• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2647-2654
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• 2011

In this paper, the algorithm that recognizes the gesture by configuring the feature information obtained through edge orientation histogram and principal component analysis as low dimensional gesture symbol was described. Since the proposed method doesn't require a lot of computations compared to the existing geometric feature based method or appearance based methods and it can maintain high recognition rate by using the minimum information, it is very well suited for real-time system establishment. In addition, to reduce incorrect recognition or recognition errors that occur during gesture recognition, the model feature values projected in the gesture space is configured as a particular status symbol through clustering algorithm to be used as input symbol of hidden Markov models. By doing so, any input gesture will be recognized as the corresponding gesture model with highest probability.

• Advances in Computational Design
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• v.4 no.2
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• pp.155-177
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• 2019

Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.16-23
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• 2001

In this paper, we propose the pseudo n-gram language models for speech recognition with middle size vocabulary compared to large vocabulary speech recognition using the statistical n-gram language models. The proposed method is that it is very simple method, which has the standard structure of ARPA and set the word probability arbitrary. The first, the 1-gram sets the word occurrence probability 1 (log likelihood is 0.0). The second, the 2-gram also sets the word occurrence probability 1, which can only connect the word start symbol and WORD, WORD and the word end symbol . Finally, the 3-gram also sets the ward occurrence probability 1, which can only connect the word start symbol , WORD and the word end symbol . To verify the effectiveness of the proposed method, the word recognition experiments are carried out. The preliminary experimental results (off-line) show that the word accuracy has average 97.7% for 452 words uttered by 3 male speakers. The on-line word recognition results show that the word accuracy has average 92.5% for 20 words uttered by 20 male speakers about stock name of 1,500 words. Through experiments, we have verified the effectiveness of the pseudo n-gram language modes for speech recognition.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.132-140
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• 1994

SCRIPT (Symbol/Character Recognition In Pen-based Technology) is an algorithm for on-line recognition of handwriting Hangeul. English upperacase letters, decimal digits, and some keyboard symbols. The shape of handwriting symbols has a large variation even when written by the same person. Though the feature analysis approach using a conventional decision tree is efficient, it is not robust under shape variations and prone to misclassification. Thus, a new method to overcome this shortcoming is necessary. In this paper, a feature analysis algorithm using two fuzzy decision trees which utilize the hierarchical property of the pattern is proposed. The first tree is used to represent the stroke shape, and the other tree is used to represent the relation between the strokes. since this method stores various possibilities. it is robust to shape variations and can readily modify false selections. In addition, there is a large increase in the recognition rate of high-level patterns due to low-level candidated. Experimental results show 91% recognition rate for Hangeul at the recognition speed of 0.33 second per character, and the recognition rate of alphanumerics and some keyboard symbols is 95% at 0.08 second per symbol. This is 8~18% increase in the recognition rate over th method not applying fuzzy decision trees.

• Archives of design research
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• v.13 no.3
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• pp.7-16
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• 2000

Aesthetics undertakes important roll in design as a competitive factor. The importance of aesthetics can be found in experimental aesthetics, Gestalt psychology and design related literatures. These literatures suggest that, besides the importance of aesthetics, many other aesthetic factors would affect consumer reaction(recognition, emotional reaction, meaning), but the study is still in insufficient condition. Hense, this study tries to give a guideline -'how to design symbols'based on the apprehension of what kind of design is well recognized(correct recognition), gives positive emotional reaction(affect) to customers, and moreover, what sort of aesthetic factors affect these reactions by analyzing existing symbol designs.

• Proceedings of the Korea Society of Design Studies Conference
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• 1999.05a
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• pp.56-57
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• 1999

경험적 심미성(experimental aesthetics), Gestalt심리학, 그래픽디자인 및 심볼관련문헌에서는 많은 디자인 심미적 특성들이 심볼에 대한 감정적 반응(affective reactions)에 영향을 미치고있음을 알 수 있다. 그러나 불행하게도 이러한 디자인 문헌속에서는 디자인의 심미적 영향요소들이 인자(recognition), 친밀감(familiarity), 의미(meaning)에 어떻게 영향을 주는지에 대해서는 체계적인 연구가 이루어지지 모하고 있고 실증적으로 시험되지도 않고 있어 심볼 디자인에 대한 지침을 제공하지 못하고 있는 실정이다.(중략)

• Journal of Elementary Mathematics Education in Korea
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• v.14 no.3
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• pp.937-957
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• 2010

The purpose of this study is to discover the features of symbol sense. This study tries to sum up the meaning and elements of symbol sense and the measures to improve them through documents. Also based on this, it analyzes the learning conditions about symbol sense for 6th grade mathematically able students and suggests the method that activates symbol sense in the math of elementary schools. Considering various studies on symbol sense, symbol sense means the exact knowledge and essential understanding in a comprehensive way. Symbol sense is an intuition about symbols that grasps the meaning of symbols, understands the situation of question, and realizes the usefulness of symbols in resolving a process. Considering all other scholars' opinions, this study sums up 5 elements of the symbol sense. (The recognition of needs to introduce symbol, ability to read the meaning of symbols, choice of suitable symbols according to the context, pattern guess through visualization, recognize the role of symbols in other context) This study draws the following conclusions after applying the symbol questionnaires targeting 6th grade mathematically able students : First, although they are math talents, there are some differences in terms of the symbol sense level. Second, 5 elements of the symbol sense are not completely separated. They are rather closely related in terms of mainly the symbol understanding, thereby several elements are combined.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.410-415
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• 2005

Recently, most of the speaker verification systems are based on the pattern recognition approach method. And performance of the pattern-classifier depends on how to classify a variety of speakers' feature parameters. In order to classify feature parameters efficiently and effectively, it is of great importance to enlarge variations between speakers and effectively measure distances between feature parameters. Therefore, this paper would suggest the positively mixed model scheme that can enlarge inter-speaker variation by searching the individual model with world model at the same time. During decision procedure, we can maximize inter-speaker variation by using the proposed mixed model scheme. We also make use of a symbol probability weighting function in this system so as to reduce vector quantization errors by measuring symbol probability derived from the distance rate of between the world codebook and individual codebook. As the result of our experiment using this method, we could halve the Detection Cost Function (DCF) of the system from $2.37\%\;to\;1.16\%$.

• Journal of the Korean Society of Costume
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• v.54 no.8
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• pp.35-48
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• 2004

This thesis researches consumers' behaviors in Purchasing avatar fashion products depending on their motives and point of reference as the avatar fashion marketing is conducted. Also, it explores the correlation between avatar's fashion products and the point of reference by which consumers actually purchase casual wear. The results were as follows: First, Avatar's fashion product purchasing motivation is done through four classified dimensions, conformity, differentiation, fashionability, and substitution. The standard of Avatar's fashion product choice was classified by the symbol (Product name recognition) and two dimensions of aesthetics. Second. the more valued the aesthetic component of Avatar's fashion product the greater effect on the order the dimensions used in correlation in this case being substitution, differentiation, conformity, and fashionability. Should the consumer place greater value on the Product symbol the dimension order is affected in order by fashionability, conformity, and differentiation. Third, fashionability was a stronger consideration for women as opposed to men in terms of demographical feature. whereas symbol (Product recognition) was of greater importance to higher income people. Last, when aesthetics is considered to buy Avatar's fashion products it is favorably comparable to other casual wear lines. In other words, symbol is considered to buy casual's, it brings to the same result when buying Avatar's. Avatar's fashion product was great tool to research new casual wear line because of approving by the correlation to each other.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.89-95
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• 2020

Recently, studies are being conducted to recognize a sketch image of a GUI (Graphical User Interface) based on a deep learning and to make it into a code implemented in an application. UI / UX designers can communicate with developers through storyboards when developing mobile applications. However, UI / UX designers can create different widgets for ambiguous widgets. In this paper, we propose an automatic UI detection method using symbol markers to improve the accuracy of DNN (Deep Neural Network) based UI identification. In order to evaluate the performance with or without the symbol markers, their accuracy is compared. In order to improve the accuracy according to of the symbol marker, the results are analyzed when the shape is a circle or a parenthesis. The use of symbol markers will reduce feedback between developer and designer, time and cost, and reduce sketch image UI false positives and improve accuracy.