• Korean Deer Journal
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• v.12 no.2 s.65
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• pp.60-66
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• 2006

사슴뿔은 다른 동물의 뿔과는 달리 영구조직이 아닌 1년생의 탈락성 조직으로 구성되어 있다. 광주기의 변화에 의해 매년 봄에 탈락이 되고 새 뿔이 돋아나는 계절성을 가지고 있는 것이 특징이다. 식물에서 촉성재배와 억제재배라는 기술을 응용하여 생산시기를 조절하는 것처럼 사슴뿔의 성장생리 조절연구는 뿔 성장주기를 조절하여 녹용의 생산시기를 조절할 수 있고 장차 소비자가 선호하는 양질의 녹용을 생산 할 수도 있다.

• Development and Reproduction
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• v.13 no.4
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• pp.297-303
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• 2009

Implantation of blastocyst into the uterine endometrium is established by the existence of histologically and functionally prepared uterine endometrium. Doc-1, an oral cancer suppressor gene, is expressed under the control of steroid hormones and has been suggested as a proliferation regulator of endometrial cells. However, the role is not much clear and in this study we examined the expression modulation of Doc-1 in decidualizing cells in vitro. In vitro decidualization was performed in endometrial stroma cells using progesterone and estrogen. Until 24 hr after decidual induction the proliferation of stroma cell was significantly increased but decreased after then. On the other hand, most of the cells differentiated into decidual cell after 48 hr of induction. The Doc-1 protein was co-localized in a specific deciudal cells and colocalization rate was increased in a parallel manner with the induction time. Based on these results, it is suggested that Doc-1 expression is under the control of both steroid hormones and decidual signals, and Doc-1 protein is involved in suppression of the proliferation of decidualizing cells.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.34-41
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• 2021

Sidewalks are facilities used for the safe and comfortable passage of pedestrians and are paved with blocks of various materials. Currently, Korea does not have a quantitative survey method for the pavement condition of sidewalks, so it is necessary to develop an efficient survey method. Drones are being used as an efficient survey tool in various fields, but there are limited studies in which sidewalks have been investigated. This study investigates the possibility of detection by limiting the missing sidewalk blocks using a drone. This study is an initial study on the development of a method for detecting damage in sidewalk blocks. For this, sidewalk blocks were artificially removed to simulate a dropout situation, and images were acquired with 0.7-cm resolution using a drone. As a characteristic of the point cloud data acquired through image pre-processing, there was high variance of the elevation of the points in the missing area of the sidewalk block. Using these characteristics, an experiment was conducted to detect the missing parts of the sidewalk block by applying four thresholds to the variance of the elevation of points included in the grid corresponding to the sidewalk area. As a result, the detection accuracy was shown with a positive detection ratio of 70-80%, omission errors of 20-30%, and commission errors lower than 2%. It is judged that the possibility of detecting missing sidewalk blocks is high. This study focused on detecting a simulated missing sidewalk block in a limited environment. Therefore, it is expected that an efficient and quantitative method of detecting damaged sidewalk blocks can be developed in the future through additional research with considerations of the actual environment.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.32-40
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• 2009

In order to reduce time-to-market, the demand for fast fault diagnosis has been increased. In this paper, a fault dropping technique with fault candidate ordering and test pattern ordering for fast fault diagnosis is proposed. Experimental results using the full-scanned ISCAS 89 benchmark circuits show the efficiency of the fault dropping technique with fault candidate ordering and test pattern ordering.

• Korean Journal of Social Welfare
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• v.61 no.4
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• pp.191-215
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• 2009

The purposes of this study were to investigate the factors that influence the school drop-out of North Korean refugee youth and to generate recommendations for social work practice and the resettlement policies of the government to ameliorate the high school drop-out rate among North Korean refugee youth. This study examined the effects of the environmental factors such as the quality of parenting practice, peer attachment and the kind of school a youngster attends, and personal characteristics such as self-respect and acculturation stress level, and academic efficacy on the school drop-out intention. Gender, duration of stay in Korea, family economic status were established as control variables. The drop-out intention was used as a proxy for drop-out behavior. The study findings indicate that the personal characteristics such as gender, self-respect and acculturation stress, academic efficacy were the significant influencing factors, whereas environmental factors such as quality of parenting, peer attachment did not exert any statistically significant effect on the drop-out intention. At the conclusion, the implications of the study findings for research, social work practice and the government policies were discussed.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.43-51
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• 2002

In this paper, we study the new packet dropping scheme using an active queue management algorithm. Active queue management mechanisms differ from the traditional drop tail mechanism in that in a drop tail queue packets are dropped when the buffer overflows, while in active queue management mechanisms, packets may be dropped early before congestion occurs, However, it still incurs high packet loss ratio when the buffer size is not large enough, By detecting congestion and notifying only a randomly selected fraction of connection, RED causes to the global synchronization and fairness problem. And also, it is the biggest problem that the network traffic characteristics need to be known in order to find the optimum average queue length, We propose a new efficient packet dropping method based on the active queue management for congestion control. The proposed scheme uses the per-flow rate and fair share rate estimates. To this end, we present the estimation algorithm to compute the flow arrival rate and the link fair rate, We shows the proposed method improves the network performance because the traffic generated can not cause rapid fluctuations in queue lengths which result in packet loss

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.37-43
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• 2021

This study proposed an effective automatic classification technique to identify dropout patterns of university students, and based on this, an intelligent recommender system to prevent dropouts. To this end, 1) a data processing method to improve the performance of machine learning was proposed based on actual enrollment/dropout data of university students, and 2) performance comparison experiments were conducted using five types of machine learning algorithms. 3) As a result of the experiment, the proposed method showed superior performance in all algorithms compared to the baseline method. The precision rate of discrimination of enrolled students was measured to be up to 95.6% when using a Random Forest(RF), and the recall rate of dropout students was measured to be up to 80.0% when using Naive Bayes(NB). 4) Finally, based on the experimental results, a method for using a counseling recommender system to give priority to students who are likely to drop out was suggested. It was confirmed that reasonable decision-making can be conducted through convergence research that utilizes technologies in the IT field to solve the educational issues, and we plan to apply various artificial intelligence technologies through continuous research in the future.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.49-58
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• 2023

Dropouts of students not only cause financial loss to the university, but also have negative impacts on individual students and society together. To resolve this issue, various studies have been conducted to predict student dropout using machine learning. This paper presents a model implemented using DNN (Deep Neural Network) and LGBM (Light Gradient Boosting Machine) to predict dropout of university students and compares their performance. The academic record and grade data collected from 20,050 students at A University, a small and medium-sized 4-year university in Seoul, were used for learning. Among the 140 attributes of the collected data, only the attributes with a correlation coefficient of 0.1 or higher with the attribute indicating dropout were extracted and used for learning. As learning algorithms, DNN (Deep Neural Network) and LightGBM (Light Gradient Boosting Machine) were used. Our experimental results showed that the F1-scores of DNN and LGBM were 0.798 and 0.826, respectively, indicating that LGBM provided 2.5% better prediction performance than DNN.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.289-295
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• 2008

The purpose of this study was to examine the flexural behavior of reinforced concrete beams strengthened with CFRP strips. A total of 12 rectangular beams were tested. Test variables in this study were the shapes, bonded length and the number of longitudinal layers of CFRP strips. From the experimental study, flexural capacity of the beams strengthened with CFRP strips significantly increased compared to the reinforced concrete beam without a CFRP strip. Maximum increase of ultimate strength was found about 120% more than the control beam. In this test, most of the strengthened beams failed suddenly due to the debonding of CFRP strips. It is also observed that the debonding of the strip was initiated in the flexural zone of the beam and propagated rapidly to the end of the beam. The ultimate tensile strains of CFRP strips in this test were occurred at the level of 36% of rupture tensile strength of the CFRP strip, and an analytical approach to compute the flexural strength of reinforced beams strengthened with CFRP strips based on the effective stresses was conducted.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.51-52
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• 2011

본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)기법을 결합한 WSVD(Wavelet Singular Value Decomposition)를 사용하여, 송전계통에서 부하 탈락 시 나타나는 특성 및 외란검출의 유효성을 분석하였다. WSVD 방식을 이용한 외란검출을 모의하기 위해 EMTP-RV를 이용하여 부산 및 경남 일부지역 345kV급 송전계통을 모델링하였고, 이 계통에서 부하 탈락을 모의하였다. WSVD의 계산은 MATLAB을 통해 수행하였으며, 이 결과를 바탕으로 전력계통에서 부하 탈략량의 변화에 따른 특징을 분석하였다