• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.15-17
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• 2022

In the aftermath of the avian influenza that occurred from the second half of 2020 to the beginning of 2021, 17.8 million laying hens were slaughtered. Although the government invested more than 100 billion won for egg imports as a measure to stabilize prices, the effort was not that easy. The sharp volatility of egg prices negatively affected both consumers and poultry farmers, so measures were needed to stabilize egg prices. To this end, the egg prices were successfully predicted in this study by using the analysis algorithm of a machine learning regression. For price prediction, a total of 8 independent variables, including monthly broiler chicken production statistics for 2012-2021 of the Korean Poultry Association and the slaughter performance of the national statistics portal (kosis), have been selected to be used. The Root Mean Square Error (RMSE), which indicates the difference between the predicted price and the actual price, is at the level of 103 (won), which can be interpreted as explaining the egg prices relatively well predicted. Accurate prediction of egg prices lead to flexible adjustment of egg production weeks for laying hens, which can help decision-making about stocking of laying hens. This result is expected to help secure egg price stability.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.66-73
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• 2023

The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.593-600
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• 2022

Various sensors such as lidar, radar, and camera are fused and used in autonomous vehicles. Rider and radar sensors are difficult to popularize because they are expensive equipment. In order to popularize autonomous vehicles, research that can replace expensive equipment is continuously being conducted. In this paper, we use a single camera that is inexpensive and can be easily mounted. We propose a method for detecting the wheels and adjacent lanes of a front-side vehicle of a driving vehicle and estimating distances. Our proposed method detects lanes and wheels from frame images after frame extraction via input images. In addition, the distance is measured and compared with the actual distance measured in the actual road environment. The distance could be calculated relatively accurately within the error range of ± 3 cm. Through this, it is expected that the camera can be used as an alternative means when the cost of autonomous vehicles is reduced or when the lidar or radar sensor fails.

• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.517-544
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• 2023

This study presents the process and outcomes of developing mathematical-informatics linkage·convergence class materials, based on previous research findings that indicate a lack of such materials in high schools despite the increasing need for development of interdisciplinary linkage·convergence class materials In particular, this research provides insights into the discussions of six teachers who participated in the same professional learning community program, aiming to create materials that are suitable for linkage·convergence class materials and highly practical for classroom implementation. Following the material development process, a theme-based design model was applied to create the materials. In alignment with prior research and consensus among teacher learning community members, mathematics and informatics teachers developed instructional materials that can be utilized together during a 100-minute block lesson. The developed materials utilize societal issue contexts to establish links between the two subjects, enabling students to engage in problem-solving through mathematical modeling and coding. To increase the validity and practicality of the developed resources during their field application, CVR verification was conducted involving field teachers. Incorporating the results of the CVR verification, the finalized instructional materials were presented in the form of a teaching guide. Furthermore, we aimed to provide insights into the trial-and-error experiences and deliberations of the developers throughout the material development process, with the intention of offering valuable information that can serve as a foundation for conducting related research by field researchers. These research findings hold value as empirical evidence that can explore the applicability of teaching material development models in fields. The accumulation of such materials is expected to facilitate a cyclical relationship between theoretical teaching models and practical classroom applications.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.244-250
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• 2007

Membrane inlet mass spectrometer (MIMS) has been used to accurately quantify dissolved gases in liquid samples. In this study, the MIMS system was applied to measure dissolved methane in seawater and sediment porewater. To evaluate the accuracy of the measurement, liquid samples saturated with different methane partial pressure were prepared and the methane concentrations were quantified with the MIMS system. The measured values correspond well with the expected values calculated from solubility constants. The standard error of the measurements were $0.13{\sim}0.9%$ of the mean values. The distribution of dissolved methane concentration in seawater of the South Sea of Korea revealed that the physical parameters primarily control the methane concentration in sea water. The MIMS system was effective to resolve the small dissolved methane difference among water masses. The probe type inlet in MIMS system was proven to be effective to measure porewater methane concentration.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.1
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• pp.63-71
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• 2024

Through the development of construction technology, various construction projects such as redevelopment projects, undergrounding of roads, expansion of subways, and metro railways are being carried out. However, this has led to an increase in the number of construction projects in existing urban centers and neighborhoods, resulting in an increase in the number of damages and disputes between neighboring buildings and residents, as well as an increase in safety accidents due to the aging of existing buildings. In this study, digital data was applied to a graphics program to objectify the progress of cracks by comparing the creation of cracks and the increase in length and width through photographic images and presenting the degree of cracks numerically. Through the application of the program, the error caused by the subjective judgment of crack change, which was mentioned as a shortcoming of the existing field survey, was solved. It is expected that the program can be used universally in the building diagnosis process by improving its reliability if supplemented and improved in the process of use. As a follow-up study, it is necessary to apply the extraction algorithm of the digital graphic data program to calculate the length and width of the crack by itself without human intervention in the preprocessing work and to check the overall change of the building.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.165-179
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• 2024

It is crucial to have a comprehensive understanding of inundation and water cycle in urban areas for mitigating flood risks and sustainable water resources management. In this study, we developed a Cellular Automata-based integrated Water cycle model (CAW). A comparative analysis with physics-based and conventional cellular automata-based models was performed in an urban watershed in Portland, USA, to evaluate the adequacy of spatiotemporal inundation simulation in the context of a high-resolution setup. A high similarity was found in the maximum inundation maps by CAW and Weighted Cellular Automata 2 Dimension (WCA2D) model presumably due to the same diffuse wave assumption, showing an average Root-Mean-Square-Error (RMSE) value of 1.3 cm and high scores of binary pattern indices (HR 0.91, FAR 0.02, CSI 0.90). Furthermore, through multiple simulation experiments estimating the effects of land cover and soil conditions on inundation and infiltration, as the impermeability rate increased by 41%, the infiltration decreased by 54% (4.16 mm/m²) while the maximum inundation depth increased by 10% (2.19 mm/m²). It was expected that high-resolution integrated inundation and water cycle analysis considering various land cover and soil conditions in urban areas would be feasible using CAW.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.77-90
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• 2024

While discussions on ESG are actively taking place in Europe and other countries, the number of countries pushing for mandatory ESG information disclosure related to non-financial information of listed companies is rapidly increasing. However, as companies respond to mandatory global ESG information disclosure, problems are emerging such as the stringent requirements of global ESG disclosure standards, the complexity of data management, and a lack of understanding and preparation of the ESG system itself. In addition, it requires a reasonable analysis of how business management opportunities and risk factors due to climate change affect the company's financial impact, so it is expected to be quite difficult to analyze the results that meet the disclosure standards. In order to perform tasks such as ESG management activities and information disclosure, data of various types and sources is required and management through an information system is necessary to measure this transparently, collect it without error, and manage it without omission. Therefore, in this study, we designed an ESG data integrated management model to integrate and manage various related indicators and data in order to transparently and efficiently convey the company's ESG activities to various stakeholders through ESG information disclosure. A framework for implementing an information system to handle management was developed. These research results can help companies facing difficulties in ESG disclosure at a practical level to efficiently manage ESG information disclosure. In addition, the presentation of an integrated data management model through analysis of the ESG disclosure work process and the development of an information system to support ESG information disclosure were significant in the academic aspects needed to study ESG in the future.