• Journal of Digital Convergence
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• v.11 no.9
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• pp.311-318
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• 2013

For face detection techniques, the correctness of detection decreases with different lightings and backgrounds so such requires new methods and techniques. This study has aimed to obtain data for reasoning human emotional information by analyzing the components of the eyes and mouth that are critical in expressing emotions. To do this, existing problems in detecting face are addressed and a detection method that has a high detection rate and fast processing speed good at detecting environmental elements is proposed. This method must detect a specific part (eyes and a mouth) by using Haar-like Feature technique with the application of an integral image. After which, binaries detect elements based on color information, dividing the face zone and skin zone. To generate correct shape, the shape of detected elements is generated by using a bezier curve-a curve generation algorithm. To evaluate the performance of the proposed method, an experiment was conducted by using data in the Face Recognition Homepage. The result showed that Haar-like technique and bezier curve method were able to detect face elements more elaborately.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.38-47
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• 2008

The most commonly used location recognition system is the GPS-based approach. However, the GPS is inefficient for an indoor or urban area where high buildings shield the satellite signals. To overcome this problem, this paper propose the indoor positioning method using wavelet and neural network. The basic idea of proposed method is estimated the location using the received signal strength from wireless APs installed in the indoor environment. Because of the received signal strength of wireless radio signal is fluctuated by the environment factors, a feature that is strength of signal noise and error and express the time and frequency domain is need. Therefore, this paper is used the wavelet coefficient as the feature. And the neural network is used for estimate the location. The experiment results indicate 94.6% an location recognition rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.99-107
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• 2009

Visible Light Communication (VLC) is a promising wireless communication technology. It offers huge, worldwide available and free bandwidth without electro-magnetic interference, which makes it very attractive for RF-sensitive operating environments. We propose colored LED-based VLC system for hospital use which includes voice recognition system for operating the medical equipments. New Mr hlation Scheme based on the Light Color Space is suggested to overcome the effect of noise generated by background light. Different color space constellations for different symbol sizes are also suggested which would give better bit error rate performance. Finally, Slotted ALOHA or TDMA medium access control protocols are suggested for multi-user operations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.116-127
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• 2002

A new approach to improve the speaker adaptation algorithm by means of the variable number of observation density functions for CDHMM speech recognizer has been proposed. The proposed method uses the observation density function with more than one mixture in each state to represent speech characteristics in detail. The number of mixtures in each state is determined by the number of frames and the determinant of the variance, respectively. The each MAP Parameter is extracted in every mixture determined by these two methods. In addition, the state segmentation method requiring speaker adaptation can segment the adapting speech more Precisely by using speaker-independent model trained from sufficient database as a priori knowledge. And the state duration distribution is used lot adapting the speech duration information owing to speaker's utterance habit and speed. The recognition rate of the proposed methods are significantly higher than that of the conventional method using one mixture in each state.

• Hwankyungkyoyuk
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• v.8 no.1
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• pp.66-80
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• 1995

The purpose of this study was to investigate the housewives's recognition and practice on prevention of environmental pollution. The subjects of this study were 250 housewives, school students' mothers, living in Cheong-ju. Major findings were as follows: 1. In washing their faces and brushing their teeth, they saved the water very well, but in taking bath, washing the dished, using the water of the lavatory they did not save the water so well. 2. The kinds of the cleansers differed in taking a bath, washing the hair, and doing the laundry respectively : what they use most was hard soaps in taking bath, liquid cleansers mixed with shampoo and linse in washing the hair, and synthetic powder detergent in laundrying. They used more synthetic detergent than natural soaps, which is known to be a cause of water pollution. Especially, when they cleansed, they did not use a measuring cup. It resulted in the waste of detergent and accelerating of water pollution. Therefore, the environmental education for them was very urgently needed. 3. In handling domestic waste, the separate collection rate of empty bottles and old newspapers was very high, but that of used phone-call cards and used batteries was extremely low. It was truly nessesary to educate and step up publicic activities on the separate collection of phone-call cards and batteries caused environmental pollution. 4. The housewives had much knowledge about environmental pollution, but they did not practice it so well in their home. 5. The housewives made more effort than their children in preventing environmental pollution and saving resources. In conclusion, what is most important for solving environmental problem was for each citizen to make an effort to prevent environmental pollution, and the government's support and producing the atmosphere of the society for this was really needed.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.141-150
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• 2020

This study examined the experience of cosmetic surgery and its related factors in order to establish the correct values for female college students' appearance. Data were collected from 283 female college students in Gyeonggi, Chungcheong, and Jeolla-do provinces, and analyzed by Chi-square test, T-test and Binary logistic regression using SPSS 18.0 program. As a result, the experience rate of cosmetic surgery was 66.1%, and the experience of cosmetic surgery was high as the grade was increased. The most common source of information was 'family and people around' at 45.9%, and the cosmetic surgery type 'eye surgery' was the highest at 25.8%. Appearance of interest and cosmetic surgery recognition were higher than those who had no cosmetic surgery experience. Factors related to cosmetic surgery experience were grade, allowance, and appearance interest. It is necessary to prepare basic data on cosmetic information and to develop a program to establish proper beauty values, and education and counseling to make rational decisions about cosmetic surgery will be required.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2017-2024
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• 1997

The main focus of this paper is the recognition of printed Hangul documents in terms of typeface, character size and character slope for IICS(Intelligent Image Communication System). The fixed-size blocks extracted from documents are analyzed in frequency domain for the typeface classification. The vertical pixel counts and projection profile of bounding box are used for the character size classification and the character slope classification, respectively. The MLP with variable hidden nodes and error back-propagation algorithm is used as typeface classifier, and Mahalanobis distance is used to classify the character size and slope. The experimental results demonstrated the usefulness of proposed system with the mean rate of 95.19% in typeface classification. 97.34% in character size classification, and 89.09% in character slope classification.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.44-52
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• 2001

This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1002-1012
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• 2019

360VR content requires short latency, such as immediate response to viewers' viewport changes and high quality video delivery. It is necessary to consider efficient transmission that guarantees the QoE(Quality of Experience) of the 360VR contents with limited bandwidth. Several research has been introduced to reduce overall bandwidth consumption by predicting a user's viewport and allocating different bit rates to the area corresponding to the viewport. In this paper, we propose novel viewport prediction scheme that uses sound source location information of 360VR contents as auditory recognition information along with visual recognition information. Also, we propose efficient transmission algorithm by allocating a bit rate properly based on improved viewport prediction. The proposed scheme improves the accuracy of the viewport prediction and provides high quality videos to tiles corresponding to the user's viewpoint within the limited bandwidth.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.81-103
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• 2005

The Neuron structure in a nervous system consists of inhibitory neurons and excitory neurons. Both neurons are activated by agonistic neurons and inactivated by antagonist neurons. In this paper, we proposed a physiological fuzzy neural network by analyzing the physiological neuron structure in the nervous system. The proposed structure selectively activates the neurons which go through a state of excitement caused by agonistic neurons and also transmit the signal of these neurons to the output layers. The proposed physiological fuzzy neural networks based on the nervous system consists of a input player, and the hidden layer which classifies features of learning data, and output layer. The proposed fuzzy neural network is applied to recognize bronchial squamous cell carcinoma images and car plate images. The result of the experiments shows that the learning time, the convergence, and the recognition rate of the proposed physiological fuzzy neural networks outperform the conventional neural networks.