• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1271-1279
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• 2020

Text region detection is a technology that detects text area in handwriting or printed documents. The detected text areas are digitized through a recognition step, which is used in various fields depending on the purpose of use. However, the detection result of the small text unit is not suitable for the industrial field. In addition, the border of tables in the document that it causes miss-detected results, which has an adverse effect on the recognition step. To solve the issues, we propose a method for detecting text region using the border information of the table. In order to utilize the border information of the table, the proposed method adjusts the flow of two decoders. Experimentally, we show improved performance using the table border pseudo label based on weak supervised learning.

• Hwankyungkyoyuk
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• v.9 no.1
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• pp.39-57
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• 1996

All kinds of environmental problems are related to each local and geographical environment. For this reason, it is necessary for schools in each region to provide environmental education which suits the geographical character of their particular region. In order to provide solutions to the environmental problems of each school's geographic region, the goal of this research is as follows: 1. We can make students realize the relationship between the human race and the environment by teaching according to the environmental conditions in each local area. 2. By teaching students about the problems in their own local environment, we can increase their concern about the state of their local surroundings. 3. When teaching about the environment, it is useful to use educational material which suits the character of each local region. 4. Students' interest in environmental preservation can be aroused through extracurricular environmental activities. The ares concerned are Chonnam and Kwangju City, which are divided into urban, industrial, rural, coastal, and mountainous areas. The conclusion about considering environmental education in environmental school social studies is as follows: 1. Kwangju and Chonnam should be divided into five sections, each with similar geographical environments. This will be an improvement over the old uniform approach to environmental studies in which all regions were treated as being the same each region will now receive special attention. 2. It is necessary to maximize the efficient use of the Environmental Education Building. When Media, environmental data and special materials for environmental education are used effectively, teachers can lead class effectively and students will be more interested in the class. 3. We can detect the cause of pollution, increase interest in the environment and easily solve environmental problems by collecting and displaying environmental educational materials. 4. An environmental education corner could boost students' interest in environmental problems and could act as a kind of bridge between theoretical and practical education. 5. Media and environmental data must be specialized according to the geographic character of each region. In this way, we can expect to improve the quality of environmental education over the simplistic environmental education of previous years. 6. Students will become interested in the problems of the region in which they live through social studies, and primarily through the environmental curriculum. 7. We can prevent learning deficiencies by making a consistent teaching plan. The teaching and learning methods will be improved and the teachers will be proud of what they teach. 8. The purpose of the Education Procedure Content Analysis is to make teaching and learning concise and easy by systematizing environmental and related subjects. This can be done by adding an environmental unit to the geographic section of social studies. 9. Citizens' interest in their own residential environment can be increased through action by sustaining environmental preservation movements to local region people.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.717-733
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• 2021

This study is aimed to provide basic data to set the direction of polar literacy education and to raise awareness of the importance of polar research. Elementary, middle, and high school students' perception of the polar region was examined in terms of current status of polar information, impression regarding polar regions, and awareness of related issues. The study included 975 students from nine elementary, middle, and high schools, who responded to 16 questions, including close-ended and open-ended items. The results suggest that students had more experiences regarding the polar region on audiovisual media, but relatively limited learning experiences in school education. The impression they had of the polar region was confined to the monotonous image of a polar bear in crisis, following the melting of the glacier due to global warming. The students formed powerful images by combining scenes they saw in audiovisual media with emotions. In terms of recognizing problems in the polar region, the students were generally interested in creatures, natural environment, and climate change, but their interests varied depending on their school level and their own career path. The students highly valued the scientist's status as agents to address the problems facing the region, and gave priority to global citizenship values rather than practical standards. Based on the results, we suggest the following: introducing and systematizing content focusing on the polar region in the school curriculum, providing a differentiated learning experience through cooperation between scientists and educators, establishing polar literacy based on concepts that are relevant to various subjects, earth system-centered learning approach, setting the direction for follow-up studies and the need for science education that incorporates diverse values.

• The Journal of Information Systems
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• v.22 no.1
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• pp.165-180
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• 2013

Using long-term panel data of OKCashbag, this study analyzes whether learning effect influencing in effectiveness of coalition loyalty program exists. We found that there is learning effect in the behavior of loyalty program customers, and discovered that learning effect appears more greatly in using (redeeming) behavior than accumulating behavior. The authors also found a long-lasting structural changes in the pattern of point redemption after a major marketing activities associated with the act of using points. The results of this research can contribute to suggest direction to the future researches to examine differences of learning effect according to demographic (gender, age, region, ect.) and transactional (frequency or scale in point accumulation and redemption etc.) characteristics.

• Korean Journal of Child Studies
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• v.33 no.6
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• pp.71-84
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• 2012

The purpose of this study is to analyze the relationship between decision making abilities young children and their self-directed learning abilities. A survey was carried out using 160 young children in the J region. The collected data were analyzed by Pearson correlation and multiple regression techniques using the SPSS statistics program. The conclusions are as follows : First, decision making abilities in young children exhibited a positive correlation with their self-directed learning abilities. Second, decision making abilities in young children were an influential variable in terms of their self-directed learning abilities. As a result, decision making abilities in young children were an important variable in predicting their self-directed learning abilities.

• Journal of Korean Elementary Science Education
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• v.21 no.2
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• pp.241-252
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• 2002

Field learning have not well performed in elementary school for various reasons, in spite of the benefits of field study. Absence of suitable geological field courses for elementary science education is one of several reasons The purpose of this study is to develop learning materials for the field geology in Hampyeong region and apply them to the geological related units for elementary science education. The 5 observation sites for the field geology learning in study area include various rocks and geological structure such as granite, gneiss, conglomerate, sandstone, mudstone, plant fossil, fold, fault and weathering phenomenon changing rocks to soil. This study area is suitable place for the field geology learning of elementary science education in Kwangju and Chonnam province because of convenience access, fresh outcrops and distribution of various geological learning materials as rocks and structure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1652-1662
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• 1995

In this paper, a hybrid neural network is proposed to improve the learning ability of a neural network. The union of the characteristics of a Self-Organizing Neural Network model and of multi-layer perceptron model using the backpropagation learning method gives us the advantage of reduction of the learning error and the learning time. In learning process, the proposed hybrid neural network reduces the number of nodes in hidden layers to reduce the calculation time. And this proposed neural network uses the fuzzy feedback values, when it updates the responding region of each node in the hidden layer. To show the effectiveness of this proposed hybrid neural network, the boolean function(XOR, 3Bit Parity) and the solution of inverse kinematics are used. Finally, this proposed hybrid neural network is applied to the visual tracking control of a PUMA560 robot, and the result data is presented.

• Asian Journal of Innovation and Policy
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• v.7 no.1
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• pp.55-78
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• 2018

This paper investigates the linkage between the mode of transformation of entrepreneurial learning into outcomes and the subsequent impact of these learning outcomes in enhancing the survival of high-tech startups in India. The study uses data from 45 high-tech startups headquartered across different locations in India for the purpose of analysis. Survival Analysis of the data is conducted to determine which mode of learning transformation and what type of en trepreneurial decision making preference have a significant influence on the survival of Indian high-tech startups and to what extent do they impact their survival. The results indicate that entrepreneur's prior startup experience, explorative mode of learning transformation, causal decision making of the entrepreneur and availability of funding for the startup as the key factors that reduce the time to survival of Indian high-tech startups. They also provide key insights on how these factors impact the startup survival in this region.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.175-184
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• 2014

This paper examines how learning orientation and self-efficacy contributed to explaining innovation behaviors. In order to verify the relationships and mediating effect, data were collected from 368 individuals in employees working in small and medium-sized firms at Gyeongnam region to test theoretical model and its hypotheses. All data collected from the survey were analyzed using with SPSS 18.0. This study reports findings as follows: first, the relationship between the learning orientation and the employee's self-efficacy is positively related. Second, there was also a positive correlation between the employee's self-efficacy and the innovation behaviors. Third, the relationship between the learning orientation and the innovation behaviors is positively related. Finally, the employee's self-efficacy played as a partial mediator on the relationship between learning orientation and innovation behaviors. Based on these findings, the implications and the limitations of the study were presented including some directions for future studies.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.353-370
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• 2023

Corrosion detection and analysis is a very important topic in reducing costs and preventing disasters. Recently, image processing techniques have been widely applied to corrosion identification and analysis. In this work, we briefly introduces traditional image processing techniques and machine learning algorithms applied to detect or analyze corrosion in various fields. Recently, machine learning, especially CNN-based algorithms, have been widely applied to corrosion detection. Additionally, research on applying machine learning to region segmentation is very actively underway. The corrosion is reddish and brown in color and has a very irregular shape, so a combination of techniques that consider color and texture, various mathematical techniques, and machine learning algorithms are used to detect and analyze corrosion. We present examples of the application of traditional image processing techniques and machine learning to corrosion detection and analysis.