• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.802-811
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• 2023

Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.577-589
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• 2023

In Korea, the technical techniques for assessing visual impacts are standardized, but the methods for assessing the marine landscape itself are not standardized and need to be improved. In particular, in the landscape impact assessment of offshore wind power generation in Korea, it is necessary to recognize the landscape itself as a receptor and prepare a system that can evaluate the characteristics and sensitivity of the landscape. In this study, we propose an evaluation method for preparing a marine landscape quality assessment document that reflects the project characteristics of offshore wind power projects, and examine the possibility of utilization by applying it to actual project sites as an example. To evaluate the quality of marine scenery in offshore wind power projects, evaluation items of landscape characteristics, physical characteristics, and socio-cultural characteristics were evaluated based on the preliminary survey contents, and the quality of marine scenery was divided into five grades. Next, the evaluation criteria of the evaluation items were synthesized and the quality of the marine landscape was classified into preservation grade (grade 5), semi-preservation grade (grade 4), buffer grade (grade 3), semi-improvement grade (grade 2), and improvement grade (grade 1). In addition, the Sinan-Ui Offshore Wind Farm, an actual project site, was randomly selected to conduct the evaluation process and examine its utilization. This study aims to complement the existing method of visual impact assessment in offshore wind power projects and evaluate the quality of the marine landscape itself to effectively conserve marine landscape resources during offshore wind power projects. Rather than relying on mechanical and quantitative evaluation, this study is expected to be used as a basis for comprehensive understanding of the location and socio-cultural characteristics of the project site and for communication and cooperation with stakeholders.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.389-406
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• 2023

The research area, located in the northern coastal region of South Korea's West Sea, involves three bird habitats. Among these are two newly established habitats in Songdo International Business District, created by filling and developing tidal flats that were previously utilized as stopover sites for migratory birds. One of these areas showed decrease (Residual tidal flats, site.1) while the other showed increase (Artificial lake, site.2) in bird influx. The third habitat (Namdong reservoir, site.3) is a pre-existing stable habitat which has been maintained as a stable habitat. This study conducts an assessment of habitats based on avian population clusters and environmental surveys and proposes habitat management measures. A survey of bird populations and habitat environments was conducted for a total of 39 occasions from January to December 2022. The observed bird species totaled 14 families and 48 species with 20,760 individuals. Compared to the existing habitats, the newly established habitats showed relatively lower influx of bird species and individuals. During the habitat assessment, the newly established habitats were rated as I to II grade, while the existing habitat was rated as relatively high III grade on the grading assessment of the tidal flat. An analysis of habitat types revealed that the existing habitat, in which diverse strategies for habitat type diversity and mitigating anthropogenic interference were demonstrated, attracted a diverse range of bird species. Through this research, it was deduced that the diversity of habitat types plays a significant role in attracting various bird species. Upon evaluation of habitat types concerning the habitat characteristics of the bird species selected for habitat management, as habitat management measures, it is deemed that the creation of shielded green areas (referred to as 'buffer green') to minimize interference from the surroundings, the establishment of reed fields (site.1, 2) positively correlated with reservoirs, and the improvement of sandbanks (site.1) positively associated with tidal flats, the two relations which we drew from correlation analysis between occurrence species and habitat types, would contribute to the future restoration and maintenance of stable habitats. The results of this study can be applied not only to the study area but also to other development zones, such as coastal reclamation sites, which share similar geographical and environmental characteristics, including arrival sites for migratory birds.

• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.449-456
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• 2023

In this study, we developed Rapid Enrichment Broth for Vibrio parahaemolyticus (REB-V), a broth capable enriching V. parahaemolyticus from 10⁰ CFU/mL to 10⁶ CFU/mL within 6 hours, which greatly facilitates the rapid detection of V. parahaemolyticus. Using a modified Gompertz model and response surface methodology, we optimized supplement sources to rapidly enrich V. parahaemolyticus. The addition of 0.003 g/10 mL of D-(+)-mannose, 0.002 g/10 mL of L-valine, and 0.002 g/10 mL of magnesium sulfate to 2% (w/v) NaCl BPW was the most effective combination of V. parahaemolyticus enrichment. Optimal V. parahaemolyticus culture conditions using REB-V were at pH 7.84 and 37℃. To confirm REB-V culture efficiency compared to 2% (w/v) NaCl BPW, we assessed the amount of enrichment achieved in 7 hours in each medium and extracted DNA samples from each culture every hour. Real-time PCR was performed using the extracted DNA to verify the applicability of this REB-V culture method to molecular diagnosis. V. parahaemolyticus was enriched to 5.452±0.151 Log CFU/mL in 2% (w/v) NaCl BPW in 7 hours, while in REB-V, it reached 7.831±0.323 Log CFU/mL. This confirmed that REB-V enriched V. parahaemolyticus to more than 10⁶ CFU/mL within 6 hours. The enrichment rate of REB-V was faster than that of 2% (w/v) NaCl BPW, and the amount of enrichment within the same time was greater than that of 2% (w/v) NaCl BPW, indicating that REB-V exhibits excellent enrichment efficiency.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.106-113
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• 2023

We examined the heading responses of rice varieties over two years in Dandong, China to select the varieties that are adaptable to the bordering northwestern plains of North Korea. Dandong had slightly lower mean temperature than Sinuiju, North Korea but slightly higher than Supung, but it had almost the same day-length as the two regions in North Korea. In the two experimental years and two transplanting-date treatments, eight varieties (Jinbuol, Baegilmi, Joun, Jinok, Jopyeong, Jinbu, Sanhomi, and Odae) from South Korea and five varieties (Olbyeo2, Sonbong9, Onpo1, Gilju1, and Pyongdo5) from North Korea reached the heading stage not later than the latest heading dates of Dandong domestic varieties and the safe marginal heading dates of Dandong. We examined the basic vegetative phase (BVP), photoperiod-sensitivity (PS), and thermo-sensitivity (TS) of rice heading in a phytotron study to characterize the heading ecotypes of rice varieties adaptable to Dandong. For the rice varieties grown in Dandong experimental field, number of days to the heading stage was highly positively correlated with PS and, except middle and mid-late maturing three varieties, it was significantly positively correlated with BVP. Two-dimensional distribution plotting revealed that both 35 days or less BVP and 25 days or less PS were the characteristic heading ecotypes of the rice varieties adaptable to Dandong.

• The Korean Journal of Archival Studies
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• no.78
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• pp.153-195
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• 2023

RDBMS is a widely used database system worldwide, and the term dataset refers to the vast amount of data produced in administrative information systems using RDBMS. Unlike business systems that mainly produce administrative documents, administrative information systems generate records centered around the unique tasks of organizations. These records differ from traditional approval documents and metadata, making it challenging to seamlessly transfer them to standard record management systems. With the 2022 revision of the 'Public Records Act Enforcement Decree,' dataset was included in the types of records for which only management authority is transferred. The core aspect of this revision is the need to manage the lifecycle of records within administrative information systems. However, there has been little exploration into how to manage dataset within administrative information systems. As a result, this research aims to design a database for a record management module that needs to be integrated into administrative information systems to manage the lifecycle of records. By modifying and supplementing ISO 16175-1:2020, we are designing an "human resource management system" and identifying and evaluating personnel management dataset. Through this, we aim to provide a concrete example of record management within administrative information systems. It's worth noting that the prototype system designed in this research has limitations in terms of data volume compared to systems currently in use within organizations, and it has not yet been validated by record researchers and IT developers in the field. However, this endeavor has allowed us to understand the nature of dataset and how they should be managed within administrative information systems. It has also affirmed the need for a record management module's database within administrative information systems. In the future, once a complete record management module is developed and standards are established by the National Archives, it is expected to become a necessary module for organizations to manage dataset effectively.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.521-535
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• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.560-576
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• 2023

The purpose of this investigation is to: (1) to derive an improvement factor for inquiry-based simulated teaching-learning in pre-service teacher training programs, and pre-service teachers practice simulated teaching that reflect the improvement factor, (2) to analyze the difference in science intrinsic motivation according to science self-efficacy and inquiry-based simulated teaching-learning experience. To achieve these goals, we recruited five elementary and secondary teachers as experts to help us develop an improvement factor based on expert interviews. Subsequently, third-year pre-service teachers of a university of education participated in our analysis of differences in science intrinsic motivation, according to their level of science self-efficacy and experience with inquiry-based simulated teaching-learning. Our methodology involved applying the analytic hierarchy process to expert interviews to derive improvement factor for inquiry-based simulated teaching-learning, followed by a two-way ANOVA to identify significant differences in science intrinsic motivation between groups with varying levels of science self-efficacy. We also conducted post-analysis through MANOVA statements. The results of our study indicate that inquiry-based simulated teaching-learning can be improved through activities that foster digital literacy, ecological literacy, democratic citizenship, and scientific inquiry skills. Moreover, small group activities and student-centered teaching-learning approaches were found to be effective in developing core competencies and promoting science achievements. Specifically, pre-service teachers prepared a teaching-learning course plan and inquiry-based simulated teaching-learning in seventh-grade in the Earth and Space subject area. Pre-service teachers' science intrinsic motivation analyze significant differences in all levels of science self-efficacy before and after simulated teaching-learning and significant difference in the interaction effect between simulated teaching-learning and scientific self-efficacy. Particularly, group with low scientific self-efficacy, the difference in science intrinsic motivation according to simulated teaching-learning was most significant. Teachers' scientific self-efficacy and intrinsic motivation are needed to improve science achievement and affective domains of students in class. Therefore, this study contributes to suggest inquiry-based simulated teaching-learning reflecting school practices from the pre-service teacher curriculum.