• Education of Primary School Mathematics
• /
• v.25 no.4
• /
• pp.313-328
• /
• 2022

The purpose of this study is to understand the characteristics of the questions presented in shapes area and Measurement area of elementary mathematics textbooks. For this purpose, the types of questions presented in shapes area and measurement area of elementary mathematics textbooks and their working functions were comparatively analyzed by area and by grade cluster. As a result of the analysis, the number of questions per lesson increased sharply in the 3rd and 4th grade cluster compared to the 1st and 2nd grade cluster in both shapes area and measurement area. In these two areas, the most common reasoning questions are presented. It is presented relatively more in measurement area than in shapes area. There was a clear difference between the types of questions presented in shapes area and measurement area. In common with the two areas, questions mainly were acted as a function to help students learn to reason mathematically, a function to help students to determine whether something is mathematically correct, and a function to help students learn to conjecture, invent, and solve problem. The characteristics of the questions identified in this study can provide teaching/learning implications for the design and application of the questions suitable for the guidance of shapes area and measurement area, and can be used as a reference material when writing mathematics textbooks.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.953-966
• /
• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Journal of Intelligence and Information Systems
• /
• v.28 no.3
• /
• pp.161-183
• /
• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Journal of the Korean Society of Radiology
• /
• v.16 no.5
• /
• pp.661-672
• /
• 2022

After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

• Journal of Christian Education in Korea
• /
• v.71
• /
• pp.155-179
• /
• 2022

This study aims to apply Hannah Arendt's concept of 'collective responsibility' to the Christian education on environmental issues around the world, focusing on climate change. This study prepares the concept of 'collective responsibility' and the concept of 'collective guilt' and emphasizes the fact that the current climate change problem should be seen as a political task rather than a task of personal ethics. According to Arendt's theory, Christian education activities applying 'collective responsibility' for climate change can become action. This study has four suggestions for Christian learning to understand and recognize climate change. First, presenting and justifying the anxiety and anger toward climate change in the classroom. Second, transcending self-interest (egocentrism) through "Common Sense (enlarged mentality)" in Kantian terms. Third, building education communities through 'citizen participatory education,' running communication, and conversation. Fourth, encouraging experience and practice in every education community with "faith expressing itself through love (Gal 5:6)." Then, to be sure, this refers to not only love of neighbor in Christianity but also political friendship (philia politikē). The academic significance of this study is that it is the first interdisciplinary research paper in Korea which dealt with Arendt's political theory in relation to Christian education. Although it claims to be a theoretical work that applies Arendt's political theory from a systematic theological perspective to Christian education, the author is proud that it is accompanied by practical elements that can be actualized in the education field.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.913-924
• /
• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• Journal of Practical Engineering Education
• /
• v.13 no.3
• /
• pp.515-532
• /
• 2021

The purpose of this study was to analysis of PBL for Korean Apprenticeship Program in Mechanical Engineering. The details of the study were as follows: First, the perception related to the PBL of Korean apprenticeship program was investigated. Second, the utilization and the operational difficulties of PBL for Korean Apprenticeship Program were investigated. Third, the supporting system for PBL was suggested. Research methods were literature research, questionnaire survey and FGI. The survey was conducted online from July 15 to August 14, 2021. A total of 515 respondents responded. A total of 108 in 515 respondents were in Mechanical Engineering. FGI conducted a total of 25 people who actual use PBL in the field of Korean Apprenticeship Program. Conclusions and suggestions based upon the result of this study are as follows. First, It is necessary to improve the utilization of PBL for Korean Apprenticeship Program in Industry. Second, PBL is necessary to apply optionally according to the job and field situation. Third, it is necessary to support system of evaluation for PBL in Korean Apprenticeship Program. Finally, related operation model and guideline need to be prepared for best practice.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.5
• /
• pp.3-14
• /
• 2022

Construction projects have high potentials of claims among a variety of stakeholders. Claims on their own are not disputes but they have high potentials leading to disputes if agreements are not made between parties due to conflicting opinions. In the event of the construction disputes between clients and contractors, it could give negative impacts to both parties and, to minimize or pro-actively manage construction disputes, the role of clients is more significant. The objective of the study is to analyze a level of associations between the types of disputes and causes of construction projects based on the association rule analysis, and to identify and discuss key characteristics and implications from client's perspectives. The study analyzes associations between the types of disputes and causes, and also identifies those with a high level of associations. It also presents the outcomes of more systematic analysis compared to descriptive statistics just based on frequencies. Through the analysis of the data cases, the study proposes the directions to resolve the causes of disputes from client's perspectives. It can assist to improve understandings of the relationships between the types of disputes and causes and to pro-actively manage the disputes of construction projects.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_2
• /
• pp.793-810
• /
• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• Journal of Appropriate Technology
• /
• v.6 no.2
• /
• pp.200-207
• /
• 2020

The purpose of the establishment of Fab Lab is to promote the sustainable development of local communities around the world. To this end, The Fab foundation are preparing a resource-circulating society that maintains a city's self-sufficiency rate of 50% or more by 2054. In developed countries, Fab Lab is not only a manufacturing space for startup support, but an open innovation space for learning and creation. In addition, in emerging countries, Fab Lab is playing a role as a digital production center to create and share appropriate new technologies by reflecting the needs of local communities. India has 70 Fab Labs, the largest emerging country, ahead of Russia's 48. India's Fab Lab is conducting a collaboration project through regular meetings held every six months. The subject of this study, Fab Lab Vigyan Ashram, is defined as a place to transfer the concept of digital lab to alternative schools in rural India. In this study, we looked at a case in which an alternative school for an agricultural community called Vigyan Ashram, the modern version of the Gurukula system, successfully combined with the digital fabrication called Fab Lab to become a new citizen-led making community of the 4th Industrial Revolution. Based on this, we explored the development model of the Indian Fab Lab that fits the local situation.