• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.171-179
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• 2010

The purpose of the present study is to suggest composing the graph topology of sketch drawing element and the recognition of the shape pattern for the earthwork quantity calculation. The algorithm which can extract the topology element such as vertex, edge, face and establish the relation between each topology was developed. The model which can define earthwork graph and recognize the shape pattern of earthwork was presented. As a result of the study, the shape pattern of earthwork that can't be calculated by existing earthwork calculation program could be recognized as expanding this model. The earthwork shape recognition automation using the graph topology model can be applied to the automation for the earthwork quantity estimation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.539-546
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• 2006

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. The sensor module which includes two independent sensing elements for responding to diesel and gasoline exhaust gases, and temperature sensor and humidity sensor was designed for intelligent AQS in automobile. With this sensor module, AVR microcontroller was designed with back propagation neural network to a powerful gas/vapor pattern recognition when the motor vehicles pass a pollution area. Momentum back propagation algorithm was used in this study instead of normal backpropagation to reduce the teaming time of neural network. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation in this study. One chip microcontroller, ATmega 128L(ATmega Ltd., USA) was used for the control and display. And our developed system can intelligently reduce the malfunction of AQS from the dampness of air or dense fog with the backpropagation neural network and the input sensor module with four sensing elements such as reducing gas sensing element, oxidizing gas sensing element, temperature sensing element and humidity sensing element.

• Journal of the Korean housing association
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• v.23 no.5
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• pp.19-29
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• 2012

It is very necessary to know about child recognition of residential environment to plan and design an environment proper for children's growth and development. The research method using Cognitive Map, which may be defined as "an overall mental image of representation of the space and layout of a setting" can be a good tool for studying child recognition of residential environment. This study analyzed the child recognition of the size of home range, the number of residential environment elements, the types of Cognitive Map and the levels of Cognitive Map to understand the contents of child recognition about their residential environment. Subjects were 206 children in age6, 8 and 10 in Gwanju and Jeonnam area. As the result of the study, we found that 70% of child recognized 100~500 M as the size of home range, and that the number of the elements of residential environment was 7, average. And we also found that sequential map was more popular than spatial map in child's Cognitive Map type and that almost 60% of child respondents drew the Cognitive Map of level 1 complexity type. As the result of this study, we could know that the research method using Cognitive Map was very useful for understanding the child recognition of residential environment.

• Journal of the Korean Home Economics Association
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• v.41 no.3
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• pp.1-15
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• 2003

This study was conducted to analyze the actual wearing conditions and body fit preferences of the middle-aged women's ready-to-wear lower body clothing. The aim was also to analyze lower body recognition, lower body satisfaction, fit preferences and size satisfaction according to age and degree of girth size. A questionnaire was developed and administered to 300 middle-aged women aged 34 to 59. Statistical tests such as descriptive analysis, crosstabs, and X²-tests were conducted to analyze the data and ascertain the differences between the ages. Lower body satisfaction and recognition were compared by T-test. Also, Anova was used to analyze lower body recognition, satisfaction, fit preferences, and size satisfaction according to age and degrees of girth size. The results indicated that women aged 50 to 59 were more dissatisfied with the ready-to-wear sizing system and because of their body shapes had changed, their need for a larger size range system had also increased. Moreover, the element that most affected their purchase of ready-to-wear lower body clothing was the design followed by the size. The women, especially of the ages 50 to 59, showed a tendency to he dissatisfied with their lower bodies and they recognized that their lower bodies had thickened compared to women aged 34 to 39 and 40 to 49. Analysis of body satisfaction, recognition, and fit preference according to girth size showed that the group of larger girth size recognized that their lower bodies were thicker and were more dissatisfied and preferred looser fittings than the groups of smaller women.

• Journal of The Korea Institute of Healthcare Architecture
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• v.22 no.1
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• pp.7-15
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• 2016

Purpose: There are the number of color tactile walking surface indicators installed in Korea, because of indefinite regulation in blind and vision-impaired persons' tactile walking surface indicators. In case of yellow tactile walking surface indicators, it shows a deviation severe color. In this study, the researchers suggested color and brightness reference for helping blind and vision-impaired persons' walking through analyzing the color references of tactile walking surface indicators and the color luminance between tactile walking surface indicators and sidewalk currently used. Method: Reasonable luminance contrast criteria is suggested by examining ways of improving the recognition and recognition of objects according to color contrast visually impaired through literature review and analyzing standards of tactile walking surface indicators and the Europe, Japan and Australia of color and luminance contrast criteria. And by examining the color of the tactile walking surface indicators reported in Korea currently used to derive the problem presented by the luminance contrast in the reference and comparison. Finally, the visually impaired tactile walking surface indicators is set for color selection criteria for the recognition rate improves. Results: In order to improve the recognition rate to be tactile walking surface indicators of the contrast of the visually impaired and the environment than the color of the tactile walking surface indicators itself to secure always a certain level or more of brightness contrast values in the set of the color of the tactile walking surface indicators so important. Implication: In order to set the blind tactile walking surface indicators color recognition based on the verification of the real pedestrian based on the results presented in this paper it is required. It is to be understood as an element of the barrier free configuration for securing the walking pedestrian safety.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.675-680
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• 2018

In this paper, we propose a hand gesture recognizer using restricted coulomb energy (RCE) neural network, and present hardware implementation results for real-time learning and recognition. Since RCE-NN has a flexible network architecture and real-time learning process with low complexity, it is suitable for hand recognition applications. The 3D number dataset was created using an FPGA-based test platform and the designed hand gesture recognizer showed 98.8% recognition accuracy for the 3D number dataset. The proposed hand gesture recognizer is implemented in Intel-Altera cyclone IV FPGA and confirmed that it can be implemented with 26,702 logic elements and 258Kbit memory. In addition, real-time learning and recognition verification were performed at an operating frequency of 70MHz.

• Convergence Security Journal
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• v.24 no.2
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• pp.201-207
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• 2024

Voice is a critical element of human communication, and the development of speech recognition models is one of the significant achievements in artificial intelligence, which has recently been applied in various aspects of human life. The application of speech recognition models in the military field is also inevitable. However, before artificial intelligence models can be applied in the military, it is necessary to research their vulnerabilities. In this study, we evaluates the military applicability of the multilingual speech recognition model "Whisper" by examining its vulnerabilities to battlefield noise, white noise, and adversarial attacks. In experiments involving battlefield noise, Whisper showed significant performance degradation with an average Character Error Rate (CER) of 72.4%, indicating difficulties in military applications. In experiments with white noise, Whisper was robust to low-intensity noise but showed performance degradation under high-intensity noise. Adversarial attack experiments revealed vulnerabilities at specific epsilon values. Therefore, the Whisper model requires improvements through fine-tuning, adversarial training, and other methods.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.3
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• pp.248-259
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• 2001

This paper proposes a human action recognition scheme to recognize nonverbal human communications automatically. Based on the principle that a human body action can be defined as a combination of multiple articulation movements, we use the method of inferencing stochastic grammars to understand each human actions. We measure and quantize each human action in 3D world-coordinate, and make two sets of 4-chain-code for xy and zy projection plane. Based on the fact that the neighboring information among articulations is an essential element to distinguish actions, we designed a new stochastic inference procedure to apply the neighboring information of hands. Our proposed scheme shows better recognition rate than that of other general stochastic inference procedures. ures.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.102-110
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• 1992

In this paper, a new method of character recognition is proposed. It uses density information, in addition to positional and directional information generally used, to recognize a character. Four directional feature primitives are extracted from the thinning templates on the observation that the output of the templates have directional property in general. A simple and fast feature extraction scheme is possible. Features are organized from recursive nonary tree(N-tree) that corresponds to normalized character area. Each node of the N-tree has four directional features that are sum of the features of it's nine sub-nodes. Every feature primitive from the templates are added to the corresponding leaf and then summed to the upper nodes successively. Recognition can be accomplished by using appropriate feature level of N-tree. Also, effectiveness of each node's feature vector was tested by experiment. A method to implement the proposed feature vector organization algorithm into hardware is proposed as well. The third generation node, which is 4$\times$4, is used as a unit processing element to extract features, and it was implemented in hardware. As a result, we could observe that it is possible to extract feature vector for real-time processing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.281-284
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• 2010

In this paper, we present Hand-gesture recognition for actual computing into color images from camera. Color images are binarization and labeling by using the YCbCr Color model. Respectively label area seeks the center point of the hand from to search Maximum Inscribed Circle which applies Voronoi-Diagram. This time, searched maximum circle and will analyze the elliptic ingredient which is contiguous so a hand territory will be able to extract. we present the presentation contral system using elliptic element and Maximum Inscribed Circle. This algorithm is to recognize the various environmental problems in the hand gesture recognition in the background objects with similar colors has the advantage that can be effectively eliminated.