• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.63-65
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• 2023

BIM and AR technologies have been assessed as a means of enhancing productivity within the construction industry, through the provision of effortless access to critical data on site, achieved via the projection of 3D models and associated information onto actual structures. However, most of the previous researches for applying AR technology in construction quality management has been performed for construction projects in general, resulting in only overall on-site management solutions. Also, a few previous researches for the application of AR in the quality management of specific elements like reinforcements focused only on simple projection, so conducting specific quality inspection was impossible. Hence, this study aimed to develop a practically applicable BIM-based AR quality management system targeted for reinforcements. For the development of this system, the reinforcement inspection items on the quality checklist used at railway construction sites were analyzed, and four types of AR functions that can effectively address these items were developed and installed. The validation result of the system for the actual railway bridge showed a degradation of projection stability. This problem was solved through model simplification and enhancement of the AR device's hardware performance, and then the normal operation of the system was validated. Subsequently, the final developed reinforcement quality inspection system was evaluated for practical applicability by on-site quality experts, and the efficiency of inspection would significantly increase when using the AR system compared to the current inspection method for reinforcements.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.

• Membrane Journal
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• v.33 no.6
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• pp.447-453
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• 2023

The performance of computer systems and the development of various computer simulation programs have made it possible to analyze chemical systems composed of more complex elements, and accordingly, research using molecular dynamics simulation is being actively conducted. Research on calculating the gas permeation characteristics of polymer membranes by molecular dynamics, which was previously conducted mainly through experiments, is receiving attention for gas barrier membranes used in food packaging and pharmaceuticals. Recently, there has been a report that a gas barrier effect appears when a coating film is made using silk fibroin, and in this study, a study was conducted using molecular dynamics simulation to confirm whether an oxygen barrier effect appears when a composite film is made using silk fibroin. We built a single model, calculated the gas permeation characteristics, and compared it with the experimental value to confirm that the model reflects the actual experimental results. Actual composite membrane models were then built and the gas movement path within the polymer was analyzed. As a result, oxygen molecules were found that they could not pass through and was blocked in the fibroin region. Therefore, the composite membrane with silk fibroin has excellent oxygen barrier property and is expected to be useful in food packaging, etc.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.992-1001
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• 2023

OWEC (Overtopping Wave Energy Converter) is a wave power generation system using the wave overtopping. The performance and safety of the OWEC are affected by wave characteristics, such as wave height, period. To mitigate this issue, optimal OWEC designs based on wave characteristics must be investigated. In this study, the environmental conditions along the Ulleungdo coast were used. The hydraulic efficiency of the OWEC was calculated using SPH (Smoothed Particle Hydrodynamics) by comparing 4 models that changed the substructure. As a result, it was possible to change the substructure. Through design optimization, a new truss-type structure, which is a substructure capable of carrying the design load, was proposed. Through a case study using member diameter and thickness as design variables, structural safety was secured under allowable stress conditions. Considering wave load, the natural frequency of the proposed structure was compared with the wave period of the relevant sea area. Harmonic response analysis was performed using wave with a 1-year return period as the load. The proposed substructure had a reduced response magnitude at the same exciting force, and achieved weight reduction of more than 32%.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.537-549
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• 2023

The distribution characteristics of tidal flat sediment components are used as an essential data for coastal environment analysis and environmental impact assessment. Therefore, a reliable classification map of surface sedimentary facies is essential. This study evaluated the applicability of regression kriging to generate a classification map of the sedimentary facies of tidal flats. For this aim, various factors such as the number of field survey data and remote sensing-based auxiliary data, the effect of regression models on regression kriging, and the comparison with other prediction methods (univariate kriging and regression analysis) on surface sedimentary facies classification were investigated. To evaluate the applicability of regression kriging, a case study using unmanned aerial vehicle (UAV) data was conducted on the Hwang-do tidal flat located at Anmyeon-do, Taean-gun, Korea. As a result of the case study, it was most important to secure an appropriate amount of field survey data and to use topographic elevation and channel density as auxiliary data to produce a reliable tidal flat surface sediment facies classification map. In addition, regression kriging, which can consider detailed characteristics of the sediment distributions using ultra-high resolution UAV data, had the best prediction performance compared to other prediction methods. It is expected that this result can be used as a guideline to produce the tidal flat surface sedimentary facies classification map.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.1-16
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• 2023

Due to the progress of the 4th industrial revolution and the COVID-19 pandemic, the subscription economy was rapidly expanding. In particular, the subscription economy was expected to expand further as the servicing of products(servitization) rapidly progresses. In this study, we tried to empirically analyze the factors that promote and hinder the spread of the subscription economy from the consumer's point of view. To this end, based on the Service Profit Chain (SPC) model, which identified mechanisms leading from quality to satisfaction, loyalty, and performance, a research model was established by combining the framework of the Value-based Adoption Model (VAM), which covers both benefit and sacrifice factors. Usefulness and convenience were derived as benefit factors, and perceived risks and perceived costs were derived as sacrifice factors. The effects of these factors on satisfaction and continuous use intention were analyzed. For empirical analysis, a survey was conducted targeting people who have experience in subscription economy, and 300 effective samples were analyzed. The analysis was performed as a structural equation model using AMOS 24. As a result of the empirical study, it was found that convenience had a significant positive (+) effect on satisfaction. Perceived risk and perceived cost were analyzed to have a negative (-) effect on satisfaction. On the other hand, usefulness was found to have no significant effect on satisfaction. The influences affecting satisfaction were in the order of perceived cost, convenience, and perceived risk. Satisfaction was found to have a significant positive (+) effect on continuous use intention. The results of this study were considered meaningful in that they broadened the horizons of research by combining existing validated models at the academic level and testing their validity, and found that perceived cost was still an important factor at the practical level.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.134-139
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• 2023

Rehabilitators perform outpatient treatment and daily rehabilitation exercises to recover physical function with the aim of quickly returning to society after surgical treatment. Unlike performing exercises in a hospital with the help of a professional therapist, there are many difficulties in performing rehabilitation exercises by the patient on a daily basis. In this paper, we propose a CNN-LSTM-based upper limb rehabilitation real-time monitoring system so that patients can perform rehabilitation efficiently and with correct posture on a daily basis. The proposed system measures biological signals through shoulder-mounted hardware equipped with EMG and IMU, performs preprocessing and normalization for learning, and uses them as a learning dataset. The implemented model consists of three polling layers of three synthetic stacks for feature detection and two LSTM layers for classification, and we were able to confirm a learning result of 97.44% on the validation data. After that, we conducted a comparative evaluation with the Teachable machine, and as a result of the comparative evaluation, we confirmed that the model was implemented at 93.6% and the Teachable machine at 94.4%, and both models showed similar classification performance.

• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.445-471
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• 2023

Long-term safety over millennia is the top priority consideration in the construction of disposal sites. However, ensuring the mechanical stability of deep geological repositories for spent fuel, a.k.a. radwaste, disposal during construction and operation is also crucial for safe operation of the repository. Imposing restrictions or limitations on tunnel support and lining materials such as shotcrete, concrete, grouting, which might compromise the sealing performance of backfill and buffer materials which are essential elements for the long-term safety of disposal sites, presents a highly challenging task for rock engineers and tunnelling experts. In this study, as part of an extensive exploration to aid in the proper selection of disposal sites, the anticipation of constructing a deep geological repository at a depth of 500 meters in an unknown state has been carried out. Through a review of 2D and 3D numerical analyses, the study aimed to explore the range of properties that ensure stability. Preliminary findings identified the potential range of rock properties that secure the stability of central and disposal tunnels, while the stability of the vertical tunnel network was confirmed through 3D analysis, outlining fundamental rock conditions necessary for the construction of disposal sites.