• Journal of KIISE:Software and Applications
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• v.29 no.6
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• pp.367-376
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• 2002

XML allows users to define elements using arbitrary words and organize them in a nested structure. These features of XML offer both challenges and opportunities in information retrieval and document management. In this paper, we propose a new methodology for computing similarity considering XML semantics - meanings of the elements and nested structures of XML documents. We generate extended-element vectors, using thesaurus, to normalize synonyms, compound words, and abbreviations and build similarity matrix using them. And then we compute similarity between XML elements. We also discover and minimize XML structure using automata(NFA(Nondeterministic Finite Automata) and DFA(Deterministic Finite automata). We compute similarity between XML structures using similarity matrix between elements and minimized XML structures. Our methodology considering XML semantics shows 100% accuracy in identifying the category of real documents from on-line bookstore.

• Journal of KIISE
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• v.44 no.3
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• pp.239-245
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• 2017

Probabilistic grammar is used in natural language processing, and the parse result of the grammar has to preserve the probability of the original grammar. As for the representative parsing method, LL parsing and LR parsing, the former preserves the probability information of the original grammar, but the latter does not. A characteristic of a probabilistic parsing automaton has been studied; but, currently, the generating model of probabilistic parsing automata has not been known. The paper provides a model of probabilistic parsing automata based on the single state parsing automata. The generated automaton preserves the probability of the original grammar, so it is not necessary to test whether or not the automaton is probabilistic parsing automaton; defining a probability function for the automaton is not required. Additionally, an efficient automaton can be constructed by choosing an appropriate parameter.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.361-367
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• 2011

In this paper, we propose encryption method to using complemented MLCA(Maximum Length Cellular Automata) based on NBCA(Null Boundary CA) and 2D CAT (Two-Dimensional Cellular Automata Transform) for efficient image encryption. The encryption method is processed in the following order. First, a transition matrix T is created using the Wolfram Rule matrix. Then, the transition matrix T is multiplied to the original image that is intended to be encrypted, which transfers the pixel values of the original image. Furthermore, the converted original image goes through a XOR operation with complemented vector F to convert into a complemented MLCA applied image. Then, the gateway value is set and 2D CAT basis function is created. Also, the 2D CAT is encrypted by multiplying the created basis function to the complemented MLCA applied image. Lastly, the stability analysis verifies that proposed method holds a high encryption quality status.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1050-1052
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• 1987

This study presents mental model based on cognitive psychology and deals with implementation of associative comparator using learning automata with random access memories.

• Journal of the Chungcheong Mathematical Society
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• v.30 no.3
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• pp.305-311
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• 2017

We investigate periodicities of characteristic matrices of some hybrid cellular automata configured with rules 60 and 102 and an intermediate boundary condition.

• Journal for History of Mathematics
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• v.12 no.1
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• pp.73-81
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• 1999

We survey the researches on self-reproducing structures on cellular automata. Self-reproduction is the foremost characteristic of life, and cellular automata are ideal model for studying artificial life. From the early studies by Von Neumann to late results on computational models using self-reproducing structures and emergence of self-replication are covered. Also possible applications of self-replicating structures are listed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.711-714
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• 2001

We present a detailed analysis of the behavior of a multiple-attractor cellular automata.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.263-266
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• 1996

Cellular Automata are a discrete mathematical system whose evolution is governed by a deterministic rule involving local interactions. In this paper, one designed and implemented the evolution system based on GUI which can analyse how random intitial stated evolve easily.

• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.186-190
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• 2005