• Journal of the Korean Data and Information Science Society
• /
• v.25 no.4
• /
• pp.715-725
• /
• 2014

This study uses a quantile regression analysis to investigate intergenerational economic mobility in Korea. The analysis is based on data from the 1st through 11th waves of the Korean Labor and Income Panel Study (KLIPS) conducted from 1998-2008. The household nature of the data allows us to link parents' incomes to children's incomes at different points in time. Using a quantile regression analysis instead of mean one reveals that the effect of fathers' earnings are different across the conditional distribution of sons' earnings, particularly being larger on the upper quantile than on the lower quantile. After controlling effect of sons' college education by including a dummy variable for the degree, however, the pattern among quantile effects for fathers' earnings is no longer clear. Instead a new pattern emerges that education has a much larger effect on the upper quantiles than on the lower ones. Using nonparametric estimates of conditional density curves based on the quantile regression results, we derive some interesting features in graphical forms, which are not obvious in numerical analysis.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.12
• /
• pp.3855-3865
• /
• 2000

The automatic indexing is a compulsory part for the text retrieval system. However it is impossible to rank the appropriate texts at top. Furthermore, it is more difficult to prevent to rank the inappropriate texts having homonyms at top by only the automatic indexing. In this paper, we proposed the two-level retrieval system to enhance the retrieval efficiency, in which Automatic Keyword Network (AKN) is used at the second-level process. The firsHevel search is carried out with an inverted index file generated by the automatic indexing. On the other hand the second-level search exploits AKN based on the degree of asslxiation between terms. We have developed several formulas for rearranging the rank of texts at second-level search, and evaluated the performance of the effects of them on resolving the word sense ambiguities.

• 대학교육
• /
• s.70
• /
• pp.92-99
• /
• 1994

대학의 목적 성취에서 행정직원의 역할은 증대되고, 그들에게 투입되는 인건비는 대학재정의 상당 부분을 차지한다. 대학 조직의 효과성을 제고하고 자원의 효율적인 활용을 도모하기 위하여 행정직원에 대한 평가는 거부될 수 없으며, 조직구성원으로서 감수해야 할 의무라고 할 수 있다. 행정직원에 대한 평가가 실시된다면 하위직뿐만 아니라 상위직까지 모두가 그 대상이 되어야 한다. 행정직원에 대한 평가에는 인적.물적 자원이 소요되고, 평가 결과는 대학의 인적 자원 관리에 많은 기여를 할 수 있다. 따라서 평가는 효율적.효과적으로 수행되어야 하며, 그 결과도 유용하게 활용되어야 한다.

• The Journal of the Korea Contents Association
• /
• v.16 no.8
• /
• pp.611-623
• /
• 2016

This research used one of the qualitative research techniques, in-depth interview method, on Taekwondo Gym instructors in their 30s to 50s with over 10 years experiences in various age groups, to elicit the empirical cases of emotional labor and exhaustion from their work. It categorized the cases into 3 main subjects that identified 2 areas to emphasized in each subjects through the phenomenological classification method. First subject listed, "recognition of emotional labor of the instructors", highlighted "recognition as a manager" and "recognition as an educator". Second subject listed. "meaning and need of emotional labor at the Taekwondo Gym", highlighted "emotional labor as a business strategy" and "emotional labor for educational effects". Third subject listed, "exhaustion from work experienced by the instructors", highlighted "a sense of shame experienced in the field" and "directions for change".

• Journal of KIISE
• /
• v.44 no.6
• /
• pp.621-627
• /
• 2017

Collaborative filtering is a technique that effectively recommends unrated items for users. Collaborative filtering is based on the similarity of the items evaluated by users. The existing top-N recommendation methods are based on pair-wise and list-wise preference models. However, these methods do not effectively represent the relative preference of items that are evaluated by users, and can not reflect the importance of each item. In this paper, we propose a new method to represent user's latent preference by combining an existing preference model and the notion of inverse user frequency. The proposed method improves the accuracy of existing methods by up to two times.

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.537-540
• /
• 2018

우리는 단어 임베딩에 외부지식을 내재할 수 있는 Ontofitting 방법을 제안한다. 이 방법은 retrofitting의한 방법으로 유의어, 반의어, 상위어, 하위어 정보를 단어 임베딩에 내재할 수 있다. 유의어와 반의어 정보를 내재하기 위해서 벡터의 각 유사도를 사용하였고 상하위어 정보를 내재하기 위해서 벡터의 길이 정보를 사용하였다. 유의어 사이에는 작은 각도를 가지고 반의어 사이에는 큰 각도를 가지게 된다. 하위어는 상위어보다 상대적으로 작은 길이를 가지게 된다. SimLex와 HyperLex로 실험하여 효과와 안정성을 검증하였다. 의미정보를 내재한 임베딩을 사용할 수 있다면 QA, 대화 등 응용에서 보다 좋은 성능을 보일 수 있을 것이다.

• Journal of Korea Technology Innovation Society
• /
• v.19 no.1
• /
• pp.191-229
• /
• 2016

As Korean national R&D projects have steadily grown in size, the needs of enhancing the efficiency and effectiveness of the national R&D budge spending has been also discussed. Therefore, many efforts have been made to establish performance assessment system to improve the efficiency and effectiveness of the national R&D project. One example of such efforts is the stipulation of connecting the results of performance evaluation ranking of the national R&D projects with the budge allocation of for the coming fiscal year. Unlike the stipulated article in the law/regulation that 'more budge shall be allocated to a project rated over excellent grade and vice versa', however, precedent studies have been casting mixed opinions over to the effectiveness of the connection between assessment results and budge allocation. In this respect, the present study attempted to empirically examine if the laws and institutions related to the results of performance evaluation ranking of the national R&D projects with the budge allocation work properly, using panel regression analysis and quantitative data. In addition, this study investigated into the deterrent factors to the connectivity between the performance results of the national R&D projects and budge allocation and sought for a way to improve the system of performance assessment and enhance the reliability of the results by minimizing the hindrance factors.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2012.01a
• /
• pp.153-157
• /
• 2012

이 연구는 자기조절학습전략 활용 과제기반언어학습을 영어수업에 적용한 후 학업성취도와 영어 학습태도 차원에서 그 효과성을 규명하고자 하였다. 먼저 학습자의 능동적인 학습과정을 도울 수 있는 자기조절학습전략 활용 과제기반언어 교수 학습 모형을 도출하였다. 이어서 초등영어 5학년 정규교육과정운영 틀에서 자기조절학습전략 활용 과제기반언어학습 수업을 설계하고 실제 적용하였다. 연구결과 첫째, 자기조절학습전략 활용 과제기반언어학습은 학업성취 상위, 중위, 하위 집단에 따른 학업성취도 변화에 대한 분석 결과 학업성취 상위집단과 하위집단 간에 유의미한 차이를 보였다. 둘째, 자기조절학습전략 활용 과제기반언 어학습은 영어에 대한 자아개념, 영어에 대한 태도, 영어에 대한 학습 습관으로 정의된 영어 학습태도의 모든 영역에서 유의미한 차이가 있었다. 자기조절학습전략 활용 과제기반언어학습은 학습자 중심 교육이라는 초등영어교육 추세를 고려할 때 교육현장에 유용하므로 자기조절학습력과 실제적 의사소통능력에 초점을 둔 보다 다양한 교수설계 연구가 요청된다.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.38 no.9
• /
• pp.663-670
• /
• 2001

This paper proposes a new power reduction method for 2D FIR (Finite Impulse Response) filters. We exploited the spatial redundancy of image data in order to reduce power dissipation in multiplication of FIR filters. Since the higher bits of input pixels are hardly changed, the redundant multiplication of higher bits is avoided by separating multiplication into higher and lower parts. The calculated values of higher bits are stored in memory cells, cache such that they can be reused when a cache hit occurs. Therefore, we can reduce power in 2D FIR Filter modules about 15% by using the proposed separated multiplication Technique (SMT).

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.23 no.5
• /
• pp.475-482
• /
• 2010

In this paper, an efficient two-level parallel domain decomposition algorithm is suggested to solve large-DOF structural problems. Each subdomain is composed of the coarse problem and local problem. In the coarse problem, displacements at coarse nodes are computed by the iterative method that does not need to assemble a stiffness matrix for the whole coarse problem. Then displacements at local nodes are computed by Multi-Frontal Sparse Solver. A parallel version of PCG(Preconditioned Conjugate Gradient Method) is developed to solve the coarse problem iteratively, which minimizes the data communication amount between processors to increase the possible problem DOF size while maintaining the computational efficiency. The test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF structural problems.