• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.4
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• pp.11-20
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• 2022

Currently, the operation rule of agricultural reservoirs in case of drought events follows the drought forecast warning standard of agricultural water supply. However, it is difficult to preemptively manage drought in individual reservoirs because drought forecasting standards are set according to average reservoir storage ratio such as 70%, 60%, 50%, and 40%. The equal standards based on average water level across the country could not reflect the actual drought situation in the region. In this study, we proposed the improvement of drought operation rule for agricultural reservoirs based on the percentile approach using past water level of each reservoir. The percentile approach is applied to monitor drought conditions and determine drought criteria in the U.S. Drought Monitoring (USDM). We applied the drought operation rule to reservoir storage rate in extreme 2017 spring drought year, the one of the most climatologically driest spring seasons over the 1961-2021 period of record. We counted frequency of each drought criteria which are existing and developed operation rules to compare drought operation rule determining the actual drought conditions during 2016-2017. As a result of comparing the current standard and the percentile standard with SPI6, the percentile standard showed severe-level when SPI6 showed severe drought condition, but the current standard fell short of the results. Results can be used to improve the drought operation criteria of drought events that better reflects the actual drought conditions in agricultural reservoirs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1826-1834
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• 2021

In this paper, we check the possibility of continuous tracking when photographing unknown space objects in a short period of time in an optical observation system on the ground. Simulated observation data were generated for target limited to low-orbit areas. The performance index of the prediction error was set in consideration of the property of targets. Kalman Filter was applied to predict the next location of the target. A constant velocity/acceleration dynamic model was applied to the two axes of the azimuth/elevation of the unknown space object respectively. As a result of performing the Monte Carlo simulation, the maximum error ratio of the maximum nonlinear section was less than 2%, which could be determined to ensure continuous tracking. The CA model had little change in the prediction error value for each case, making it more suitable for tracking unknown space objects. This analysis could provide a foundation for determining the orbit of unknown space objects using optical observation.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.185-185
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• 2023

Agricultural water demand is considered as the major sector of water withdrawal due to irrigation. The majority part of the global agricultural field depends on various irrigation techniques. Therefore, a timely and sufficient supply of water is the most important requirement for agriculture. Irrigation is implemented in different ways in various land surface models, it can be modeled empirically based on observed irrigation rates or by calculating water supply and demand. Certain models can also calculate the irrigation demand as per the soil water deficit. In these implementations, irrigation is typically applied uniformly over the irrigated land regardless of crop types or irrigation techniques. Whereas, the latest version of Community Land Model (CLM) in the Community Terrestrial Systems Model (CTSM) uses a global distribution map of irrigation with 64 crop functional types (CFTs) to simulate the irrigation water demand. It can estimate irrigation water withdrawal from different sources and the amount or the areas irrigated with different irrigation techniques. Hence, we set up the model for the simulation period of 16 years from 2000 to 2015 to analyze the global irrigation demand at a spatial resolution of 1.9° × 2.5°. The simulated irrigation water demand is evaluated with the available observation data from FAO AQUASTAT database at the country scale. With the evaluated model, this study aims to suggest new sustainable scenarios for the ratios of irrigation water withdrawal, high depending on the withdrawal sources e.g. surface water and groundwater. With such scenarios, the CFT maps are considered as the determining factor for selecting the areas where the crop pattern can be altered for a sustainable irrigation water management depending on the available withdrawal sources. Overall, our study demonstrate that the scenarios for the future sustainable water resources management in terms of irrigation water withdrawal from the both the surface water and groundwater sources may overcome the excessive stress on exploiting the groundwater in major river basins globally.

• Asia Marketing Journal
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• v.17 no.3
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• pp.105-127
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• 2015

This study compares experienced and inexperienced consumers' patterns in cue utilisation in product evaluations in the arts market. Borrowing the notion of high- and low-scope cues introduced by the cue-diagnosticity framework, we differentiate between the two most readily discernible extrinsic cues in the fine arts market - an art gallery's brand reputation (a high-scope cue) and certificates of authenticity (a low-scope cue). These two cues are different in nature; the former is more abstract, intangible, and rich in content, so is more difficult to interpret than the latter. Given the differences in experienced and inexperienced consumers' information processing styles, we hypothesise that experienced arts consumers form perceived credibility of and purchase intentions towards artworks based on high-scope cues, whereas inexperienced consumers do so based on low-scope cues. To test our hypothesis, we conducted a consumer intercept study at Korea's two most representative art fairs. The survey participants were categorised into either experienced or inexperienced consumers based on their prior purchase experience, and their responses to a set of attribute combinations about two artworks created by the same artist were collected. The results indicate that experienced participants show higher purchase intentions when an art gallery's reputation is very high, whereas inexperienced participants show higher purchase intentions when artworks are accompanied by certificates of authenticity. This congruency effect between prior experience and cue type is mediated by the perceived credibility of the artworks. The findings suggest a correspondence between a consumer's prior experience and the types of extrinsic cues that are important in product evaluations. To the best of our knowledge, this study is the first attempt ever to investigate the role of prior experience in determining when to use high- or low-scope cues. It also provides a useful frame of reference to advise marketers on the effective sales approach based on a client's prior purchase experience.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• Nutrition Research and Practice
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• v.16 no.sup1
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• pp.57-69
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• 2022

BACKGROUND/OBJECTIVES: Vitamin D is produced in the skin during sun exposure and is also ingested from foods. The role of vitamin D needs to be considered in the prevention and management of various diseases. Moreover, since the majority of Koreans spend their days indoors, becoming susceptible to the risk of vitamin D deficiency. The current study aims to prepare a basis for determining dietary reference intake of vitamin D in Korea, by reviewing the evidence against various diseases and risks. MATERIALS/METHODS: Literature published in Korea and other countries between 2014 and 2018 was prioritized based on their study design and other criteria, and evaluated using the RoB 2.0 assessment form and United States Department of Agriculture Nutrition Evidence Library Conclusion Statement Evaluation Criteria. RESULTS: Of the 1,709 studies, 128 studies were included in the final systematic analysis after screening. To set the dietary reference intakes of vitamin D based on the selected articles, blood 25(OH)D levels and indicators of bone health were used collectively. Blood vitamin D levels and ultraviolet (UV) exposure time derived from the Korean National Health and Nutrition Examination Survey were analyzed to establish the dietary reference intakes of vitamin D for each stage of the life cycle. The adequate intake levels of vitamin D, according to age and gender, were determined to be in the range of 5-15 ㎍/day, and the tolerable upper intake level was established at 25-100 ㎍/day. CONCLUSIONS: The most important variable for vitamin D nutrition is lifestyle. A balanced diet comprising foods with high contents of vitamin D is important, as is vitamin D synthesis after UV exposure. The adequate intake level of vitamin D mentioned in the 2015 Dietary Reference Intakes for Korean (KDRI) remained unchanged in the 2020 KDRI for the management of vitamin D nutrition in Koreans.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.186-197
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• 2023

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.417-425
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• 2023

The glomerular filtration rate (GFR) has been the subject of much research as a key indicator for diagnosing, treating, and monitoring kidney function. The gamma camera method (Gates method) is simple and allows simultaneous acquisition of GFR and renal scintigraphy for each kidney, however its accuracy is inferior. This study aimed to investigate changes in GFR depending on how region of interest (ROI) are set up, which is one of many factors influencing accuracy. GFR was calculated by setting the ROI for each phase of the image acquisition time (Gates-1: 0~1 minutes, Gates-2: 1~3 minutes, Gates-3: 3~27 minutes), and statistical significance was verified based on probability value 0.05 through ANOVA analysis. While there was no statistically significant difference among results from Gates-1, 2, 3 (p=0.481>0.05), overall results from the Gates method tended to overestimate compared to those from the multiple blood sampling-dual exponential (MBSDE) method. When comparing averages between phases, results from Gates-2 were most similar to those from the MBSDE method. Moreover, paired t-test p-values between MBSDE method and phases were as follows Gates-1: 0.021 (p<0.05), Gates-2: 0.280 (p>0.05), and Gates-3: 0.164 (p>0.05) indicating that only Gates-1 had statistically significant differences compared with MBSDE method. Thus, setting ROI around 2~3 minutes is calculated can aid in accurately determining GFR when Gates Method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.1
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• pp.149-168
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• 2024

This study aims to propose methods for determining the minimum book purchase cost budget in university libraries in accordance with the "University Library Promotion Act" and efficiently allocating and executing the secured book purchase cost budget to each department. To achieve this, the current status of university libraries and legal standards were examined and strategies for securing the minimum book purchase cost budget in accordance with legal standards were suggested, and a method for efficiently distributing the secured budget to departments was proposed. First, we determined the material acquisition budget for university libraries by applying the average price of domestically published books to the standards set forth in the University Library Promotion Act. The allocated budget was distributed with 80% assigned to departments and 20% budget for librarians. The department's allocated budget of 80% was then recalculated to 100% and distributed by applying three criteria: book prices by topic, student enrollment, and utilization rates.