• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.66-74
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• 2022

Background: The health effects of particulate matter (PM_2.5) bonded with various harmful chemicals differ based on their composition, so investigating and managing their concentrations and composition is vital for long-term management. As industrial complexes emit considerable quantities of pollutants, higher PM_2.5 concentrations and chemical component effects are expected than in other places. Objectives: We investigated the concentration distribution ratios of PM_2.5 chemical components to provide basic data to inform future major emissions control and PM_2.5 reduction measures in industrial complexes. Methods: We monitored five sites near the Ansan and Siheung industrial complexes from August 2020 to July 2021. Samples were collected and analyzed twice per week in spring/winter and once per week in summer/autumn according to the National Institute of Environmental Research in the Ministry of Environments' Air Pollution Monitoring Network Installation and Operation Guidelines. We investigated and compared composition ratios of 29 ions, carbon, and elemental components in PM_2.5. Results: The analysis of PM_2.5 components at the five sites revealed that ion components accounted for the greatest total mass at approximately 50% while carbon components and elemental components contributed 23~28% and 8~10%, respectively. Among the ionic components, NO₃^- occupies the greatest proportion. OC occupies the greatest proportion of the carbon components and sulphur occupies the greatest proportion of elemental components. Conclusions: This study investigated the concentration distribution ratios of PM_2.5 chemical components in industrial complexes. We believe these results provide basic chemical component concentration ratio data for establishing future air management policies and plans for the Ansan and Siheung industrial complexes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.459-468
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• 2022

Long-term data analyses and bioassay experiments were conducted to assess limiting nutrients in Cheonsu Bay and Taean sea. First, long-term nutrient data (2004-2016) provided by the National Water Quality Monitoring Network were used to assess potential limiting nutrients. Analysis of the long-term data showed that the dissolved inorganic nitrogen/dissolved inorganic phosphate (DIN/DIP) ratio was mostly below 16, with N limitation being dominant. A subsequent analysis using the concentration ratios of N, P, and Si showed that N limitation was dominant during summer and autumn but that Si limitation occasionally occurred during winter and spring in relatively limited areas. However, the dominant limiting nutrient was not determined. The nutrient analysis of the field water collected during the bioassay experiment showed that DIN/DIP revealed P limitation at all stations in March and May, whereas N limitation was dominant in July and October. In the analysis using the concentration ratios of N, P, and Si, P and Si limitation appeared in March and May, but there were points with no dominant limiting nutrient. However, N limitation was dominant in July and October. In the bioassay experiment for assessment of the actual limiting nutrient, the results showed no specific limiting nutrient in March, whereas NH₄⁺ and NO₃^- showed responses in May, July, and October, which confirmed that N was a substantial limiting nutrient directly involved in phytoplankton growth during this period.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1065-1076
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• 2022

The purpose of this study was to investigate the effect of the expansion and withering of Salix subfragilis communities on the water quality in Namgang Dam reservoir. The distribution area of the Salix subfragilis communities was 0.12 km² in 2003 for the first time, but it was 3.58 km² in 2019, which has increased rapidly by about 30 times in 16 years. However, in 2013, the distribution area has decreased by 0.17 km² due to long-term immersion in high turbidity, and self-thinning in Salix subfragilis communities. The lake characteristics of reservoir showed a combination of lake type and river type in terms of average water depth, watershed area/lake surface area ratio, water residence time, flushing rate, and stratification. From the result of analyzing long-term changes in lake water quality, COD, TP, and chlorophyll-a in Salix subfragilis communities were significantly larger than those in the three points located in the central part of reservoir. In particular, the fact that the value of chlorophyll-a showed the maximum value in winter rather than summer, unlike the trend of the three points in the Namgang Dam water quality monitoring network, is thought to have occurred internally rather than externally. It can be estimated that one cause of this deterioration of the water quality in Namgang Dam reservoir is the huge amount of nutrients generated in the decomposition process of by-products such as fallen leaves, branches and withered trees in Salix subfragilis communities.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.515-522
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• 2022

This study analyzed the child protection system in Germany from a preventive perspective and attempts to find the applicable implications to Korea. The research method was analyzed in terms of legal, policy and professionalism. The result is as follows. First, Child and Youth Support Act in Germany stipulated a preventive support system to restore the function of the family. Second, according to the Civil Act, it was stipulated that the family court could intervene early. Third, the federal Child Protection Act stipulated community cooperation for thd child protection system. Fourth, the Youth Agency as the general authority made it possible to provide preventive support and intervention at the same time. Firth, qualification standards were specified in the Child and Youth Support Act. Child protection specialists are granted to public officials who have worked for more than three years. The implications are as follows. First, the child protection system, which operates as a child abuse reporting system, should be expanded to a preventive support system. Second, it is necessary to expand monitoring by establishing an early warning system between networks in order to establish a support system for potentially at-risk children. Third, local governments should support children and parents flexibly and comprehensively for dysfunction caused by difficulties at home. Fourth, it is necessary to enact the Child Protection System Cooperation Act for a network cooperation system.

• Journal of Environmental Health Sciences
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• v.49 no.2
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• pp.108-117
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• 2023

Background: When particles are absorbed into the human body, they penetrate deep into the lungs and interact with the tissues of the body. Heavy metals in PM_2.5 can cause various diseases. The main source of PM_2.5 emissions in South Korea's atmosphere has been surveyed to be places of business. Objectives: The concentration of heavy metals in PM_2.5 near the Ulsan Industrial Complex was measured and a health risk assessment was performed for residents near the industrial complex for exposure to heavy metals in PM_2.5. Methods: Concentrations of heavy metals in PM_2.5 were measured at four measurement sites (Ulsan, Mipo, Onsan, Maegok) near the industrial complexes. Heavy metals were analyzed according to the Air Pollution Monitoring Network Installation and Operation Guidelines presented by the National Institute of Environmental Research. Among them, only five substances (Mn, Ni, As, Cd, Cr⁶⁺) were targeted. The risk assessment was conducted on inhalation exposure for five age groups, and the excess cancer risk and hazard quotient were calculated. Results: In the risk assessment of exposure to heavy metals in PM_2.5, As, Cd, and Cr⁶⁺ exceeded the risk tolerance standard of 10^-6 for carcinogenic hazards. The highest hazard levels were observed in Onsan and Mipo industrial complexes. In the case of non-carcinogenic hazards, Mn was identified as exceeding the hazard tolerance of 1, and it showed the highest hazard in the Ulsan Industrial Complex. Conclusions: This study presented a detailed health risk from exposure to heavy metals in PM_2.5 by industrial complexes located in Ulsan among five age groups. It is expected to be utilized as the basis for preparing damage control and industrial emission reduction measures against PM_2.5 exposure at the Ulsan Industrial Complex.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.371-401
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• 2022

If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.327-342
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• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.91-101
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• 2023

In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R²), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R²: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.