• Journal of the Ergonomics Society of Korea
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• v.33 no.1
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• pp.49-58
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• 2014

Objective: The aim of this study is to enhance the efficiency of education and training through application and management of 'Transfer of Training' in nuclear power plants. Background: Despite the sophistication and standardization of job-related skills and techniques of workers, accidents/incidents keep taking place due to human errors and unsafe actions and behaviors, which translates into the necessity to review and examine the effectiveness and influence of education and training on the workers of nuclear power plants. Method/Results: This study drew the factors of 'Transfer of Training' through a review on the preceding studies and document research. In addition, through expert examination, this study explored the expected effects and possibility of application when managing the influencing factors of 'Transfer of Training' in nuclear power plants. And lastly, management priority order for nuclear power plants was drawn through an AHP analysis. Conclusion: Among the 'Transfer of Training' factors, the training design factor was the most important. In addition, the design of the training and transfer and goal setting showed a high degree of importance among the influencing factors. Application: The management of 'Transfer of Training' in nuclear power plants enhances the capability of workers and improves the operational integrity of nuclear power plants.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.117-124
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• 2004

This paper proposes an efficient algorithm of NaiveBayes without loss of its accuracy. The proposed method uses the transposition of category vectors, and minimizes the computation of the probability of NaiveBayes. The proposed method was implemented on the existing framework of the text categorization, so called, AI::Categorizer and it was compared with the conventional NaiveBayes with the well-known data, Router-21578. The comparisons show that the proposed method outperforms NaiveBayes about two times with respect to the executing time.

• International Journal of Contents
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• v.1 no.2
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• pp.26-30
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• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.47-51
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• 2021

The article analyzes and studies that pedagogical design of the educational process using information and communication technologies in educational institutions of higher education based on the development of a model and methodology personalization of training will improve the quality of the educational process at the university and solve the identified contradiction. A qualitative analysis of foreign countries in the possibility of using information and communication technologies in educational institutions of higher education is carried out.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.391-398
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• 2022

The purpose of this study was to determine the factors that influence the training quality of Van Lang University's Finance Banking faculty (VLU). Another goal was to discover a way to increase training quality and give students the greatest experience possible. To achieve the following goals, qualitative research was used in combination with questionnaires and document reviews. A total of 700 surveys were sent out, with 624 responses. In-depth interviews with 12 graduates were conducted during the qualitative stage to obtain their perspectives on their time at VLU. The impact of five factors (instructor qualification, facility, education program, accessibility, and student interaction) was investigated in this study, and the findings revealed that all of them significantly mediated the relationship with the training quality of VLU's Finance Banking faculty. The findings show that it is vital to improve the training quality to increase student satisfaction and boost their academic abilities. With the framework from this study, policymakers, researchers, and institutes can cooperate in developing and upgrading the general training quality at higher education institutions in Vietnam. Improving the training quality of a faculty will continue to be a challenge. Therefore, this is a topic that requires continuous research.

• Research in Mathematical Education
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• v.13 no.2
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• pp.141-150
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• 2009

This study gives opportunity for investigating how student teachers view the teaching profession and how they transfer their pedagogical knowledge into practice. The aim of the study is to investigate the teaching skills student teachers gained in the assessment of micro teaching of their peers. The participants are 30 mathematics student teachers enrolled in the teacher training program in a state university. Document analysis and semi-structured interviews are the research instruments and inferential & descriptive statistics are used for the data analysis. The findings suggest that the qualitative and quantitative peer assessments of student teachers were graded differently which results from the difference of perceptions about teaching and different conceptualizations of the teaching qualifications.

• The Mathematical Education
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• v.42 no.5
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• pp.595-606
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• 2003

In this paper we analyze the Russian national curriculum for training of mathematics teachers at universities published by Russian Ministry of Education. From the document we are able to know the structure of the curriculum, compulsory subjects, and minimum mathematical contents for training mathematics teachers at universities.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.171-181
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• 2001

The previous Bayesian document categorization method has problems that it requires a lot of time and effort in word clustering and it hardly reflects the semantic information between words. In this paper, we propose a weighted Bayesian document categorizing method based on association word knowledge base acquired by mining technique. The proposed method constructs weighted association word knowledge base using documents in training set. Then, classifier using Bayesian probability categorizes documents based on the constructed association word knowledge base. In order to evaluate performance of the proposed method, we compare our experimental results with those of weighted Bayesian document categorizing method using vocabulary dictionary by mutual information, weighted Bayesian document categorizing method, and simple Bayesian document categorizing method. The experimental result shows that weighted Bayesian categorizing method using association word knowledge base has improved performance 0.87% and 2.77% and 5.09% over weighted Bayesian categorizing method using vocabulary dictionary by mutual information and weighted Bayesian method and simple Bayesian method, respectively.

• International Journal of Contents
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• v.8 no.3
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• pp.83-93
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• 2012

In this paper, we propose a novel method that automatically generates real character images to familiarize existing OCR systems with new fonts. At first, we generate synthetic character images using a simple degradation model. The synthetic data is used to train an OCR engine, and the trained OCR is used to recognize and label real character images that are segmented from ideal document images. Since the OCR engine is unable to recognize accurately all real character images, a substring matching method is employed to fix wrongly labeled characters by comparing two strings; one is the string grouped by recognized characters in an ideal document image, and the other is the ordered string of characters which we are considering to train and recognize. Based on our method, we build a system that automatically generates 2350 most common Korean and 117 alphanumeric characters from new fonts. The ideal document images used in the system are postal envelope images with characters printed in ascending order of their codes. The proposed system achieved a labeling accuracy of 99%. Therefore, we believe that our system is effective in facilitating the generation of numerous character samples to enhance the recognition rate of existing OCR systems for fonts that have never been trained.

• Journal of the Korea Institute of Construction Safety
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• v.5 no.1
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• pp.1-8
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• 2023

The purpose of this study is to suggest a way to solve the excessive paperwork of safety managers in domestic construction sites, and to suggest a work efficiency plan that can shorten the time required to prevent safety accidents. First, a function to automatically generate a safety document and find the necessary data is applied using the RPA program. The second is document creation using mobile devices. After safety training, use the Moleil app to keep the training log. Third, to prevent omission of essential safety and health documents, the automatic warning function is activated according to the RPA submission time and sent to the person in charge by e-mail or text. Fourth, the function to find the latest data with high accuracy and speed through 'Google Cloud Search', a search function, was applied.