• Journal of Pharmacopuncture
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• v.22 no.3
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• pp.166-170
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• 2019

Objectives: Attentional and memory functions are important aspects of neural plasticity that, theoretically, should be amenable to pharmacopuncture treatments. A previous study from our laboratory suggested that quantitative electroencephalographic (qEEG) measurements of theta/beta ratio (TBR), an index of attentional control, may be indicative of academic performance in a first-semester medical school course. The present study expands our prior report by extracting and analyzing data on frontal theta and beta asymmetries. We test the hypothesis that the amount of frontal theta and beta asymmetries (fTA, fBA), are correlated with TBR and academic performance, thereby providing novel targets for pharmacopuncture treatments to improve cognitive performance. Methods: Ten healthy male volunteers were subjected to 5-10 min of qEEG measurements under eyes-closed conditions. The qEEG measurements were performed 3 days before each of first two block examinations in anatomy-physiology, separated by five weeks. Amplitudes of the theta and beta waveforms, expressed in ${\mu}V$, were used to compute TBR, fTA and fBA. Significance of changes in theta and beta EEG wave amplitude was assessed by ANOVA with post-hoc t-testing. Correlations between TBR, fTA, fBA and the raw examination scores were evaluated by Pearson's product-moment coefficients and linear regression analysis. Results: fTA and fBA were found to be negatively correlated with TBR (P<0.03, P<0.05, respectively) and were positively correlated with the second examination score (P<0.03, P=0.1, respectively). Conclusion: Smaller fTA and fBA were associated with lower academic performance in the second of two first-semester medical school anatomy-physiology block examination. Future studies should determine whether these qEEG metrics are useful for monitoring changes associated with the brain's cognitive adaptations to academic challenges, for predicting academic performance and for targeting phamacopuncture treatments to improve cognitive performance.

• Journal of Environmental Impact Assessment
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• v.30 no.5
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• pp.297-304
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• 2021

The environmental impact assessment(EIA) project in Korea has undergone changes and revisions in various evaluation items for about 30 years after the introduction of the Environmental Conservation Act (1997). However, despite the importance of land use evaluation items under the current EIA Act, there are insufficient studies to consider. Therefore, this study focused on the land-use evaluation items based on the EIA guidelines, reviewed 90 of the evaluation documents and consultation documents, and tried to suggest implications and supplementary points forthe domestic EIA land-use evaluation items. As a result, the paradigm was changing from land efficiency centered on development in the past to land efficiency centered on the natural environment and resource conservation. However, in spite of the manual for fitting the paradigm change, opinions on the conservation of the natural environment are still being drawn in the consultation document, so it needs improvement. Two improvements in the impact assessment process suggested in this study are the establishment of standardized spatial data and a quantitative impact and reduction method evaluation tool based on it. In particular, there is a need for a plan evaluation tool for land use arrangement and distribution that can solve the needs of minimizing damage to the natural environment and securing green space and a green network.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.149-157
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• 2019

Recent research has been actively carried out on systems that want to optimize resource utilization by analyzing the intended behavior and pattern of behavior of objects (users, consumers). A service system that applies information about an object's location or behavior must include a location trigger processing system for tracking an object's real-time location. In this paper, we analyze design problems for the implementation of a context-awareness based location trigger system, and present system models based on analysis details. For this purpose, this paper introduces the concept of location trigger for intelligent location tracking techniques about moving situations of objects, and suggests a mobile agent system with active rules that can perform monitoring and appropriate actions based on sensing information and location context information, and uses them to design and implement the location trigger system for context-awareness based location services. The proposed system is verified by implementing location trigger processing scenarios and trigger service and action service protocols. In addition, through experiments on mobile agents with active rules, it is suggested that the proposed system can optimize the role and function of the application system by using rules appropriate to the service characteristics and that it is scalable and effective for location-based service systems. This paper is a preliminary study for the establishment of an optimization system for utilizing resources (equipment, power, manpower, etc.) through the active characteristics of systems such as real-time remote autonomous control and exception handling over consumption patterns and behavior changes of power users. The proposed system can be used in system configurations that induce optimization of resource utilization through intelligent warning and action based on location of objects, and can be effectively applied to the development of various location service systems.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.1
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• pp.69-80
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• 2021

The new town in Korea, developed as a large-scale housing plan, has created urban ecological corridors to provide habitat and movement routes to wildlife and to promote natural ecological flow. This study aimed to investigate the use of wildlife in 10 ecological corridors in Gwanggyo New Town through camera trap technology and confirm effectiveness by identifying environmental factors affecting the use of wildlife's urban ecological corridors. Our researchers installed 20 unmanned sensor cameras at each the entrance and exit of the ecological corridors, and monitored urban wildlife for 10 weeks. According to the monioring results, the main species in Gwanggyo New Town were identified not only raccons, cats, water deer, korean hare and avain but also magpies, dove, eurasian tree sparrow, ring-necked pheasant, and eurasian jay. The number of uses ecological corridors of urban residents was 801(13.49%), as high as that of urban wildlife (1,140, 19.20%), which was judged to have disturbed the use of ecological corridors by wildlife. However, most dominant species of urban wildlife are nocturnal so that, it was judged that they share home range with urban residents at a time interval. In addition, according to the correlation analysis results between the mammal using rate of the urban ecological corridors and environmental factors(ecological corridor-specific length, ecological corridor-specific width, cover degree, shielding degree, connected green area, separation of movement routes, and presence of streetlights), environmental factors were not statistically significant. However, the more the area of green space connected to ecological corridors, the more increasing the mammal using rate of ecological corridor(r=0.71, p<0.05). Therefore, the area of green space connected to the ecological corridors that is associated with rate of wildlife using corridors should be considered as a priority when developing an urban ecological corridors. In the future, this study will extend the observation period of the ecological corridors and continuously accumulate data by adding the number of observation cameras. Furthermore, it is expected that the results of this study can be used as basic data for the standards for urban ecological corridors installation.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.79-90
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• 2021

Landscape composition and structure are important factors determining biological diversity including pests and natural enemires in agricultural ecosystem. This study was conducted to indentify effect of landscape composition on occurrence of lepidopteran pest population in Geochang, Gyoungdnam. For this, orchard characteristics and management practices were surveyed in 80 conventional apple orchards in Geochang, Korea, along with the monitoring of pest population densities. The landscape features of each surveyed orchard also obtained by extracting information from the public-service map. Grapholita molesta was the most dominat and damaging pest followed by Phyllonorycter ringoniella and Carposina sasakii in trap catches. Adoxophyes paraorana occurrences were low. Farmers spray insecticides and fungicides ap. 12.4 times per year respectively while acaricides were sprayed 2.4 times. Major landscape features such as surrounding apple orchard or paddy field did not influence the pest populations but presence of plum, peach, wild peach, graph, and even abandoned orchards significantly resulted in higher pest population mostly on G. molesta. C. sasakii population was higher in orchards with grape, peach, and P. ringoniella with peach, grape, abandoned orchards and jujube. Results highlight the need of landscape management not only for the rural amenity but also for increasing functional diversity of agroecosystem as well as reducing pest population.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Journal of Apiculture
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• v.34 no.1
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• pp.47-55
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• 2019

Honey bees are a vital part of the food chain as the most important pollinators for a broad palette of crops and wild plants. The climate change and colony collapse disorder (CCD) phenomenon make it challenging to develop ICT solutions to predict changes in beehive and alert about potential threats. In this paper, we report the test results of the bee-counting system which stands out against the previous analogues due to its comprehensive components including an improved dual infrared sensor to detect honey bees entering and leaving the hive, environmental sensors that measure ambient and interior, a wireless network with the bluetooth low energy (BLE) to transmit the sensing data in real time to the gateway, and a cloud which accumulate and analyze data. To assess the system accuracy, 3 persons manually counted the outgoing and incoming honey bees using the video record of 360-minute length. The difference between automatic and manual measurements for outgoing and incoming scores were 3.98% and 4.43% respectively. These differences are relatively lower than previous analogues, which inspires a vision that the tested system is a good candidate to use in precise apicultural industry, scientific research and education.

• 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.