• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.54-60
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• 1996

In most pattern recognition and image understanding applications, images are degraded by noise and other distortions. Therefore, it is more relevant to decide how similar two objects are rather than to decide whether the two are exactly the same. In this paper, we propose a method for recognizing degraded symbols using a distance measure between two graphs representing the symbols. a symbol is represented as a graph consisting of nodes and edges based on the run graph concept. The graph is then transformed into a reference model graph with production rule containing the embedding transform. The symbols are recognized by using the distance measure which is estimated by using the number of production rules used and the structural homomorphism between a transformed graph and a model graph. the proposed approach is applies to the recognition of non-note musical symbols and the result are given.

• Plant Journal
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• v.17 no.3
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• pp.37-41
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• 2021

P&ID((Piping and Instrument Diagram) is a key drawing in the engineering industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks like listing symbols in P&ID drawings have been done manually, consuming lots of time and manpower. Currently, a deep learning model based on CNN(Convolutional Neural Network) is studied for drawing object detection, but the detection time is about 30 minutes and the accuracy is about 90%, indicating performance that is not sufficient to be implemented in the real word. In this study, the detection of symbols in a drawing is performed using 1-stage object detection algorithms that process both region proposal and detection. Specifically, build the training data using the image labeling tool, and show the results of recognizing the symbol in the drawing which are trained in the deep learning model.

• Convergence Security Journal
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• v.23 no.5
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• pp.3-8
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• 2023

The Fourth Industrial Revolution is bringing about great changes in many industrial fields, and among them, active research is being conducted on convergence technology using artificial intelligence. Among them, the demand is increasing day by day in the field of object recognition using artificial intelligence and digital transformation using recognition results. In this paper, we proposed an optimal learning model construction method to accurately recognize letters, symbols, and lines in images and save the recognition results as files in a standardized format so that they can be used in simulations. In order to recognize letters, symbols, and lines in images, the characteristics of each recognition target were analyzed and the optimal recognition technique was selected. Next, a method to build an optimal learning model was proposed to improve the recognition rate for each recognition target. The recognition results were confirmed by setting different order and weights for character, symbol, and line recognition, and a plan for recognition post-processing was also prepared. The final recognition results were saved in a standardized format that can be used for various processing such as simulation. The excellent performance of building the optimal learning model proposed in this paper was confirmed through experiments.

• Journal of the Korean Society of Costume
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• v.54 no.2
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• pp.135-148
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• 2004

The purpose of this thesis is to examine how typography, which has become apparent in many areas of modern society, is expressed, portrayed and how its value, function and significance in fashion can be understood. In order to undertake this study, the concept of typography was examined in detail, the verbal and formative function of typography carefully considered, and the different types of typography were analyzed and categorized in to the below areas : - Typography for the increasing of brand logo recognition - Typography as a social slogan - Typography for the increasing of collective belongingness - Typography as an image - Typography as a symbol. As a result, the typography plays an important role of a verbal tool in modern fashion design. Through typography, fashion was able to explain in much detail the overstatement of society criticizing character and functionality of information conveyance. However, the role of typography will continue to change and evolve according to the constant changes of fashion

• ETRI Journal
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• v.38 no.5
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• pp.896-902
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• 2016

Luby transform (LT) codes were the first practical rateless erasure codes proposed in the literature. The performances of these codes, which are iteratively decoded using belief propagation algorithms, depend on the degree distribution used to generate the coded symbols. The existence of degree-one coded symbols is essential for the starting and continuation of the decoding process. The absence of a degree-one coded symbol at any instant of an iterative decoding operation results in decoding failure. To alleviate this problem, we proposed a method used in the absence of a degree-one code symbol to overcome a stuck decoding operation and its continuation. The simulation results show that the proposed approach provides a better performance than a conventional LT code and memory-based robust soliton distributed LT code, as well as that of a Gaussian elimination assisted LT code, particularly for short data lengths.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5C
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• pp.371-377
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• 2008

In this paper, we present a framework for vision-based two-arm gesture recognition. To capture the motion information of the hands, we perform color-based tracking algorithm using adaptive kernel for each frame. And a feature selection algorithm is performed to classify the motion information into four different phrases. By using gesture phrase information, we build a gesture model which consists of a probability of the symbols and a symbol sequence which is learned from the longest common subsequence. Finally, we present a similarity measurement for two-arm gesture recognition by using the proposed gesture models. In the experimental results, we show the efficiency of the proposed feature selection method, and the simplicity and the robustness of the recognition algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2356-2376
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• 2021

In this paper, we proposed a novel modulation recognition method based on quantum elephant herding algorithm (QEHA) evolving neural network under impulse noise environment. We use the adaptive weight myriad filter to preprocess the received digital modulation signals which passing through the impulsive noise channel, and then the instantaneous characteristics and high order cumulant features of digital modulation signals are extracted as classification feature set, finally, the BP neural network (BPNN) model as a classifier for automatic digital modulation recognition. Besides, based on the elephant herding optimization (EHO) algorithm and quantum computing mechanism, we design a quantum elephant herding algorithm (QEHA) to optimize the initial thresholds and weights of the BPNN, which solves the problem that traditional BPNN is easy into local minimum values and poor robustness. The experimental results prove that the adaptive weight myriad filter we used can remove the impulsive noise effectively, and the proposed QEHA-BPNN classifier has better recognition performance than other conventional pattern recognition classifiers. Compared with other global optimization algorithms, the QEHA designed in this paper has a faster convergence speed and higher convergence accuracy. Furthermore, the effect of symbol shape has been considered, which can satisfy the need for engineering.

• International Journal of Quality Innovation
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• v.9 no.2
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• pp.79-89
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• 2008

Each amusement park has a wayfinding system, while symbols are important mediums to guide tourists to find their destinations. It is very important that whether the meanings of symbols recognized by tourists immediately. This paper mainly discusses the recognition of graphic symbols in amusement park, and proposes the improvement suggestions. Materials for this study were drawn from 20 different graphic symbols of a theme amusement park in Taiwan. The testees were required to evaluate the design of graphic symbols based on symbolic meaning and graphics recognition to summarize the confusion matrix. The results show that there are three groups of graphic symbols easy to be confused, and five symbols not meeting a criterion of 67% correct responses. The reasons were discussed, and improvement and relevant suggestions have been proposed, which may be helpful to redesign of symbols.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.188-194
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• 2008

We propose the new method for the traffic signs recognition that is one of the DAS(Driving assistance system) in the intelligent vehicle. Our approach estimates a varied degree by using a geometric method from the varied traffic signs in noise, rotation and size, and extracts the recognition symbol from the compensated traffic sign for a recognition by using the sequential color-based clustering. This proposed clustering method classify the traffic sign into the attention, regulation, indication, and auxiliary class. Also, The circular tracing method is used for the final traffic sign recognition. To evaluate the effectiveness of the proposed method, varied traffic signs were built. As a result, The proposed method show that the 95 % recognition rate for a single variation, and 93 % recognition rate for a mixed variation.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.612-622
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• 2017

This paper is about on the most representative ethnic of China Mongolian as the research object, through the questionnaire survey to establish the understanding of national cultural symbol and the system of national identity, and lay a theoretical foundation for the application of Mongolian communication and design in the future. In order to achieve the objectivity of the data, so a questionnaire survey was conducted on 300 populations of Mongolian and other nationalities. The result is that the majority of the Mongolians believe that as the Mongolian people have a sense of pride, and the Mongolian nationality is a representative of china. Mongolian is a kind of aesthetic, creative, reliable, aggressive and like the decoration of the nation. The cultural symbols for design elements are cyan, Gen Gi Khan graphics, agate, and peaceful meaning and so on. The cultural symbols are used for celebration, as well as clothing accessories. The symbol of culture has played a positive role in the establishment of Inner Mongolia identity and the propaganda of the nation. The construction of Mongolian cultural symbol system plays an important role in the establishment of Mongolian national identity. To combine the meaning of nation and the mission of culture with national cultural resources. It is not only to help the development of minority culture, but also to promote the sense of pride of ethnic minorities.