• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.8
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• pp.707-716
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• 2013

Tire noise is divided into two parts. One is pattern noise the other one is road noise. Pattern noise primarily occurs in over 500 Hz frequency but road noise occurs mainly in low frequency. It is important to develop a technology to predict the pattern noise at the design stage. Prediction technology of pattern noise has been developed by using image processing. Shape of tire pattern is computed by using imaging signal processing. Its results are different with the measured one. Therefore, the prediction of actual measured pattern noise is valuable. In the signal processing theory is applied to calculate the impulse response for the measurement environment. This impulse response used for the prediction of pattern noise by convolving this impulse response by the results of image processing of tire pattern.

• ETRI Journal
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• v.31 no.4
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• pp.463-465
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• 2009

In this letter, we present an event stream processing system that can evaluate a pattern query for a data sequence with predicates. We propose a pattern query language and develop a pattern query processing system. In our system, we propose novel techniques for run-time aggregation and negation processing and apply our system to stream data generated from vehicles to monitor unusual driving patterns.

• The Journal of Korean Medicine
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• v.41 no.3
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• pp.1-8
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• 2020

Objectives: This paper aims to investigate the Donguibogam-based pattern diagnosis by applying natural language processing and machine learning. Methods: A database has been constructed by gathering symptoms and pattern diagnosis from Donguibogam. The symptom sentences were tokenized with nouns, verbs, and adjectives with natural language processing tool. To apply symptom sentences into machine learning, Word2Vec model has been established for converting words into numeric vectors. Using the pair of symptom's vector and pattern diagnosis, a pattern prediction model has been trained through Logistic Regression. Results: The Word2Vec model's maximum performance was obtained by optimizing Word2Vec's primary parameters -the number of iterations, the vector's dimensions, and window size. The obtained pattern diagnosis regression model showed 75% (chance level 16.7%) accuracy for the prediction of Six-Qi pattern diagnosis. Conclusions: In this study, we developed pattern diagnosis prediction model based on the symptom and pattern diagnosis from Donguibogam. The prediction accuracy could be increased by the collection of data through future expansions of oriental medicine classics.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.157-165
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• 2002

This paper describes our ongoing Korean-Chinese machine translation system, which is based on verb patterns. A verb pattern consists of a source language pattern part for analysis and a target language pattern part for generation. Knowledge description on lexical level makes it easy to achieve accurate analyses and natural, correct generation. These features are very important and effective in machine translation between languages with quite different linguistic structures including Korean and Chinese. We performed a preliminary evaluation of our current system and reported the result in the paper.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.262-267
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• 2003

At process of production according to development of accumulation degree of semi-conductor element, because functional mistake examination time required increases, is becoming big obstacle factor in cost-cutting. Studied pattern generator that generate pattern and address that is bundle enemy to process these controversial point effectively.

• Proceedings of the Korean Society of Laser Processing Conference
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• 2000.11a
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• pp.51-59
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• 2000

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2367-2370
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• 2003

A fast pattern classification algorithm with Cellular Parallel Processing Network-based dynamic programming is proposed. The Cellular Parallel Processing Networks is an analog parallel processing architecture and the dynamic programming is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast Pattern classification with optimization is formed. On such CPPN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1385-1402
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• 2019

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.838-841
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• 2005

DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

• Design & Manufacturing
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• v.12 no.1
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• pp.47-51
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• 2018

As the IT industry rapidly progresses, the functions of electronic devices and display devices are integrated with high density, and the model is changed in a short period of time. To implement the integration technology, a uniform micro-pattern implementation technique to drive and control the product is required. The most important technology for the micro pattern generation is the exposure processing technology. Failure to implement the basic pattern in this process cannot satisfy the demands in the manufacturing field. In addition, the conventional exposure method of the mask method cannot cope with the small-scale production of various types of products, and it is not possible to implement a micro-pattern, so an alternative technology must be secured. In this study, the technology to implement the required micro-pattern in semiconductor processing is presented through the photolithography process and plasma etching.