• Korea journal of population studies
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• v.18 no.1
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• pp.41-61
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• 1995

본 연구는 노동시장의 성별직종분리(occupational sex segregation)를 초래하는 요인들을 대분류 및 세분류 사업체를 단위로 규명하고자 하였다. 분석결과를 요약하면, 첫째, 사업체 성별직종분리에 영향을 미치는 요인 중 가장 중요한 것은 직급근로자 비율, 숙련기술자 비율, 그리고 사업체의 조직화 정도로 구성되어 있는 내부노동시작 특성으로 나타났다. 둘째, 사업체는 산업의 성별직종분리에 의해 영향을 받는 것으로 밝혀져 산업 전반에서 남성과 여성의 직종을 구분해 온 관행이 개별 사업체의 성별분리구조를 형성하고 고착화시키는 역할을 하는 것으로 보인다. 세째, 가정한 바와는 달리, 여성의 개인적인 자질향상이 성별직종분리의 개선과 직결되지는 않을 것으로 보인다. 그러나 평균 근속년수비는 성별직종분리를 감소시키는 것으로 나타나 여성이 노동시장에 지속적으로 참여하는 것이 성별직종분리를 개선할 수 있음을 시사한다. 네째, 사업체 성별직종분리 현상에 대한 내부노동시장 특성들의 높은 설명력과 여성의 경쟁력이 보여준 극히 미미한 설명력은 앞으로 산업구조 및 노동력의 유연화 추세에 직면하여 성별직종분리 구조의 개선 가능성에 대해 상반된 기대를 갖게 만든다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.588-590
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• 2016

사용자의 성별은 기본적이면서도 중요한 마케팅 데이터다. 그러나 최근에는 개인정보보호 강화 추세로, 회원가입 시 성별이나 나이 등의 세부 정보를 입력하지 않는 간편 가입이 많아졌다. 이러한 입력되지 않은 정보 추출을 위해 성별 예측 연구의 필요성이 증가되었다. 성별이 입력된 사용자의 정보를 바탕으로 성별이 입력되지 않은 사용자의 성별을 예측하는 기존 연구가 다양한 방법으로 진행되어왔고, 우수한 식별이 가능한 기법들은 이진분류기인 SVM을 기반으로 한 연구가 다수 존재한다. 그러나 SVM 알고리즘은 이진 분류만 가능하기 때문에 성별예측에 대한 정확률은 알 수가 없다. 성별예측의 정확률을 활용하면 부정확한 분류를 예방할 수 있으며 상품추천의 가중치로 사용 될 수 있다. 본 연구는 확률을 기반으로 하여 정확률을 추론 가능한 나이브 베이지안을 응용한다. 그리고 데이터 집합 사례를 균형있게 늘려주는 SMOTE기법을 이용해 클래스 불균형 문제를 개선했으며 또한 성별 예측의 특성에 맞게 노이즈를 제거하고, 성별 분류에 확정적인 아이템에 가중치를 적용했다. 더불어 제안 방법을 실제 데이터에 적용시켜 우수성을 입증하였다.

• Korean Journal of Cognitive Science
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• v.14 no.2
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• pp.37-46
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• 2003

Two experiments were conducted to explore the implicit representation of gender-stereotype using primed naming task for prime-target pairs. In Experiment 1, Participants were presented gender's attributes as primes at SOA 250ms and were asked to pronounce person's names which differed in typicality and preference of gender's attributes. The results showed that gender congruent effects was not found, but typicality effects and interactions were found. In Experiment 2, Participants were presented gender's attributes as primes at SOA 250ms and were asked to pronounce gender's attributes which differed in typicality of gender's attributes. The results showed that woman's attributes superiority effects were found, but typicality effects were not. These results were discussed from a point of view of graded representation of gender stereotype and asymmetrical processing of gender stereotype to priming conditions in the implicit level.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.568-574
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• 2010

In an effort to improve the speech recognition rate, we investigated performance comparison between speaker-independent and gender-specific speech recognitions. For this purpose, 20 male and 20 female speakers each pronounced 300 isolated Korean words and the speeches were divided into 4 groups: female, male, and two mixed genders. To examine the validity for the gender-specific speech recognition, Fourier spectrum and MFCC feature vectors averaged over male and female speakers separately were examined. The result showed distinction between the two genders, which supports the motivation for the gender-specific speech recognition. In experiments of speech recognition rate, the error rate for the gender-specific case was shown to be less than50% compared to that of the speaker-independent case. From the obtained results, it might be suggested that hierarchical recognition of gender and speech recognition might yield better performance over the current method of speech recognition.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.397-400
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• 2009

본 연구는 국가교육과정에서 문자 교육 입문기인 초등학교 1학년을 대상으로 하여 글자크기와 성별에 따른 가독성 차이를 알아보기 위한 연구로서 초등학교 1학년 학생에게 교과서 본문에 쓰이는 글자 크기는 실제 학습에 있어 가독성에 유의미한지 초등학교 1학년 학생들은 성별에 따라 본문 읽기는 어떤 다른 가독성 효과를 보이는지에 대하여 살펴보았다. 본 논문 주제에 대한 접근방법으로 먼저, 가독성의 개념, 가독성에 영향을 미치는 요소, 가독성 측정방법에 대한 고찰과 함께 초등학교 1학년 교과서 본문 글자 크기와 성별에 따라 가독성이 어떻게 달라지는지에 대하여 실험을 통하여 검증하였다. 초등학교 1학년 대상으로 글자 크기에 따른 가독성 차이를 살펴봄으로써 현행 교과서의 체제 개선에 필요한 기초 자료를 마련하고 성별에 따라 가독성 효과가 어떻게 차이가 나는지 살펴봄으로써 성별에 따른 남녀의 언어 발달 차이에 대한 이해와 성별에 따른 읽기 지도 전략에 시사점을 제공하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.63-65
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• 2012

본 논문에서는 입력된 음성이 남성화자인지 여성화자인지를 구분하는 FFT 스펙트럼 및 LPC 켑스트럼 입력에 의한 성별인식 알고리즘을 제안한다. 본 논문에서는 특히 남성화자와 여성화자의 특징벡터를 비교 분석하여, 이러한 남녀의 음향학적인 특징벡터의 차이점을 이용하여 신경회로망에 의한 성별 인식에 대한 실험을 수행한다. 특히 12차의 LPC 켑스트럼 및 8차의 저역 FFT 스펙트럼의 특징벡터를 사용한 경우에, 남성화자 및 여성화자에 대해서 양호한 남녀 성별인식률이 구해졌다.

• Communications of Mathematical Education
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• v.33 no.4
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• pp.445-453
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• 2019

Gender might be interpreted in different roles and meanings depending on social and cultural backgrounds. Based on the premise that understanding of gender may change the direction of mathematics education, this paper confirmed how gender is interpreted in the preceding study of mathematics education in Korea by applying the literature research method. In particular, predictive model based on empirical perspective and gender schema model based on constructivist perspective. Based on the analysis of gender and research methods in cultural and historical composition models based on historical perspectives and postmodernism models based on postmodernism perspectives, this study analyzed trends in domestic mathematics education. As a result of the analysis, it is confirmed that gender is recognized as a biological difference in domestic mathematics education, and that analysis of gender and related elements of mathematics education is mainly used using statistical analysis techniques. This suggests that various approaches to interpreting gender's role in future mathematics education are needed. The existing mathematics education research on gender is composed in terms of gender differences. Since biology at the time did not explain this difference, however, it should now be based on the concept of gender, which is socially defined gender. Accurate understanding of gender and gender can be the basis for clearer understanding and interpretation of gender-related mathematics research.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.37-44
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• 2017

While IoT (Internet of Things) industry has been spreading, it becomes very important for object to recognize user's information by itself without any control. Above all, gender (male, female) is dominant factor to analyze user's information on account of social and biological difference between male and female. However since each gender consists of diverse face feature, face-based gender classification research is still in challengeable research field. Also to apply gender classification system to IoT, size of device should be reduced and device should be operated with low power. Consequently, To port the function that can classify gender in real-world, this paper contributes two things. The first one is new gender classification algorithm based on deep learning and the second one is to implement real-time gender classification system in embedded board operated by low power. In our experiment, we measured frame per second for gender classification processing and power consumption in PC circumstance and mobile GPU circumstance. Therefore we verified that gender classification system based on deep learning works well with low power in mobile GPU circumstance comparing to in PC circumstance.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.147-163
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• 2016

Gender information of a smart device user is essential to provide personalized services, and multi-modal data obtained from the device is useful for predicting the gender of the user. However, the method for utilizing each of the multi-modal data for gender prediction differs according to the characteristics of the data. Therefore, in this study, an ensemble method for predicting the gender of a smart device user by using three classifiers that have text, application, and acceleration data as inputs, respectively, is proposed. To alleviate privacy issues that occur when text data generated in a smart device are sent outside, a classification method which scans smart device text data only on the device and classifies the gender of the user by matching text data with predefined sets of word. An application based classifier assigns gender labels to executed applications and predicts gender of the user by comparing the label ratio. Acceleration data is used with Support Vector Machine to classify user gender. The proposed method was evaluated by using the actual smart device log data collected from an Android application. The experimental results showed that the proposed method outperformed the compared methods.

• Journal of Oral Medicine and Pain
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• v.34 no.3
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• pp.303-316
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• 2009

This study was designed to evaluate the Temporomandibular Disorders(TMD) with Tension-Type Headache(TTH) by gender. Patients with TMD and/or TTH visited the Department of Oral Medicine, Kyung Hee University Dental Hospital were recruited to this study. Experimental group(n=60) is composed of TMD with TTH and control group(n=111) is composed of TMD without TTH. Evaluation list was pain quality, pain intensity, pain laterality, pain increase by routine physical activity and then it was analyzed statistically. The results were as follows ; 1. In the control group, pain quality was significantly different by gender(p=0.04). But, in the experimental group, pain quality was not significantly different by gender. 2. In the control group, pain intensity was not significantly different by gender. And, in the experimental group, pain intensity was not significantly different by gender. 3. In the control group, pain laterality was not significantly different by gender. And, in the experimental group, pain laterality was not significantly different by gender. 4. In the control group, pain increase by routine physical activity was not significantly different by gender. And, in the experimental group, pain increase by routine physical activity was not significantly different by gender. Therefore, it is considered that not temporomandibular disorder patients with tension-type headache but temporomandibular disorder patients without tension-type headache was influenced by gender in the pain quality.