• Journal of Venture Innovation
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• v.5 no.2
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• pp.85-99
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• 2022

Dryers becoming commercially available for experimental and industrial use are classified to general drying oven, hot-air dryer, vacuum dryer, freezing dryer, etc. and kinds of them are various from the function, size and volume, etc. But the moisture measurement is not applied although it is important factor for the quality control and the performance improvement of products, and then now is very passive because the weight is weighed arbitrarily after dry-end. Generally the method for measuring moisture is divided by a direct measurement method and a indirect measurement method, and the former such as the change of weight or volume on the front and rear of separation of moisture, etc. is mainly used. Relatively a indirect measurement is very limited to apply due to utilize measurement apparatuses using temperature conductivity and micro-wave etc. In this research, we easily designed the moisture measurement system using the open-source based Arduino, and monitored moisture fluctuations and weight profiles in the real-time without the effect of external environment. Concretely the temperature-humidity and load cell sensors were packaged into a drying oven and the various change values were measured, and their sensors capable to operate 60℃ and 80℃ were selected to suitable for the moisture sensitive materials and the food dry. And also the performance safety using the organic samples of banana, pear, sawdust could be secured because the changes of evaporation rate as the dry time and temperature, and the measurement values of load cell appeared stable response characteristics through repeated experiments. Hereafter we judge that the reliability can be improved increasingly through the expansion of temperature-humidity range and the comparative analysis with CFD(Computational Fluid Dynamics) program.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.16-24
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• 2024

Background: Indoor PM_2.5 concentrations in residential houses can be affected by various factors depending on the season. This is because not only do the climate characteristics depend on the season, but the activity patterns of occupants are also different. Objectives: The purpose of this study is to compare factors affecting indoor PM_2.5 concentrations in apartments and detached houses in Daegu according to seasonal changes. Methods: This study included 20 households in Daegu, South Korea. The study was conducted during the summer (from July 10 to August 10, 2023) and the autumn (from September 11 to October 9, 2023). A sensor-based instrument for PM_2.5 levels was installed in the living room of each residence, and measurements were taken continuously for 24 hours at intervals of one minute during the measurement period. Based on the air quality monitoring system data in Daegu, outdoor PM_2.5 concentrations were estimated using ordinary kriging (OK) in Python. In addition, the indoor activities of the occupants were investigated using a time-activity pattern diary. The affecting factors of indoor PM_2.5 concentration were analyzed using multiple regression analysis. Results: Indoor and outdoor PM_2.5 concentrations of the residences during summer were 15.27±11.09 ㎍/m³ and 11.52±7.56 ㎍/m³, respectively. Indoor and outdoor PM_2.5 concentrations during autumn were 13.82±9.61 ㎍/m³ and 9.57±5.50 ㎍/m³, respectively. The PM_2.5 concentrations were higher in summer compared to autumn both indoors and outdoors. The primary factor affecting indoor PM_2.5 concentration in summer was occupant activity. On the other hand, during the autumn season, the primary affecting factor was outdoor PM_2.5 concentration. Conclusions: Indoor PM_2.5 concentration in residential houses is affected by occupant activity such as the inflow of outdoor PM_2.5 concentration, cooking, and cleaning, as found in previous studies. However, it was revealed that there were differences depending on the season.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.6-15
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• 2024

Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM_2.5) concentrations. Additionally, the level of population exposure to PM_2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM_2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM_2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM_2.5 concentration. To assess the factors influencing changes in the ambient PM_2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM_2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM_2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM_2.5, potentially altering the levels of PM_2.5 exposure in the population.

• Economic and Environmental Geology
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• v.57 no.2
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• pp.271-280
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• 2024

This study examines the European Union (EU)'s policies on managing nitrate contamination in groundwater and provides implications for the future groundwater management in South Korea. Initiated by the 1991 Nitrate Directive, the EU has pursued a multifaceted approach to reduce agricultural nitrate pollution through sustainable ('good') farming practices, regular nitrate level monitoring, and designating Nitrate Vulnerable Zones. Further policy integrations, like the Water Framework Directive and Groundwater Directive, have established comprehensive protection strategies, including the use of pollutant threshold values. Recently, the 2019 Green Deal escalated efforts against nitrates, aligning with broader environmental and climate objectives. This review aims to explore these developments, highlighting key mitigation strategies against nitrate pollution, and providing valuable insights for the future sustainable groundwater nitrate management in South Korea, emphasizing the importance of preventive measures and collaborative efforts to restore and improve groundwater quality.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.85-93
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• 2024

The monitoring of environmental information (e.g. noise, dust, vibration, temperature, humidity) is crucial to the safe and sustainable operation of a construction site. However, commercial sensors exhibit certain drawbacks when applied on-site. First, the installation cost is prohibitively high. Second, these sensors have been engineered without considering the rugged and harsh conditions of a construction site, resulting in error-prone sensing. Third, construction sites are compelled to allocate additional resources in terms of manpower, expenses, and physical spaces to accommodate individual sensors. This research developed an integrated sensing module to measure the environmental information in construction site. The sensing module slashes the installation cost to 3.3%, is robust enough to harsh and outdoor sites, and consolidates multiple sensors into a single unit. The sensing module also supports GPS, LTE, and real-time sensing. The evaluation showed remarkable results including 97.5% accuracy and 99.9% precision in noise measurement, an 89.7% accuracy in dust measurement, and a 93.5% reliability in data transmission. This research empowers the collection of substantial volumes and high-quality environmental data from construction sites, providing invaluable support to decision-making process. These encompass objective regulatory compliance checking, simulations of environmental data dispersion, and the development of environmental mitigation strategies.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.37-46
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• 2024

Recently, 3D laser scanning technology, which can collect accurate and quick information on phenomena, has been attracting attention among smart construction technologies. 3D laser scanning technology can obtain information most similar to reality at construction sites. In this study, we would like to apply a new member identification method to an actual building and present the possibility of applying point cloud data, which can be collected using 3D laser scanning technology, to measuring progress at construction sites. In order to carry out the research, we collected location information for component identification from BIM, set a recognition margin for the collected location information, and proceeded to identify the components that make up the building from point cloud data. Research results We confirmed that the columns, beams, walls, and slabs that make up a building can be identified from point cloud data. The identification results can be used to confirm all the parts that have been completed in the actual building, and can be used in conjunction with the unit price of each part in the project BOQ for prefabricated calculations. In addition, the point cloud data obtained through research can be used as accurate data for quality control monitoring of construction sites and building maintenance management. The research results can contribute to improving the timeliness and accuracy of construction information used in future project applications.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.93-101
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• 2024

Background: As pollutants caused by non-point sources flow into rivers, river water quality monitoring for fecal pollution is becoming increasingly important. Objectives: This study was conducted to investigate the distribution of microbial communities in the Yeongsangang River water system and sewage treatment plants in Gwangju and to evaluate their antibiotic resistance. Methods: In the experiment, samples were distributed to five selective media at each point and then cultured for 18 to 24 hours. When bacteria were observed, they were sub-cultured by size and shape and identified using MALDI-TOF MS equipment. When identification was completed, 17 types of antibiotic susceptibility tests were performed using VITEK II equipment, focusing on gram-negative dominant species among the identified strains. Results: During the study period, a total of 266 strains were isolated from 39 samples. Gram-positive bacteria were 37 strains in four genera, or 13.9% of the total, and Gram-negative bacteria were 229 strains in 23 genera, or 86.1% of the total. Antibiotic susceptibility testing of 23 strains, the major dominant species, showed that one strain (4.3%) was resistant to only one antibiotic, and two strains (8.7%) were 100% susceptible to the 17 antibiotics tested. The other 20 strains (87.0%) were multidrug resistant bacteria resistant to two or more antibiotics. There were various types of multidrug resistance. Among them, penicillin and cephalosporin series showed the highest resistance. Conclusions: Based on the results of this study, it was found that the bacterial community structure changed according to regional and environmental factors, and it was judged that continuous research such as genetic analysis of antibiotic-resistant bacteria present in natural rivers is necessary.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.26 no.1
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• pp.1-10
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• 2024

Objective: Endovascular coil embolization is the primary treatment modality for intracranial aneurysms. However, its long-term durability remains of concern, with a considerable proportion of cases requiring aneurysm reopening and retreatment. Therefore, establishing optimal follow-up imaging protocols is necessary to ensure a durable occlusion. This study aimed to develop guidelines for follow-up imaging strategies after endovascular treatment of intracranial aneurysms. Methods: A committee comprising members of the Korean Neuroendovascular Society and other relevant societies was formed. A literature review and analyses of the major published guidelines were conducted to gather evidence. A panel of 40 experts convened to achieve a consensus on the recommendations using the modified Delphi method. Results: The panel members reached the following consensus: 1. Schedule the initial follow-up imaging within 3-6 months of treatment. 2. Noninvasive imaging modalities, such as three-dimensional time-of-flight magnetic resonance angiography (MRA) or contrast-enhanced MRA, are alternatives to digital subtraction angiography (DSA) during the first follow-up. 3. Schedule mid-term follow-up imaging at 1, 2, 4, and 6 years after the initial treatment. 4. If noninvasive imaging reveals unstable changes in the treated aneurysms, DSA should be considered. 5. Consider late-term follow-up imaging every 3-5 years for lifelong monitoring of patients with unstable changes or at high risk of recurrence. Conclusions: The guidelines aim to provide physicians with the information to make informed decisions and provide patients with high-quality care. However, owing to a lack of specific recommendations and scientific data, these guidelines are based on expert consensus and should be considered in conjunction with individual patient characteristics and circumstances.