• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

• Korean Journal of Food Science and Technology
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• v.54 no.4
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• pp.414-421
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• 2022

The purpose of this study was to evaluate the quality characteristics and antioxidant activity of Jeung-pyun containing 0, 2.5, 5, 7.5, and 10% Rudbeckia laciniata L. powder. In this study, increase in the content of Rudbeckia laciniata L. powder led to an increase in pH, hardness, adhesiveness, chewiness, and gumminess while moisture of Jeung-pyun had decreased. Scanning electron microscopy analysis showed that the pores in Jeung-pyun merged leading to a decrease in the number of pores, while the pore size increased along with the increase in R. laciniata L. content. In the sensory evaluation tests, Jeung-pyun with 5% R. laciniata L. powder showed the best results. Moreover, the antioxidant activity of Jeung-pyun increased with the addition of R. laciniata L. powder. Based on these results, we conclude that R. laciniata L. has good quality characteristics and antioxidant activity, making it a good ingredient for Jeung-pyun.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.35 no.3
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• pp.218-223
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• 1990

This experiment was carried out to obtain basic information on the lodging characteristics and yield components of rice plants by new anti-lodging reagent 'KIM-112' (3%, Wp) application at 30 days before heading (DBH) to 5 DBH under two dosage levels (lg 2g, a. i. /10a) at the Yeongnam Crop Experiment Station in 1989. Culm length was shortened by 10-17% at 1g, a. i. /10a and by 16-23% at 2g of KIM -112 applications. The shortening effect of internode was different by dosages and application times: 2g treatment was greater effect than 19 and early application resulted in shortening of lower internode while this was upper internode at the late application. There were positive correlation between culm length and lodging index, the 1st and the 4th internode lengths had on important effect to lodging index. Thickness of culm wall, culm diameter and weight of basal part of culm were not affected by KIM-112 application. However anti-lodging characters improved by increasing the breaking weight and by decreasing the moment. Lodging index was related to breaking weight, moment and weight of panicle. Heading date by KIM-112 application was delayed one to four days and number of grains per panicle was decreased by shortened panicle length as compared with untreated control, but yield capacity was high a little because of improvement ripening ratio by no lodging.

• Journal of Life Science
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• v.33 no.8
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• pp.612-622
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• 2023

T-cell deficiency may occur in various clinical conditions including congenital defects, cell/organ transplantation, HIV infection and aging. In this regard, the development of artificial thymus has recently been attracting much attention. To achieve this aim, the development of techniques for 3D culture of thymic stromal cells is necessary because thymocytes grown only in a 3D thymic microenvironment can be differentiated fully to become mature, immunocompetent T cells; the same cannot be achieved for thymocytes grown in 2D. This study aimed to develop a nanotechnology-based 3D culture technique using polymeric scaffolds for thymic epithelial cells (TECs), the main component of thymic stromal cells. Scanning electron microscopic observation revealed that the pores of both PCL and PCL/PLGA scaffolds were filled with TECs. Interestingly, TECs grown in 3D on polydopamine-coated scaffolds exhibited enhanced cell attachment and proliferation compared to those grown on non-coated scaffolds. In addition, the gene expression of thymopoietic factors was upregulated in TECs cultured in 3D on polydopamine-coated scaffolds compared to those cultured in 2D. Taken together, the results of the present study demonstrate an efficient 3D culture model for TECs using polymeric scaffolds and provide new insights into a novel platform technology that can be applied to develop functional, biocompatible scaffolds for the 3D culture of thymocytes. This will eventually shed light on techniques for the in vitro development of T cells as well as the synthesis of artificial thymus.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1295-1303
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• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.87-98
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• 2022

In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

• Journal of the Korean Institute of Gas
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• v.27 no.1
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• pp.70-77
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• 2023

Air environment regulations have been strengthened due to increasing air pollutant emissions, the target of reducing emissions has increased and interest in gas measurement methods is also increasing. The sampling method is mainly used, but due to the spatial and temporal measurement limitations, the laser absorption spectroscopy which is a real-time and in-situ method is in the spotlight. In this study, we studied the wavelength modulation spectroscopy and described the calibration-free algorithm. The developed algorithm was modified to reflect 46 multi-absorption lines and was applied to light absorption signal analysis in visible and mid-infrared regions. In addition, the difference between the modulation parameters of laser was analyzed. As a result of reviewing the performance through O₂ and NO gas measurement experiments of various concentration conditions, the linearity was R²_O2=0.99999 and R²_NO=0.99967.

• Journal of Science Education
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• v.47 no.1
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• pp.24-36
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• 2023

In this study, we investigated chemistry teachers' the Stage of Concern (SoC) and the Level of Use (LoU) regarding competency assessment, which was emphasized along with the introduction of the 2015 revised curriculum. A questionnaire was developed based on the CBAM, and responses from 123 chemistry teachers were analyzed. The frequency was investigated for both SoC and LoU, and then the chi-square test was performed according to demographic variables. As a result of the SoC analysis, most of the teachers stayed in stage 3 (management concern, 26.8%) and stage 2 (personal concern, 19.5%). Additionally, among the demographic variables, there was a statistically significant difference in whether or not related education experience was present during the pre-service teacher period. In LoU analysis, Level III (mechanical) was the most frequent (26.8%), followed by Level I (orientation, 22.8%), Level II (preparation, 13.8%). In LoU, there was also a statistically significant difference in whether or not related education experience was present during the pre-service teacher period. The Spearman correlation coefficient between SoC and LoU in the competency assessment was .298 and there was a positive correlation. Based on the above results, educational implications for improving the concern and use of chemistry teachers for competency assessment were discussed.