• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.473-480
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• 2006

Extraction is tile most important step in global minimization. Its approache is to identify and extract subexpressions, which are multiple-cubes or single-cubes, common to two or more expressions which can be used to reduce the total number of literals in a Boolean network. Extraction is described as either algebraic or Boolean according to the trade-off between run-time and optimization. Boolean extraction is capable of providing better results, but difficulty in finding common Boolean divisors arises. In this paper, we present a new method for Boolean extraction to remove the difficulty. The key idea is to identify and extract two-cube Boolean subexpression pairs from each expression in a Boolean network. Experimental results show the improvements in the literal counts over the extraction in SIS for some benchmark circuits.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3251-3257
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• 2011

This paper presents a new Boolean extraction technique for logic synthesis. This method extracts kernel-kernel pairs as well as cokernel-kernel pairs. The given logic expressions can be translated into Boolean divisors and quotients with kernel-kernel pairs. Next, kernel intersection method provides the common sub-expressions for several logic expressions. Experimental results show the improvement in literal count over previous other extraction methods.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.9-16
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• 2008

This paper presents a new Boolean extraction technique for logic synthesis. This method extracts two-cube Boolean subexpression pairs from each logic expression. It begins by creating two-cube array, which is extended and compressed with complements of two-cube Boolean subexpressions. Next, the compressed two-cube array is analyzed to extract common subexpressions for several logic expressions. The method is greedy and extracts the best common subexpression. Experimental results show the improvements in the literal counts over well-known logic synthesis tools for some benchmark circuits.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.67-84
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• 2012

An important amount of clinical data concerning the medical history of a patient is in the form of clinical reports that are written by doctors. They describe patients, their pathologies, their personal and medical histories, findings made during interviews or during procedures, and so forth. They represent a source of precious information that can be used in several applications such as research information to diagnose new patients, epidemiological studies, decision support, statistical analysis, and data mining. But this information is difficult to access, as it is often in unstructured text form. To make access to patient data easy, our research aims to develop a system for extracting information from unstructured text. In a previous work, a rule-based approach is applied to a clinical reports corpus of infectious diseases to extract structured data in the form of named entities and properties. In this paper, we propose the use of a Boolean inference engine, which is based on a cellular automaton, to do extraction. Our motivation to adopt this Boolean modeling approach is twofold: first optimize storage, and second reduce the response time of the entities extraction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3715-3722
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• 2011

This paper presents a new Boolean extraction technique for logic synthesis. This method first calculates divisor/2-cube quotients, 2-cube quotient pairs, and 2-cube quotient matrices. Then we find candidates, which can be common sub-expressions, from 2-cube quotients and matrices. Next, candidate intersection provides the common sub-expressions for several logic expressions. Experimental results show the improvements in literal counts over the previous methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1325-1328
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• 2006

본 논문은 기계 가공시 형상의 인지 절차에 대해 기술한다. 주조와 단조 공정의 특성 중 한가지는 기계 가공시 원재료가 최종 형상에 매우 근접하다는 것이다. 이때 가공 형상 추출은 가공될 면을 인지하는 것과 가공면을 군집으로 그룹화 하는 두 단계로 수행될 수 있다. 이중 가공될 면을 인지하기 위한 기존의 방법은 3D Boolean difference operation을 수행하는 것이다. 그러나 3D Boolean difference operation의 계산적 난점 때문에 복잡한 형상에는 실용적이지 못하다. 본 논문의 목적은 가공 면을 인지하는 효율적인 알로리즘을 개발하는 것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2214-2218
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• 2010

Association rule is one of meaning and useful extraction methods from large amounts of data, and furnish useful information to user for data describing a pattern or similarity among attributes in database. Association rule have been studied about existence and nonexistence rule in boolean database. In this paper, we propose an intelligent query system using fuzzy association rule by extraction association rule changing a quantitative attribute data to a nominal attribute value.

• Journal of the Korean Society for Library and Information Science
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• v.33 no.2
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• pp.119-139
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• 1999

It Is the purpose of this research to analyse users' understanding how keyword and boolean search work in SELIS(SEoul Women's University Library and Information System) OPAC. Results of analyses of the subject, SELIS OPAC system processing, are: comprehension percentage of keyword extraction is $67(22.48\%)$ out of total 298 persons, no comprehension is $231(77.52\%)$ understanding of boolean OR In keyword search appears $115(22.48\%)$ out of 297, no understanding does $182(77.52\%)$ : comprehension of boolean AND is $98(33.11\%)$ out of 296, no understanding appears $198(66.89\%)$ understanding of using boolean and symbols is $109(36.49\%)$ out of 285, no understanding is $181(63.51\%)$ which Is lower percentage generally. And in SELIS OPAC system, in Intentional analyses to see any difference in understanding of keyword search between experience of keyword search or no, It shows no difference in interrelation $5\%$ level of significance, but In boolean search it does in interrelation $5\%$ level of significance.

• Korean Journal of Computational Design and Engineering
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• v.4 no.1
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• pp.43-51
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• 1999

Producing the relevant information (features) from the CAD models of CAM, called feature recognition or extraction, is the essential stage for the integration of CAD and CAM. Most feature recognition methods, however, have problems in the recognition of intersecting features because they do not handle the intersection geometry properly. In this paper, we propose a machining feature recognition algorithm, which has a solid model consisting of orthogonal primitives as input. The algorithm calculates candidate features and constitutes the Intersection Geometry Matrix which is necessary to represent the spatial relation of candidate features. Finally, it recognizes machining features from the proposed candidate features dividing and growing systems using half space and Boolean operation. The algorithm has the following characteristics: Though the geometry of part is complex due to the intersections of design primitives, it can recognize the necessary machining features. In addition, it creates the Maximal Feature Volumes independent of the machining sequences at the feature recognition stage so that it can easily accommodate the change of decision criteria of machining orders.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5744-5749
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• 2014

An extraction technique for a common logic expression is an extremely important part of multiple-output logic synthesis. This paper presents a new Boolean extraction technique using an exclusive-OR logic synthesis principle. The logic circuits produced only have AND, OR and NOT gates. Heuristic methods can also be applied to reduce the execution time and the number of literals. The experimental results showed improvements in the literal counts over the previous methods.