• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.155-161
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• 2024

In this paper, we propose a new model by adding landmark information as a feature vector to the existing CNN-based facial emotion classification model. Facial emotion classification research using CNN-based models is being studied in various ways, but the recognition rate is very low. In order to improve the CNN-based models, we propose algorithms that improves facial expression classification accuracy by combining the CNN model with a landmark-based fully connected network obtained by ASM. By including landmarks in the CNN model, the recognition rate was improved by several percent, and experiments confirmed that further improved results could be obtained by adding FACS-based action units to the landmarks.

• Journal of Family Resource Management and Policy Review
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• v.9 no.3
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• pp.97-112
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• 2005

This research has studied the people's perception and understanding of the 'Healthy Family Act' that has been enacted and practised from the year 2005. For this purpose, a survey has been conducted during October 2004 in several central and local cities in Korea, including Seoul, and a total of 741 samples have been used for the final analysis. The results of this study is as follows. The participants showed a very low level of recognition of the 'Healthy Family Act', and they Perceived that establishing a home-friendly atmosphere was of primary importance among the tasks that should be conducted by the State and local governments to encourage 'healthy families' The participants chose 'supporting the mental & physical health of family members' for the government supporting programs to make healthy families, and chose 'healthy life cultures such as clothes, food, and housing' for the government programs to support the everyday living cultures of the people. 1 Two thirds(2/3) of the participants indicated a willingness to participate in voluntary activities, and more than half of the participants said that they will participate in educational programs. Also, the participants indicated that divorce counselling should be offered only to the people who want the counselling, and as far as 'contents' are concerned, the participants indicated that 'the upbringing of children' should be the most important subject of the counselling. Finally, the participants indicated a willingness of participating educational programs in the order of parent education, family ethics education, realization of family values and family life education.

• Journal of Korean Elementary Science Education
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• v.33 no.2
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• pp.380-400
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• 2014

This study investigated the influence of the application of the career education programs related to the science of the elementary school on the career choice. For this study, a total of 32 lessons (4 units) utilizing the career education programs related the science curriculum were developed. The study subjects were 128 students from Y elementary school located in Incheon. A test with regard to the science related career choice and the science related career choice factors was performed before and after the lessons. For more detailed analysis, the experimental group was divided into two groups of female and male students; students who hope and do not hope career in science-related fields. As a result of the performance of career education programs, it showed a significant improvement in the 'science related career choice'. And, it also showed all significant improvements in 'science related major/department, education lecture selection'. It was possible to know that the students who do not wish science related jobs in the future also changed their mind on to the science. In addition, all the subcategories of the 'preference for science learning' area such as 'preference for science subject', 'preference for experiment', 'recognition of science subject availability', 'recognition of the impact of teacher' showed a significant improvement. The 'perception about career related to science' showed a significant improvement on the whole. There was no significant improvement on the whole in 'participation in science related activities'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1397-1406
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• 2019

In everyday mobile phone calls between the disabled and non-disabled people due to neurological impairment, the communication accuracy is often hindered by combining the accuracy of pronunciation due to the neurological impairment and the pronunciation features of the disabled. In order to improve this problem, the limiting method is MEMS (micro electro mechanical systems), which includes an induction line that artificially corrects difficult vocalization according to the oral characteristics of the language impaired by improving the word of out of vocabulary. mechanical System) Microphone device improvement. S/W improvement is decision tree with invert function, and improved matrix-vector rnn method is proposed considering continuous word characteristics. Considering the characteristics of H/W and S/W, a similar dictionary was created, contributing to the improvement of speech intelligibility for smooth communication.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.1-9
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• 2021

Deep learning in computer vision has made accelerated improvement over a short period but large-scale learning data and computing power are still essential that required time-consuming trial and error tasks are involved to derive an optimal network model. In this study, we propose a similar image classification performance improvement method based on CR (Confusion Rate) that considers only the characteristics of the data itself regardless of network optimization or data reinforcement. The proposed method is a technique that improves the performance of the deep learning model by calculating the CRs for images in a dataset with similar characteristics and reflecting it in the weight of the Loss Function. Also, the CR-based recognition method is advantageous for image identification with high similarity because it enables image recognition in consideration of similarity between classes. As a result of applying the proposed method to the Resnet18 model, it showed a performance improvement of 0.22% in HanDB and 3.38% in Animal-10N. The proposed method is expected to be the basis for artificial intelligence research using noisy labeled data accompanying large-scale learning data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.679-686
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• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.180-186
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• 2004

The presence of noise in speech signals degrades the performance of recognition systems in which there are mismatches between the training and test environments. To make a speech recognizer robust, it is necessary to compensate these mismatches. In this paper, we studied about an improvement of stochastic feature extraction based on band-SNR for robust speech recognition. At first, we proposed a modified version of the multi-band spectral subtraction (MSS) method which adjusts the subtraction level of noise spectrum according to band-SNR. In the proposed method referred as M-MSS, a noise normalization factor was newly introduced to finely control the over-estimation factor depending on the band-SNR. Also, we modified the architecture of the stochastic feature extraction (SFE) method. We could get a better performance when the spectral subtraction was applied in the power spectrum domain than in the mel-scale domain. This method is denoted as M-SFE. Last, we applied the M-MSS method to the modified stochastic feature extraction structure, which is denoted as the MMSS-MSFE method. The proposed methods were evaluated on isolated word recognition under various noise environments. The average error rates of the M-MSS, M-SFE, and MMSS-MSFE methods over the ordinary spectral subtraction (SS) method were reduced by 18.6%, 15.1%, and 33.9%, respectively. From these results, we can conclude that the proposed methods provide good candidates for robust feature extraction in the noisy speech recognition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.28-35
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• 2008

Most organizations have recently put more emphasis on the improvement in service quality. This phenomenon could come from the recognition that service quality plays an essential role in enhancing organization's business performance. Hence this paper presents a framework for improving such service quality. The presented framework involves the methodology for (i) developing service quality indices, (ii) measuring and evaluating service quality, (iii) analyzing the level of service quality, (iv) constructing the quality improvement road map, (v) determining the quality improvement action plan. This methodology is intended to create self-sustaining improvement in service quality from the entire organization's perspective. An illustration is also given.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.341-342
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• 2010

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.