• Toxicological Research
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• v.34 no.1
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• pp.7-12
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• 2018

Laboratory animal models have been developed to investigate preventive or therapeutic effect of medicinal products, or occurrence or progression mechanism of atopic dermatitis (AD), a pruritic and persistent inflammatory skin disease. The murine model with immunologic phenomena resembling human AD was introduced, which demonstrated skewedness toward predominance of type-2 helper T cell reactivity and pathophysiological changes similar as human AD following 2,4-dinitrochlorobenzene (DNCB) sensitization and challenge. Molecular mechanism on the DNCB-mediated AD was further evaluated. Skin tissues were collected from mice treated with DNCB, and each tissue was equally divided into two sections; one for protein and the other for mRNA analysis. Expression of filaggrin, an important protein for keratinocyte integrity, was evaluated through SDS-PAGE. Level of mRNA expression for cytokines was determined through semi-quantitative reverse transcriptase polymerase chain reaction. Expression of filaggrin protein was significantly enhanced in the mice treated with DNCB compared with the vehicle (acetone : olive oil = 4 : 1 mixture) treatment group or the normal group without any treatment. Level of tumor necrosis factor-alpha and interleukin-18 mRNA expression, cytokines involved in activity of type-1 helper T ($T_H1$) cell, was significantly downregulated in the AD group compared with other control groups. These results suggest that suppression of $T_H1$ cell-mediated immune response could be reflected into the skin tissue of mice treated with DNCB for AD induction, and disturbance of keratinocyte integrity might evoke a compensatory mechanism.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1947-1954
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• 2012

The first frame is encoded in intra mode which generates a larger number of bits. In addition, the first frame is used for the inter mode encoding of the following frames. Thus the initial QP for the first frame affects the first frame as well as the following frames. Traditionally, the initial QP is determined among four constant values only depending on the bpp. In the case of low bit rate video coding, the initial QP value is fixed to 40 regardless of the output bandwidth. Although this initialization scheme is simple, yet it is not accurate enough. An accurate initial QP prediction scheme should not only depends on bpp but also on the complexity of the video sequence and the output bandwidth. In the proposed scheme, we determine the initial QP according to the ratio of the first frame to the total bits allocated to a GOP. To estimate the QP of the allocated bits, Rate-QP model is used. It is shown by experimental results that the new algorithm can predict the optimal initial QP more accurately and generate the PSNR performance better than that of the existing JVT algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1957-1964
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• 2010

In Video coding, the first frame is encoded in intra mode which generates a larger number of bits. In addition, the first frame is used for the inter mode encoding of the following frames. Thus the intial QP for the first frame of GOP affects the first frame as well as the following frames. Traditionally, the initial QP of a GOP is determined by the initial QP of the previous GOP and the average QP of the inter mode frames. In case of JM, the initial QP of a GOP is adjusted as the initial QP being less than the average QP of inter mode frames by two. However, this method is not suitable for the low bit rate video coding. In this paper, the linear relationship between the optimal QP and the ratio of the PSNR of the first frame and the average PSNR of the inter mode frames is first investigated and the linear model is proposed based on the results of the investigation. The proposed model calculate the optimal initial QP using the encoding results of the previous GOP. It is shown by experimental results that the new algorithm can predict the optimal initial QP more accurately and generate the PSNR performance better than that of the existing JM algorithm.

• Molecules and Cells
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• v.40 no.8
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• pp.558-566
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• 2017

Regular monitoring on experimental animal management found the fluctuation of ART outcome, which showed a necessity to explore whether superovulation treatment is responsible for such unexpected outcome. This study was subsequently conducted to examine whether superovulation treatment can preserve ultrastructural integrity and developmental competence of oocytes following oocyte activation and embryo culture. A randomized study using mouse model was designed and in vitro development (experiment 1), ultrastructural morphology (experiment 2) and functional integrity of the oocytes (experiment 3) retrieved after PMSG/hCG injection (superovulation group) or not (natural ovulation; control group) were evaluated. In experiment 1, more oocytes were retrieved following superovulation than following natural ovulation, but natural ovulation yielded higher (p < 0.0563) maturation rate than superovulation. The capacity of mature oocytes to form pronucleus and to develop into blastocysts in vitro was similar. In experiment 2, a notable (p < 0.0186) increase in mitochondrial deformity, characterized by the formation of vacuolated mitochondria, was detected in the superovulation group. Multivesicular body formation was also increased, whereas early endosome formation was significantly decreased. No obvious changes in other microorganelles, however, were detected, which included the formation and distribution of mitochondria, cortical granules, microvilli, and smooth and rough endoplasmic reticulum. In experiment 3, significant decreases in mitochondrial activity, ATP production and dextran uptake were detected in the superovulation group. In conclusion, superovulation treatment may change both maturational status and functional and ultrastuctural integrity of oocytes. Superovulation effect on preimplantation development can be discussed.

• The Journal of Korean Academic Society of Nursing Education
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• v.7 no.1
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• pp.94-112
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• 2001

The main purpose of this study was to investigate the effectiveness of a standardized patients managed instruction program for a fundamentals of nursing. The standardized patients managed instruction was evaluated by using a quasi-experimental, nonequivalent control group posttest design with two separate classes of sophomore students attending fundamentals of nursing classes at one baccaleureate nursing school in Korea. Control group was taught by traditional lecture/model instruction and experimental group was taught by standardized patient managed instruction. Data were collected from December, 1999 to July, 2000 using checklist developed by researcher on following areas; clinical nursing performance, communication skills, and learning motivation. There were 36 students in the experimental group and 40 students in the control group. Data analysis was done using SPSS WINDOW. The results were summarized as follows ; 1. Clinical nursing performances were evaluated by change position, back care and hot bag apply. The total score was statistically significant higher in the experimental group than the control group(t=3.325, p=.000). Thus hypothesis 1 was supported. 2. Communication skill was evaluated by professional attitude and ability to explain to patients. There was a statistically significant difference between the experimental group and the control group (t=4.232, p=.000). Thus hypothesis 2 was supported. 3. Learning motivation was evaluated by self-reported questionnaires. There was statistically a significant difference between the experimental group and the control group(t=3.024, p=.004). Thus hypothesis 3 was supported. In conclusion, this study suggests that standardized patients managed instruction is an effective learning method to nursing students. By utilizing a standardized patient managed instruction, learning can proceed in a more relaxed environment and reduce the risks to patients because student inexperience are avoided. It is recommended to develop more standardized patients cases for wider areas of nursing educational and evaluate the program with more students using logitudinal method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.6
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• pp.607-613
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• 2009

In this paper, we made a simple paper feeding system which is one of MTS (media transport system) and controllers. The plant has a flexible paper and two driving rollers and two driven rollers. The control system has two conventional PID controllers. Skew angle and feeding speed of MTS deteriorate the quality of feeding system. In order to control a feeding speed and skew of feeding paper, we control rotational velocity of two driving rollers. Therefore, this controller has two inputs and two outputs as MIMO (multi-input and multi-output) system. The control inputs were the feeding speed and the skew displacement of the paper. The control outputs were the rotational velocity to each driving roller. To find appropriate PID gains of two controllers, we proposed an optimization technique. We assume the system variables and performance of a whole system as follows. PID gains of two controllers for skew and feeding speed are system variables. System performance is both skew and feeding speed. We simulates to making mathematical correlation using global Kriging interpolation. To find appropriate value of system variables, optimization method is simulation in sequence as following method. First, the optimization solver simulates with DOE (design of experiment) tables to find correlation equation of both system variable and performances. Then, the solver guesses the appropriate values and simulates if the system variables are appropriate or not. If the result of validation doesn't satisfy the convergence and iteration tolerance, the solver makes a new Kriging models and iterates this sequence until satisfy the tolerances.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.217-229
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• 2013

As customers' demands for diversified small-quantity products have been increased, there have been great efforts for a firm to respond to customers' demands flexibly and minimize the cost of inventory at the same time. To achieve that goal, in SCM perspective, many firms have tried to control the inventory efficiently. We present an mathematical model to determine the near optimal (s, S) policy of the supply chain, composed of multi suppliers, a warehouse and multi retailers. (s, S) policy is to order the quantity up to target inventory level when inventory level falls below the reorder point. But it is difficult to analyze inventory level because it is varied with stochastic demand of customers. To reflect stochastic demand of customers in our model, we do the analyses in the following order. First, the analysis of inventory in retailers is done at the mathematical model that we present. Then, the analysis of demand pattern in a warehouse is performed as the inventory of a warehouse is much effected by retailers' order. After that, the analysis of inventory in a warehouse is followed. Finally, the integrated mathematical model is presented. It is not easy to get the solution of the mathematical model, because it includes many stochastic factors. Thus, we get the solutions after the stochastic demand is approximated, then they are verified by the simulations.

• Journal of The Korean Association For Science Education
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• v.16 no.4
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• pp.365-375
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• 1996

Improving of scientific inquiring ability is the major goal of current science curriculum, and the 6th science curriculum. But science educators consider that the existing textbooks and teaching manuals are insufficient to achieve this goal. For science teachers at teaching site to guide students efficiently in research work, development of teaching-learning programs is urgently demanded. Hypothesis Verification Learning Model(HVLM) was applied to classroom situation to improve ability of scientific inquiry in experiment teaching of middle school biology. The effects of the model were analyzed to suggest some approach method to reach the goal of science education in this study. The major results of this study are as following: 1. The students and teachers responded positively on this new learning model. an students were willing to participate in biology experiment and they said that to know what was unknown to them while exchanging ideas and opinions through the discussion, It was hard for teachers to instruct at the first time and it took much time for them to arrange materials ready, but it turned to be easier as time went on. 2. In science process skills, there was no significant difference statistically by new leaning model. Only the formulating a generalization or model showed significant difference statistically between the two groups. 3. For scientific attitude, experimental group did not show significant difference statistically between the two groups, but the experimental group showed statistically more significant positiveness in all areas afterwards than before. 4. In science achievement test, there was significantly higher than the control group. It is also analyzed that they remember the experiments in courses and results they planned and performed by themselves longer than these guided by teachers.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.246-246
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• 2023

Multi-purpose dams are operated accounting for both physical and socioeconomic factors. This study aims to evaluate the utility of a deep learning algorithm-based model for three multi-purpose dam operation (Seomjin River dam, Juam dam, and Juam Control dam) in Seomjin River. In this study, the Gated Recurrent Unit (GRU) algorithm is applied to predict hourly water level of the dam reservoirs over 2002-2021. The hyper-parameters are optimized by the Bayesian optimization algorithm to enhance the prediction skill of the GRU model. The GRU models are set by the following cases: single dam input - single dam output (S-S), multi-dam input - single dam output (M-S), and multi-dam input - multi-dam output (M-M). Results show that the S-S cases with the local dam information have the highest accuracy above 0.8 of NSE. Results from the M-S and M-M model cases confirm that upstream dam information can bring important information for downstream dam operation prediction. The S-S models are simulated with altered outflows (-40% to +40%) to generate the simulated water level of the dam reservoir as alternative dam operational scenarios. The alternative S-S model simulations show physically inconsistent results, indicating that our deep learning algorithm-based model is not explainable for multi-purpose dam operation patterns. To better understand this limitation, we further analyze the relationship between observed water level and outflow of each dam. Results show that complexity in outflow-water level relationship causes the limited predictability of the GRU algorithm-based model. This study highlights the importance of socioeconomic factors from hidden multi-purpose dam operation processes on not only physical processes-based modeling but also aritificial intelligence modeling.