• Journal of Korean Home Economics Education Association
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• v.19 no.3
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• pp.91-106
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• 2007

The purpose of this study was to provide the information for the development of gender-equality oriented content of Technology Home Economics subject. For this purpose, a total of 404 male and female middle high school students in Chuncheon city were sampled and asked to estimate the degree of practical use and preference for the 47 units of Technology Home Economics subject. Results were summarized as following : 1. The 47 units were classified into 4 groups on the basis of similarity in the degree of practical use and preference: 23 units estimated as 'better than average' by male and female students were classified into group 1; 4 units estimated as 'better than average' by female students but as 'less than average' by male students were classified into group 2; 10 units estimated as 'less than average' by male and female students were classified into group. 3; 10 units estimated as 'far less than average' by male and female students were classified into group 4. Most of the units in Home Economics area were classified Into group 1 or 2, but most of the units in Technology area were classified into group 3 or 4. 2. Gender difference was confirmed between male and female students' estimation of the degree of practical use and preference for the 47 units. In about three-quaters of the units in Home Economics area, female students' estimation of the degree of practical use and preference was higher than male students' estimation. In about half of the units in Technology area, male students' estimation of the degree of practical use and preference was higher than female students' estimation. However, possibility was detected in several units of Technology Home Economics subject that gender difference could be decreased.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.75-79
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• 2007

We propose an effective voice-based gender identification method using a support vector machine(SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model(GMM) using the mel frequency cepstral coefficients(MFCC). A novel means of incorporating a features fusion scheme based on a combination of the MFCC and pitch is proposed with the aim of improving the performance of gender identification using the SVM. Experiment results indicate that the gender identification performance using the SVM is significantly better than that of the GMM. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

• International Journal of Costume and Fashion
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• v.6 no.2
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• pp.28-42
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• 2006

In present modern society, media contributes more to the constructing of personal identities than any other medium. Music video, a postmodernism branch among a variety of media, offers a complex experience of sounds combined with visual images. In particular. fashion in music video helps conveying contexts effectively and functions as a medium of immediate communication by visual effect. Considering the socio-cultural effects of music video. gender identity represented in fashion in it can be of great importance. Therefore, this study is geared to the reconsidering of gender identity represented through costumes in music video by analyzing fashions in it. Gender identity in socio-cultural category is classified as masculinity, femininity, and the third sex. By examining fashions based on the classification. this study will help to create new design concepts and to understand gender identity in fashion. The results of this study are as follows: First. masculinity in music video fashion was categorized into stereotyped masculinity, sexual masculinity. and metro sexual masculinity. Second, femininity in music video fashion was categorized into stereotyped femininity. sexual femininity, and contra sexual femininity. Third, the third sex in music video fashion was categorized into transvestism, masculinization of female, and feminization of male. This phenomenon is presented into music videos through females in male attire and males in female attire. Through this research, gender identity represented in fashion of music video was demonstrated, and the importance of the relationship between representation of identity through fashion and socio-cultural environment was reconfirmed.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.43-51
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• 2023

In this paper, we propose an approach for dialect classification based on the speed and pause of speech utterances as well as the age and gender of the speakers. Dialect classification is one of the important techniques for speech analysis. For example, an accurate dialect classification model can potentially improve the performance of speaker or speech recognition. According to previous studies, research based on deep learning using Mel-Frequency Cepstral Coefficients (MFCC) features has been the dominant approach. We focus on the acoustic differences between regions and conduct dialect classification based on the extracted features derived from the differences. In this paper, we propose an approach of extracting underexplored additional features, namely the speed and the pauses of speech utterances along with the metadata including the age and the gender of the speakers. Experimental results show that our proposed approach results in higher accuracy, especially with the speech rate feature, compared to the method only using the MFCC features. The accuracy improved from 91.02% to 97.02% compared to the previous method that only used MFCC features, by incorporating all the proposed features in this paper.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.165-175
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• 2008

For an advanced intelligent service, the need of HRI technology has recently been increasing and the technology has been also improved. However, HRI components have been evaluated under stable and controlled laboratory environments and there are no evaluation results of performance in real environments. Therefore, robot service providers and users have not been getting sufficient information on the level of current HRI technology. In this paper, we provide the evaluation results of the performance of the HRI components on the robot platforms providing actual services in pilot service sites. For the evaluation, we select face detection component, speaker gender classification component and sound localization component as representative HRI components closing to the commercialization. The goal of this paper is to provide valuable information and reference performance on appling the HRI components to real robot environments.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.552-555
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• 2011

최근 스마트폰, 태블릿 PC와 같은 모바일 스마트 디바이스(mobile smart devices)와 더불어 스마트 TV에 대한 관심이 크게 증가하면서 사용자들의 컨텐츠와 기능에 대한 요구 또한 다양해지고 있다. 스마트 TV가 컨텐츠와 기능적 측면에서 사용자의 편의와 재미, 그리고 유익함을 동시에 만족시키기 위해서는 더욱 지능화된 기능을 탑재할 필요가 있다. 일반적으로 남녀에 따라 TV를 시청하는 경향이 다르기 때문에 현재 TV를 시청하는 사용자의 성별분류(gender classification)를 통해 성별에 따른 따른 채널이나 광고, 응용 프로그램을 달리 제공하는 성별 기반의 스마트 TV 응용을 개발할 수 있게 된다. 본 논문에서는 스마트 TV 응용에 적합한 BGOLAM 기반의 성별분류 방법에 대해 제안하고, 실험을 통해 제안하는 방법의 적절성을 보인다.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.1
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• pp.246-259
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• 2013

The principal purpose of this study is to analyze school organizational culture in secondary school in Busan. This study measures background variables such as gender, teaching experience, classification of school, grade of school, and scale of school. The results of the study are as follows : First, to see the difference on the perception of organizational culture depending on gender, female teachers have a stronger sense of professionalism, community spirit and consideration than male teachers. Second, to see the difference on the perception of organizational culture in terms of teaching experience, teachers who have more than 21 years of teaching experience have a more positive perception on decision-making and consideration than those who have 11~20 years of teaching experience. Third, to see the difference on the perception of organizational culture according to classification of school, public schools have a more positive perception on every item such as professionalism, decision-making, community spirit, and consideration than private school. Fourth, to see the difference on the perception of organizational culture in terms of classification of schools, secondary schools have a more positive perception on professionalism and community spirit than high schools. Lastly, as it is seen in the difference on the perception of organizational culture depending on scale of school, schools which have 13~35 classes have a more positive perception on professionalism than others.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.483-486
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• 2020

Age estimation and gender classification for human is a classic problem in computer vision. Almost research focus just only one task and the models are too heavy to run on low-cost system. In our research, we aim to apply multitasking learning to perform both task on a lightweight model which can achieve good precision on embedded system in the real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1705-1720
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• 2013

Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.

• The Journal of Korean Physical Therapy
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• v.26 no.5
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• pp.315-323
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• 2014

Purpose: This study was conducted in order to investigate the effect of motor ability on mastery motivation in children with cerebral palsy. Methods: Sixty children with cerebral palsy (5~12 years) and their parents participated in the study. Data on general characteristics and disability condition, Gross Motor Functional Classification System, Manual Ability Classification System, and The Dimensions of Mastery questionnaire were collected for this study. Independent t-test, and ANOVA were used for analysis of the effect of The Dimensions of Mastery questionnaire according to general and disability condition, Gross Motor Functional Classification System, and Manual Ability Classification System. Linear regression analysis was performed to determine the effects of Gross Motor Functional Classification System and Manual Ability Classification System on The Dimensions of Mastery questionnaire. SPSS win. 22.0 was used and Tukey was used for post hoc analysis, level of statistical significance was less than 0.05. Results: The Dimensions of Mastery questionnaire score showed statistically significant difference according to gender, region, type, disability rating, Gross Motor Functional Classification System, and Manual Ability Classification System (p<0.05). Gross Motor Functional Classification System and Manual Ability Classification System were the effect factor on The Dimensions of Mastery questionnaire significantly (p<0.05). Conclusion: These results suggest that motor ability of children with cerebral palsy was an important factor having an effect on The Dimensions of Mastery questionnaire.