• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.723-735
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• 2010

Evaluating the level of achievement and providing the knowledge which is appropriate at the evaluated level have great influence in studying of the human beings. This shows the importance of the order of training and the training order should be considered in machine learning. In this research, to assess the influence of the order of training, we propose a method of controlling the order of training samples utilizing the experience of supervisor in the training of MLP. The supervisor finds out the current state of MLP using teaching experience and student evaluation, and then selects the most instructive sample for MLP in that state. We use CRF to represent and utilize the experience of supervisor. While the proposed method is similar to active learning in selecting samples, it is basically different in that selection is not to reduce the number of samples to be used but to assist the learning progress. The result from classification problem shows that the method is usually effective in terms of time taken in training in contrast to random selection.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.489-494
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• 2015

Background: Once limited with face-to face courses, health education has now moved into the web environment after new developments in information technology This study was carried out in order to give training to the university academic and administrative female staff who have difficulty in attending health education planned for specific times and places. The web-supported training focuses on healthy diet, the importance of physical activity, damage of smoking and stress management. Materials and Methods: The study was carried out in Sakarya University between the years 2012-2013 as a descriptive and quasi experimental study. The sample consisted of 30 participants who agreed to take part in the survey, filled in the forms and completed the whole training. The data were collected via a "Personel Information Form", "Health Promotion Life-Style Profile (HPLSP)", and "Multiple Choice Questionnaire (MCQ). Results: There was a statistically significant difference between the total points from "Health Promotion Life-Style Profile" and the total points from the sub-scale after and before the training (t=3.63, p=0.001). When the points from the multiple choice questionnaire after and before training were compared, it was seen that the average points were higher after the training (t=8.57, p<0.001). Conclusions: It was found that web-supported health training has a positive effect on the healthy living behaviour of female staff working at a Turkish university and on their knowledge of health promotion.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.195-208
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• 1999

In the classification of satellite images, the representative of training of classes is very important factor that affects the classification accuracy. Hence, in order to improve the classification accuracy, it is required to optimize pre-classification stage which determines classification parameters rather than to develop classifiers alone. In this study, the normality of training are calculated at the preclassification stage using SPOT XS and LANDSAT TM. A correlation coefficient of multivariate Q-Q plot with 5% significance level and a variance of initial training are considered as an object function of genetic algorithm in the training normalization process. As a result of normalization of training using the genetic algorithm, it was proved that, for the study area, the mean and variance of each class shifted to the population, and the result showed the possibility of prediction of the distribution of each class.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.463-472
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• 2018

The purpose of this study was to investigate the influence of hotel training satisfaction to on the job satisfaction, organizational commitment, and service quality. The sample was obtained during 3weeks periods from Oct $14^{th}$ 2017 to Nov $4^{th}$ 2017 and out of 230 copies of the questionnaire, 223 copies responded with sincerity were made an object of the analysis. The results of the study were as follows, Firstly, training had an positive impact on the job satisfaction, Secondly, training significantly effected on organizational commitment. And practical training in the hotel has a positive impact on improving the quality of service. Third, job satisfaction has a positive effect on quality of service. Finally, organizational commitment also has a positive effect on service quality.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1167-1187
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• 2020

We are facing the situation where cyber threats such as hacking, malware, data leakage, and theft, become an important issue in the perspective of personal daily life, business, and national security. Although various efforts are being made to response to the cyber threats in the national and industrial sectors, the problems such as the industry-academia skill-gap, shortage of cybersecurity professionals are still serious. Thus, in order to overcome the skill-gap and shortage problems, we propose a Cybersecurity technical response Job Competency(CtrJC) framework by adopting the concept of cybersecurity personnel's job competency. As a sample use-case study, we implement the CtrJC against to personals who are charged in realtime cybersecurity response, which is an important job at the national and organization level, and verify the our framework's effects. We implement a sample model, which is a CtrJC against to realtime cyber threats (We call it as CtrJC-R), and study the verification and validation of the implemented model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.997-1008
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• 2022

Today, AI(Artificial Intelligence) technology is being extensively researched in various fields, including the field of malware detection. To introduce AI systems into roles that protect important decisions and resources, it must be a reliable AI model. AI model that dependent on training dataset should be verified to be robust against new attacks. Rather than generating new malware detection, attackers find malware detection that succeed in attacking by mass-producing strains of previously detected malware detection. Most of the attacks, such as adversarial attacks, that lead to misclassification of AI models, are made by slightly modifying past attacks. Robust models that can be defended against these variants is needed, and the Robustness level of the model cannot be evaluated with accuracy and recall, which are widely used as AI evaluation indicators. In this paper, we experiment a framework to evaluate robustness level by generating an adversarial sample based on one of the adversarial attacks, C&W attack, and to improve robustness level through adversarial training. Through experiments based on malware dataset in this study, the limitations and possibilities of the proposed method in the field of malware detection were confirmed.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2096-2106
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• 2023

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-driven fault diagnosis faces the problem of small and imbalanced samples, resulting in low model training efficiency and poor generalization performance. Therefore, a deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis. First, a conditional generative adversarial model is designed based on convolutional neural networks to effectively augment imbalanced samples. The original sample features can be effectively extracted by the model based on conditional generative adversarial strategy and appropriate number of filters. In addition, high-quality generated samples are ensured through the visualization of model training process and samples features. Then, a deep convolutional neural network (DCNN) is designed to extract features of mixed samples and implement intelligent fault diagnosis. Finally, based on multi-fault experimental data of motor and bearing, the performance of DCCGAN model for data augmentation and intelligent fault diagnosis is verified. The proposed method effectively alleviates the problem of imbalanced samples, and shows its application value in intelligent fault diagnosis of actual NPPs.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.53-64
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• 2014

The purpose of the study is to develop a scale for measuring learning outcomes in the distance teacher training programs. In order to develop the measurement instrument, the forty-four items were developed based on the literature review and ten experts' review. For data collection, a web-based survey was conducted among teachers taking a distance teacher training program at National Education Training Institute. With the data of 205 sample size from the first survey, the Exploratory Factor Analysis was conducted and seven factors were identified. In order to validate the test, the Confirmatory Factor Analysis was performed with 293 respondents from the second survey. In conclusion, this study reports the reliability and validity of a scale for learning outcomes in distance teacher training programs consisting of seven factors with 34 items; 1) system quality, 2) content quality, 3) service quality, 4) use, 5) benefit, 6) satisfaction, 7) transfer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.15
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• pp.6421-6423
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• 2014

Background: Recent studies have revealed a prognostic impact of the MPV (mean platelet volume)/platelet count ratio in terms of survival in advanced non-small cell lung cancer. However, there has been no direct analysis of the survival impact of MPV in patients with mCRC. The aim of the study is to evaluate the pretreatment MPV of patients with metastatic and non-metastatic colorectal cancer (non-mCRC) and also the prognostic significance of pretreatment MPV to progression in mCRC patients treated with bevacizumab-combined chemotherapy. Materials and Methods: Fifty-three metastatic and ninety-five non-metastatic colorectal cancer patients were included into the study. Data on sex, age, lymph node status, MPV, platelet and platecrit (PCT) levels were obtained retrospectively from the patient medical records. Results: The MPV was significantly higher in the patients with mCRC compared to those with non-mCRC ($7.895{\pm}1.060$ versus $7.322{\pm}1.136$, p=0.013). The benefit of bevacizumab on PFS was significantly greater among the patients with low MPV than those with high MPV. The hazard ratio (HR) of disease progression was 0.41 (95%CI, 0.174-0.986; p=0.04). In conclusion, despite the retrospective design and small sample size, MPV can be considered a prognostic factor for mCRC patients treated with bevacizumab-combined chemotherapy.