• 한국통신학회논문지
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• 제33권11B호
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• pp.1020-1029
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• 2008

본 논문은 네트워크 침입 탐지 시스템에서 고속 패턴 매칭 알고리듬과 그 구조를 제안한다. 제안된 알고리듬은 실시간 입력 패킷에서 특정 패턴을 검사하며 정확한 문자열, 문자열 값의 범위, 그리고 문자열 값의 조합 등을 검색한다. 본 연구에서는 입력 패킷과 패턴은 동시에 겹치는 문자열들을 검색하기 위해 상태 전이 그래프로 모델링 하였으며 상태 전이 그래프는 구현 복잡도를 줄이기 위해 입력 임플리컨트 단위로 분할하였다. 제안된 패턴 매칭구조는 상태 전이 그래프와 입력된 문자열을 입력으로 사용한다. 제안된 패턴 매칭기는 VHDL 언어로 모델링하여 구현하였으며, 성능 분석을 통하여 제안된 기법의 적절성을 검증하였다.

• 센서학회지
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• 제17권6호
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.560-563
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• 1999

In this paper, we present an optimal hardware implementation for preprocessing of a person identification algorithm utilizing vein pattern of dorsal surface of hand. For the vein pattern recognition, the computational burden of the algorithm lies mainly in the preprocessing of the input images, especially in lowpass filtering. we could reduce the identification time to one tenth by hardware design of the lowpass filter compared to sequential computations. In terms of the computation accuracy, the simulation results show that the CSD code provided an optimized coefficient value with about 91.62% accuracy in comparison with the floating point implementation of current coefficient value of the lowpass filter. The post-simulation of a VHDL model has been performed by using the ModelSim$^{TM}$. The implemented chip operates at 20MHz and has the operational speed of 55.107㎳.㎳.

• 한국컴퓨터산업학회논문지
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• 제5권4호
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• pp.461-470
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• 2004

본 연구는 지하수 관정 인터페이스를 객체지향 기반으로 설계하였다. 복합적 형태의 현실 세계의 지리 객체를 위한 지리 데이터베이스 구현을 위하여 추상화 단계에서 분석 유형에 대하여 연구하였다. 응용영역에 적합한 유형을 규정하고 객체지향 방법론에 기반 한 UML을 이용하여 분석유형을 설계함으로서 대규모 개방 시스템을 개발하고 배포할 수 있는 컴포넌트의 재사용 성을 증가시키는데 기여하고자 한다.

• 한국IT서비스학회지
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• 제12권3호
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• pp.421-432
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• 2013

The changes in the game platform is appeared since the advent of smart-phones. Apple's iOS or Google's Android platform is gradually expanding their territories in the mobile game area. Android's platform fragmentation and the absence of game development framework act as barriers for game developments. In the development of game applications on the smart-phone, the standardized development procedures under game framework can achieve the productivity improvement. In this paper, we propose a new design pattern suitable for the design of a framework for new areas of application through the expansion of existing framework. The design and implementation of the Android game development framework is presented by taking advantage of existing design patterns and a proposed pattern. Also we propose the standardized development procedure of game applications under the proposed framework.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.187-190
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• 2000

In this paper, implementation of speech Recognizer system, Separated from Personal computer. By using DSP, this intends to extend the voice recognizing, limited into PC because of amount of data and calculations. For this performance The thesis uses the real time End point detector and organizes no additional device between human and the system, characteristic vector are that detects End point and voice from absolute energy and ZCR, that uses 12 difference Cepstrum from LPC, that uses the method to compensate the process of pattern separating and pre-calculated standard pattern limitation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.211-212
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• 2013

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 대한원격탐사학회지
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• 제22권5호
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 한국광학회:학술대회논문집
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• 한국광학회 1991년도 광학 및 양자전자학 워크샵
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• pp.33-39
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• 1991

We have developed a new holographic associative memory(HAN) based on an adaptive learning which uses learning pattern method (LPM). The LPM utilizes the simple optical implementation of outer-product learning, performance of adapitive learning. simulation are represented.