• 한국멀티미디어학회논문지
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• 제20권3호
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• pp.571-580
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• 2017

Recently, there are many communication softwares based on text on various smart devices. Unlike traditional print publishing, mobile publishing and SNS tools tends to utilize more decorative or more emotional fonts so that users can pass some feelings from contents. So font providers have released new fonts which deal with the requirements of the market. Nevertheless being released lots of new fonts, general users have not used them because they searched only by font name or font provider's name. It means that there is no way for users to know and find new things. In this study, we suggest font shape classification rules for font registration system based on font design features. We proved the validity of classification standard study through some experiments with 50 commercial fonts. Also the result of this study was provided for Korea Telecommunication Technology Association and adopted by the Korea industrial standard.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.103-117
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• 2023

This study focuses on the behavioural lexical classification for extracting animation character actions and the analysis of the character's upper and lower body movements. The behaviour and state of characters in the animation industry are crucial, and digital technology is enhancing the industry's value. However, research on animation motion application technology and behavioural lexical classification is still lacking. Therefore, this study aims to classify the predicates enabling animation motion, differentiate the upper and lower body movements of characters, and apply the behavioural lexicon's motion data. The necessity of this research lies in the potential contributions of advanced character motion technology to various industrial fields, and the use of the behavioural lexicon to elucidate and repurpose character motion. The research method applies a grammatical, behavioural, and semantic predicate classification and behavioural motion analysis based on the character's upper and lower body movements.

• 한국과학교육학회지
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• 제32권6호
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• pp.1063-1071
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• 2012

The purpose of this study is to investigate the relation between the classification ability quotient and cortisol-hormonal change of middle school students. Thirty-three students, second graders in middle school, performed the classification task that can be an indicator of students' classification ability. And then amount of the secreted hormone was analyzed during task performance. The study results were as follows: First, the classification methods of students mostly utilized visual, qualitative. Their classification patterns for each subject were static, partial, and non-comparative. Second, the amount of stress-hormone was secreted from students during the experiment decreased in overall after the free classification. It seemed that student-centered activity relieved stress. Third, the classification ability quotient turned out to be significantly correlated to the stress hormone, which means that there was a close relationship between classification ability and stress level. It was also considered that stress had a positive effect on the improvement of classification ability. This study provided physiologically more accurate information on the stress increased in the learning process than other conventional studies based on reports or interviews. Finally, researchers could recognize the effect of stress in the cognitive activity and the need to find an appropriate level of stress in learning processes.

• Journal of Preventive Medicine and Public Health
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• 제29권4호
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• pp.877-897
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• 1996

In recent years, the Korean Medical Association has undertaken the feat of establishing the Korean Standard Terminology of Medical Procedures with the dedicated help of 32 medical academic societies. However, because the project is being conducted by several different circles, it has yet to see a clear system of classification. This thesis, therefore, proposes the three principles of scientific properties, usefulness and ideology as the basis for classification system and has developed the Classification System of Medical Procedures in Korea upon their foundation. The methodology and organization of this thesis as follows. First, by adopting scientific classification system of Feinstein(1988), an analysis of the classification systems of the medical procedures in the United States, Japan, Taiwan, WHO was carried out to reveal the framework and the basic principles in each system. Second, the direction of classification system has been constructed by applying the normative principle of medical field in order to show the future direction of the medical field and realize its ideology. Third, a finalized framework for the classification system will be presented as based on the direction of classification system. Of the three basis principles mentioned above, the analysis on the principles of usefulness was left out of this thesis due to the difficulty of establishing specific standards of analysis. The results of the study are as follows. The overall structure of the thesis is aimed at showing the 'Prevention-Therapy-Rehabilitation' quality of comprehensive health care and consists of six chapters; I. Prevention and Health Promotion II. Evaluation and Management III. Diagnostic Procedures IV. Endoscopy V. Therapeutic Procedures VI. Rehabilitation Chapter three Diagnostic Procedures is divided into four parts : Functional Diagnosis, Visual Diagnosis, Pathological Diagnosis, Biopsy and Sampling. Chapter five Therapeutic Procedures is divided into Psychiatry, Non-Invasive Therapy, Invasive Therapy, Anaesthesia and Radiation Oncology. Of these sub-divisions, Functional Diagnosis, Biopsy and Sampling, Endoscopy and Invasive Therapy employs the anatomical system of classification. On the other hand, Visual Diagnosis, Pathological Diagnosis, Anesthesia and Diagnostic Radiology, namely those divisions in which there is little or no overlapping in services with other divisions, used the classification system of its own division. The classification system introduced in this thesis can be further supplemented through the use of the cluster analysis by incorporating the advice and assistance of other specialists.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.

• 한국실내디자인학회논문집
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• 제14권5호
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• pp.71-79
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• 2005

Thinking methods have been widely recognized as phenomenon of problem solving in architectural design process and as one of the bases of creativity. In recent years the study of thinking methods have become a major focus of design research. And the purpose of the paper will understand the phenomenon of characteristic and classification of thinking methods in the architectural design process. Extensive protocols are recorded. In particular, the protocols contain sufficient information to make a detailed picture of the architect's problem-solving processes. A protocol study is reported in which the experimental data by architect's is analyzed through the visual protocol analysis method. These findings will help understand the architectural design nature. And they supply a direction for creative education for architects and the base for CAAD system development through understanding for architect's thinking methods.

• International Journal of Contents
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• 제4권2호
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• pp.24-28
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• 2008

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

• 한국정보통신학회논문지
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• 제24권10호
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• pp.1394-1397
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• 2020

The urine test used as a basic test method of in vitro diagnosis for health care has been used for a long time to be simple and convenient. The urine test method is using a color that appears depending on the change in the ion concentration that reacts over time buried in the standard color test paper(Strips) with a urine sample applied to some reaction reagents. In this paper, it was proposed a neural network algorithm to obtain a suitable and reproducibility and accuracy classifier suitable for the urine analysis system. The experimental results were compared with the visual colorimetric analysis, and the neural network algorithm showed better results.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.161-176
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• 2022

There has been active research in image classification using deep learning convolutional neural network (CNN) models. ImageNet large-scale visual recognition challenge (ILSVRC) (2010-2017) was one of the most important competitions that boosted the development of efficient deep learning algorithms. This paper introduces and compares six monumental models that achieved high prediction accuracy in ILSVRC. First, we provide a review of the models to illustrate their unique structure and characteristics of the models. We then compare those models under a unified framework. For this reason, additional devices that are not crucial to the structure are excluded. Four popular data sets with different characteristics are then considered to measure the prediction accuracy. By investigating the characteristics of the data sets and the models being compared, we provide some insight into the architectural features of the models.