• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.257-264
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• 2019

Objective: Dairy cattle nutrient requirement systems acknowledge amino acid (AAs) requirements in aggregate as metabolizable protein (MP) and assume fixed efficiencies of MP used for milk protein. Regulation of mammary protein synthesis may be associated with AA input and milk protein output. The aim of this study was to evaluate the effect of nanoemulsified methionine and cysteine on the in-vitro expression of milk protein (casein) in bovine mammary epithelial cells (MAC-T cells). Methods: Methionine and cysteine were nonionized using Lipoid S 75 by high-speed homogenizer. The nanoemulsified AA particle size and polydispersity index were determined by dynamic light scattering correlation spectroscopy using a high-performance particle sizer instrument. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay was performed to determine the cytotoxicity effect of AAs with and without nanoionization at various concentrations (100 to $500{\mu}g/mL$) in mammary epithelial cells. MAC-T cells were subjected to 100% of free AA and nanoemulsified AA concentration in Dulbecco's modified Eagle medium/nutrient mixture F-12 (DMEM/F12) for the analysis of milk protein (casein) expression by the quantitative reverse transcription polymerase chain reaction method. Results: The AA-treated cells showed that cell viability tended to decrease (80%) in proportion to the concentration before nanogenesis, but cell viability increased as much as 90% after nanogenesis. The analysis of the expression of genetic markers related to milk protein indicated that; ${\alpha}_{s2}$-casein increased 2-fold, ${\kappa}$-casein increased 5-fold, and the amount of unchanged ${\beta}$-casein expression was nearly doubled in the nanoemulsified methionine-treated group when compared with the free-nanoemulsified methionine-supplemented group. On the contrary, the non-emulsified cysteine-administered group showed higher expression of genetic markers related to milk protein ${\alpha}_{s2}$-casein, ${\kappa}$-casein, and ${\beta}$-casein, but all the genetic markers related to milk protein decreased significantly after nanoemulsification. Conclusion: Detailed knowledge of factors, such nanogenesis of methionine, associated with increasing cysteine and decreasing production of genetic markers related to milk protein (casein) will help guide future recommendations to producers for maximizing milk yield with a high level of milk protein casein.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.473-479
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• 2019

PET-CT improves performance and reduces the time by combining PET and CT of spatial resolution, and uses CT scan for attenuation correction. This study analyzed PET image evaluation. The condition of the tube voltage and current of CT will be changed using. Uniformity phantom and resolution phantom were injected with 37 MBq $^{18}F$ (fluorine ; 511 keV, half life - 109.7 min), respectively. PET-CT (Biograph, siemens, US) was used to perform emission scan (30 min) and penetration scan. And then the collected image data were reconstructed in OSEM-3D. The same ROI was set on the image data with a analyzer (Vinci 2.54, Germany) and profile was used to analyze and compare spatial resolution and image quality through FWHM and SI. Analyzing profile with pre-defined ROI in each phantom, PET image was not influenced by the change of tube voltage or exposure dose. However, CT image was influenced by tube voltage, but not by exposure dose. When tube voltage was fixed and exposure dose changed, exposure dose changed too, increasing dose value. When exposure dose was fixed at 150 mA and tube voltage was varied, the result was 10.56, 24.6 and 35.61 mGy in each variables (in resolution phantom). In this study, attenuation image showed no significant difference when exposure dose was changed. However, when exposure dose increased, the amount of dose that patient absorbed increased too, which indicates that CT exposure dose should be decreased to minimum to lower the exposure dose that patient absorbs. Therefore future study needs to discuss the conditions that could minimize exposure dose that gets absorbed by patient during PET-CT scan.

• Clean Technology
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• v.25 no.3
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• pp.263-272
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• 2019

Air pollutants have a high impact on everyday life as well as on human health; therefore, new technologies such as low-emission vehicles and add-on systems for air pollutant reduction are needed for our society. However, the environmental benefits and costs of those technologies are not taken into account in existing economic feasibility assessments, which is a barrier that needs to be overcome for green technology to achieve wide dissemination and fast penetration in the market. Thus, this study develops a methodology to assess the economic feasibility of an air pollutant reduction technology by taking into account the social costs from air pollutants and carries out a case study to validate the methodology. Because the social unit costs for air pollutants have not been evaluated yet in South Korea, the methodology uses the social unit costs evaluated for the European Union that are then converted to those for South Korea based on the measuring criteria for vehicle emission gases, parity purchasing price, foreign currency exchange rate, and customer price index. The social unit costs for South Korea are used to assess economic feasibility. A case study was performed to assess the economic feasibility of a dual fuel system using diesel and compressed natural gas by taking into account social costs from air pollutants as well as economic costs. This study could contribute to assessing the true economic feasibility of green technology, projects, and policy related with air pollutant reduction.

• Journal of Korean Society of Neurocognitive Rehabilitation
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• v.10 no.2
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• pp.45-52
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• 2018

The purpose of the present study was to determine correlations between the Berg Balance Scale (BBS), Montreal Cognitive Assessment-Korean (MoCA-K) and Modified Barthel Index (MBI) targeting stroke patients, and it seeks to analyze the influence among each factor to establish the fundamental research in evaluating the functional performance capability of stroke patients. The study was conducted between December 2017 and March 2018 and the target of the study was 34 stroke patients who are hospitalized and treated in Y rehabilitation hospital located in Goyang city. Following in criteria of how participants were selected. First, a person without the onset of 6months or more. Second, a person who can communicate and score over 20 points on MMSE-K. Third, a person without unilateral neglect. Fourth, a person without lower motor neuron lesion and orthopedic disease on the bilateral lower extremity. Fifth, a person without audiovisual problem and history of using drug or surgery that influence athletic function. sixth, patients who agreed on participating in the study. The evaluation was processed by measuring BBS, MoCA-K, and MBI with the occupational therapist and physical therapist. Also, one assistant was participated in measuring balanced ability for the safety reason. It was found that significantly correlates (p<.01) with BBS and MoCA-K (r=.459), BBS and MBI (r=.550), MoCA-K and MBI (r=.565). This study is meaningful that it provided the basis for the active use of BBS, MoCA-K and MBI as a clinical evaluation tool and its usefulness.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Journal of Physiology & Pathology in Korean Medicine
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• v.34 no.6
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• pp.348-354
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• 2020

Oryeong-san (ORS) is a traditional Korean herbal medicine widely used for renal associated diseases, composed of five medicine herbs; Atractylodes japonica Koidzumi, Cinnamomum cassia Presl, Polyporus umbellatus Fries, Poria cocos Wolf and Alisma orientale Juzepzuk. We studied to improve the convenience of intake and portability by developing modernized dosage forms, and examined the effect on anti-inflammation of ORS. In order to develop the tablet formulation of ORS (ORS-F), the tablets were evaluated on the basis of physical characteristics include diameter, thickness, weight variation, hardness, friability and disintegration. To analyze the marker components of ORS-F, eight index markers from five herbal medicines were chosen. And the method using high performance liquid chromatography (HPLC) with diode-array detector method was established for the simultaneous analysis. The biological activities were examined the effect of ORS-F on pro-inflammation mediated by LPS-stimulation. The production of nitric oxide (NO) and cytokines were determined by reacting cultured medium with griess reagent and enzyme-linked immunosorbent assay (ELISA). The expression of cyclooxygenase-2 (COX-2) and inducible NO synthase (iNOS) were investigated by Western blot and RT-PCR. The anti-oxidant activities of OJS-F increased markedly, in a dose-dependent manner. and, The total phenolic compound and flavonoids contents of OJS-F were 10.20±0.09 ㎍/㎎ and 12.86±0.86 ㎍/㎎. OJS-F which is LPS has diminished in the LPS-induced release of inflammatory mediators (NO, iNOS, COX2 and PGE2) and pro-inflammatory cytokines (TNF-α, IL-6 and IL-1β) from the RAW264.7 macrophages. Therefore, the developed formulation for tablet of ORS-F provide efficiency and usability, and indicated effect of anti-inflammation.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.1
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• pp.20-25
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• 2021

The cement clinker, the main raw material of cement, is manufactured using limestone as the main material. Depending on the quality of limestone, the use of subsidiary materials changes, and has a great influence on the production of cement clinkers. In this study, the effect of CaO content of limestone, a cement clinker material, on Raw Mill grinding and sintering of cement clinker was investigated. The grinding time of the union materials changed in the content of limestone CaO was measured to identify the grinding properties. The raw material combination was cleaned within a range of 1,350-1,500℃. The sintering performance of cement clinker by Burnability index calculation was identified. The lower the grade of limestone, the lower the grinding quality of the raw material combination. The lower the CaO content of limestone, the greater the variation in F-CaO for sintering temperature. The lower the class of limestone, the higher B. I. value was calculated, indicating the lower cement clinker sintering. In addition, the mineral analysis results of cement clinker showed that if the F-CaO value was low due to the increase in sintering temperature, the Belite content decreased and the Alite content increased. In the case of Alite, the ratio of R-type decreased and that of M-type increased as the content of limestone CaO increased.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.147-161
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• 2021

The purpose of this study was to investigate the psychological state and driving safety of drivers driving around the truck platoon driving. Using the driving simulator, the experimental environment was constructed with the situation of changing lanes to the platoon and driving within the platoon. We tried to qualitatively and quantitatively analyze the driver's psychological state and driving safety through simulation driving experiments. As a result, in the case of the older driver group, there were many cases where they judged themselves to be driving safely, even though they were driving dangerously in the actual lane change to the platoon or driving within the platoon. In particular, this group showed that the narrower the distance between vehicles, the greater the misrecognition. The results of this study are expected to be useful in deriving the optimum interval when the interval between platooning of trucks needs to be temporarily extended.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.543-552
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• 2022

When frost occurs, crops are directly damaged. When crops come into contact with low temperatures, tissues freeze, which hardens and destroys the cell membranes or chloroplasts, or dry cells to death. In July 2020, a sudden sub-zero weather and frost hit the Minas Gerais state of Brazil, the world's largest coffee producer, damaging about 30% of local coffee trees. As a result, coffee prices have risen significantly due to the damage, and farmers with severe damage can produce coffee only after three years for crops to recover, which is expected to cause long-term damage. In this paper, we tried to predict frost using frost generation data and weather observation data provided by the Korea Meteorological Administration to prevent severe frost. A model was constructed by reflecting weather factors such as wind speed, temperature, humidity, precipitation, and cloudiness. Using XGB(eXtreme Gradient Boosting), SVM(Support Vector Machine), Random Forest, and MLP(Multi Layer perceptron) models, various hyper parameters were applied as training data to select the best model for each model. Finally, the results were evaluated as accuracy(acc) and CSI(Critical Success Index) in test data. XGB was the best model compared to other models with 90.4% ac and 64.4% CSI, followed by SVM with 89.7% ac and 61.2% CSI. Random Forest and MLP showed similar performance with about 89% ac and about 60% CSI.