• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.1-11
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• 2023

The purpose of this study is to develop a discussion-centered teaching and learning model for nurturing creative and convergence talents. Regarding the research method, a draft model on discussion-centered teaching and learning was devised, and the model was completed through expert validation. The final draft was revised and supplemented by verifying how valid the model was when applied in class by using the derived final draft. Compared with the draft on discussion-centered teaching and learning model, the final model focused on text-reading emphasis, methods of questioning, and question generation strategies, excluding jigsaw discussions. The discussion-centered teaching and learning model developed in this study is expected to help instructors foster creative and convergence talents. Three suggestions have been provided to effectively apply this model to the field. First, an attitude of listening and respect is required during a discussion. Second, a plan should be considered on how to induce active participation of learners participating in the discussion. Third, the importance of managing discussion time was emphasized.

• Computers and Concrete
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• v.33 no.2
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• pp.175-193
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• 2024

Researchers have embarked on an active investigation into the feasibility of adopting alternative materials as a solution to the mounting environmental and economic challenges associated with traditional concrete-based construction materials, such as reinforced concrete. The examination of concrete's mechanical properties using laboratory methods is a complex, time-consuming, and costly endeavor. Consequently, the need for models that can overcome these drawbacks is urgent. Fortunately, the ever-increasing availability of data has paved the way for the utilization of machine learning methods, which can provide powerful, efficient, and cost-effective models. This study aims to explore the potential of twelve machine learning algorithms in predicting the tensile strength of geopolymer concrete (GPC) under various curing conditions. To fulfill this objective, 221 datasets, comprising tensile strength test results of GPC with diverse mix ratios and curing conditions, were employed. Additionally, a number of unseen datasets were used to assess the overall performance of the machine learning models. Through a comprehensive analysis of statistical indices and a comparison of the models' behavior with laboratory tests, it was determined that nearly all the models exhibited satisfactory potential in estimating the tensile strength of GPC. Nevertheless, the artificial neural networks and support vector regression models demonstrated the highest robustness. Both the laboratory tests and machine learning outcomes revealed that GPC composed of 30% fly ash and 70% ground granulated blast slag, mixed with 14 mol of NaOH, and cured in an oven at 300°F for 28 days exhibited superior tensile strength.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.459-463
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• 2024

Frequent closures among self-employed individuals lead to national economic losses. Given the high closure rates in the restaurant industry, predicting changes in this sector is crucial for business survival. While research on factors affecting restaurant industry survival is active, studies predicting commercial district changes are lacking. Thus, this study focuses on forecasting such alterations, designing a deep learning model for Seoul's administrative district commercial district changes. It collects 2023 and 2022 second-quarter variables related to these changes, converting yearly fluctuations into percentages for augmentation. The proposed deep learning model aims to predict commercial district changes. Future policies, considering this study, could support restaurant industry growth and economic development.

• Journal of the Korean School Mathematics Society
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• v.13 no.3
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• pp.459-483
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• 2010

This study aims to develop materials related to math education for the aged and to identify the effects of application as part of active measures to the aging society with its growing elderly population which is one of the greatest changes in our society. In this purpose, the necessity and objectives for development of materials of 'Silver Math' as education for the aged are explained. Developing and disseminating materials with a role as a program for intelligent needs and physical and spiritual health of the aged presents standards for development of more systemic and meaningful educational materials at this point of time when the importance of education of the aged increases to help the old enjoy qualitatively successful lives in later years in the perspective of lifelong education. Also it aims to present standards of contents and requirements in learning that are adequate and meaningful to old learners at the actual learning sites where education takes place only in terms of making good use of spare time while at the same time suggesting plans of teaching and learning as well as conditions for learning environment. Next, the effectiveness of 'Silver Math' are explored by applying developed materials to the aged. materials of 'Silver Math' for the aged with contents that are appropriate to the definitive and cognitive level of the aged are presented. The developed materials for mathematical activities are divided into 'computation of basic numbers' for those wishing to learn calculation and concepts of numbers, 'active math' that corresponds to definitive factors of old learners, facilitates leisure time through mathematical activities, and Improves communication abilities through cooperative learning among learners, and 'math with thinking power' to solve simple calculation problems by applying to various actual situations.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.811-822
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• 2005

Automated text categorization is to classify free text documents into predefined categories automatically and whose main goals is to reduce considerable manual process required to the task. The researches to improving the text categorization performance(efficiency) in recent years, focused on enhancing existing classification models and algorithms itself, but, whose range had been limited by feature based statistical methodology. In this paper, we propose RTPost system of different style from i.ny traditional method, which takes fault tolerant system approach and data mining strategy. The 2 important parts of RTPost system are reinforcement training and post-processing part. First, the main point of training method deals with the problem of defining category to be classified before selecting training sample documents. And post-processing method deals with the problem of assigning category, not performance of classification algorithms. In experiments, we applied our system to documents getting low classification accuracy which were laid on a decision boundary nearby. Through the experiments, we shows that our system has high accuracy and stability in actual conditions. It wholly did not depend on some variables which are important influence to classification power such as number of training documents, selection problem and performance of classification algorithms. In addition, we can expect self learning effect which decrease the training cost and increase the training power with employing active learning advantage.

• Therapeutic Science for Rehabilitation
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• v.13 no.2
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• pp.69-84
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• 2024

Objective : This study aimed to categorize the lifestyles of older adults into two types - healthy and unhealthy, and use machine learning to identify the personal values that influence these lifestyles. Methods : This cross-sectional study targeting middle-aged and older adults (55 years and above) living in local communities in South Korea. Data were collected from 300 participants through online surveys. Lifestyle types were dichotomized by the Yonsei Lifestyle Profile (YLP)-Active, Balanced, Connected, and Diverse (ABCD) responses using latent profile analysis. Personal value information was collected using YLP-Values (YLP-V) and analyzed using machine learning to identify the relative importance of personal values on lifestyle types. Results : The lifestyle of older adults was categorized into healthy (48.87%) and unhealthy (51.13%). These two types showed the most significant difference in social relationship characteristics. Among the machine learning models used in this study, the support vector machine showed the highest classification performance, achieving 96% accuracy and 95% area under the receiver operating characteristic (ROC) curve. The model indicated that individuals who prioritized a healthy diet, sought health information, and engaged in hobbies or cultural activities were more likely to have a healthy lifestyle. Conclusion : This study suggests the need to encourage the expansion of social networks among older adults. Furthermore, it highlights the necessity to comprehensively intervene in individuals' perceptions and values that primarily influence lifestyle adherence.

• Communications of Mathematical Education
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• v.33 no.3
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• pp.231-254
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• 2019

As the teacher-centered education is transformed into learning-centered education, the active knowledge construction of learner becomes important. Along with this change, project-based learning is receiving attention. However, there are many problems to apply the results of research to pre-service teachers because most of the previous studies have focused on elementary middle high school students. Therefore, this study examined the changes in perceptions of pre-service mathematics teachers while project-based learning progressed for one year. Pre-service mathematics teachers had less experience with project-based learning than group discussions, group activities. Also their perceptions was classified as five factors: 'Instructional effects', 'Application and participant of project-based learning', 'Achievement', 'Diffusion of project-based learning', 'Student motivation'. Pre-service mathematics teachers responded positive changes in perception that project-based learning could be motivated to students but they responded negative changes in perception that project-based learning could be distributed to school. They responded positive changes in perception that teachers can show their achievements by project-based learning but they responded negative change in perception that teachers would be fun to apply project-based learning. Also, they responded positive changes in perception that teachers and students were easy to apply or utilize project-based learning.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.163-170
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• 2016

The purpose of this study is to determine the effect of R&D learning organization activities of domestic small and medium-sized businesses on economic/technological results. This study, through investigation on preceding studies of domestic and foreign learning organization researchers, examined the definition, characteristics, and deteriorating factors of learning organization, and learned dependent variables, which are the definition of organizational performance, and relationship between learning organization and organizational performance. Then it performed a survey targeting small- and medium-sized businesses in Gumi and grasped the relationship between R&D capability (study planning, vision goal adequacy, project management, commercialization of technologies) and learning organization capability (creation of constant learning opportunities, knowledge sharing and utilizing system, strategic learning leadership) by classifying them to seven independent variables, using regression analysis. Because this study grasped the effect of R&D learning organization activities on organizational performance, it is expected to promote forming R&D learning organization for active R&D activities and contribute to enhancing small and medium-sized businesses' recognition on the need of R&D activities.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.505-512
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• 2007

This paper presents the quantitative evaluation of the fearfulness of the human driver in the case of the short range (time) on the highway. The driving situation is realized by using the driving simulator based on CAVE, which provides three-dimensional stereoscopic immersive visual information. The examinees' responses and personal information are categorized reasonably by applying the competitive learning algorithm. The characteristics of each group are analyzed. The following two situations are also compared: (1) the active approaching situation where the examinee drives the vehicle near the preceding vehicle, and (2) the passive approaching situation where the preceding vehicle nears the examinee's vehicle by gradually decelerating. The range time that the examinee feels fear in the active approaching case tends to be shorter than that in the passive approaching case.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1261-1267
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• 2015

The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.