• Journal of Veterinary Clinics
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• v.28 no.5
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• pp.486-496
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• 2011

A special mesenchymal tissue layer called perichondrium has a chondrogenic capacity and is a candidate tissue for engineering of cartilage. To overcome limited potential for chondrocyte proliferation and re-absorption, we studied a method of cartilage tissue engineering comprising chondrocyte-hydrogel pluronic complex (CPC) and cultured perichondrial cell sheet (cPCs) which entirely cover CPC. For effective cartilage regeneration, cell-sheet engineering technique of high-density culture was used for fabrication of cPCs. Hydrogel pluronic as a biomimetic cell carrier used for stable and maintains the chondrocytes. The human cPCs was cultured as a single layer and entirely covered CPC. The tissue engineered constructs were implanted into the dorsal subcutaneous tissue pocket on nude mice (n = 6). CPC without cPCs were used as a controls (N = 6). Engineered cartilage specimens were harvested at 12 weeks after implantation and evaluated with gross morphology and histological examination. Biological analysis was also performed for glycosaminoglycan (GAG) and type II collagen. Indeed, we performed additional in vivo studies of cartilage regeneration using canine large fullthickness chondrial defect model. The dogs were allocated to the experimental groups as treated chondrocyte sheets with perichondrial cell sheet group (n = 4), and chondrocyte sheets only group (n = 4). The histological and biochemical studies performed 12 weeks later as same manners as nude mouse but additional immunofluorescence study. Grossly, the size of cartilage specimen of cPCs covered group was larger than that of the control. On histological examination, the specimen of cPCs covered group showed typical characteristics of cartilage tissue. The contents of GAG and type II collagen were higher in cPCs covered group than that of the control. These studies demonstrated the potential of such CPC/cPCs constructs to support chondrogenesis in vivo. In conclusion, the method of cartilage tissue engineering using cPCs supposed to be an effective method with higher cartilage tissue gain. We suggest a new method of cartilage tissue engineering using cultured perichondrial cell sheet as a promising strategy for cartilage tissue reconstruction.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.275-284
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• 2008

Purpose: We intended to evaluate myocardial oxygen consumption ($MVO_2)$ by applying recirculation correction and modified one-compartment model to have a reference range of $MVO_2$ in normal young population and to reveal the effect of recirculation on time-activity curve (TAC). Materials and Methods: In nine normal male volunteers with mean age of $26.3{\pm}4.0$, $MVO_2$ was estimated with 925 MBq (25mCi) of $^{11}C$-Acetate (Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea) and PET/CT (Biograph 6, Siemens Medical Solution, Germany). Analysis software such as $MATLAB^{(R)}$ v7.1 (Mathworks, Inc., United States), $Excel^{(R)}$ 2007 (Microsoft, United States), and $SPSS^{(R)}$ v12.0 (Apache Software Foundation, United States) were used. Twenty three frames were of $12{\times}10$, $5{\times}60$, $3{\times}120$, $2{\times}300's$ duration, respectively. The modified one-compartmental model and the recirculation correction method were applied. Statistical analysis was performed by using Test of Normality, ANOVA and Post-Hoc (Scheffe's) analysis, and p-value less than 0.05 was considered as significant. Results: The normal reference ranges of $MVO_2$ were presented as $3.18-4.64\;{\times}\;10^{-4}\;ml/g/sec$, $1.91-3.94\;{\times}\;10^{-4}\;ml/g/sec$, $4.31-6.40\;{\times}\;10^{-4}\;ml/g/sec$, $2.84-4.53\;{\times}\;10^{-4}\;ml/g/sec$ and $3.42-5.00\;{\times}\;10^{-4}\;ml/g/sec$ in the septum, the inferior wall, the lateral wall, the anterior wall and the entire wall, respectively. In addition, it was noted that the dual exponentiality of the clearance curve is due to the recirculation effect and that the characteristic of the curve is essentially mono-exponential. Conclusion: $^{11}C$-Acetate is a radiotracer worthwhile to assess $MVO_2$. Re-circulated $^{11}C$ can influence TAC of $^{11}C$ in myocadia and so the recirculation correction must be considered when measuring $MVO_2$.

• Restorative Dentistry and Endodontics
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• v.36 no.1
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• pp.37-49
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• 2011

Objectives: The aim of this study was to evaluate the surface color of indirect resin restoration according to the layering placement of different shade of incisal composite. Materials and Methods: In this study, CIE $L^*a^*b^*$ value of 16 Body composite of Tescera ATL (Bisco, Schaumburg IL,USA) was measured by spectrophotometer (NF999, Nippon Denshuku, Japan), and compared to CIE $L^*a^*b^*$ value of Vitapan shade guide. Nine shade Incisal composite of Tescera ATL were buildup to 1 mm thickness on Body composites inlay block, and CIE $L^*a^*b^*$ value was measured. Incisal composite was ground to 0.5 mm thickness and CIE $L^*a^*b^*$ value was re-measured. Color difference between Body composite and Incisal composites layered on Body composite was calculated as a function of thickness. Results: Color difference between corresponding shade of Tescera Body composite and Vitapan shade guide was from 6.88 to 12.80. $L^*$ and $b^*$ value was decreased as layering thickness of Incisal composite on Body composite was increased. But, $a^*$ value did not show specific change tendency. Conclusions: Surface color difference between Body composites and Incisal composites layered on Body composite was increased as the layering thickness of Incisal composite increased (p < 0.05).

• Korean Journal of Plant Taxonomy
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• v.32 no.3
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• pp.339-362
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• 2002

Pollen morphology of 13 species of Korean Euphorbia was re-examined by means of LM and SEM. Taxonomic evaluation of palynological characters and relationships among taxa were also discussed based on the analysis of polar length, equatorial diameter, aperture size and exine thickness. Korean Euphorbia species were classified into three groups based on the mean size of polar length (P) and equatorial diameter (E) as follows:Group 1. sect. Tulocarpa and Tithymalus of subgenus Esula; $(P){\times}(E)=(54.88-67.17{\mu}m){\times}(44.30-64.75{\mu}m)$, Group 2. sect. Esula and Helioscpiae of subgenus Esula; $(P){\times}(E)=(39.98-47.24{\mu}m){\times}(36.07-38.83{\mu}m)$, Group 3. sect. Chamaesyce and Hypericifoliae of subgenus Chamaesyce; $(P){\times}(E)=(30.32-32.51{\mu}m){\times}(21.71-26.23{\mu}m)$. Various features of surface sculpturing were also grouped into 8 types by the characteristics of perporation size and distance of perporations as well as connection state of it. Pollen size and surface sculpturing were comparatively available in the levels of subgenus and section. Especially subgenus Chamaesyce was distinctly different from subgenus Esula by having compactly distributed perporations on exine surface as well as its small size of pollen grains. Because of the great variations in pollen size and the occurrence of various types of surface sculpturing according to the local poulations of each species, it was evaluated that they were unsuitable in classifying each species of Euphorbia. But such cases, that is, E. hylonoma being more familiar with E. ebracteolata than E. Pallasii, and E. pekinensis and E. fauriei as well as E. pallasii being strongly related with each other based on the similarity of surface sculpturing, reflected its usefulness in the classification of some Euphorbia species.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.4
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• pp.487-496
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• 2021

Full mouth rehabilitation is re-organizing the occlusion of the remaining teeth and missing teeth considering the functions, esthetics, and neuromuscular harmony. With the loss of multiple teeth, the patient's occlusal plane gradually collapses and the vertical dimension can be reduced. Since reduced vertical dimension can be a potential etiology of the temporomandibular joint and masticatory muscles, prosthetic restoration with increased vertical dimension is required. This case report is about a 68 years old patient with vertical dimension loss due to worn dentition and multiple loss of teeth. In this case, the loss of vertical dimension is assessed carefully using the digital dentistry technology. Using CAD software in digital analysis step, the occlusal plane was established and evaluated using several criteria. Orienting the position of the bone and teeth using CBCT image, patient's condition was visualized in 3 dimension and treatment planning was possible virtually. The information that matches the patient's condylar position with the articulator, which is the virtual face bow, is reproduced on the actual articulator, and evaluated again. After the evaluation, provisional prosthesis was fabricated and it was confirmed that the patient adapts without any abnormality. This was implemented as a final prosthesis. As a result, the patient obtained satisfying results, utilizing the benefits of digital dentistry technology and traditional methods.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.352-363
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• 2021

The purpose of this study was to evaluate the load of nutrients contained in the drainage discharged from the facility horticultural complex and to use them for re-use of fluids and design for introduction of water treatment plants. Representative hydroponic cultivation crops were selected as tomato, paprika, cucumber, and strawberry, and the total number of samples analyzed for water quality was 80. As a result of the analysis, since various fertilizer components such as N, P, K⁺, Na⁺, Mg²⁺, Ca²⁺, Si₄⁺, HCO₃^-, Cl^-, S^2-, Fe, Mn, Cu, Zn, Mo and B are contained at very high concentrations in the drainage, the need for water treatment was confirmed. Through statistical analysis, it was analyzed that the drainage concentration of strawberries was lower than that of tomatoes, paprika, and cucumbers. In the case of tomatoes, these essential ion concentrations are the highest, so it was confirmed that they are subject to valuable resources in terms of reuse of fertilizers. The load of N and P of the drainage discharged from the facility horticultural complex 1m² was analyzed. For N, the daily processing capacity of 4.0 kg of tomatoes, 3.3 kg of paprika, 3.0 kg of cucumbers, and 1.5 kg of strawberries was calculated based on 1 ha. It was suggested that the P concentration needs a scale and capacity that can handle 0.5 kg of tomatoes, 0.6 kg of paprika, 0.4 kg of cucumber, and 0.2 kg of strawberries per day. Through this study, the amount of nitrogen and phosphorus contained in the drainage discharged from the greenhouse of each crop was evaluated to analyze the economy. In addition, it was expected to be used as basic data that can be used to calculate the treatment capacity to be reflected when introducing water treatment facilities in facility horticultural complexes for sustainable agriculture.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.33 no.12
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• pp.81-90
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• 2017

This study was conducted to investigate the thermal environment status of nursery rooms in workplace daycare centers in Jeju and propose measures to improve their indoor physical thermal environment. For this purpose, measurements were performed in the winter indoor physical environment of 51 nursery rooms in 11 workplace daycare centers and a psychological evaluation survey on the thermal environment of nursery rooms was conducted for 70 nursery teachers. The investigation was carried out over 11 days in January 2017. The results are as follow. The average indoor temperature of the nursery rooms was $21.3^{\circ}C$($18.7-23.8^{\circ}C$) and the indoor temperatures of 47 nursery rooms (92.9%) were higher than the environmental hygiene management standard for domestic school facilities ($18-20^{\circ}C$). The average relative humidity was 33.9% (16.4-56.0%), and 37 nursery rooms (86.3%) showed a lower average relative humidity than the standard (40-70%). The average absolute humidity was $9.1g/m^3$ ($4.7-13.6g/m^3$), which was lower than the standard for preventing influenza ($10g/m^3$). When the indoor temperature and humidity of the nursery rooms were compared with international standards, it was found that 85% or more of the 51 nursery rooms maintained appropriate indoor temperatures, but 40-50% of the nursery rooms maintained a low humidity condition. Therefore, they need to pay attention to maintaining the appropriate humidity of the nursery room to keep the children healthy. The average indoor temperature of the nursery rooms showed a weak negative correlation with the average relative humidity. The indoor temperature had a significant effect on the relative humidity: a higher indoor temperature resulted in lower relative humidity. Regarding the fluctuations in the average indoor temperature of the nursery rooms during the day, in daycare centers that used floor heating, the indoor temperature gradually increased form the morning to the afternoon and tended to decrease during lunch time and the morning and afternoon snack times, due to ventilation. The daycare centers that used both floor heating and ceiling-type air conditioners showed a higher indoor temperature and greater fluctuations in temperature compared to the daycare centers that used floor heating only. In the survey results, the average value of the whole body thermal sensation was 3.0 (neutral): 32 respondents (62.7%) answered, "Neutral", Which was the largest number, followed by 21 respondents (30%) who answered, "Slightly hot" and 17 respondents (24.2%) who answered, "Slightly cold." Twenty-nine respondents answered, "Slightly dry," which was the largest number, followed by 28 respondents (54.9%) who answered, "Neutral" and 10 respondents (19.6%) who answered, "Dry." The total number of respondents who answered, "Slightly dry" or "Dry" was large at 39 (56.4%), which suggests the need for indoor environment management to prevent a low-humidity environment. To summarize the above results about the thermal environment of nursery rooms, as the indoor temperature increased, the relative humidity decreased. This suggests the effect of room temperature on the indoor relative humidity; however, frequent ventilations also greatly decrease the relative humidity. Therefore, the ventilation method and the usage of air conditioning systems need to be re-examined.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.