• Journal of KIISE:Databases
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• v.29 no.3
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• pp.217-229
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• 2002

Regular path expressions are primary elements for formulating queries over the semistructured data that does not assume the conventional schemas. In addition, the query pruning is an important optimization technique to avoid useless traversals in evaluating regular path expressions. However, the existing query pruning often fails to fully optimize multiple regular path expressions, and the previous methods that post-process the result of the existing query pruning must check exponential combinations of sub-results. In this paper, we present a new query pruning technique that consists of the preprocessing phase and the pruning phase. Our two-phase query pruning is affective in optimizing multiple regular path expressions, and is more scalable than the previous methods in that it never check the exponential combinations of sub-results.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.107-123
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• 2006

We propose the Generalized Binary Second-order Recurrent Neural Networks(GBSRNNf) being equivalent to regular grammars and ?how the implementation of lexical analyzer recognizing the regular languages by using it. All the equivalent representations of regular grammars can be implemented in circuits by using GSBRNN, since it has binary-valued components and shows the structural relationship of a regular grammar. For a regular grammar with the number of symbols m, the number of terminals p, the number of nonterminals q, and the length of input string k, the size of the corresponding GBSRNN is $O(m(p+q)^2)$ and its parallel processing time is O(k) and its sequential processing time, $O(k(p+q)^2)$.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.395-404
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• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.

• Journal of IKEEE
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• v.22 no.1
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• pp.87-92
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• 2018

Like CPUs, regular expression processors that perform regular expression pattern matching using instructions have been proposed recently. Of these, only REMPc provides features for character class matching. In this paper, we propose an architecture for efficient character class matching in a regular expression processor, which use character class bitmap format in a instruction operand field and implement the hard-wired character class comparator for several frequently used character classes. Using the proposed method, most of the character classes used in Snort rule can be represented by an operand or an instruction. Thus, character class matching can be performed more efficiently in the proposed archiecture than in REMPc.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.5
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• pp.419-433
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• 2004

As XML becomes a standard for data representation, integration, and exchange on the Web, several XML query languages have been proposed. World Wide Web Consortium(W3C) has proposed XQuery as a standard for the XML query language. Like SQL, XQuery allows nested queries. Thus, normalization rules have been proposed to transform nested XQuery queries to semantically equivalent ones that could be executed more efficiently. However, previous normalization rules are applicable only to restricted forms of nested XQuery queries. Specifically, they can not handle FLWR expressions having nested expressions in the where clause. In this paper, we propose normalization rules for XQuery queries by extending those for SQL queries. Our proposed rules can handle FLWR expressions haying nested expressions in every clause. The major contributions of this paper are as follows. First, we classily nesting types of XQuery queries according to the existence of correlation and aggregation. We then propose normalization rules for each nesting type. Second, we propose detailed algorithms that apply the normalization rules to nested XQuery queries.

• Digital Contents
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• no.10 s.65
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• pp.107-111
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• 1998

필자는 정규화가 실현할 수 없는 몇가지 것들에 대하여 이야기하는 것을 끝으로 정규화에 관한 연재를 마치고자 한다.(우리가 크게 의존하는 기술이 가진 한계점들을 이해하는 일은 항상 중요하다.) 이러한 본인의 견해가 정규화에 대한 어떠한 종류의 비난도 아니라는 점을 분명히 하고자 한다. 그와 정반대로 필자는 과거에 정규화가 '예술에 가까운 노력에 의해 탄생한' 진정한 과학의 한 부분으로 표현한적이 있다. 그 노력이라 함은 물론 데이터베이스 설계이다.(실상 우리는 과거에 비해 조금 더 발달된 과학 기술을 접한다. 하지만 데이터베이스 설계는 여전히 주관적인 판단에 따른 문제라는 기본 사실은 아직도 유효하다.) 정규화는 주관적이기보다 객관적이라는 믿을만한 주장이 있지만, 이러한 주장과 전혀 일치하지 않는 데이터베이스 설계상의 몇 가지 경우도 있다는 사실도 여전히 존재한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.487-490
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• 2003

기계번역 시스템에서 복합단위 처리는 원문의 분석 부담을 줄이고 조합적으로 대역문의 의미를 생성하지 못하는 원문의 처리를 위해 필수적이다. 본 논문에서는 정규표현(Regular Expression)을 이용하여 영어의 연속(Non-Interrupted) 및 불연속(Interrupted) 복합 단위를 인식하는 복합단위 인식기를 제안한다. 제안된 방법은, 기존에 trie 와 같은 index 의 갱신 과정이 불필요하므로, 다수의 작업자에 의해 복합단위 사전을 동시에 구축하는 경우에, 한 작업자의 결과가 실시간으로 다른 작업자의 작업에 반영되는 장점이 있으며, 복합단위 인식에 있어 정규 표현을 이용함으로써 복합단위 인식기의 성능을 선언적으로 향상시킬 수 있다. 번역 실행시의 고속 탐색을 위해서는 전체 복합단위로부터 FSA(finite State Automata) 를 자동으로 구축하여 빠른 속도로 인식 가능하도록 하였다.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4
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• pp.210-216
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• 2005

We Propose a new feature normalization scheme based on eigenspace for achieving robust speech recognition. In general, mean and variance normalization (MVN) is Performed in cepstral domain. However, another MVN approach using eigenspace was recently introduced. in that the eigenspace normalization Procedure Performs normalization in a single eigenspace. This Procedure consists of linear PCA matrix feature transformation followed by mean and variance normalization of the transformed cepstral feature. In this method. 39 dimensional feature distribution is represented using only a single eigenspace. However it is observed to be insufficient to represent all data distribution using only a sin91e eigenvector. For more specific representation. we apply unique na independent eigenspaces to cepstra, delta and delta-delta cepstra respectively in this Paper. We also normalize training data in eigenspace and get the model from the normalized training data. Finally. a feature space rotation procedure is introduced to reduce the mismatch of training and test data distribution in noisy condition. As a result, we obtained a substantial recognition improvement over the basic eigenspace normalization.

• Proceedings of the Korean Statistical Society Conference
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• 2001.11a
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• pp.131-136
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• 2001

projection pursuit을 이용하여 이변량 정규분포의 적합도 검정을 위한 통계량을 제안한다. 기본적인 생각은 이변량 정규분포의 가정하에 표준정규분포를 갖는 모든 선형조합을 고려하여 이들의 순서통계량과 이론적인 분위수를 비교하는 것이다. 이와 같이 제안된 통계량은 선형변환에 대해서 불변(invariant)이다. 본 논문에서는 제안된 통계량의 극한분포를 적절한 Gaussian process의 적분으로 표현한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1207-1212
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• 2013

Arithmetic operations over finite fields are widely used in coding theory and cryptography. In both of these applications, there is a need to design low complexity finite field arithmetic units. The complexity of such a unit largely depends on how the field elements are represented. Among them, representation of elements using a optimal normal basis is quite attractive. Using an algorithm minimizing the number of 1's of multiplication matrix, in this paper, we propose a multiplier which is time and area efficient over finite fields with optimal normal basis.