• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.4
• /
• pp.427-435
• /
• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.4
• /
• pp.398-403
• /
• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.

• Korean Journal of Poultry Science
• /
• v.50 no.3
• /
• pp.143-159
• /
• 2023

The study aimed to evaluate the antioxidative effects of rosemary (Rosmarinus officinalis L.) and clove (Syzgyium aromaticum L.) essential oils on fried Korean native thigh meat, including their impact on processed characteristics and flavor compounds. Clove essential oil showed higher DPPH scavenging activity, FRAP and total phenol content compared to rosemary essential oil (P<0.05). The treatments with the addition of 0.005% and 0.01% rosemary (0.005RB and 0.01RB) and clove (0.005CB and 0.01CB) essential oils to the batter weight compared to control that did not include essential oils in batter. The addition of rosemary and clove essential oils to fried Korean native chicken thigh meat did not significant affect proximate composition, pH, TBARS, sensory characteristics. Except for 0.005CB, treatments adding essential oils decreased cooking loss (P<0.05) and 0.005CB showed significantly higher pick-up value than control. Addition of clove essential oil in fried Korean native chicken thigh meat resulted in higher levels of arachidonic acid compared to control (P<0.05). Volatile organic compounds (VOCs) analysis showed that addition of rosemary essential oil might mask its own VOCs, while clove essential oil addition reduced some pyrazine compounds. Although addition of rosemary and clove essential oil did not have significant sensory characteristics on fried Korean native chicken thigh meat, instrumental analysis revealed changes in the compounds that influenced flavor. Further studies are required to evaluate the stability of flavor and sensory characteristics of fried Korean native chicken thigh meat with added essential oils during storage.

• Journal of Nutrition and Health
• /
• v.56 no.6
• /
• pp.730-741
• /
• 2023

Purpose: The 2020 Dietary Reference Intakes for Koreans (KDRIs) serves as a foundation for daily nutrient and energy recommendations aiming to enhance public health and prevent chronic diseases. They act as guidelines for maintaining proper nutrition and overall health. Using KDRIs is crucial for promoting healthier lifestyles and making informed dietary choices. Thus, this study explores the influence of a nutrition education program, based on the 2020 KDRIs, on the nutrition knowledge and dietary habits of undergraduates in Gyeongsangnam-do and Gyeonggi-do. Methods: The nutrition education program, designed with diverse instructional materials, was executed across a wide range of universities. The education group (n = 75) engaged in the program for a 6-week instructional period, while the control group (n = 53) underwent the survey without participating in the education program. Nutrition Quotient (NQ) and knowledge assessments were administered to both groups immediately before and after the instructional period. Results: Within the education group, the nutrition education program positively impacted responses to NQ practice items, including knowledge of nutrition, daily intake, and portion sizes (p < 0.05). In contrast, there were no significant differences between the before and after responses of the control group for most survey items. Post-program evaluations showed significantly higher self-assessment scores and increased satisfaction levels (p < 0.05), with the satisfaction rate for the education program using the 2020 KDRIs reaching 99.2%. Conclusion: This study has demonstrated the positive impact of an effective nutrition education program. However, there is a need for the continuous development and implementation of nutrition education programs to sustain these outcomes and further enhance the nutritional education experience.

• Journal of Service Research and Studies
• /
• v.13 no.4
• /
• pp.97-112
• /
• 2023

Background: In modern society, the importance of Public Design has become increasingly significant in contributing to the enhancement of urban functionality and the quality of life of citizens. Smart Public Facilities have played a pivotal role in enriching user experience by improving accessibility, convenience, and safety, and in elevating the value of the city. This research recognizes the importance of Public Facilities and explores the potential of Smart Public Facilities in solving urban challenges and progressing towards sustainable and Inclusive cities. Method: The literature review comprehensively examines existing theories and research results on Smart Public Facilities. The case study analyzes actual examples of Smart Public Facilities implemented in cities both domestically and internationally, drawing out effects, user satisfaction, and areas for improvement. Through analysis and discussion, the results of the case studies are evaluated, discussing the potential development of Smart Public Facilities. Results: Smart Public Facilities have been found to bring positive changes in various aspects such as urban management, energy efficiency, safety, and information accessibility. In terms of urban management, they play a crucial role in optimization, social Inclusiveness, environmental protection, fostering citizen participation, and promoting technological innovation. These changes create a new form of urban space, combining physical space and digital technology, enhancing the quality of life in the city. Conclusion: This research explores the implications, current status, and functions of Smart Public Facilities in service and design aspects, and their impact on the urban environment and the lives of citizens. In conclusion, Smart Public Facilities have brought about positive changes in the optimization of urban management, enhancement of energy efficiency, increased information accessibility, User-Centric design, increased interaction, and social Inclusiveness. Technological innovation and the integration of Public Facilities have made cities more efficient and proactive, enabling data-based decision-making and optimized service delivery. Such developments enable the creation of new urban environments through the combination of physical space and digital technology. The advancement of Smart Public Facilities indicates the direction of urban development, where future cities can become more intelligent, proactive, and User-Centric. Therefore, they will play a central role in Public Design and greatly contribute to improving the urban environment and the quality of life of citizens.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.7
• /
• pp.915-929
• /
• 2023

Improvements in people's quality of life, diversification of leisure activities, and changes in population structure have led to an increase in the demand for tourism and an expansion of the diversification of tourism activities. In particular, for coastal cities where land and marine tourism elements coexist, various factors influence their tourism demands. Tourism requires the construction of infrastructure and content development according to the demand at the tourist destination. This study aims to improve the prediction accuracy and explore influencing factors through time series analysis of tourism scale using agent-based data. Basic local governments in the Busan area were examined, and the data used were the number of tourists and the amount of tourism consumption on a monthly basis. The univariate time series analysis, which is a deterministic model, was used along with the SARIMAX analysis to identify the influencing factor. The tourism consumption propensity, focusing on the consumption amount according to business types and the amount of mentions on SNS, was set as the influencing factor. The difference in accuracy (RMSE standard) between the time series models that did and did not consider COVID-19 was found to be very wide, ranging from 1.8 times to 32.7 times by region. Additionally, considering the influencing factor, the tourism consumption business type and SNS trends were found to significantly impact the number of tourists and the amount of tourism consumption. Therefore, to predict future demand, external influences as well as the tourists' consumption tendencies and interests in terms of local tourism must be considered. This study aimed to predict future tourism demand in a coastal city such as Busan and identify factors affecting tourism scale, thereby contributing to policy decision-making to prepare tourism demand in consideration of government tourism policies and tourism trends.

• Journal of Nutrition and Health
• /
• v.56 no.6
• /
• pp.629-640
• /
• 2023

Purpose: Non-alcoholic fatty liver disease (NAFLD) is characterized by the accumulation of fat in the liver which is not a result of excessive alcohol consumption. Its global prevalence was estimated to be approximately 32% in the years 1994-2019. More than half of obese individuals and patients with diabetes are reported to have NAFLD as a comorbidity. This study aimed to investigate the impact of the autumn olive (Elaeagnus umbellata Thunb.) berry on insulin resistance and steatosis in rats fed a high-fructose diet. Methods: Six-week-old Wistar rats were divided into four groups. The control group received a diet consisting of 65% corn starch, while the fructose and experimental groups were fed a diet comprising 65% fructose (FRU) and an FRU diet containing 0.5% (low-dose autumn olive berry group; LAO) or 1.0% (high-dose autumn olive berry group; HAO) ethanol extract of autumn olive berry, respectively, for 10 weeks. Results: The HAO group exhibited significantly lower blood glucose levels compared to the fructose-fed group. Both the LAO and HAO groups showed a substantial reduction in serum insulin levels and insulin resistance when compared to the fructose-fed group. The consumption of LAO and HAO significantly ameliorated dyslipidemia and reduced the levels of triglycerides in the liver compared to the fructose-fed group. Additionally, the consumption of HAO resulted in lower serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities compared to the fructose group. The hepatic expression of the sterol regulatory element-binding protein-1c (SREBP-1c) and carbohydrate-responsive element-binding protein (ChREBP) was significantly reduced in the LAO and HAO groups compared to the fructose group. Conclusion: Autumn olive berries improved steatosis by ameliorating insulin resistance and down-regulating the lipogenesis proteins in rats fed on high fructose diet.

• Journal of Nutrition and Health
• /
• v.56 no.6
• /
• pp.667-682
• /
• 2023

Purpose: This study aimed to investigate the changes in health behavior, mental health, and nutritional status of Korean adolescents before and after the coronavirus disease 2019 (COVID-19) pandemic outbreak. Methods: A total of 800 adolescents (12~18 years old) who participated in the 2019-2020 Korea National Health and Nutrition Examination Survey (KNHANES) were included as study subjects and divided into four groups (204 middle school boys, 172 middle school girls, 219 high school boys, and 205 high school girls). The 2019 and 2020 KNHANES data were classified into data collected before and after the COVID-19 outbreak, respectively. Results: After the COVID-19 pandemic outbreak, middle school boys showed an increased tendency toward becoming overweight and obese, with significantly increased levels of diastolic blood pressure and insulin. While there was no major change in the subjective health status among adolescents, the high school boys showed a significantly decreased physical activity after COVID-19 outbreak. Moreover, the proportion of middle school students feeling a little stressed significantly increased after the COVID-19 outbreak. The rate of skipping breakfast significantly increased in middle school girls, but the rate of having lunch with companions significantly increased among all adolescents after the COVID-19 outbreak. However, the intake of milk, vegetables, fruits, seaweeds, and pulses significantly decreased, although the intake of sugars, beverages, and seasonings significantly decreased as well, during this period. These changes may lead to an increased proportion of adolescents with insufficient intake of nutrients, including potassium, vitamin C, and riboflavin. Conclusion: These results highlight the impact of COVID-19 on comprehensive changes in physical and mental health status, lifestyle behavior, and nutritional status in adolescents, suggesting the need for targeted prevention and intervention for physical and mental well-being during the pandemic.

• The Korean Journal of Archival Studies
• /
• no.78
• /
• pp.197-249
• /
• 2023

This paper focus on the demand for broadcast and video archive contents by users outside broadcasters as the archive openness and sharing projects of terrestrial broadcasters have become more active in recent years. In the process of creating works using broadcasters' released video footage, the study examined the criteria by which video footage is selected and the methods and processes utilized for editing. To this end, the study analyzed the the case of the 5.18 footage video sharing project 〈May Story(Owol-Iyagi)〉 contest organized by KBS in 2022, in which KBS released its footage about the May 18 Democratic Uprising and invited external users to create new content using them. Analyzing the works that were selected as the winners of the contest, the research conducts in-depth interviews with the creators of each work. As a result, the following points are identified. Among the submitted works, many works deal with the direct or indirect experience of the May 18 Democratic Uprising and focus on the impact of this historical event on individuals and our current society. The study also examined the ways in which broadcasters' footage is used in secondary works. We found ways to use video as a means to share historical events, or to present video as evidence or metaphor. It is found that the need for broadcasters to provide a wider range of public video materials such as the May 18 Democratic Uprising, describing more metadata including copyright information before releasing selected footage, ensuring high-definition and high-fidelity videos that can be used for editing, and strengthening streaming or downloading functions for user friendliness. Through this, the study explores the future direction of broadcasters' video data openness and sharing business, and confirms that broadcasters' archival projects can be an alternative to fulfill public responsibilities such as strengthening social integration between regions, generations, and classes through moving images.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.695-713
• /
• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.