• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.649-660
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• 2021

Through analytical method based on S-76 model, the level of rotor hub vibration reduction was analyzed according to higher harmonic actuating by individual blade control. The higher harmonic actuating method for individual blades was divided into a method of generating an additional actuating force from the pitch-link in the rotating part and generating actuating force through the active trailing edge flap control of the blade. In the 100kts forward flight conditions, the hub load analysis was performed by changing the phase angle of 15 degree for the 2P/3P/4P/5P harmonic actuation for individual blades. Through the harmonic actuation results, the sensitivity of the rotor system according to the actuating conditions was analyzed, and the T-matrix representing the characteristics of the rotor system was derived based on this analysis result. And through this T-matrix, optimal higher harmonic actuating condition was derived to minimize hub vibration level for flight condition. In addition, the effect on the performance of the rotor system and the pitch-link load under minimum hub vibration condition, as well as the noise influence through the noise analysis were confirmed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.434-445
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• 2020

In this study, the minimization of harbor oscillation using permeable breakwater was applied to the actual harbor and investigated an effect of minimization by computer simulation in order to take into account the water quality problems and measures of harbor oscillation by infragravity waves at the same time. The study site is Mukho harbor located at East coast of Korea that harbor oscillation has been occurred frequently. The infragravity waves obtained by analyzing the observed field data for five years focused on the distribution between wave periods of 40 s and 70 s and wave heights in less than 0.1 m was 94% of analyzing data. The target wave periods was 68.0 s. The most effective method of minimization of harbor oscillation by infragravity waves was to install a detached permeable breakwater with transmission coefficient of 0.3 on the outside harbor and replace some area of the vertical wall in the harbor with wave energy dissipating structure to achieve a reflectivity of 0.9 or less. The amplitude reduction rate of this method shown in 27.4%. And the effect of the difference in transmission coefficient of permeable breakwater on the reduction rate of the amplitude was not significant.

• Proceedings of the Korean Geotechical Society Conference
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• 1991.10a
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• pp.87-102
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• 1991

It has been reported that the failure of Carsington Dam in Eng1and occured due to the existence of a thin yellow clay layer which was not identified during the design work, and due to pre-existing shears of the clay layer. The slope stability analyses during the design work, which utilized traditional circular arc type failure method and neglected the existence of the clay layer, showed a safety factor of 1.4. However, the post-failure analyses which utilized translational failure mode considering the clay layer and the pre-existing shear deformation revealed the reduction of safety factor to unity. The post-failure analysis assumed 10。 inclination of the horizontal forces onto each slice based on the results of finite element analyses. In this paper, Bishop's simplified method, Janbu method, and Morgenstern-Price method were used for the comparison of both circular and translational failure analysis methods. The effects of the pre-existing shears and subsquent movement were also considered by varying the soil strength parameters and the pore pressure ratio according to the given soi1 parameters. The results showed factor of safefy 1.387 by Bishop's simplified method(STABL) which assumed circular arc failure surface and disregarding yellow clay layer and pre-failure material properties. Also the results showed factor of safety 1.093 by Janbu method(STABL) and 0.969 by Morgenstern-Price method(MALE) which assumed wedge failure surface and considerd yellow clay layer using post failure material properties. In addition, dam behavior was simulated by Cam-Clay model FEM program. The effects of pore pressure changes with loading and consolidation, and strength reduction near or at failure were also considered based on properly assumed stress-strain relationship and pore pressure characteristics. The results showed that the failure was initiated at the yellow clay layer and propagated through other zones by showing that stress and displacement were concentrated at the yel1ow clay layer.

• The Korean Journal of Pharmacology
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• v.31 no.2
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• pp.251-259
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• 1995

Pharmacokinetics and pharmacodynamics of metoprolol, a selective beta-l blocker, were examined for 360 minutes after intravenous bolus administration of metoprolol to 6 dogs. Plasma concentration and excreted amount in the urine metoprolol were measured by liquid chromatography with fluorescence detection. PR interval and heart rate were measured by ECG monitoring. Blood pressure was monitored through intraarterial catheter in femoral artery and cardiac output by thermodilution method using Swan-Ganz catheter. To analyze the effect site concentration-response relationship, plasma concentration and pharmacological effects were simultaneously fitted to a two pharmacokinetic compartment linked to pharmacodynamic model with NONLIN program. Results are as follows. 1) The plasma concentration of metoprolol after intrvenous injection decreased biexponentially. The terminal half-life estimated was $1.33{\pm}0.40$ hours and the volume of distribution at steady state (Vdss) and the total body clearance were $1.04{\pm}0.4\;L/kg,\;6.55{\pm}2.21\;L/hr$, respectively. The central compartment volume of distribution and peripheral compartment volume of distribution were $0.35{\pm}0.14L/kg\;and\;0.69{\pm}0.34L/kg$. The renal clearance and intercompartment clearance were $0.53{\pm}0.25\;L/min\;and\;0.35{\pm}0.19\;L/min$. 2) Simulated biophase concentration-response curve shows hyperbolic relationship and the estimated concentration-effect relationship was best explained by Emax model when the prolongation of PR interval and the reduction of the heart rate were used as pharmacodynamic parameters. Emax and EC50 were estimated to be $26.3{\pm}4.7\;msec\;and\;88.8{\pm}82.3\;g/ml$ for PR interval, and $48.7{\pm}18.8\;beats/min\;and\;113.5{\pm}78.7\;ng/ml$ for heart rate, respectively. 3) The changes of cardiac output-effect site concentration relationship was best fitted by a linear model and the slope of the relationship was $0.005{\pm}0.003$. Diastolic blood pressure-effect site concentration relationship was also explained by the linear model and the slope of the relationship was $0.038{\pm}0.034$.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Wind and Structures
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• v.18 no.2
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• pp.155-180
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• 2014

The safety of road vehicles on the ground in crosswind has been investigated for many years. One of the most important fundamentals in the safety analysis is aerodynamic characteristics of a vehicle in crosswind. The most common way to study the aerodynamic characteristics of a vehicle in crosswind is wind tunnel tests to measure the aerodynamic coefficients and/or pressure coefficients of the vehicle. Due to the complexity of wind tunnel test equipment and procedure, the features of flow field around the vehicle are seldom explored in a wind tunnel, particularly for the vehicle moving on the ground. As a complementary to wind tunnel tests, the numerical method using computational fluid dynamics (CFD) can be employed as an effective tool to explore the aerodynamic characteristics of as well as flow features around the vehicle. This study explores crosswind effects on a high-sided lorry on the ground with and without movement through CFD simulations together with wind tunnel tests. Firstly, the aerodynamic forces on a stationary lorry model are measured in a wind tunnel, and the results are compared with the previous measurement results. The CFD with unsteady RANS method is then employed to simulate wind flow around and wind pressures on the stationary lorry. The numerical aerodynamic forces are compared with the wind tunnel test results. Furthermore, the same CFD method is extended to investigate the moving vehicle on the ground in crosswind. The results show that the CFD results match with wind tunnel test results and the current way using aerodynamic coefficients from a stationary vehicle in crosswind is acceptable. The CFD simulation can provide more insights on flow field and pressure distribution which are difficult to be obtained by wind tunnel tests.

• Geotechnical Engineering
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• v.9 no.1
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• pp.45-58
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• 1993

Paper drain method is one of the methods used for the improvement of soft clay as hydraulic fill sites or the seaside industrial complex. This method adopts a card board as the drain materials instead of sand piles in sand drain method. In this paper 3 types of drain board are used to fond out the characteristics of consolidation by vacuum consolidation model test. So does the no drain board test. This test causes the reduction of pore water pressure to promote the settlement without change of ground water level. Conclusively, the vacuum consolidation shows 3-dimensional behaviors and pore water pressure reaches a negative value in a short time. In addition, it is expected to have a comparatively good consolidation effect using non -woven board, and vacuum loading results in increasing the shear strength at the bottom and top of call layers.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.241-254
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• 2017

Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in analysis of covariance (ANCOVA) models. A comparison to simple random sampling (SRS) is made to demonstrate efficiency. The results indicate that the required sample sizes for a given precision are smaller under RSS than under SRS. The modified RSS protocol was applied to an experimental study. The experimental study was designed to obtain a better understanding of the pathways by which positive experiences (i.e., goal completion) contribute to higher levels of happiness, well-being, and life satisfaction. The use of the RSS method resulted in a cost reduction associated with smaller sample size without losing the precision of the analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.757-764
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• 2017

As the reduction of greenhouse gases(GHGs) emission has become a global issue, the microgrid markets are growing rapidly. With the sudden changes in the market, Korean government suggested a new business model called 'Self-Sufficient Energy Islands'. Its main concern is a stand-alone microgrid composed of Distributed Energy Resources(DERs) such as Renewable Energy Sources(RESs), Energy Storage System(ESS) and Fuel Cell, in order to minimize the emission of GHGs. According to these trend, this paper is written to propose an optimal sizing method of DERs in a stand-alone microgrid by using Genetic Algorithm(GA), one of the representative stochastic methods. It is to minimize the net present cost with the variables, size of RESs and ESS. In the process for optimization, the sunless days are considered as additional constraints. Through the case study analysis, the size of DERs installed in a microgrid system has been computed using the proposed method in MATLAB. And the result of MATLAB is compared with that of HOMER(Hybrid Optimization of Multiple Energy Resources), a well-known energy modeling software.