• Journal of the Korea Institute of Building Construction
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• v.21 no.6
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• pp.677-687
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• 2021

If a fire breaks out in a building, occupants can evacuate more rapidly if they are able to identify the location of the fire, the exits, and themselves. This study derives the requirements of system development, such as distance non-limitation, a non-additional device, a non-centralized server system, and low power for an emergency, to identify information about the fire and the location of evacuees. The objective is to receive and transmit information and reduce the time and effort of the database for location tracking. Accordingly, this study develops a server-independent system that collects information related to a building fire and an evacuee's location and provides information to the evacuee on their mobile device. The system is composed of a transmitting unit to disseminate fire location information and a mobile device application to determine the locations of the fire and the evacuee. The developed system can contribute to reducing the damage to humans because evacuees can identify the location of the fire, exits, and themselves regardless of the impaired server system by fire, the interruption of power source, and the evacuee's location. Furthermore, this study proposes a theoretical basis for reducing the effort required for database construction of the k-nearest neighbor fingerprint.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.63-71
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• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.41-58
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• 2022

This study aims to provide lesson plans that can simultaneously achieve both the learning goals of the 'Human Development & Family' domain of the 2015 revised Technology & Home Economics curriculum and the Sustainable Development Goals. Four steps including analysis, design, development, and evaluation and revision were followed. In the analysis step, the 'Changing Families and Healthy Families' unit was selected as it is relevant to the nine subgoals of the SDGs. In the design step, three sessions were planned with a problem-solving project approach. In the development step, three lesson plans for each session, individual and group activity worksheets for students, and guidelines for teachers were constructed. In the evaluation and revision step, criteria for evaluating the lesson plans were developed reflecting both the goals of the Home Economic curriculum and the SDGs. The validity of the lesson plans was reviewed by a panel of experts. Then, the revised lesson plans were finalized. This study provides an illustrative example of the lesson plans in the secondary education context that can be used to achieve the learning goals of the Home Economic curriculum and the Sustainable Development Goals at the same time.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1044-1053
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• 2022

Time domain reflectometry (TDR) is a diagnostic technique to evaluate the physical integrity of cable and finds application in leak detection and localization of piping system. In this study, a cable-shaped leak detection sensor was proposed using the TDR technique for monitoring leakage detection of ship's engine room seawater piping system. The cable sensor was developed using a twisted pair arrangement and wound by an absorbent material. The availability and performance of the sensor for leak detection and localization were evaluated on a lab-scale pipeline set up. The developed sensor was installed onto the pipes and flanges of the lab-scale set up and various TDR waveforms were acquired and analyzed according to the dif erent variables including the number of twists and sheath thickness. The result indicated that the twisted cable sensor was able to produce clear and smooth signal as compared to the TDR sensor with a parallel arrangement. The optimal number of twist was determined to be above 10 per the unit length. The optimal diameter of sheath thickness that results in the desired sensitivity was determined to be ranging from 80% up to 120% of the diameter of the conductor. The linear regression analysis for estimation of leak localization was carried out to estimate the location of the leakage, and the result was a determination coefficient of 0.9998, indicating a positive relationship with the actual leakage point. The proposed TDR based leak detection method appears to be an effective method for monitoring leakage of ship's seawater piping system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.651-658
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• 2022

To cope with climate change, studies are being conducted on natural-based solutions (NBS) that reduce carbon by utilizing ecosystems and ecological resources ultimately to achieve carbon neutrality. In this study, carbon storage and economic value evaluations were conducted of the coastal land and sea of Busan using InVEST's Carbon and Coastal Blue Carbon models, which are ecosystem service-based evaluation models. As a result, it is estimated that the amount of carbon storage per unit area is lower than that of the entire Busan land area and that if the currently underway or planned development works are completed, the carbon storage of the coastal land areas would be decreased more. Coastal sea areas have less carbon storage than coastal land, but there is great potential for NBS that utilize ecological resources in the future. If the reclamation of public water affects important habitats with high carbon storage levels, it will reduce these levels, and such negative effects could last for a long time. For the sustainable management of Busan coastal areas, ecosystem service-based management strategies are needed considering carbon storage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.29-35
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• 2022

This paper proposes a fuel cell education framework installed on a Metaverse environment, which is to reduce the burden of education costs and improve the effect of education or learning. This Meta-Fuel cell platform utilizes the Unity 3D Web and enables not only theoretical education but also hands-on training. The platform was designed and developed to accommodate a variety of unit education contents, such as ppt documents, videos, etc. The platform, therdore, integrates ppt and video demonstrations for theoretical education, as well as software content "STACK-Up" for hands-on training. Theoretical education section provides specialized liberal arts knowledge on hydrogen, including renewable energy, hydrogen economy, and fuel cells. The software "STACK-Up" provides a hands-on practice on assembling the stack parts. Stack is the very core component of fuel cells. The Meta-Fuelcell platform improves the limitations of face-to-face education. It provides educators with the opportunities of non-face-to-face education without restrictions such as educational place, time, and occupancy. On the other hand, learners can choose educational themes, order, etc. It provides educators and learners with interesting experiences to be active in the metaverse space. This platform is being applied experimentally to a education project which is to develop advanced manpower in the fuel cell industry. Its improvement is in progress.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.77-100
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• 2022

In the era of low growth, many provincial cities are experiencing population decline and aging. Population decline phenomena such as reduction of productive manpower, reduction of finances, deterioration of quality of life, and collapse of the community base are occurring in a chain and are being pushed to the brink of extinction of the cities. This study aims to propose a methodology to objectively estimate the employment creation centers and setting the basic unit of industrial-centered zoning by applying spatial statistical techniques and GIS for the application of the compact city plan as an efficient spatial management policy in a city with a declining population. In details, based on reviewing previous studies on compact city, 'employment complex index(ECI)' were defined considering the number of workers, the number of settlers, and the area of development land, the employment creation center was estimated by applying the 'Local Moran's I' and 'Getis-Ord's Hot-Spot Analysis'. As a case study, changes in the four years of 2013, 2015, 2017, and 2019 were compared and analyzed for Changwon City. As a result, it was confirmed that the employment creation center is becoming compacted and polycentric, which is a significant result that reflects the actual situation well. This results provide the basic data for functional and institutional territorial governance for the regional revitalization platform, and provide meaningful information necessary for spatial policy decision-making, such as population reduction, regional gross domestic product, and public facility arrangement that can respond to energy savings, transportation plans, and medical and health plans.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.2
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• pp.149-157
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• 2022

The aim of this study was to evaluate the effects of erythrosine-mediated photodynamic therapy (PDT) on Streptococcus mutans biofilm recovery by counting its colony-forming units (CFUs) and via confocal laser scanning microscopy analysis at different time points following PDT. In PDT, photosensitizer was an erythrosine. S. mutans ATCC25175 biofilms were irradiated using an LED curing light. Chlorhexidine (CHX) was used as positive control. After each antimicrobial treatment, samples were cultured to allow biofilm recovery. Viability was measured by calculating the CFU counts after treatment and after every 3 hours for up to 24 hours. Immediately after treatment, the PDT and CHX groups showed equally significant decreases in S. mutans CFU counts compared to the negative control. After 12 hours of reculture, the PDT group showed no significant difference in the decrease in CFU count compared to the negative control, whereas the CHX group showed significantly lower CFU counts throughout the 24-hour period. Erythrosine-mediated PDT can effectively inhibit S. mutans biofilm formation. However, biofilm recovery occurred earlier in the CHX group after PDT. This study provides insights into the clinical effectiveness of PDT in preventing dental caries.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.391-396
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• 2021

In this study, items for forest policy and forest resource research in Austria, Japan, New Zealand, and Indonesia, which are major forest advanced countries, were investigated, and the applicability of point cloud data acquired through laser scanning was identified. Through the study, it was found that forest policies in developed countries are being pursued for the purpose of sustainable forest conservation and management, job creation, and timber productivity improvement, and that new technologies are being researched and applied to actual projects. Korea has a high proportion of forests compared to the national land area compared to major forestry developed countries, but the accumulation of trees is relatively low, so it is a time for scientific forest management to improve the accumulation of trees. To understand the applicability of laser scanning technology, a forest resource survey using point cloud data was conducted, and the diameter of breast height, height, number of trees per unit area were calculated, and the shape of the crown was identified. If field experiments and accuracy evaluations applying various laser scanning technologies are carried out in the future, it will be possible to present the quantitative improvement of forest resource survey using foil cloud.