• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.1
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• pp.135-151
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• 2015

DMZ is considered as an ecologically sensitive landscape and one of the highest biodiversity regions in the Republic of Korea. There have been, albeit the significant value, increased interests in developing this region for a variety of purposes including tourism and commemorative events. As this region has been already facing a range of problems derived from previous development, natural disaster and invasive species, the necessity for active management of ecological health within this region has been increased, which weighs the importance of executing ecological restoration. The objective of this study was to develop evaluation indices as an effective management means of properly evaluating ecological restoration and sustainably maintaining the restored conditions on a long-term scale. Through literature review existing evaluation indices related to restoration were collected, and then the most suitable indices were selected based upon two interviews and one questionnaire survey targeting experts in the relevant field to ecological restoration. They were categorized by two major division and their subclasses (Ecological base - vegetation structure & composition, habitat characteristics, soil environment; landscape ecology - connectivity, landscape patch, boundary & surrounding) and 40 indices. These indices were considered helpful to comprehensively evaluate ecological restoration on degraded environments within ecologically sensitive areas, and sustainably manage target areas by employing a long-term monitoring approach. As this result played a meaningful role in providing the fundamentals of evaluating ecological restoration, it should develop a suitable evaluation system through further research.

• Journal of Forest and Environmental Science
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• v.27 no.3
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• pp.205-210
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• 2011

This study aims to assess MEE(management effectiveness evaluations) on PAs(protected areas) for forest genetic resources which play an important role in biodiversity conservation, and then to suggest better ways to manage PAs for forest genetic resources. This study applies same indicators of the MEE on PAs as the ones described in the prior study(Ryu et al. 2011). The indicators applied are composed of five elements, thirty-two indicators which all would be grouped into one element by each traits. Overall indicators belonging to the element of output and outcome are comparatively low. Especially the ones related to the change of biodiversity, degree of ecosystem health, variation of civil complaint and visitor satisfaction are ranked mostly low. The element of input shows the low rank on the number of staff and budget. The score of indicators related to the identification of the threats of PAs and local communities' supports turn out to be low in the element of Context. The element of process, however, has scored low on Staff management, Education/Awareness programs and Governance, while the law enforcement, management regulation and capacity to prevent forest disasters have made relatively high score. Meanwhile, all indicators in the element of planning have scored relatively high as compared to the indicators belonged to other elements. This study suggests to strengthen a few constructive proposals, such as facilitating efficient management framework for PAs, developing local community cooperation program, establishing survey, research and monitoring system, and registering PAs to the WDPA(World Database on Protected Areas) according to the IUCN categories.

• Journal of Forest and Environmental Science
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• v.37 no.4
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• pp.280-291
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• 2021

The study examined the influence of climate and soil dynamics on vegetation health across the ecological zones in Rivers State, Nigeria. MODIS imagery was used to assess the vegetation health through NDVI and point grid pattern of meteorological data for total precipitation (TP), air temperature (AT), soil moisture (SM) and soil temperature (ST) of 2000, 2003, 2006, 2009, 2012 and 2015 were used for the study. Descriptive and inferential statistics were used for data analysis. Findings showed that NDVI ranged between 0.420 and 0.612 in the freshwater swamp (FWS) while between 0.465 and 0.611 in the rainforest and the NDVI in the mangrove was generally low. The highest mean AT was experienced in the mangrove ecological zone and the least was experienced in the rainforest. The mean SM was generally highest in the rainforest with highest value in 2000 (774.44 m³/m³). The ST was highest in the mangrove and the least was experienced in the rainforest while the TP was highest in the mangrove. NDVI correlated significantly with SM (r=0.720; p<0.05) and ST (r= -0.493; p<0.05). NDVI, SM, TP and ST significantly varied among the ecological zones. Regression analysis showed that vegetation health was significantly related to the combination of soil temperature and soil moisture (R²=0.641; p=0.000). Thus, monitoring the factors that affect vegetation health in a changing climate and soil environments is highly required.

• Steel and Composite Structures
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• v.46 no.6
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• pp.731-744
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• 2023

Vehicle load information is an important role in operating and ensuring the structural health of cable-stayed bridges. In this regard, an efficient and economic method is proposed for vehicle load detection based on the observed cable tension and vehicle position using a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), a robust program for modeling and considering both geometric and material nonlinearities of bridge structures subjected to vehicle load with low computational costs. With the superiority of GNN, the proposed model is demonstrated to precisely capture complex nonlinear correlations between the input features and vehicle load in the output. Four popular machine learning methods including artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machines (SVM) are refereed in a comparison. A case study of a cable-stayed bridge with the typical truck is considered to evaluate the model's performance. The results demonstrate that the GNN-based model provides high accuracy and efficiency in prediction with satisfactory correlation coefficients, efficient determination values, and very small errors; and is a novel approach for vehicle load detection with the input data of the existing monitoring system.

• Parasites, Hosts and Diseases
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• v.57 no.6
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• pp.691-698
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• 2019

The seasonal abundance of hard ticks that transmit severe fever with thrombocytopenia syndrome virus was monitored with a collection trap method every April to November during 2015-2018 and with a flagging method every July and August during 2015-2018 in Ganghwa-do (island) of Incheon Metropolitan City, Republic of Korea. This monitoring was performed in a copse, a short grass field, coniferous forest and broad-leaved forest. A total of 17,457 ticks (8,277 larvae, 4,137 nymphs, 3,389 females, and 1,654 males) of the ixodid ticks comprising 3 species (Haemaphysalis longicornis, H. flava, and Ixodes nipponensis) were collected with collection traps. Of the identified ticks, H. longicornis was the most frequently collected ticks (except larval ticks) (94.26%, 8,653/9,180 ticks (nymphs and adults)), followed by H. flava (5.71%, 524/9,180) and Ix. nipponensis (less than 0.04%, 3/9,180). The ticks collected with collecting traps were pooled and assayed for the presence of SFTS virus with negative results. In addition, for monitoring the prevalence of hard ticks, a total of 7,461 ticks (5,529 larvae, 1,272 nymphs, 469 females, and 191 males) of the ixodid ticks comprising 3 species (H. longicornis, H. flava, and Ix. nipponensis) were collected with flagging method. H. longicornis was the highest collected ticks (except larval ticks) (99.53%, 1,908/1,917 ticks (nymphs and adults)), followed by H. flava (1.15%, 22/1,917).

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.117-128
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• 2023

Tree dieback in Geumgang pine forest has occurred in Uljin and Bonghwa since the 2010s. In order to identify status of tree dieback and prevent further damages, a monitoring project for tree dieback in Geumgang pine forest had been launched by Southern regional office of forest service in 2020. This study was conducted to understand the characteristics of tree dieback occurrence and assess the high risk areas using the occurrence data in the project. Pine tree dieback occurred frequently in areas with mountain ridges in high elevation, dry south-facing slopes, mature stands, and high temperature rise in winter. Furthermore, the result of risk assessment showed that 6.2 percent(5,294ha) of Geumgang pine forest(85,000 ha) in total study area are at high risk of tree dieback. As the pine trees in the high risk area are prone to experience the dieback due to temperature and drought-related extreme weather events, regular forest management activities are needed to reduce the drought stress of pine trees. Forest health management for the pine forest with high protection priority can be also useful strategy to counter the risk of decline. This results can be used as the basic information for the adaptive forest management to climate change.

• Safety and Health at Work
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• v.10 no.4
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.1
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• pp.105-119
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• 2011

In order to develop the indicators which evaluate the management effectiveness for the protected forest areas in Korea, candidate indicators were listed based on literature and experts interviews, then questionnaire survey on the experts were conducted. 5 elements of context, planning, input, process, output and outcome and 32 indicators were selected. Context element includes 6 indicators of 1) documentation and assessment of values; 2) documentation and assessment of threats, 3) influence of government policy, 4) related regulations, 5) community cooperation and 6) the structure of management organization. 6 indicators of Planning element were 1) the management objective, 2) protected area design, 3) protected area size and number, 4) representation, 5) standards and categories and 6) management planning. Input element of 3 indicators were 1) management staff, 2) funding, 3) establishment and application of information. Process element were consisted of 1) governance, 2) management guidelines, 3) human resource management, 4) law enforcement, 5) eco-management, 6) disaster management, 7) education program and 8) research and monitoring. The element of outputs and outcomes were 1) accomplishment of plan, 2) accomplishment of program, 3) private land management, 4) threats change, 5) biodiversity change, 6) ecosystem health and vitality, 7) impact on community, 8) international management level and 9) visitors' satisfaction and variation in civil compliant. It is recommended to have further research on evaluation methods development by applying those above developed indicators for the protected forest areas to ensure the practicality of the indicators.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.109-123
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• 2020

The purpose of this study is to provide basic data for the establishment of future countermeasures by diagnosing the growth status and actual condition of undesignated old trees distributed in Hyeongok-myeon, Gyeongju, Gyeongsangbuk-do. The number of old trees surveyed was 2 weeks in Gajeong-ri, 2 weeks in Haguri, 3 weeks in Nae-Tae-ri, 1 week in Nawon-ri, 6 weeks in Oryu-ri, 3 weeks in Sangguri, and 2 weeks in Sohyeon-ri, The trees species composition was 6 trees Celtis sinensis Pers., 1 Diospyros lotus L. trees, 4 trees Salix chaenomeloides Kimura trees, 2 Styphnolobium japonicum L. trees, and 7 Zelkova serrata (Thunb.) Makino trees. Growth status is 7.1~22.0m in height, 14.6~25.1m in long axis, 10.2~19.2m in short axis, root diameter is 76.0~236.4cm, diamter at breast height is 67.0~220.0cm, soil acidity is pH4.9~7.0, soil The hardness was measured to be 4.0-27.0mm. The result grade of the scoring data of health information is represented by monitoring generally, monitoring critically, and absolute monitoring, and it was confirmed that out of the 20 trees population in Hyeongok-myeon, the general monitoring grade was 7 weeks, the major monitoring grade was 13 weeks, and there was no absolute monitoring grade. Accordingly, the number of old trees of the general surveillance level was maintained at the current level, and ecological surgical operations were introduced for the major surveillance level, but the case of village forests should be different, and sequential treatments were the old tree urgently needed. The level and bark of the target tree, the state of the crown, the root exposure, the presence of pests and pests, the vitality and the ground condition, the degree of pollution are normal, poor, or very poor, operation and protection management, soil improvement, removal of cover, and disinfection were urgently needed for the old trees with the surveyed data. In order to compensate for these matters, continuous monitoring and management measures for the old number should be sought.

• The Journal of Korean Academic Society of Nursing Education
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• v.24 no.2
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• pp.137-148
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• 2018

Purpose: The purpose of this study was to explore the monitoring experience of nursing students and to suggest considerations when developing mentoring programs. Methods: This qualitative study was conducted by online surveys and individual interviews with 7 nursing students who participated in the health promotion program as mentors. Data were analyzed using qualitative content analysis to identify motives for participating in mentoring and to explore their changes through mentoring. Results: The results were as follows: Motives for participating were 'inquisitiveness about children', 'interest in mentoring activities' and 'curiosity about research'. Recognition of mentor roles were 'actively involved guide', 'exemplary role model' and 'empathetic emotional supporter'. Changes through mentoring experiences were revealed by 'understanding the characteristics of children', 'improvement of interaction ability with children', 'understanding self and changes' and 'recognition of excellence in forest activities'. Conclusion: Nursing students had opportunities to learn the characteristics of general children and to understand themselves through natural interaction. Participation in mentoring has the potential to be a creative educational method of field learning as a form of service learning.