• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.182-195
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• 2023

The purpose of this study was to analyze reports from research middle schools based on the criteria for process-focused assessment to find out how the characteristics of process-focused assessment were being implemented in middle school science classes. The analysis criteria for the characteristics of process-focused assessment (integration of lessons and assessments, evaluation elements and methods, content and timing of feedback, and learner growth management) were extracted. Using the analysis framework, the result reports of seven research middle schools for process-focused assessment were analyzed. In terms of integration of lessons and assessments, when the process-focused assessment was operated, the class and evaluation plan were well implemented based on the curriculum achievement standards, but the process-focused assessment was recognized as a performance evaluation. In terms of evaluation elements and methods, the evaluation element for knowledge was the main component, and competency was presented in the planning stage, but competency was not dealt with in class execution. The evaluation method was biased toward teacher-centered observation evaluation and written test, and the setting of scoring criteria for each evaluation element was insufficient. In terms of the content and timing of feedback, feedback was mainly provided based on achievement confirmation, but no case was found in which scaffolding was provided at an appropriate time for insufficient parts in the learning process. In terms of the learner's growth management, the competencies cultivated through science classes were included in the detailed subject specialties of the school record. However, little was shown in the report on how to systematically manage the process of developing learners' competencies and reflect the evaluation results to teachers' class improvement.

• Journal of Korean Elementary Science Education
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• v.42 no.3
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• pp.455-466
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• 2023

This study explored the relationship between science academic passion, positive experience about science and scientific creativity in elementary science-gifted students. To do this, 108 science-gifted students from grades 3 to 6 were selected. After conducting the tests on their science academic passion, positive experience about science and scientific creativity, descriptive statistics, correlation analysis, and multiple regression analysis were conducted. The results revealed that the students exhibited relatively high levels of science academic passion and positive experience about science, but their scientific creativity was not relatively high. While there was no statistically significant correlation between the overall science academic passion and scientific creativity, there was a significant negative correlation with scientific creativity in the aspect of 'obsessive passion' of the five subcategories ('importance', 'like', 'time/energy investment', 'harmonious passion', and 'obsessive passion'). Furthermore, the five subcategories, particularly 'like', 'harmonious passion', and 'obsessive passion' were statistically significant predictors of scientific creativity. However, the five subcategories of positive experience about science ('science academic emotion', 'science-related self-concept', 'science learning motivation', 'science-related career aspiration', and 'science-related attitude') did not exhibit statistically significant correlations with scientific creativity and did not had a significant influence on it. Additionally, neither the overall science academic passion nor the overall positive experience about science had a statistically significant effect on scientific creativity. Educational implications of these results were discussed.

• Journal of the Korean Geotechnical Society
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• v.39 no.9
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• pp.13-24
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• 2023

To investigate the stability of temporary retaining walls during excavation, it is essential to develop reverse analysis technologies capable of precisely evaluating the properties of the ground and a learning model that can assess stability by analyzing real-time data. In this study, we targeted excavation sites where the C.I.P method was applied. We developed a Deep Neural Network (DNN) model capable of evaluating the stability of the retaining wall, and estimated the physical properties of the ground being excavated using a Differential Evolution Algorithm. We performed reverse analysis on a model composed of a two-layer ground for the applicability analysis of the Differential Evolution Algorithm. The results from this analysis allowed us to predict the properties of the ground, such as the elastic modulus, cohesion, and internal friction angle, with an accuracy of 97%. We analyzed 30,000 cases to construct the training data for the DNN model. We proposed stability evaluation grades for each assessment factor, including anchor axial force, uneven subsidence, wall displacement, and structural stability of the wall, and trained the data based on these factors. The application analysis of the trained DNN model showed that the model could predict the stability of the retaining wall with an average accuracy of over 94%, considering factors such as the axial force of the anchor, uneven subsidence, displacement of the wall, and structural stability of the wall.

• Korean Journal of Comparative Education
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• v.20 no.2
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• pp.95-128
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• 2010

This article presents a one and half-year process of Lesson Study conducted at a K-8 school in an urban district in the eastern U.S. Lesson Study, a Japanese form of professional development that centers on collaborative study of live classroom lessons, has spread rapidly in the U.S. since 1999 and has been argued as a promising alternative model for teacher-led school reform through professional development. The Lesson Study group described here was composed of five teachers, one administrator, and one instructional improvement coordinator belonging to the participant school and two instructional super-intendants from the school district. Data was collected from October 2007 to February 2009 and a qualitative case study method was employed for this study. Drawing a case of Lesson Study, this article intended to show how Lesson Study group members participated in planning, teaching, observing, discussing, and improving lessons collaboratively for student learning by enhancing teacher professional competence so that find directions for future implementation in Korea. This article investigates (1) process of Lesson Study, (2) issues Lesson Study group members mainly dealt with, and (3) changes have taken place in Lesson Study as it is conducted over time. (4) Finally, this article concludes with challenges to adopting Lesson Study successfully in Korea.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.1-16
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• 2023

This study investigated the level of academic passion for pre-service elementary teachers' science pedagogical content knowledge (PCK) and the factors that influence the passion. To this end, 182 first to fourth grade students in advanced non-science majors who were taking science-related courses in the second semester were selected, and two tests were then administered to evaluate their academic passions for science subject matter knowledge and science pedagogical knowledge. Individual in-depth interviews were also conducted with some of the participants. It was found that the factors such as "importance" and "harmonious passion" for learning science subject matter knowledge and science pedagogical knowledge were found at a high level. On the other hand, the factors such as "like" and "investment of time and energy" were slightly higher than normal, and the factor such as "obsessive passion" was slightly lower than normal. The differences in academic passion for science subject matter knowledge and science pedagogical knowledge were greater according to the high school track than the grade. The pre-service elementary teachers selected more often the factors such as "individual interests", "high school track", "contents of science-related courses at the university of education", "characteristics of professor in charge of science-related courses at the university of education", and "experience in teaching practicum" as the factors that influenced their academic passion for science subject matter knowledge and science pedagogical knowledge. However, there was a slight difference in the selection ratio depending on the high school track.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.104-108
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• 2023

Because of recent expansion of the electric car market. it is highly growing that should be supplemented its performance and safely issue. The EMI problem due to the interlocking of electrical components that causes various safety problems such as fire in electric vehicles is emerging every time. We strive to achieve optimal charging efficiency by combining various technologies and reduce radioactive noise among the EMI noise of a weirless charging control module, one of the important parts of an electric vehicle was designed and tested. In order to analyze the EMI problems occurring in the wireless charging control module, the optimized wireless charging control module by applying the optimization design technology by learning the accumulated test data for critical factors by utilizing the Python-based script function in the Ansys simulation tool. It showed an EMI noise improvement effect of 25 dBu V/m compared to the charge control module. These results not only contribute to the development of a more stable and reliable weirless charging function in electric vehicles, but also increase the usability and efficiency of electric vehicles. This allows electric vehicles to be more usable and efficient, making them an environmentally friendly alternative.

• Research in Community and Public Health Nursing
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• v.33 no.1
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• pp.13-31
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• 2022

Purpose: This study conducted a job analysis of visiting nurses in the process of change. Methods: Participants were the visiting nurses working for the Seoul Metropolitan city. On the basis of the Public Health Intervention Wheel model, two times of the focus group interview (FGI) with seven visiting nurses and one time of the Developing a Curriculum (DACUM) with 34 visiting nurses were performed. A questionnaire survey of 380 visiting nurses was conducted to examine the frequency, importance and difficulty levels of the tasks created by using the FGI and DACUM. Results: Visiting nurses' job was derived as the theme of present versus transitional roles. The present role was categorized as 'providing individual- and group-focused services' and 'conducting organization management', while the transitional role was categorized as 'providing district-focused services' and 'responding to new health issues'. The job generated 13 duties, 28 tasks, and 73task elements. The tasks showed the levels of frequency (3.65 scores), importance (4.27 scores), and difficulty (3.81 scores). All the tasks were determined as important, exceeding the average 4.00 scores. The group- and district-focused services of the tasks were recognized as more difficult but less frequent tasks. Conclusion: The visiting nurses exert both present and transitional roles. The transitional roles identified in the present study should be recognized as an extended role of visiting nurses in accordance with the current changing healthcare needs in South Korea. Finally, the educational curriculum for visiting nurses that reflects the transitional roles from the present study is needed.