• Food Science and Preservation
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• v.20 no.4
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• pp.467-474
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• 2013

This study demonstrated that the physiochemical properties and anti-oxidants activities of soy sauce with Oak mushroom (MK) and Astragalus memyranaceus (AK) improved in sensory acceptability and functionality during the ripening period of 30 days. The pH content was reduced and the total acidity content was increased with time. The total sugar of AK and MK was higher than traditional soy sauce (TK), and the changes in amino nitrogen of the AK increased dramatically from 0.50 to 0.98%. During the antioxidant experiments, the total polyphenol and flavonoid contents increased at a steady rate and studies showed that the DPPH free radical scavenging activities were higher in all treatments except in the traditional soy sauce. According to the results of this study, the antioxidant activities of the AK and MK were higher than the TK, while the preference for the AK and MK was higher than the TK. In conclusion, the AK could be used as a functional soy sauce.

• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.1-14
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• 2015

The purpose of this study is to examine North Korean defector students' characteristics in science learning through their voice in an "Angbuilgu" program, one of the Korean traditional science knowledge (TSK). We compared them with two other groups of contrasting backgrounds. The Angbuilgu program contains meaningful questions of time, everyday-life knowledge, Korean TSK, and western modern science (WMS). The teaching strategy consists of interactions between teacher and students, and scientific experiments. We applied this program to three groups and analyzed: North Korean defector students, elementary science gifted students, high school students in an advanced class. The characteristics of their science learning show the following: First, their interpretation of time as nature itself in their everyday life. They have rich experience and are familiar with time in nature. Second, they prefer science with complementary, caring, and humanist perspectives, which is in contrast to other groups with preference to the updated and practical science. Third, they lack scientific concepts but possess an abundance of everyday-life knowledge. Their linguistic expressions are ordinary rather than scientific. Fourth, they are familiar with narrative thinking more than scientific thinking. The results show that the science program using Korean TSK can help them accept new scientific knowledge as well as cultural pride, which plays a role in reconfirming their identity as one ethnicity. We expect that the contents of Korean TSK can be an intercultural field between North Korean defector students and our science curriculum.

• The Journal of Traditional Korean Medicine
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• v.15 no.1
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• pp.113-127
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• 2006

Objectives: This study was produced to examine the effects of moxibustion that had been played important role to traditional oriental medical treatment on disease. Recently, it was reported that moxi-tar which is generated in the process of moxibustion as burning combustibles decreased nitric oxide(NO) and inducible NO synthase (iNOS) generation in cellular experiments. Methods: Carrageenan-induced arthritis rat model was used to test the effect of moxi-tar as a chronic pain model. Diluted moxi-tar was single injected in several acupoints or combined with electroacupuncture (l ms, 2 Hz, and 2 mA) into contralateral ST36 acupoint for 30 min to assess the synergic effects. After the treatment, behavioral tests measuring stepping force were periodically conducted during the next 12 hours. Endogenous NO and iNOS, cyclooxygenase-2 (COX-2), and c-Fos protein expression in the spinal cord were examined on a rat model of carrageenan-induced arthritis. Results : After the induction of arthritis, rats subsequently showed a reduced stepping force of the affected limb for at least the next 4 days. The reduced stepping force of the limb was presumably due to a painful knee, since oral injection of indomethacin produced temporary improvement of weight bearing. Maxi-tar produced significant improvement of stepping force of the hindlimb affected by the arthritis lasting at least 9 hours. The magnitude of this improvement was equivalent to that obtained after an oral injection of 3 mg/kg of indomethacin and this improvement of stepping force was interpreted as an analgesic effect. Maxi-tar produced the improvement of stepping force of the affected hindlimb in a dose-dependent manner. Both NO production and iNOS, COX-2 protein expression increased by arthritis were suppressed by maxi-tar. Moxi-tar on combination with electroacupuncture (EA) produced more powerful and longer lasting improvement of stepping force of the hindlimb affected by the arthritis than either moxi-tar or EA did. Conclusion : The present study suggest that maxi-tar produces a potent analgesic effect on the chronic knee arthritis pain model in the rat and that moxi-tar-induced analgesia modulate endogenous NO through the suppression of iNOS/COX-2 protein expression.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.133-140
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• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.21-27
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• 2022

Traditional automobile or 2-wheeled robot have limitations on mobility because of their mechanical structure. As traditional automobile is being replaced by electric cars, robot technology is applied to the car industry. In robotics, many researchers worked on omnidirectional mobile robot and produced lots of noticeable results. However in many of the results, specialized wheels such as Mecanum wheels are required. That imposes restrictions on robot speed and outdoor driving. We proposed a 2-wheeled modular robot that has omnidirectional mobility without using specialized wheels. In this paper, we propose a 4-wheeled omnidirectional mobile robot that consists of those two modular robots. The proposed robot adopts electric brakes to combine wheel housings and the robot body or to separate wheel housings from the robot body. Two absolute-type encoders and four incremental encoders are used to control the position of the wheel housing and velocities of the wheels. The proposed robot has omnidirectional mobility and can move fast and outdoor with normal tire wheels. We implemented the proposed robot and the feasibility and stability of the robot is verified by two separate experiments.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.360-366
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• 2022

This paper presents a AI model structure for restoring Korean traditional palace photographs, which remain only black-and-white photographs, to color photographs using Pix2Pix, one of the adversarial generative neural network techniques. Pix2Pix consists of a combination of a synthetic image generator model and a discriminator model that determines whether a synthetic image is real or fake. This paper deals with an artificial intelligence model by adjusting a receptive field of the discriminator, and analyzes the results by considering the characteristics of the ancient palace photograph. The receptive field of Pix2Pix, which is used to restore black-and-white photographs, was commonly used in a fixed size, but a fixed size of receptive field is not suitable for a photograph which consisting with various change in an image. This paper observed the result of changing the size of the existing fixed a receptive field to identify the proper size of the discriminator that could reflect the characteristics of ancient palaces. In this experiment, the receptive field of the discriminator was adjusted based on the prepared ancient palace photos. This paper measure a loss of the model according to the change in a receptive field of the discriminator and check the results of restored photos using a well trained AI model from experiments.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1802-1813
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• 2023

Conjugate heat transfer between liquid metal and solid is a common phenomenon in a liquid-metal-cooled fast reactor's fuel assembly and heat exchanger, dramatically affecting the reactor's safety and economy. Therefore, comprehensively studying the sophisticated conjugate heat transfer in a liquid-metal-cooled fast reactor is profound. However, it has been evidenced that the traditional Simple Gradient Diffusion Hypothesis (SGDH), assuming a constant turbulent Prandtl number (Pr_t,, usually 0.85 - 1.0), is inappropriate in the Computational Fluid Dynamics (CFD) simulations of liquid metal. In recent decades, numerous studies have been performed on the four-equation model, which is expected to improve the precision of liquid metal's CFD simulations but has not been introduced into the conjugate heat transfer calculation between liquid metal and solid. Consequently, a four-equation model, consisting of the Abe k - ε turbulence model and the Manservisi k_𝜃 - ε_𝜃 heat transfer model, is applied to study the conjugate heat transfer concerning liquid metal in the present work. To verify the numerical validity of the four-equation model used in the conjugate heat transfer simulations, we reproduce Johnson's experiments of the liquid lead-bismuth-cooled turbulent pipe flow using the four-equation model and the traditional SGDH model. The simulation results obtained with different models are compared with the available experimental data, revealing that the relative errors of the local Nusselt number and mean heat transfer coefficient obtained with the four-equation model are considerably reduced compared with the SGDH model. Then, the thermal-hydraulic characteristics of liquid metal turbulent pipe flow obtained with the four-equation model are analyzed. Moreover, the impact of the turbulence model used in the four-equation model on overall simulation performance is investigated. At last, the effectiveness of the four-equation model in the CFD simulations of liquid sodium conjugate heat transfer is assessed. This paper mainly proves that it is feasible to use the four-equation model in the study of liquid metal conjugate heat transfer and provides a reference for the research of conjugate heat transfer in a liquid-metal-cooled fast reactor.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.3
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• pp.209-222
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• 2024

The Earth Pressure Balance (EPB) shield Tunnel Boring Machine (TBM) is widely used for underground tunnel construction for its advantages, such as eliminating the need for additional facilities compared to the slurry shield TBM, which requires Slurry Treatment Plant (STP). During EPB shield TBM excavation, a soil conditioning technique is employed to enhance the physical properties of the excavated soil by injecting additives, thus broadening the range of applicable ground conditions to EPB shield TBMs. This study explored the use of xanthan gum, a type of biopolymer, as an alternative to the commonly used polymer additive. Biopolymers, derived from biological sources, are fully biodegradable. In contrast to traditional polymers such as polyacrylic acid, which contain environmentally harmful components, xanthan gum is gaining attention as an eco-friendly material due to its minimal toxicity and environmental impact. Test conditions with similar workability were established through slump tests, and the rheological characteristics were assessed using a laboratory pressurized vane shear test apparatus. The experiments demonstrated that, despite exhibiting similar workability, the peak strength in the flow curve decreased with increasing the content of xanthan gum. Consequently, a correlation between the xanthan gum content and peak strength was established. Replacing the traditional polymers with xanthan gum could enable stable EPB shield TBM operation by reducing equipment load, in addition to offering environmental benefits.

• Journal of the Korean Chemical Society
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• v.50 no.6
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• pp.506-514
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• 2006

purpose of this work was to study the applied effects of out-of-class Chemical Experience Learning (CEL) Programs on scientific process skills and science-related attitude for middle school students. The out-of-class CEL Programs which were developed to make the funny out-of-class chemistry and the exciting science class', included the nature-friendly chemical experiments suitable for natural environment and composed of real life-centered experiences. The out-of-class CEL programs were applied to natural environment through all-day improvement activity. The science club students in D middle school in Busan were selected as the objects of the study consisting of one experiment group and one control group. The out-of-class CEL programs were applied to the experiment group and traditional class method was applied to the control group. The change of scientific process skills and science-related attitudes between two groups were compared and analyzed. And students reaction on the out-of-class CEL programs was investigated. As a result, out-of-class nature-friendly chemical experiments were improved scientific process skills and science-related attitudes of middle school students. Also, more than 70% of students in the experimental group gave positive feedbacks to the out-of-class CEL programs and increased attention, interest, and degree of self-participation in science.