• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.517-529
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• 2021

This study analyzes changes in the efficiency of the Department of Early Childhood Education in Korea to examine the effectiveness of the National Evaluation for Teacher Education Institution. We provide policy implications from exploring factors influencing efficiency and comparing characteristics of efficient and inefficient departments. With 149 Department of Early Childhood Education in Korea, DEA was conducted to estimate the relative efficiency, and the Tobit model was applied to explore factors affecting efficiency. The results confirm that the Department of Early Childhood in Korea is run efficiently, though there was no change in scale efficiency and relative efficiency after the two phases of the National Evaluation for Teacher Education Institution. The results show the number of books per student was significantly lower despite a significantly higher employment rate. Efficiency of college departments, department greater than 60 (per cohort), and department in metropolitan city (except Seoul area) is confirmed greater. These results provide policy implications on developing evaluation measure and processes to improve education quality and efficiency.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.561-564
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• 2009

본 연구는 벤처기업의 기술사업화 촉진을 위한 전략 틀을 제공하고, S사를 통해 실제적인 기술사업화 사례를 제안하고자 한다. 기존의 기술사업화 내용이 국부적인 내용을 취급하고 있는 반면, 본 연구에서는 기존에 경영학에서 연구된 여러 가지 전략적 요소들을 재통합함으로써 기술이전을 받았거나 이미 개발된 기술에 적용하기에 적합한 하나의 새로운 종합적이고 구체적인 기술사업화 틀을 제공하고 있다. 주요 내용으로는 시장에서의 니즈를 해결할 수 있는 기술의 독특성을 파악하여 이를 제품으로 아이디어를 창출하고, 도출된 제품을 대상으로 기술사업화 기업이 사업화를 실행하였을 경우, 기능적인 면과 전략적인 면에서 사업으로의 생존 가능성과 발전 가능성 진단을 통하여 선별한 후, 해당 분야의 산업지도를 파악하여 비즈니스 모형을 도출하고, 이에 적합한 시장진입전략과 확장전략을 개발하는 절차로 진행된다. 이런 절차에 따라 실제적인 국내 벤처기업인 S사에 적용해봄으로써 제안한 분석기법의 효과성을 증명하기 위하여 본 연구를 수행한다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.3
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• pp.129-138
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• 2005

This paper presents a methodology for the determination of optimal managing criteria for cable tension force in cable-stayed bridges using acceleration data acquired by monitoring system. There are many long span bridges installed with monitoring system in Korea. The monitoring systems are installed to diagnose abnormal behavior or damages in bridges and to warn these to bridge management agency. In cable-stayed bridges, the cable tension force could be an important indicator of abnormal behavior because of the geometric configuration of the cable-stayed bridge. If the management value of cable tension force is set too high or too low, then the monitoring system could not warn properly for the abnormal behavior of a bridge. Generally, the management value is set by empirical or engineering judgment, but in this paper, a new methodology for the determination of managing criteria for cable tension force is proposed based on the probability distribution model for tension force and reliability analysis. The proposed methodology is applied to a real concrete cable-stayed bridge in order to investigate its applicability.

• Journal of Veterinary Clinics
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• v.24 no.2
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• pp.77-81
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• 2007

Diagnostic performance of polymerase chain reaction (PCR) for detecting Dirofilaria immitis in dogs was evaluated when no gold standard test was employed. An enzyme-linked immunosorbent assay test kit (SnapTM, IDEXX, USA) with unknown parameters was also employed. The sensitivity and specificity of the PCR from two-population model were estimated by using both maximum likelihood using expectation-maximization (EM) algorithm and Bayesian method, assuming conditional independence between the two tests. A total of 266 samples, 133 samples in each trial, were randomly retrieved from the heartworm database records during the year 2002-2004 in a university animal hospital. These data originated from the test results of military dogs which were brought for routine medical check-up or testing for heartworm infection. When combined 2 trials, sensitivity and specificity of the PCR was 96.4-96.7% and 97.6-98.8% in EM and 94.4-94.8% and 97.1-98% in Bayesian. There were no statistical differences between estimates. This finding indicates that the PCR assay could be useful screening tool for detecting heartworm antigen in dogs. This study was provided further evidences that Bayesian approach is an alternative approach to draw better inference about the performance of a new diagnostic test in case when either gold test is not available.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.3
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• pp.60-66
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• 2012

This paper aims to constitute a feedback vibration control system using wireless sensor networks and experiment it on a model structure to verify its effectiveness. For the purpose, we set up a feedback vibration control system composed of a wireless input/output(I/O) sensor node based on bluetooth, a home-made shear type MR damper, a shaker which generates a constant size of sine wave, and a simple beam model structure. The vibration control experiment was performed by shaking the 1/4 point of beam with a shaker. At the moment of shaking, we controled the vibration with MR damper which was placed vertically on the center of beam. Simultaneously, by acquiring acceleration response at the 2/4 point of beam, we evaluated the effectiveness of control capability. The control command was set to send a voltage signal to MR damper when the acceleration response, acquired from the wireless I/O sensor node placed at the center of beam, was more than a certain amount. Although the realtime feedback vibration control system constituted in this paper is effective only within a limited command system, it has been proven that the system was able to effectively decrease the vibration of structure by generating a control command aimed for realtime purpose. The system also showed a possibility to be used as a structural response control system adapting a variety of semi-active control algorithm.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.3
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• pp.37-45
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• 2000

In recent years two reflection methods, i.e. GPR and seismic Impact-Echo, are usually performed to obtain the information about tunnel lining structures composed of concrete lining, shotcrete, water barrier, and voids at the back of lining. However, they do not lead to a desirable resolution sufficient for the inspection of tunnel safety, due to many problems of interest including primarily (1) inner thin layers of lining structure itself in comparison with the wavelength of source wavelets, (2) dominant unwanted surface wave arrivals, (3) inadequate measuring strategy. In this sense, seismic physical modeling is a useful tool, with the use of the full information about the known physical model, to handle such problems, especially to study problems of wave propagation in such fine structures that are not amenable to theory and field works as well. Thus, this paper deals with various results of seismic physical modeling to enable to show a possibility of detecting the inner layer boundaries of tunnel lining structures. To this end, a physical model analogous to a lining structure was built up, measured and processed in the same way as performed in regular reflection surveys. The evaluated seismic section gives a clear picture of the lining structure, that will open up more consistent direction of research into the development of an efficient measuring and processing technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.2
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• pp.92-98
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• 2015

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring (SHM) technique is increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and influenced by various external loads. "Abnormal behavior point" is a moment when the structure starts vibrating abnormally and this can be detected by comparing between before and after abnormal behavior point. In other words, anomalous behavior is a sign of damage on structures and estimating the abnormal behavior point can be directly related to the safety of structure. Abnormal behavior causes damage on structures and this leads to enormous economic damage as well as damage for humans. This study proposes an estimating technique to find abnormal behavior point using Hilber-Huang Transform which is a time-frequency signal analysis technique and the proposed algorithm has been examined through laboratory tests with a bridge model using a shaking table.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.269-278
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• 2011

There are many researches that have considered the distribution functions and appropriate covariates corresponding to the scores in order to improve the accuracy of a diagnostic test, including the ROC curve that is represented with the relations of the sensitivity and the specificity. The ROC analysis was used by the regression model including some covariates under the assumptions that its distribution function is known or estimable. In this work, we consider a general situation that both the distribution function and the elects of covariates are unknown. For the ROC analysis, the mixtures of normal distributions are used to estimate the distribution function fitted to the credit evaluation data that is consisted of the score random variable and two sub-populations of parameters. The AUC measure is explored to compare with the nonparametric and empirical ROC curve. We conclude that the method using normal mixtures is fitted to the classical one better than other methods.