• Journal of Labour Economics
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• v.25 no.1
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• pp.131-160
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• 2002

This article tried to find out the individual wage effect of training. This Article used 1998, 1999 KLIPS(Korea Labor and Income Panel Study) panel data. The size of the individual wage effect of training was twice of tenure's, and had significance. Training had a good effect on the job satisfaction and carrier development. To overcome self selection bias, this article regressed the first difference of wage equations, but we didn't get the significant results. Dividing sample into quitters and non-quitters in order to investigate the relation between training cost and benefit, we regressed separately the each first difference of wage equation. On quitters, the individual effect of training appeared significantly, but on non-quitters, it didn't. This results mean that employer does not raise wage rate according to upgraded skill originated in incumbent's training. And the results also mean that the upgraded skill of employee who quit pre-employer is recognized by new employer, and his wage rate rises in his new job.

• Journal of muscle and joint health
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• v.2 no.1
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• pp.41-72
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• 1995

The purpose of this study is to examine the effects of assertiveness training and value clarification training on nurse's conflict and conflict management mode. Fifty seven registered nurses participated in the study ; they were employed by three general hospital located in Daegu, Korea. The study employs two treatment groups. The assertiveness training group consisted of subjects who participated in 90-120 minutes sessions of assertiveness training nine times over five weeks. The other treatment group, was adiministed nine, 90-120 minutes sessions of value clarification during the same period. For the control group, nursing subjects were appointed the training after five weeks. Pre-test evaluation were administered to all subjects in three groups prior to one week of the treatment. Role conflict Inventory-general(RCI-G) and Communication Conflict Inventory-general (CCI-G) measure nurse's conflict management mode. Post-test evaluation were administered to all subjects in three groups two weeks after the last session by Role Conflict Inventory-Specific(RCI-S), Communication Conflict Inventory-Specific (CCI-S), Management Model-Specific(CMMI-S). The analysis of variance(ANOVA) and covariance(ANCOVA) on gain scores were running the SPSS program. In order to test statistical differences among mean scores of the scales obtained after treatment, multiple comparisons were carried out by Turkey method. Conclusions obtained from the results are as follows. 1. The assertiveness training and the value clarification training were effective in decreasing the nurse's role conflict. The value clarification was more effective than the assertiveness training in decreasing the nurse's role conflict. 2. Both assertiveness training and value clarification training were effective in decreasing nurse's communication conflict. There was, however, no differences between assertiveness training and value clarification training in decreasing the nurse's communication conflict. 3. The assertiveness training and the value clarification training were quite effective in compromizing and collaborating conflict management mode, to reducing the withdrawl and accomodate, force and accomodate conflict management mode to conflict. There was no difference in the effectiveness of assertiveness training and value clarification. In assessing the effects of the treatments, this study employed different measurements. It is unclear whether the measurement affected the test results. It is worth conducting a further test using the same measurements. The results of future studies can be compared with those of this study. The homogeneity of the control group and treatment group is questionable. Futher studies may employ homogeneous sample group to evaluate whether the sample characteristics bias the test results. Assertiveness training or value clarification training for nurses can be utilized in nursing intervention.

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.71.2-71.2
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• 2007

• MALSORI
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• no.52
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• pp.145-160
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• 2004

In this paper, a new noise compensation method based on the eigenvoice framework in feature space is proposed to reduce the mismatch between training and testing environments. The difference between clean and noisy environments is represented by the linear combination of K eigenvectors that represent the variation among environments. In the proposed method, the performance improvement of speech recognition systems is largely affected by how to construct the noisy models and the bias vector set. In this paper, two methods, the one based on MAP adaptation method and the other using stereo DB, are proposed to construct the noisy models. In experiments using Aurora 2 DB, we obtained 44.86% relative improvement with eigen-environment method in comparison with baseline system. Especially, in clean condition training mode, our proposed method yielded 66.74% relative improvement, which is better performance than several methods previously proposed in Aurora project.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.155-159
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• 2003

최근 들어 SVM(support vector machines)은 기계학습의 분야에서 많은 응용이 이루어지고 있으며 특히 분류(classification)나 회귀(regression)분석의 영역에서 많은 연구가 진행중이다. 본 논문에서는 SVM을 이용하여 입력영상자료(image data)를 분류하고자 한다. RGB 컬러 영상자료가 입력되면 이미지 크기에 관계없이 이미지 자체를 입력패턴으로 인식하고 SVM을 통한 훈련(training)을 거친 결과(weight 들과 bias 추정치)를 이용하여 입력영상자료가 사람인가를 분류할 수 있는 문제를 다룬다. 제안된 방법의 타당성은 152개의 영상자료에 적용하여 분석되었다.

• Journal of the Korean Geophysical Society
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• v.4 no.3
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• pp.175-182
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• 2001

We consider the problem of determining smoothing parameters of Gibbs priors for Bayesian methods used in the medical imaging application of emission tomographic reconstruction. We address a simple smoothing prior (membrane) whose global hyperparameter (the smoothing parameter) controls the bias/variance tradeoff of the solution. We base our maximum-likelihood (ML) estimates of hyperparameters on observed training data, and argue the motivation for this approach. Good results are obtained with a simple ML estimate of the smoothing parameter for the membrane prior.

• The Journal of Engineering Research
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• v.4 no.1
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• pp.47-54
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• 2002

We consider the problem of determining smoothing parameters of Gibbs priors for Bayesian methods used in the medical imaging application of emission tomographic reconstruction. We address a simple smoothing prior (membrane) whose global hyperparameter (the smoothing parameter) controls the bias/variance tradeoff of the solution. We base our maximum-likelihood(ML) estimates of hyperparameters on observed training data, and argue the motivation for this approach. Good results are obtained with a simple ML estimate of the smoothing parameter for the membrane prior.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.82-89
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• 2017

The range of problems that can be handled by the activation of big data and the development of hardware has been rapidly expanded and machine learning such as deep learning has become a very versatile technology. In this paper, mnist data set is used as experimental data, and the Cross Entropy function is used as a loss model for evaluating the efficiency of machine learning, and the value of the loss function in the steepest descent method is We applied the GradientDescentOptimize algorithm to minimize and updated weight and bias via backpropagation. In this way we analyze optimal reliability value corresponding to the number of exercises and optimal reliability value without overfitting. And comparing the overfitting time according to the number of data changes based on the number of training times, when the training frequency was 1110 times, we obtained the result of 92%, which is the optimal reliability value without overfitting.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.21-30
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• 2013

Korean Volunteer Fire Departments are the representative disaster-related civilian organizations which are based on "Firefighting Framework Act Article 37"and ordinance for complementing the lack of fire-fighting personnel and volunteer and they play a part as community safety keepers. They are operated by the National funding, but cannot be defined as the organization in governmental sources completely or pure volunteer organization in terms of its founding purpose and activities. In these special characteristics, some Volunteer Fire Departments play an important role in Civilian Volunteer Disaster Prevention by being managed effectively, but the others do not. There can be many cause-analyses about this difference. They aren't profit-making organizations and are groups which have no compulsion. So it is important that who the leader is, and what type of leadership he has. By solving this bias by considering these characteristics, in this study we make them perform the center role of community safety network through analyzing the existing status and problems of volunteer fire department education and customized training program reengineering to meet class-specific and regional level.

• Journal of Labour Economics
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• v.26 no.1
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• pp.23-52
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• 2003

This study focus on unemployment and nonparticipation of youth. By dividing youth nonparticipants into 'house work and child care', 'studying and training', 'the others' categories, we estimate the potential wages with selectivity bias model and analyse the factors of choosing unemployment or nonparticipation with multinomial logit model. The differences between the potential market wage and the desired wage of the groups of 'studying and training', 'the others' in the nonparticipants are greater than those of the unemployment group. In the case of the man and lower age, and low schooling the differences of potential and desire wage are larger than woman and higher age, and high schooling. In the choice of unemployment and nonparticipation, man and higher age, and householder, and holder of qualification are not likely to opt nonparticipation. The experience of job lower the rate of probability to choose employment, but raise the rate of probability to choose unemployment and nonparticipation. These results mean that the quality of youth employment is very inferior.