• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11B
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• pp.1020-1029
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• 2008

This paper proposes an high speed pattern matching algorithm and its implementation. The pattern matcher is used to check patterns from realtime input packet. The proposed algorithm can find exact string, range of string values, and combination of string values from input packet at high speed. Given string and rule set are modelled as a state transition graph which can find overlapped strings simultaneously, and the state transition graph is partitioned according to input implicants to reduce implementation complexity. The pattern matcher scheme uses the transformed state transition graph and input packet as an input. The pattern matcher was modelled and implemented in VHDL language. Experimental results show the proprieties of the proposed approach.

• Journal of Sensor Science and Technology
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• v.17 no.6
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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.

• Proceedings of the IEEK Conference
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• 1999.11a
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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㎳.㎳.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.461-470
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• 2004

This paper is to design the user interface of the groundwater well based on an object oriented. In order to implementation geographic data base of the an complex geo-object of the real world, this paper is the study of analysis pattern at the level By specifying the pattern appropriate to the application domain and designing the analysis pattern using the UML based on the object oriented methodology, this paper shall contribute to enhance the reuse of components that can develop and distribute a large scale open system.

• Journal of Information Technology Services
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• v.12 no.3
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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.

• Proceedings of the IEEK Conference
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• 2000.11d
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.211-212
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• 2013

• Proceedings of the KSRS Conference
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• v.2
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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.

• Korean Journal of Remote Sensing
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• v.22 no.5
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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.

• Proceedings of the Optical Society of Korea Conference
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• 1991.07a
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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.