• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.30-39
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• 2007

This paper is concerned with development of system to detect an obstructive vehicle which is an essential prerequisite for autonomous driving system of ASV(Advanced Safety Vehicle). First, the boundary of driving lanes is detected by a Kalman filter through the front image obtained by a CCD camera. Then, lanes are recognized by regression analysis of the detected boundary. Second, parameters of road curvature within the detected lane are used as input in error-BP algorithm to recognize the driving direction. Finally, an obstructive vehicle that enters into the detection region can be detected through setting detection fields of the front and lateral side. The experimental results showed that the proposed system has high accuracy more than 90% in the recognition rate of driving direction and the detection rate of an obstructive vehicle.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.1-9
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• 2020

In this paper, we propose a model that performs more natural facial attribute editing by utilizing mask information in the hair and hat region. STGAN, one of state-of-the-art research of facial attribute editing, has shown results of naturally editing multiple facial attributes. However, editing hair-related attributes can produce unnatural results. The key idea of the proposed method is to additionally utilize information on the face regions that was lacking in the existing model. To do this, we apply three ideas. First, hair information is supplemented by adding hair ratio attributes through masks. Second, unnecessary changes in the image are suppressed by adding cycle consistency loss. Third, a hat segmentation network is added to prevent hat region distortion. Through qualitative evaluation, the effectiveness of the proposed method is evaluated and analyzed. The method proposed in the experimental results generated hair and face regions more naturally and successfully prevented the distortion of the hat region.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.37 no.2
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• pp.177-189
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• 2011

Women starts to make up after high school graduation. They have low economic power. But they select cosmetics by themselves and have high demand. Therefore, they can be major customers of low-priced cosmetics and it can be regarded as independent cosmetics market. Thus, this study analyzes the purchasing propensity of lowpriced cosmetics in female undergraduates, who are main targets of low-priced cosmetics, satisfies the more customers desire through further segmenting the targets, suggests a continuous developmental plan for low-priced cosmetics through securing potential customers and segmenting market, and analyzes and typologizes female undergraduates lifestyle. The aim is to grasp the actual condition of using the low-priced cosmetics and the satisfaction with purchase, and to utilize it as basic date of inducing right consumption culture of female undergraduates. For this study, 305 reliable questionnaires are analyzed from the total 320 questionnaires and spss win 15.0 program was used. The results were as follows. About 90.1 percent of female undergraduates had experience using low-priced cosmetics and standard of priority selection was the quality of low-priced cosmetics. The main reason not to use was low price image.

• Korean Journal of Construction Engineering and Management
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• v.19 no.4
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• pp.43-51
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• 2018

As the inventory of aged apartments is expected to increase explosively, the importance of maintenance to improve the durability of concrete facilities is increasing. Concrete compressive strength is a representative index of durability of concrete facilities, and is an important item in the precision safety diagnosis for facility maintenance. However, existing methods for measuring the concrete compressive strength and determining the maintenance of concrete facilities have limitations such as facility safety problem, high cost problem, and low reliability problem. In this study, we proposed a model that can predict the concrete compressive strength through images by using deep convolution neural network technique. Learning, validation and testing were conducted by applying the concrete compressive strength dataset constructed through the concrete specimen which is produced in the laboratory environment. As a result, it was found that the concrete compressive strength could be learned by using the images, and the validity of the proposed model was confirmed.

• The Journal of Korean Institute of Information Technology
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• v.17 no.4
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• pp.131-136
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• 2019

People with compromised visual ability suffer from many inconveniences in daily life, such as distinguishing colors, identifying currency notes and realizing the atmospheric temperature. Therefore, to assist the visually impaired people, we propose a system by utilizing optical and infrared cameras. In the proposed system, an optical camera is used to collect features related to colors and currency notes while an infrared camera is utilized to get temperature information. The user is enabled to select the desired service by pushing the button and the appreciate voice information are provided through the speaker. The device can distinguish 16 kinds of colors, four different currency notes, and temperature information in four steps and the current accuracy is around 90%. It can be improved further through block-wise input image, machine learning, and a higher version of the infrared camera. In addition, it will be attached to the stick for easy carrying and to use it more conveniently.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.401-408
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• 1997

Human gets almist all of his knoweledge from the recognition and the accumulation of input patterns,image or sound,the he gets theough his eyes and through his ears.Among these means,his chracter recognition,an ability that allows him to recognize characters and understand their meanings through visual information, is now applied to a pattern recognition system using neural network in computer. Recurrent neural network is one of those models that reuse the output value in neural network learning.Recently many studies try to apply this recurrent neural network to the classification of static patterns like off-line handwritten characters. But most of their efforts are not so drrdtive until now.This stusy suggests a new type of recurrent neural network for an deedctive classification of the static patterns such as off-line handwritten chracters.Using the new J-E(Jordan-Elman)neural network model that enlarges and combines Jordan Model and Elman Model,this new type is better than those of before in recobnizing the static patterms such as figures and handwritten-characters.

• Fashion & Textile Research Journal
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• v.26 no.1
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• pp.78-87
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• 2024

This study aimed to propose an innovative teaching pedagogy using a half-scale body form in apparel design education and evaluate its effectiveness in augmenting students' understanding of ergonomic patterns. Constructed in alignment with Phoenix's (2018) study, which used 3D body scanning and digital editing software, the half-scale body form was created through a five-step process, encompassing body measurement, 3D body modeling, fabrication of a physical half-scale body form, pattern making, and evaluation. Implemented in an undergraduate patternmaking course offered at a 4-year university in the metropolitan Seoul, this instructional approach's effectiveness was gauged through students' course projects and exit interviews. The results underscored the positive impact of the proposed teaching pedagogy on students' grasp of ergonomic pattern development, fostering a keen understanding of diverse body shapes and sizes and the relationship between the human body and garments. Furthermore, it played a role in cultivating positive body image and self-endorsement among students. The research contributes meaningfully by presenting a fresh perspective in apparel design education, seamlessly integrating advanced anthropometric and technological tools into a conventional patternmaking classroom. It offers a novel learning experience for students majoring in apparel, creating a fun and interactive teaching environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.474-476
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• 2021

Glioblastoma is the most common brain malignancies arising from glial cells. Early diagnosis and treatment plan establishment are important, and cancer is diagnosed mainly through T1CE imaging through injection of a contrast agent. However, the risk of injection of gadolinium-based contrast agents is increasing recently. Region segmentation that marks cancer regions in medical images plays a key role in CAD systems, and deep neural network models for synthesizing new images are also being studied. In this study, we propose a model that simultaneously learns the generation of T1CE images and segmentation of cancer regions. The performance of the proposed model is evaluated using similarity measurements including mean square error and peak signal-to-noise ratio, and shows average result values of 21 and 39 dB.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.717-733
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• 2021

This study is aimed to provide basic data to set the direction of polar literacy education and to raise awareness of the importance of polar research. Elementary, middle, and high school students' perception of the polar region was examined in terms of current status of polar information, impression regarding polar regions, and awareness of related issues. The study included 975 students from nine elementary, middle, and high schools, who responded to 16 questions, including close-ended and open-ended items. The results suggest that students had more experiences regarding the polar region on audiovisual media, but relatively limited learning experiences in school education. The impression they had of the polar region was confined to the monotonous image of a polar bear in crisis, following the melting of the glacier due to global warming. The students formed powerful images by combining scenes they saw in audiovisual media with emotions. In terms of recognizing problems in the polar region, the students were generally interested in creatures, natural environment, and climate change, but their interests varied depending on their school level and their own career path. The students highly valued the scientist's status as agents to address the problems facing the region, and gave priority to global citizenship values rather than practical standards. Based on the results, we suggest the following: introducing and systematizing content focusing on the polar region in the school curriculum, providing a differentiated learning experience through cooperation between scientists and educators, establishing polar literacy based on concepts that are relevant to various subjects, earth system-centered learning approach, setting the direction for follow-up studies and the need for science education that incorporates diverse values.

• Journal of The Korean Association For Science Education
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• v.27 no.1
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• pp.93-104
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• 2007

The purpose of this study is to investigate brain activity both during the processing of a scientific hypothesis about biological phenomena and mental arithmetic using 3.0T fMRI at the KAIST. For this study, 16 healthy male subjects participated voluntarily. Each subject's functional brain images by performing a scientific hypothesis task and a mental arithmetic task for 684 seconds were measured. After the fMRI measuring, verbal reports were collected to ensure the reliability of brain image data. This data, which were found to be adequate based on the results of analyzing verbal reports, were all included in the statistical analysis. When the data were statistically analyzed using SPM2 software, the scientific hypothesis generating process was found to have independent brain network different from the mental arithmetic process. In the scientific hypothesis process, we can infer that there is the process of encoding semantic derived from the fusiform gyrus through question-situation analysis in the pre-frontal lobe. In the mental arithmetic process, the area combining pre-frontal and parietal lobes plays an important role, and the parietal lobe is considered to be involved in skillfulness. In addition, the scientific hypothesis process was found to be accompanied by scientific emotion. These results enabled the examination of the scientific hypothesis process from the cognitive neuroscience perspective, and may be used as basic materials for developing a learning program for scientific hypothesis generation. In addition, this program can be proposed as a model of scientific brain-based learning.