Giyeol Lee;Nahyeon An;Jongkoo Lim;Insu Han;Hyungtae Cho;Junghwan Kim
Korean Chemical Engineering Research
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v.61
no.2
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pp.217-225
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2023
2,3-Butanediol (2,3-BDO), which is used in various fields such as cosmetics and fertilizers, is a high value-added substance and the demand for it is gradually increasing. 2,3-BDO produced from the fermentation of microorganisms not only contains by-products of fermentation, but also varies greatly in feed composition depending on fermentation conditions, so it is difficult to efficiently operate the separation process to reach the target purity of the product. Therefore, in this study, through dynamic optimization of the bio-based 2,3-BDO distillation process, the optimal control route was explored to control the 2,3-BDO concentration of the bottom product to 99 wt% or more, when feed concentration changes. Steady and dynamic state process simulation, proportional integral (PI) controller design, and dynamic optimization were sequentially performed. As a result, the error between the 2,3-BDO concentration and the set point of the bottom product was reduced by 75.2%.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2022.05a
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pp.15-17
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2022
In the aftermath of the avian influenza that occurred from the second half of 2020 to the beginning of 2021, 17.8 million laying hens were slaughtered. Although the government invested more than 100 billion won for egg imports as a measure to stabilize prices, the effort was not that easy. The sharp volatility of egg prices negatively affected both consumers and poultry farmers, so measures were needed to stabilize egg prices. To this end, the egg prices were successfully predicted in this study by using the analysis algorithm of a machine learning regression. For price prediction, a total of 8 independent variables, including monthly broiler chicken production statistics for 2012-2021 of the Korean Poultry Association and the slaughter performance of the national statistics portal (kosis), have been selected to be used. The Root Mean Square Error (RMSE), which indicates the difference between the predicted price and the actual price, is at the level of 103 (won), which can be interpreted as explaining the egg prices relatively well predicted. Accurate prediction of egg prices lead to flexible adjustment of egg production weeks for laying hens, which can help decision-making about stocking of laying hens. This result is expected to help secure egg price stability.
This study presents the process and outcomes of developing mathematical-informatics linkage·convergence class materials, based on previous research findings that indicate a lack of such materials in high schools despite the increasing need for development of interdisciplinary linkage·convergence class materials In particular, this research provides insights into the discussions of six teachers who participated in the same professional learning community program, aiming to create materials that are suitable for linkage·convergence class materials and highly practical for classroom implementation. Following the material development process, a theme-based design model was applied to create the materials. In alignment with prior research and consensus among teacher learning community members, mathematics and informatics teachers developed instructional materials that can be utilized together during a 100-minute block lesson. The developed materials utilize societal issue contexts to establish links between the two subjects, enabling students to engage in problem-solving through mathematical modeling and coding. To increase the validity and practicality of the developed resources during their field application, CVR verification was conducted involving field teachers. Incorporating the results of the CVR verification, the finalized instructional materials were presented in the form of a teaching guide. Furthermore, we aimed to provide insights into the trial-and-error experiences and deliberations of the developers throughout the material development process, with the intention of offering valuable information that can serve as a foundation for conducting related research by field researchers. These research findings hold value as empirical evidence that can explore the applicability of teaching material development models in fields. The accumulation of such materials is expected to facilitate a cyclical relationship between theoretical teaching models and practical classroom applications.
RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.
Courier services users' experience of violating privacy affects psychology and behavior of protecting personal privacy. Depending on what privacy infringement experience (PIE) of courier services users, learning about perceived privacy infringement incidents is made, recognition is formed, affection is formed, and behavior is appeared. This paradigm of changing in privacy psychologies of courier services users has an important impact on predicting responses of privacy protective action (PPA). In this study, a theoretical research framework are developed to explain the privacy protective action (PPA) of courier services users by applying attitude theory. Based on this framework, the relationships among past privacy infringement experience (PIE), perceived privacy risk (PPR), privacy concerns (i.e., concerns in unlicensed secondary use (CIUSU), concerns in information error (CIE), concerns in improper access (CIA), and concern in information collection (CIC), and privacy protective action (PPA) are analyzed. In this study, the proposed research model was surveyed by people with experience in using courier services and was analyzed for finding relationships among research variables using structured an equation modeling software, SMART-PLS. The empirical results show the causal relationships among PIE, PPR, privacy concerns (CIUSU, CIE, CIA, and CIC), and PPA. The results of this study provide useful theoretical implications for privacy management research in courier services, and practical implications for the development of courier services business model.
I produced a secular variation model of geomagnetic field by using the magnetic component data from four geomagnetic observatories located in Northeast Asia during the years between 1997 and 2011. The Earth's magnetic field varies with time and location due to the dynamics of fluid outer core and the magnetic observatories on the surface measure in time series. To adequately represent the magnetic field or secular variations of the Earth, a spatio-temporal model is required. In making a global model, satellite observations as well as limited observatory data are necessary to cover the regions and time intervals. However, you need a considerable work and time to process a huge amount of the dataset with complicated signal separation procedures. When you update the model, the same amount of chores is demanded. Besides, the global model might be affected by the measurement errors of each observatory that are biased and the processing errors in satellite data so that the accuracy of the model would be degraded. In this study, as considered these problems, I introduced a localized method in modeling secular variation of the Earth's magnetic field over Northeast Asia region. Secular variation data from three Japanese observatories and one Chinese observatory that are all in the INTERMAGNET are implemented in the model valid between 1997 to 2011 with the interval of 6 months. With the resulting model, I compared with the global model called CHAOS-4, which includes the main, secular variation and secular acceleration models between 1997 to 2013 by using the three satellites' databases and INTERMAGNET observatory data. Also, the geomagnetic 'jerk' which is known as a sudden change in the time derivatives of the main field of the Earth, was discussed from the localized secular acceleration coefficients derived from spline models.
The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.
Journal of The Korean Association For Science Education
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v.38
no.5
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pp.705-720
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2018
The purpose of this study is to shed light on the meaning and value of interest (in Korean 'Jae-mi') in science education through literature analysis. Literature analyses were conducted on literature related to interest in various fields such as Korean language, psychology, philosophy, and education. Specifically, this study discussed the meaning of interest, the characteristics of the context of experiencing interest, the educational value of interest in science education, and the direction of science education to realize the value of interest. First, it was found that interest is an experience of emotional activation that can be felt through interaction with a specific object, and it is an emotional experience caused by the complex combination of various psychological factors, which is oriented sense, relationship, self, and object. Second, to understand the context of experience of interest, we conducted a topic modeling analysis with 1173 research articles related to interest. As a result of the analysis, it was confirmed that the context of interest is closely related with playfulness. And we addressed that this kind of playfulness is also found in science. Third, the educational values of interest in science education were discussed. In science education, fun is not only an instrumental value to induce science learning behavior, it is also one of the universal experiences that learners feel lively in science teaching-learning, and driving force of individual students' emotional development related to science. The students' active attitude to feel interest lead to creative thinking and action. Finally, we argued that the interest that should be aimed in science education should be active interest and experienced at trial and error, not passive interest induced by external stimuli. And science education culture should be encouraged to respect those who enjoy science. In particular, this study discussed the importance of each student's unique interest experience based on the philosophy of philosopher Deleuze (1976).
Kim, Yongwon;Byeon, Sangdon;Park, Jinseok;Woo, Soyoung;Kim, Seongjoon
Journal of Korea Water Resources Association
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v.54
no.10
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pp.819-833
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2021
This study is to evaluate applicability of linkage modeling using PHABSIM (Physical Habitat Simulation System) and SWAT (Soil and Water Assessment Tool) and to estimate ecological flow for target fishes of Andong downstream (4,565.7 km2). The SWAT was established considering 2 multi purpose dam (ADD, IHD) and 1 streamflow gauging station (GD). The SWAT was calibrated and validated with 9 years (2012 ~ 2020) data of 1 stream (GD) and 2 multi-purpose dam (ADD, IHD). For streamflow and dam inflows (GD, ADD and IHD), R2, NSE and RMSE were 0.52 ~ 0.74, 0.48 ~ 0.71, and 0.92 ~ 2.51 mm/day respectively. As a result of flow duration analysis for 9 years (2012 ~ 2020) using calibrated streamflow, the average Q185 and Q275 were 36.5 m3/sec (-1.4%) and 23.8 m3/sec (0%) respectively compared with the observed flow duration and were applied to flow boundary condition of PHABSIM. The target stream was selected as the 410 m section where GD is located, and stream cross-section and hydraulic factors were constructed based on Nakdong River Basic Plan Report and HEC-RAS. The dominant species of the target stream was Zacco platypus and the sub-dominant species was Puntungia herzi Herzenstein, and the HSI (Habitat Suitability Index) of target species was collected through references research. As the result of PHABSIM water level and velocity simulation, error of Q185 and Q275 were analyzed -0.12 m, +0.00 m and +0.06 m/s, +0.09 m/s respectively. The average WUA (Weighted Usable Area) and ecological flow of Zacco platypus and Puntungia herzi Herzenstein were evaluated 76,817.0 m2/1000m, 20.0 m3/sec and 46,628.6 m2/1000m, 9.0 m3/sec. This results indicated Zacco platypus is more adaptable to target stream than Puntungia herzi Herzenstein.
This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R2) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R2 was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R2 was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R2 of 0.69 and RMSE of 2.88%.
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