• Pediatric Infection and Vaccine
• /
• v.29 no.1
• /
• pp.37-45
• /
• 2022

Purpose: During the coronavirus disease 2019 (COVID-19) pandemic, we conducted a Delphi survey that included the experts from the field of COVID-19 immunization in children aged 5-11 years. The aim was to organize collective expert opinions on COVID-19 vaccination in young children in the Republic of Korea, and so thus assist the vaccination policy. Methods: The panels included pediatric infectious disease specialists, preventive medicine experts, infectious disease physicians, and COVID-19 vaccine experts consulting the Ministry of Health and Welfare. The Delphi survey was conducted online using a questionnaire from February 14 to February 27, 2022. Results: The Delphi panels agreed that children were vulnerable to COVID-19, and the severity of illness was modest. Furthermore the panels reported that children with chronic illness were more susceptible to a worsening clinical course. There were generally positive opinions on the effectiveness of COVID-19 vaccination in children aged 5-11 years, and experts gathered a slightly positive opinion that the adverse events of pediatric COVID-19 were not numerous. The benefits of COVID-19 vaccination were evaluated at a level similar to the potential risks in children. Currently, the only approved mRNA platform vaccine in children seemed to be sustainable; however, the recombinant protein platform COVID-19 vaccines were evaluated as better options. Conclusions: Due to the surge of the Omicron variant and an increase in pediatric cases, the COVID-19 vaccination in young children may have to be considered. Panels had neutral opinions regarding the COVID-19 vaccination in children aged 5-11 years. Thus monitoring of the epidemiology and the data about the safety of COVID-19 vaccination should be continued.

• Economic and Environmental Geology
• /
• v.54 no.2
• /
• pp.199-212
• /
• 2021

The Sebyeonggwan Hall (National Treasure No. 305) is located on the Naval Headquarter of Three Provinces in Tongyeong, and it has partly undergone with several rebuilding, remodeling, repairing and restorations since it's the first establishment in Joseon Dynasty (AD 1605) of ancient Korea. This study focuses on 50 foundation stones that comprise the Sebyeonggwan. These stones are made of six rock types and currently have various shapes of the surface damages. As the foundation stones, the dominant rock type was dacitic lapilli tuffs, and provenance-based interpretation was performed to supply alternative stones for conservation. Most of the provenance rocks for foundation stones showed highly homogeneity with their corresponding stones of petrography, mineralogy and magnetic susceptibility. According to surface deterioration assessments, the most serious damages of the stones were blistering and scaling. The deterioration mechanism was identified through the analysis of inorganic contaminants, and the primary reason is considered salt weathering caused by sea breeze and other combined circumstances. Based on the mechanical durability of the stones, there was no foundation stone that required the replacement of its members attributed to the degradation of the rock properties, but conservation treatment is considered necessary to delay superficial damage. The foundation stones are characterized by a combined outcome of multiple petrological factors that caused physical damage to surfaces and internal defects. Therefore, it's required to diagnosis and monitoring the Sebyeonggwan regularly for long-term preservation.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.4
• /
• pp.318-329
• /
• 2022

Plant phenology including flowering, leaf unfolding, and leaf coloring in a forest is important to understand the forest ecosystem. Temperature rise due to recent climate change, however, can lead to plant phenology change as well as snowfall in winter season. Therefore, accurate monitoring of forest environment changes such as plant phenology and snow cover is essential to understand the climate change effect on forest management. These changes can monitor using a digital camera system. This paper introduces the detection methods for plant phenology and snow cover at the mountain region using an unmanned camera system that is a way to monitor the change of forest environment. In this study, the Automatic Mountain Meteorology Stations (AMOS) operated by Korea Forest Service (KFS) were selected as the testbed sites in order to systematize the plant phenology and snow cover detection in complex mountain areas. Multi-directional Internet Protocol (IP) camera system that is a kind of unmanned camera was installed at AMOS located in Seoul, Pyeongchang, Geochang, and Uljin. To detect the forest plant phenology and snow cover, the Red-Green-Blue (RGB) analysis based on the IP camera imagery was developed. The results produced by using image analysis captured from IP camera showed good performance in comparison with in-situ data. This result indicates that the utilization technique of IP camera system can capture the forest environment effectively and can be applied to various forest fields such as secure safety, forest ecosystem and disaster management, forestry, etc.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.4
• /
• pp.346-352
• /
• 2022

Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.

• Korean Journal of Poultry Science
• /
• v.49 no.4
• /
• pp.281-286
• /
• 2022

This study was conducted to investigate the detection rate and serotypes of Salmonella spp. in conventional and welfare poultry farms. Ten welfare (five layer and five broiler) and 15 conventional farms (five layer and ten broiler farms) were visited to collect environmental samples for identification and serotyping of Salmonella spp. The detection rate of Salmonella spp. was higher in the welfare farms than in conventional farms in both layer and broiler farms. In layer farms, Salmonella spp. was detected in 0.76% (1 out of 130) of samples from one of five welfare layer farms, but was not detected in the five in conventional layer farms. No significan ifference (P>0.05) was observed between the welfare and conventional layer farms. In broiler farms, Salmonella spp. was detected in 10.5% (21 out of 200) of samples from four of five welfare broiler farms and 3.5% (7 out of 200) of samples from five of ten conventional broiler farms, and a significant difference (p <0.05) was observed between the welfare and conventional broiler farms. Among 29 Salmonella spp. isolates, five isolates were serotyped to Salmonella enterica subsp. Enteritidis (n=2), Salmonella enterica subsp. Grampian (n=1), Salmonella enterica subsp. Virchow (n=1), and Salmonella enterica subsp. Senftenberg (n=1). These results suggest that microbial risks could be higher in welfare farms than in conventional farms due to easy access to open-air areas, environmental enrichment, and reduced use of antibiotics. Therefore, continuous monitoring and surveillance for Salmonella spp. is necessary to improve the microbiological safety of poultry meat.

• Wind and Structures
• /
• v.36 no.4
• /
• pp.237-247
• /
• 2023

The emergence of high-rise buildings has necessitated frequent structural health monitoring and maintenance for safety reasons. Wind causes damage and structural changes on tall structures; thus, safe structures should be designed. The pressure developed on tall buildings has been utilized in previous research studies to assess the impacts of wind on structures. The wind tunnel test is a primary research method commonly used to quantify the aerodynamic characteristics of high-rise buildings. Wind pressure is measured by placing pressure sensor taps at different locations on tall buildings, and the collected data are used for analysis. However, sensors may malfunction and produce erroneous data; these data losses make it difficult to analyze aerodynamic properties. Therefore, it is essential to generate missing data relative to the original data obtained from neighboring pressure sensor taps at various intervals. This study proposes a deep learning-based, deep convolutional generative adversarial network (DCGAN) to restore missing data associated with faulty pressure sensors installed on high-rise buildings. The performance of the proposed DCGAN is validated by using a standard imputation model known as the generative adversarial imputation network (GAIN). The average mean-square error (AMSE) and average R-squared (ARSE) are used as performance metrics. The calculated ARSE values by DCGAN on the building model's front, backside, left, and right sides are 0.970, 0.972, 0.984 and 0.978, respectively. The AMSE produced by DCGAN on four sides of the building model is 0.008, 0.010, 0.015 and 0.014. The average standard deviation of the actual measures of the pressure sensors on four sides of the model were 0.1738, 0.1758, 0.2234 and 0.2278. The average standard deviation of the pressure values generated by the proposed DCGAN imputation model was closer to that of the measured actual with values of 0.1736,0.1746,0.2191, and 0.2239 on four sides, respectively. In comparison, the standard deviation of the values predicted by GAIN are 0.1726,0.1735,0.2161, and 0.2209, which is far from actual values. The results demonstrate that DCGAN model fits better for data imputation than the GAIN model with improved accuracy and fewer error rates. Additionally, the DCGAN is utilized to estimate the wind pressure in regions of buildings where no pressure sensor taps are available; the model yielded greater prediction accuracy than GAIN.

• Journal of Environmental Health Sciences
• /
• v.49 no.4
• /
• pp.183-189
• /
• 2023

Background: The indoor air quality of classrooms, in which the capacity per unit area is high and students spend time together, must be managed for safety and comfort. It is necessary to develop an eco-friendly indoor air quality reduction method rather than biased management that relies solely on air purifiers. Objectives: In this study, plants and air purifiers were installed in middle school classrooms to evaluate the indoor PM_2.5 reduction. Methods: Four middle school classrooms were selected as test beds. Air quality was monitored in real-time every one minute using IoT equipment installed in the classrooms, corridors, and rooftops. After measuring the background concentration, plants and air purifiers were installed in the classroom and the PM_2.5 reduction effect was analyzed through continuous monitoring. Results: After installing the plants and air purifiers, the average PM_2.5 concentration was 33.7 ㎍/m³ in the classrooms without plants and air purifiers, 25.6 ㎍/m³ in classrooms with plants only, and 21.7 ㎍/m³ in classrooms with air purifiers only. In the classroom where plants and air purifiers were installed together, it was 20.0 ㎍/m³. The reduction rates before and after installation were 4.5% for classrooms with plants only, 16.5% for classrooms with air purifiers only, and 27.6% for classrooms with both plants and air purifiers. The I/O ratio, which compares the concentration of PM_2.5 in classrooms with corridors and outside air, also showed the lowest in the order of plants and air purifiers, air purifiers, and plant-only classrooms. Conclusions: The PM_2.5 reduction effect of using plants was confirmed, and it is expected to be used as basic data for the development of environmentally-friendly indoor air quality improvement methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.317-321
• /
• 2022

In response to Incheon tap water accident in 2019, the Ministry of Environment has created the "Comprehensive Measures for Water Safety Management" to improve water operation management, provide systematic technical support, and respond to accidents. Accordingly, K-water is making a smart water supply management system for the entire process of tap water. In order to advance the response to water accidents, it is essential to secure the reliability of real-time water operation data such as flow rate, pressure, and water level, and to develop and apply a warning algorithm in advance using big data analysis techniques. In this paper, various statistical techniques are applied using water supply operation data (flow, pressure, water level, etc) to prepare the foundation for the selection of the optimal operating range and advancement of the monitoring and alarm system. In addition, the arrival time is analyzed through cross-correlation analysis of changes in raw water turbidity between the water intake and water treatment plants. The purpose of this paper is to study the model that predicts the raw water turbidity of a water treatment plant by applying raw water turbidity data considering the time delay according to the flow rate change.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.288-290
• /
• 2022

As part of the SOC digitization for smart water management and flood prevention, the government reported that automatic and remote control system for drainage facilities (180 billion won) to 57% of national rivers and established a real-time monitoring system (30 billion won). In addition, they were also planning to establish a smart dam safety management system (15 billion won) based on big data at 11 regions. Therefore, research is needed for smart water management and flood prevention system that can accurately calculate the flow rate through real-time flow rate measurement of rivers. In particular, the most important thing to improve the system implementation and accuracy is to ensure the accuracy of real-time flow rate measurements. To this end, radar sensors for measuring the flow rate of electromagnetic waves in the United States and Europe have been introduced and applied to the system in Korea, but demand for improvement of the system continues due to high price range and performance. Consequently, we would like to propose an improved flow rate measurement and flood forecast system by developing a radar sensor for measuring the electromagnetic surface current meter for real-time flow rate measurement.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.1
• /
• pp.209-220
• /
• 2022

With the worldwide spread of African swine fever, interest in livestock epidemics has increased. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but there are no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted the trajectory of livestock-related vehicles using the facility-visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority. The results are presented as exposure indices aggregating the link-time occupancy of each vehicle. As a result, 274,519 livestock-related vehicle trajectories were extracted, and the exposure values by link and zone were derived quantitatively. This study highlights the need for prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies.