• Title/Summary/Keyword: model based

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Prediction of the human in vivo antiplatelet effect of S- and R-indobufen using population pharmacodynamic modeling and simulation based on in vitro platelet aggregation test

  • Noh, Yook-Hwan;Han, Sungpil;Choe, Sangmin;Jung, Jin-Ah;Jung, Jin-Ah;Hwang, Ae-Kyung;Lim, Hyeong-Seok
    • Translational and Clinical Pharmacology
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    • v.26 no.4
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    • pp.160-165
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    • 2018
  • Indobufen ($Ibustrin^{(R)}$), a reversible inhibitor of platelet aggregation, exists in two enantiomeric forms in 1:1 ratio. Here, we characterized the anti-platelet effect of S- and R-indobufen using response surface modeling using $NONMEM^{(R)}$ and predicted the therapeutic doses exerting the maximal efficacy of each enantioselective S- and R-indobufen formulation. S- and R-indobufen were added individually or together to 24 plasma samples from drug-naïve healthy subjects, generating 892 samples containing randomly selected concentrations of the drugs of 0-128 mg/L. Collagen-induced platelet aggregation in platelet-rich plasma was determined using a Chrono-log Lumi-Aggregometer. Inhibitory sigmoid $I_{max}$ model adequately described the anti-platelet effect. The S-form was more potent, whereas the R-form showed less inter-individual variation. No significant interaction was observed between the two enantiomers. The anti-platelet effect of multiple treatments with 200 mg indobufen twice daily doses was predicted in the simulation study, and the effect of S- or R-indobufen alone at various doses was predicted to define optimal dosing regimen for each enantiomer. Simulation study predicted that 200 mg twice daily administration of S-indobufen alone will produce more treatment effect than S-and R-mixture formulation. S-indobufen produced treatment effect at lower concentration than R-indobufen. However, inter-individual variation of the pharmacodynamic response was smaller in R-indobufen. The present study suggests the optimal doses of R-and S-enantioselective indobufen formulations in terms of treatment efficacy for patients with thromboembolic problems. The proposed methodology in this study can be applied to the develop novel enantio-selective drugs more efficiently.

Wind load and wind-induced effect of the large wind turbine tower-blade system considering blade yaw and interference

  • Ke, S.T.;Wang, X.H.;Ge, Y.J.
    • Wind and Structures
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    • v.28 no.2
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    • pp.71-87
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    • 2019
  • The yaw and interference effects of blades affect aerodynamic performance of large wind turbine system significantly, thus influencing wind-induced response and stability performance of the tower-blade system. In this study, the 5MW wind turbine which was developed by Nanjing University of Aeronautics and Astronautics (NUAA) was chosen as the research object. Large eddy simulation on flow field and aerodynamics of its wind turbine system with different yaw angles($0^{\circ}$, $5^{\circ}$, $10^{\circ}$, $20^{\circ}$, $30^{\circ}$ and $45^{\circ}$) under the most unfavorable blade position was carried out. Results were compared with codes and measurement results at home and abroad, which verified validity of large eddy simulation. On this basis, effects of yaw angle on average wind pressure, fluctuating wind pressure, lift coefficient, resistance coefficient,streaming and wake characteristics on different interference zone of tower of wind turbine were analyzed. Next, the blade-cabin-tower-foundation integrated coupling model of the large wind turbine was constructed based on finite element method. Dynamic characteristics, wind-induced response and stability performance of the wind turbine structural system under different yaw angle were analyzed systematically. Research results demonstrate that with the increase of yaw angle, the maximum negative pressure and extreme negative pressure of the significant interference zone of the tower present a V-shaped variation trend, whereas the layer resistance coefficient increases gradually. By contrast, the maximum negative pressure, extreme negative pressure and layer resistance coefficient of the non-interference zone remain basically same. Effects of streaming and wake weaken gradually. When the yaw angle increases to $45^{\circ}$, aerodynamic force of the tower is close with that when there's no blade yaw and interference. As the height of significant interference zone increases, layer resistance coefficient decreases firstly and then increases under different yaw angles. Maximum means and mean square error (MSE) of radial displacement under different yaw angles all occur at circumferential $0^{\circ}$ and $180^{\circ}$ of the tower. The maximum bending moment at tower bottom is at circumferential $20^{\circ}$. When the yaw angle is $0^{\circ}$, the maximum downwind displacement responses of different blades are higher than 2.7 m. With the increase of yaw angle, MSEs of radial displacement at tower top, downwind displacement of blades, internal force at blade roots all decrease gradually, while the critical wind speed decreases firstly and then increases and finally decreases. The comprehensive analysis shows that the worst aerodynamic performance and wind-induced response of the wind turbine system are achieved when the yaw angle is $0^{\circ}$, whereas the worst stability performance and ultimate bearing capacity are achieved when the yaw angle is $45^{\circ}$.

Accessibility Analysis Method based on Public Facility Attraction Index Using SNS Data (SNS 데이터를 이용한 공공시설 매력도지수에 따른 접근성 분석기법)

  • Lee, Ji Won;Yu, Ki Yun;Kim, Ji Young
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.1
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    • pp.29-42
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    • 2019
  • In order to expand the qualitative aspects of public facility, this study used SNS data to derive user-oriented preference factors for public facilities and then were quantified in terms of supply side and demand side. To derive preference factor, LDA, one of topic modeling, was used and attraction index was calculated for each facility. In addition we analyzed spatial accessibility to measure the degree of service experience of users by using 2SFCA model. The study area covered public libraries of Seoul, Korea. As a result of study, five topics were extracted as preference factors for the public library: Circumstance, Scale of facility, Cultural program, Parenting, Books and materials. In particular topic of circumstance and parenting were newly derived preference factors unknown in previous studies. As a result of calculating attraction index for each library, the index of Songpa Library, Jungdok Library, and Namsan Library was high. Songpa library has received good evaluation in parenting factor, and Jungdok & Namsan library in circumstance factor. The accessibility of each region seems to better in center of Seoul where public libraries are crowded, but shrinking toward the outskirts. We expect that the proposed method will contribute to user-oriented public facility evaluation and policy decision making.

Dual CNN Structured Sound Event Detection Algorithm Based on Real Life Acoustic Dataset (실생활 음향 데이터 기반 이중 CNN 구조를 특징으로 하는 음향 이벤트 인식 알고리즘)

  • Suh, Sangwon;Lim, Wootaek;Jeong, Youngho;Lee, Taejin;Kim, Hui Yong
    • Journal of Broadcast Engineering
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    • v.23 no.6
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    • pp.855-865
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    • 2018
  • Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

Fabrication and Electrical Property Analysis of [(Ni0.3Mn0.7)1-xCux]3O4 Thin Films for Microbolometer Applications (마이크로볼로미터용 [(Ni0.3Mn0.7)1-xCux]3O4 박막의 제작 및 전기적 특성 분석)

  • Choi, Yong Ho;Jeong, Young Hun;Yun, Ji Sun;Paik, Jong Hoo;Hong, Youn Woo;Cho, Jeong Ho
    • Journal of Sensor Science and Technology
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    • v.28 no.1
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    • pp.41-46
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    • 2019
  • In order to develop novel thermal imaging materials for microbolometer applications, $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ ($0.18{\leq}x{\leq}0.26$) thin films were fabricated using metal-organic decomposition. Effects of Cu content on the electrical properties of the annealed films were investigated. Spinel thin films with a thickness of approximately 100 nm were obtained from the $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ films annealed at $380^{\circ}C$ for five hours. The resistivity (${\rho}$) of the annealed films was analyzed with respect to the small polaron hopping model. Based on the $Mn^{3+}/Mn^{4+}$ ratio values obtained through x-ray photoelectron spectroscopy analysis, the hopping mechanism between $Mn^{3+}$ and $Mn^{4+}$ cations discussed in the proposed study. The effects of $Cu^+$ and $Cu^{2+}$ cations on the hopping mechanism is also discussed. Obtained results indicate that $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ thin films with low temperature annealing and superior electrical properties (${\rho}{\leq}54.83{\Omega}{\cdot}cm$, temperature coefficient of resistance > -2.62%/K) can be effectively employed in applications involving complementary metal-oxide semiconductor (CMOS) integrated microbolometer devices.

A study on estimation of optimal reserves for multi-purpose reservoirs considering climate change (기후변화를 고려한 다목적댐의 적정 예비율 산정 연구)

  • Chae, Heechan;Ji, Jungwon;Yi, Jaeeung
    • Journal of Korea Water Resources Association
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    • v.51 no.spc
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    • pp.1127-1134
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    • 2018
  • According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), climate change increases the frequency of abnormal weather phenomenon. As the frequency of abnormal weather phenomenon increases, frequency of disasters related to water resources such as floods and droughts also increases. Drought is the main factor that directly affects water supply. Recently, the intensity of drought and the frequency of drought occurrence have increased in Korea. So, there is a need for water resource securing technology for stable water supply. Korean Water Plan mentioned that water reserves concept is necessary for stable water supply. Most multi-purpose reservoirs in Korea have emergency storage in addition to conservation storage used for water supply. However, there is no clear use standard for emergency storage. This study investigated the use of reservoir reserves for stable water supply. In order to consider the climate change impact, the AR5-based hydrological scenario was used as inflow data for the reservoir simulation model. Reservoir simulations were carried out in accordance with the utilization conditions of emergency storage and water supply adjustment standard. The optimal reserves for each multi-purpose reservoirs was estimated using simulation results.

Estimation of the major sources for organic aerosols at the Anmyeon Island GAW station (안면도에서의 초미세먼지 유기성분 주요 영향원 평가)

  • Han, Sanghee;Lee, Ji Yi;Lee, Jongsik;Heo, Jongbae;Jung, Chang Hoon;Kim, Eun-Sill;Kim, Yong Pyo
    • Particle and aerosol research
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    • v.14 no.4
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    • pp.135-144
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    • 2018
  • Based on a two-year measurement data, major sources for the ambient carbonaceous aerosols at the Anmyeon Global Atmosphere Watch (GAW) station were identified by using the Positive Matrix Factorization (PMF) model. The particulate matter less than or equal to $2.5{\mu}m$ in aerodynamic diameter (PM2.5) aerosols were sampled between June 2015 to May 2017 and carbonaceous species including ~80 organic compounds were analyzed. When the number of factors was 5 or 6, the performance evaluation parameters showed the best results, With 6 factor case, the characteristics of transported factors were clearer. The 6 factors were identified with various analyses including chemical characteristics and air parcel movement analysis. The 6 factors with their relative contributions were (1) anthropogenic Secondary Organic Aerosols (SOA) (10.3%), (2) biogenic sources (24.8%), (3) local biomass burning (26.4%), (4) transported biomass burning (7.3%), (5) combustion related sources (12.0%), and (6) transported sources (19.2%). The air parcel movement analysis result and seasonal variation of the contribution of these factors also supported the identification of these factors. Thus, the Anmyeon Island GAW station has been affected by both regional and local sources for the carbonaceous aerosols.

The Method for Colorizing SAR Images of Kompsat-5 Using Cycle GAN with Multi-scale Discriminators (다양한 크기의 식별자를 적용한 Cycle GAN을 이용한 다목적실용위성 5호 SAR 영상 색상 구현 방법)

  • Ku, Wonhoe;Chun, Daewon
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1415-1425
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    • 2018
  • Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

Validation of Sea Surface Wind Estimated from KOMPSAT-5 Backscattering Coefficient Data (KOMPSAT-5 후방산란계수 자료로 산출된 해상풍 검증)

  • Jang, Jae-Cheol;Park, Kyung-Ae;Yang, Dochul
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1383-1398
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    • 2018
  • Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

Study on the Effect of Training Data Sampling Strategy on the Accuracy of the Landslide Susceptibility Analysis Using Random Forest Method (Random Forest 기법을 이용한 산사태 취약성 평가 시 훈련 데이터 선택이 결과 정확도에 미치는 영향)

  • Kang, Kyoung-Hee;Park, Hyuck-Jin
    • Economic and Environmental Geology
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    • v.52 no.2
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    • pp.199-212
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    • 2019
  • In the machine learning techniques, the sampling strategy of the training data affects a performance of the prediction model such as generalizing ability as well as prediction accuracy. Especially, in landslide susceptibility analysis, the data sampling procedure is the essential step for setting the training data because the number of non-landslide points is much bigger than the number of landslide points. However, the previous researches did not consider the various sampling methods for the training data. That is, the previous studies selected the training data randomly. Therefore, in this study the authors proposed several different sampling methods and assessed the effect of the sampling strategies of the training data in landslide susceptibility analysis. For that, total six different scenarios were set up based on the sampling strategies of landslide points and non-landslide points. Then Random Forest technique was trained on the basis of six different scenarios and the attribute importance for each input variable was evaluated. Subsequently, the landslide susceptibility maps were produced using the input variables and their attribute importances. In the analysis results, the AUC values of the landslide susceptibility maps, obtained from six different sampling strategies, showed high prediction rates, ranges from 70 % to 80 %. It means that the Random Forest technique shows appropriate predictive performance and the attribute importance for the input variables obtained from Random Forest can be used as the weight of landslide conditioning factors in the susceptibility analysis. In addition, the analysis results obtained using specific sampling strategies for training data show higher prediction accuracy than the analysis results using the previous random sampling method.