• Journal of Distribution Research
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• v.17 no.3
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• pp.93-113
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• 2012

Early conflict research in channel and organization area have focused on the definition of conflict construct, its cause, consequence and identified conflict resolution management. Recent studies about conflict, however, have explored new assumption of complexity, a multidimensional conflict construct, contextual conflict management strategies, positive and negative conflict/consequence, and the conflict resolution strategy. Although many literatures exists on channel conflict resolution, little research has been done about relationship learning and performance from conflict resolution perspective. This study explores how channel members can achieve a relationship learning, as a conflict resolution mechanism, which enhance co-created value in marketing channel relationship. Therefore we propose that conflict resolution strategies(collaborating behavior and avoiding behavior) influence channel performance(effectiveness and efficiency) through relationship learning processes(learning via information exchange, joint interpretation and coordination, relationship-specific knowledge memory), in view of buyer-seller relationship. The research model is shown at

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.92-99
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• 2019

This study empirically analyzed the effects of elderly people participating in lifelong learning on their psychological well-being. For this purpose, 160 elderly people who participated in lifelong education programs in hospitals C and D located in Cheonan city were selected as the subjects. A survey was conducted for 10 days, from May 8, 2019 to May 17, 2019. First, does the goal-oriented factor, which is part of the lifelong learning motivation of the elderly, have a positive effect on their psychological well-being? Second, does the activity-oriented factor of the elderly have a positive effect on their psychological well-being? Third, does the learning-oriented factor of elderly people's motivation for participating in lifelong learning have a positive effect on their psychological well-being? To answer these research questions, variables such as gender, age, marital status, and education level were controlled through correlation analysis, and simple regression analysis was also performed. The results of the direct effect analysis showed that goal-orientation (${\beta}=.244$; p<.001) and activity-orientation (${\beta}=.321$, p<.001) have statistically significant positive effects on psychological well-being. However, a learning-orientation (${\beta}=.284$, p>.001) was found to have no statistically significant effect on psychological well-being. Based on these findings, lifelong learning programs for the elderly should be more goal-oriented and activity-oriented than learning-oriented to promote the psychological well-being of the elderly.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.551-557
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• 2024

Early childhood cultural and artistic education is a process of expressing oneself and understanding society, which has a great impact on the lives of young children. It utilizes the principle of individualization, which means that individual diversity should be considered because each toddler has different developmental characteristics; the principle of play-centeredness, which means that toddlers form active attitudes toward experiential activities through enjoyment through play; the principle of integration, which is the foundation for holistic development; and the principle of direct experience, which means that toddlers have the experience of touching and manipulating materials. In the introduction, children are encouraged to explore and think about materials, read and share books together, and express their thoughts creatively through artistic expressions such as art, music, physical expression, drama, movies, and photography in the first and second phases. In the final stage, a teaching and learning plan was developed that consisted of a circle time for the children to share their opinions with each other in the process of appreciating the results created by the children and presenting their thoughts. As the educational effectiveness of early childhood cultural arts education is best developed in the early childhood period, when learning is emphasized by children exploring according to their interests, this study presented a learning guidance plan that reflects various educational methods and genre convergence education that can be applied to early childhood cultural arts education.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.335-349
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• 2004

Recently, there is change the environment of education due to development of Science Technology Specially, As education information on web increased by internet, using education web data by mean of medium that aids learning by computer. Also It studied method that used the Computer as learning medium through the CAI(Computer Assisted Instruction), ICAI(Intelligent CAI), and ITS(Intelligent Tutoring System). But legacy system are not support efficient method that learns to vary learner suitable learning method by individual level. Specially It is not suitable the education course to direct current course of education, and not consider different of student capability, aptitude, need, interesting, not maximized the individual growable power and effect of education. To solve the this problem, our paper suggest the web-based self-directed MITS(Multimedia ITS) that supply the needed the information on web, make the environment that can self-directed learning. To maximized effect of individual learning, our paper structured coursed, characterized, related learning contents in region of numeral at mathematics of primary school. And then integrated contents and class, design and implement the web-based MITS that consist of 4 module to escape from limitation of learner grade, learning time, learning place.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.93-103
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• 2021

Despite the efforts of financial authorities in conducting the direct management and supervision of collection agents and bond-collecting guideline, the illegal and unfair collection of debts still exist. To effectively prevent such illegal and unfair debt collection activities, we need a method for strengthening the monitoring of illegal collection activities even with little manpower using technologies such as unstructured data machine learning. In this study, we propose a classification model for illegal debt collection that combine machine learning such as Support Vector Machine (SVM) with a rule-based technique that obtains the collection transcript of loan companies and converts them into text data to identify illegal activities. Moreover, the study also compares how accurate identification was made in accordance with the machine learning algorithm. The study shows that a case of using the combination of the rule-based illegal rules and machine learning for classification has higher accuracy than the classification model of the previous study that applied only machine learning. This study is the first attempt to classify illegalities by combining rule-based illegal detection rules with machine learning. If further research will be conducted to improve the model's completeness, it will greatly contribute in preventing consumer damage from illegal debt collection activities.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.125-133
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• 2022

This study attempted to find out whether learning time has a mediating effect according to the gender, region, and grade of middle school students in the relationship between academic engagement and self-esteem. To this end, a survey of 1,045 middle school students in Gyeongsangnam-do was conducted on academic engagement, learning time, and self-esteem. Difference verification was conducted to determine the difference in academic engagement, learning time, and self-esteem according to the general characteristics of the study subjects, correlation analysis was conducted to determine the correlation between major variables, and regression analysis was conducted to verify the mediating effect of learning time. As a result of the analysis, first, there was no difference in the academic engagement of middle school students by group. In the learning time, middle school students in the city area were significantly higher than those in the township area, male students had higher self-esteem than female students, and students in the city area had significantly higher self-esteem as the grade went up. Second, as a result of correlation analysis, learning time, academic engagement, and self-esteem showed a positive correlation. Third, in the entire group not divided by group, both the direct path through which academic engagement reaches self-esteem and the partial mediating model from learning time to self-esteem showed significant effects. In the analysis by gender, only female students excluding male students showed a partial mediating effect, and the analysis results by region showed a partial mediating effect only on students in the city. The analysis results by grade showed a partial mediating effect only for second-year middle school students. In order to improve the self-esteem of middle school students, education and counseling should be conducted in consideration of not only individual differences by gender and grade, but also the region in which they live.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.137-142
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• 2024

Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.

• Applied Chemistry for Engineering
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• v.35 no.2
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• pp.85-95
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• 2024

Direct air capture (DAC) technology plays a crucial role in mitigating climate change. Reports from the International Energy Agency and climate change emphasize its significance, aiming to limit global warming to 1.5 ℃ despite continuous carbon emissions. Despite initial costs, DAC technology demonstrates potential for cost reductions through research and development, operational learning, and economies of scale. Recent advancements in high-permeance polymer membranes indicate the potential of membrane-based DAC technology. However, effective separation of CO₂ from ambient air requires membranes with high selectivity and permeability to CO₂. Current research is focusing on membrane optimization to enhance CO₂ capture efficiency. This study underscores the importance of direct air capture, evolving cost trends, and the pivotal role of membrane development in climate change mitigation efforts. Additionally, this research delved into the theoretical background, conditions, composition, advantages, and disadvantages of permeance and selectivity in membrane-based DAC.

• Journal of the Korean Society of Fashion and Beauty
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• v.1 no.1 s.1
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• pp.65-78
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• 2003

This research is to provide practical help in learning hair and makeup illustration skills by presenting techniques for hair and makeup drawing; to serve efficient illustration education; and to enhance the status of beauty and contribute to artistic development. Hair style and makeup techniques include graphical one, pattern-centered one, one using pattern paper, simplifying one and mood one expressing image. Of them, this research made the illustrations to use cosmetics, color pencils and pastel based on the graphical technique. for each design of the illustrations, ethnic, sexy, natural, romantic and gorgeous images, which were considered to be appropriate to the graphical technique, were chosen by the researcher out of hair and makeup styles that appeared in the fashion magazines including Vogue, Gap, Mode et Mode from 2000 through 2001. In particular, they were chosen with focusing on basic styles. The summaries below were found with the experience of making illustrations. Various techniques and skills are required to express the ideas of hair and makeup styles. Of them, the graphical technique is very useful as the primary step to learn various techniques and improve drawing skills. First, the graphical technique may enable not only expressing what is desired to draw as is, but also accurately representing hair and makeup designs so as to convey objective expression. In this regard, it is a proper way to achieve its inherent purpose as conveyance of messages. Second, more accurate styling of hair and makeup is available through graphical expression, which helps understand related practical techniques. In addition, makeup illustration, which is expressed through direct makeup products and instruments, may serve skill improvement since such direct use provides the feeling of real makeup. Third, the graphical technique as a basic drawing skill may unrestrictedly show the artist's expression ability. Fourth, although artistic merits implying individuality and creativity should be shared through illustrations that express the artist's ideas or emotions, the graphical technique is the easiest method to beginners who just started learning of illustration, in that it enables expression without highly advanced skills.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.4
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• pp.264-274
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• 2003

This paper presents a direct generalized minimum-variance self tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior, noises and time delays. The self-tuning controller with a PID structure is a combination of the simple structure of a PID controller and the characteristics of a self-tuning controller that can adapt to changes in the environment. The self-tuning control effect is achieved through the RLS (recursive least square) algorithm at the parameter estimation stage as well as through the Robbins-Monro algorithm at the stage of optimizing the design parameter of the controller. The neural network control effect which compensates for nonlinear factor is obtained from the learning algorithm which the learning error between the filtered reference and the auxiliary output of plant becomes zero. Computer simulation has shown that the proposed method works effectively on the nonlinear nonminimum phase system with time delays and changed system parameter.