainty, the rough set theory is a viable approach for extraction of meaningful knowledge and making predictions. Reduction of data sets, finding hidden data patterns, and generation of decision rules contrasts other approaches such as regression analysis and neural networks. In this research, a RGB sensor was used for diagnosis plasma instead of optical emission spectroscopy (OES). RGB data has just three variables (red, green and blue), while OES data has thousands of variables. RGB data, however, is difficult to analyze by human's eyes. Same outputs in a variable show different outcomes. In other words, RGB data includes the uncertainty. In this research, by rough set theory, decision rules were generated. In decision rules, we could find the hidden data patterns from the uncertainty. RGB sensor can diagnosis the change of plasma condition as over 90% accuracy by the rough set theory. Although we only present a preliminary research result, in this paper, we will continuously develop uncertainty problem solving data mining algorithm for the application of semiconductor process diagnosis.

• Journal for History of Mathematics
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• v.10 no.1
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• pp.19-32
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• 1997

This paper deals with the relationship between the order structure and topological structure in the historical point of view. We first investigate how the order structure has developed along with the set theory and logic in the second half of the nineteenth century. After the general topology has emerged in the beginning of the twentieth century, two disciplines of the order theory and topology give each other a great deal of effect for their development via various dualities, compactifications by maximal filter spaces and Alexandroff's specialization order, which form eventually a fundamental setting for the development of the category theory or functor theory.

• Journal of Gifted/Talented Education
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• v.5 no.2
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• pp.37-54
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• 1995

The radical development of modern mathematics is due to the appearance of Collection Theory by George Cantor. The Set Theory is independent as an area and also closely interrelated with other areas. So its content becomes a common sense and a basic part across the whole area of modern mathematics. Accordingly, the basic element of modern mathematics is helping young children get familiar with set as early as possible. The thinking of set by which children can categorize, make partial sets and correspondences, understand the general characteristic, and conceptualize the discovered relationships is very important for young children. At this point where the Math education for young children is emphasized under the influence of the modernization movement of Math education, the systematic education for building up the set concept as the basic background of number concept during the early childhood is required. On current mathematics education for young children, graphs, the foundation of geometry, time, and patterns have been included in the traditional and practical content related to numbers. However, the education on collection which is the foundation of number concept is insufficient. A study shows that the level of young children's understanding on set is quite high, but the set concept isn't reflected in current Math curriculum for young children. And basic activities neccesary on building up the set concept, such as categorization, comparison, etc. are conducted in kindergardens but unsatisfactory because of those kindergarden teachers' premature understanding on the set concept. In conclusion, the curriculum for young children should be reorganized based on the set concept as the kernel concept. Also, the reappraisal of the training curriculum and the supplementary efucation for kindergarden teachers are urgent for raising the teaching ability of those kindergarden teachers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.662-674
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• 1997

In order to post process the vector-quantized images employing the theory of projections onto convex sets or the constrained minimization technique, the the projector onto QCS(quantization constraint set) as well as the filter that smoothes the lock boundaries should be investigated theoretically. The basic idea behind the projection onto QCS is to prevent the processed data from diverging from the original quantization region in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in the vector quantization are arbitrarilly shaped unless the vector quantization has a structural code book, the implementation of the projection onto QCS is very complicate. This paper mathematically analyzes the projection onto QCS from the viewpoit of minimizing the mean square error. Through the analysis, it has been revealed that the projection onto a subset of the QCS yields lower distortion than the projection onto QCS does. Searching for an optimal constraint set is not easy and the operation of the projector is complicate, since the shape of optimal constraint set is dependent on the statistical characteristics between the filtered and original images. Therefore, we proposed a hyper-cube as a constraint set that enables a simple projection. It sill be also shown that a proper filtering technique followed by the projection onto the hyper-cube can reduce the quantization distortion by theory and experiment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.19-26
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• 2015

This paper proposes a design method for improving the frequency-domain performance reliability of dynamic systems with uncertain and degrading components. Discrete frequencies are used in this method as surrogates for the frequency band of interest, and the conformance of the frequency responses to the specification at these frequencies is utilized to model the frequency-domain performance reliability. A meta-model for the frequency responses, an extreme-value event, and the set-theory are integrated to improve the computational efficiency of the reliability estimation. In addition, a sample-based approach is presented to evaluate and optimize the estimated performance reliability. A case study of a vibration absorber system showed that the proposed design method has engineering applications.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.137-146
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• 2005

This paper describes a research work to develop a computer-aided design for the product made by progressive working of bending and piercing. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of three main modules, which are input and shape treatment, flat pattern layout, strip layout modules. The system is designed by considering several factors, such as piercing and bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic forms, including piercing and bending sequences with punch profiles divided into for external area. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1529-1532
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• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.965-967
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• 2013

The paper proposed the DRCS(Disease Rule Creation Scheme) which generates the disease rules for efficient disease management in Healthcare system. The DRCS uses basically Rough Set Theory and computes support between each attributes and decision attributes. It creates the disease rules that judges disease after it removes the attribute which is the lowest support. Therefore, it reduces the number of disease rules and improves the exactness, compared with C4.5 algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.162-169
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• 2015

In this research, technology innovation capability evaluation model for small and medium enterprises was developed. To develop technology innovation capability evaluation model, two analytic technic was used. First one is AHP (Analytic Hierarchy Process) to give weight to each main index. Second one is fuzzy set theory to represent ambiguous index to numerical value. Finally, technology innovation capability evaluation model was achieved in combination with the same weight to AHP analysis and fuzzy set theory. With these results, small and medium enterprises can know important point in terms of strengthening the innovation capability evaluation.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.113-119
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• 2008

The World Wide Web is a dynamic collection of pages that includes a huge number of hyperlinks and huge volumes of usage informations. The resulting growth in online information combined with the almost unstructured web data necessitates the development of powerful web data mining tools. Recently, a number of approaches have been developed for dealing with specific aspects of web usage mining for the purpose of automatically discovering user profiles. We analyze sequence data, such as web-logs, protein sequences, and retail transactions. In our approach, we propose the clustering algorithm for sequence data using rough set theory. We present a simple example and experimental results using a splice dataset and synthetic datasets.