• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.105-112
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• 2023

In this paper, we propose a new method for displaying colored defects by measuring the relative density with the wide-area and local densities of X-ray. The relative density of one pixel represents a relative difference from the surrounding pixels, and we also suggest a colorization of X-ray images representing these pixels as normal and defective. The traditional method mainly inspects materials such as plastics and metals, which have large differences in transmittance to the object. Our proposed method can be used to detect defects such as sprouts or holes in images obtained by an inspection machine that detects X-rays. In the experiment, the products that could not be seen with the naked eye were colored with pests or sprouts in a specific color so that they could be used in the agricultural product selection system. Products that are uniformly filled with a single ingredient inside, such as potatoes, carrots, and apples, can be detected effectively. However, it does not work well with bumpy products, such as peppers and paprika. The advantage of this method is that, unlike machine learning, it doesn't require large amounts of data. The proposed method could be applied to a screening system using X-rays and used not only in agricultural product screening systems but also in manufacturing processes such as processed food and parts manufacturing, so that it can be actively used to select defective products.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.409-417
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• 2019

Recently, English education of educational institutions is gradually invigorated as the importance of English education for preschooler is increasing. Role-play, in particular, is known as an effective way to learn English for children because it promotes children's interest in language and naturally encounters English-speaking culture. Therefore, in this paper, we tried to find out how to effectively use UCC in role-playing for English education for preschoolers. First of all, questionnaires for pre and post-test were conducted for preschoolers. The results are analyzed by SPSS to find out children's understanding of UCC, interest in English, interest in role-playing, and interest in acting. As a result of the analysis, most children knew UCC well and showed strong interest in watching and producing UCC. Also, the more interested in English and role-playing, the more they wanted to show more advanced English and acting through the feedback of the contents they produced. Therefore, even in preschool children's English education, the development of language and acting can be shown by producing UCC through role-playing under the teacher's control and receiving feedback on it. The results of this study are expected to be effectively used when planning English education through role-playing in daycare centers or kindergartens.

• Journal of Ethics
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• no.97
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• pp.279-306
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• 2014

This study presents the leadership model that is to build of ethical and cultural leadership. This model is to operat the functions of a systemof leadership that based on the universal principles of life, that is performed bybalance and harmonized judgment of the ideal ethical oughtfulness and cultural values, and practise ethically through relationship, process, and skill of leadership. And this model turn out to lead a real impact and then overcome conflict, problem solving, motivation. To check the validity of leadership, this study analysis the case study of leadership of King Sejong. His leadership is based at heaven that on the basis of the universal principles of life. The ideal ethical oughtfulness is to cares for people and the value of the cultural is to cherish the people's will. His leadership is to be balance and harmonized judgment of the ideal ethical oughtfulness and the cultural values by practice of virtues through relationship, process, and skill of leadership. Leadership relationship is a equal role relationship that are the children of the sky, thus to be coexistence and harmonyin close collaboration. Leadership process is a process of transvaluation to ensure the validity of the values by rational discussion and persuasion. Leadership skills led to active obedience through leading by example and love of learning. King Sejong' leadership is the leadership that ethical and cultural leadership become well-implemented.

• The Korean Journal of Woman Psychology
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• v.16 no.3
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• pp.401-422
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• 2011

The present study investigated the mediating effects of parents' social networks on the relationship between parents' socioeconomic status and parent involvement. Parent involvement in the current study was composed of home-based and school-based involvement. Home-based involvement includes providing learning environment at home, guiding child's study habits, and providing educational and financial support. School-based involvement includes supporting child's school-related activities, participating at parent meetings and volunteering, and home-school communication. The subjects were 132 single mothers and 164 mothers from two-parent families, whose children are fifth and sixth graders in Seoul and Incheon. Structural Equational Modeling was used for the analysis by adopting SPSS 18.0 and AMOS 18.0. The results showed that single mothers and mothers from two-parent families differ in their structural models. For mothers from two-parent families, socioeconomic status was directly related to home-based and school-based involvement. In contrast, single mother's socioeconomic status only influenced home-based and school-based involvement indirectly through the functional aspects of mother's social networks. The results suggest that parent counseling and parent education programs might be more effective if they encouraged single mothers to exchange resources through their social networks in order to promote parent involvement in elementary schools.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.57-58
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• 2023

The working time for loading and transporting containers in the container terminal is one of the factors directly related to port productivity, and minimizing working time for these operations can maximize port productivity. Among working time for container operations, the working time of yard tractors(Y/T) responsible for the transportation of containers between berth and yard is a significant portion. However, it is difficult to estimate the working time of yard tractors quantitatively, although it is possible to estimate it based on the practical experience of terminal operators. Recently, a technology based on IoT(Internet of Things), one of the core technologies of the 4th industrial revolution, is being studied to monitoring and tracking logistics resources within the port in real-time and calculate working time, but it is challenging to commercialize this technology at the actual port site. Therefore, this study aims to develop yard tractor working time prediction model to enhance the operational efficiency of the container terminal. To develop the prediction model, we analyze actual port operation data to identify factors that affect the yard tractor's works and predict its working time accordingly.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.569-590
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• 2023

The purpose of this case study is to compare and analyze the covariational reasoning levels of two middle school students revealed in the process of solving and generalizing algebra word problems. A class was conducted with two middle school students who had not learned quadratic equations in school mathematics. During the retrospective analysis after the class was over, a noticeable difference between the two students was revealed in solving algebra word problems, including situations where speed changes. Accordingly, this study compared and analyzed the level of covariational reasoning revealed in the process of solving or generalizing algebra word problems including situations where speed is constant or changing, based on the theoretical framework proposed by Thompson & Carlson(2017). As a result, this study confirmed that students' covariational reasoning levels may be different even if the problem-solving methods and results of algebra word problems are similar, and the similarity of problem-solving revealed in the process of solving and generalizing algebra word problems was analyzed from a covariation perspective. This study suggests that in the teaching and learning algebra word problems, rather than focusing on finding solutions by quickly converting problem situations into equations, activities of finding changing quantities and representing the relationships between them in various ways.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.