More than 3,000 landslides were occurred by torrential rains in Gangneung area due to the typhoon Rusa in 2002. In order to analyze the landslide origin and its geometric characteristics, 1,365 landslide data were collected from the field survey of Sacheon, Jumunjin, and Yeongok areas in which the intensive landslides took place. The average landslide size in the study area was composed of 10m width, 30m length, and $21^{\circ}{\sim}35^{\circ}$ slope angle, and the plane view of landslides A-type (i.e. wide shape of lower part) that contains approximately 50.5% of the landslides commonly occurred. In particular the area of Sacheon heavily damaged by mountain fires had more occurrence of landslides than other areas. The landslides of uniform tendency of slope direction were examined resulted from the contribution of topographic characteristics due to the weathering and wind direction during heavy rainfalls. In order to analyze the direction of joint, 249 orientation data were collected from the study area. The window method was employed to determine the characteristics of joint density in 51 locations of the study area. The results showed that many landslides occurred in the areas of joint density with the range of $0.05{\sim}0.1$.
Kim Su-Yeon;Shim Seo-Hoon;Shin Dong-Myeong;Lee Joo-Sung;Jung Hyun-Wook;Hyun Jae-Chun
Proceedings of the Korean Society of Rheology Conference
/
2006.06a
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pp.81-84
/
2006
Slot coating process, in continuous and patch modes, has been applied for the many precise coating products, e.g., flat panel displays and second batteries. However, manufacturing uniform coating products is not a trivial task at high-speed operations because various flow instabilities or defects such as leaking, bubbles, ribbing, and rivulets are frequently observed in this process. It is no wonder, therefore, that many efforts to understand the various aspects of dynamics and coating windows of this process have been made both in academia and industry. In this study, as the first topic, flow dynamics within the coating bead in slot coating process has been investigated using the one-dimensional viscocapillary model by lubrication approximation and two-dimensional model by Flow-3D software. Especially, operability windows in both 1D and 2D cases with various slot die lip designs have been successfully portrayed. Also, effects of process conditions like viscosity and coating gap size on slot coating window have been analyzed. Also, some experiments to find minimum coating thickness and coating windows have been conducted using slot die coater implemented with flow visualization device, corroborating the numerical results. As the second topic, flow dynamics of both Newtonian and Non-Newtonian fluids in patch or pattern slot coating process, which is employed in manufacturing IT products such as secondary batteries, has been investigated for the purpose of optimal process designs. As a matter of fact, the flow control in this system is more difficult than in continuous case because od its transient or time-dependent nature. The internal die and die lip designs for patterned uniform coating products have been obtained by controlling flow behaviors of coating liquids issuing from slot. Numerical simulations have been performed using Fluent and Flow-3D packages. Flow behavior and pressure distribution inside the slot die has been compared with various die internal shapes and geometries. In the coating bead region, efforts to reduce irregular coating defects in head and tail parts of one patterned coating unit have been tried by changing die lip shapes. It has been concluded that optimal die internal design gas been developed, guaranteeing uniform velocity distribution of both Newtonian and shear thinning fluids at the die exit. And also optimal die lip design has been established, providing the longer uniform coating layer thickness within one coating unit.
$YMnO_3$thin films are deposited on Si(100) and $Y_2O_3/Si(100)$ substrate by radio frequency sputtering. The deposition condition of oxygen partial pressure and annealing temperature have significant influences on the preferred orientation of $YMnO_3$film and the size of memory window. The results of x-ray diffraction show that the film deposited in the oxygen partial pressure of 0% is highly oriented along c-axis after annealing at $870^{\circ}C$ for 1 hr in oxygen ambient. However, the films deposited on Si and $Y_2O_3/Si$ in the oxygen partial pressures of 20% show $Y_2O_3$ peak, the excess $Y_2O_3$ in the $YMnO_3$film suppresses the c-axis oriented crystallization. Especially memory windows of the $Pt/YMnO_3/Y_2O_3/Si$ capacitor are 0.67~3.65 V at applied voltage of 2~12 V, which is 3 times higher than that of the film deposited on $Y_2O_3/Si$ in 20% oxygen (0.19~1.21 V) at the same gate voltage because the film deposited in 0% oxygen is well crystallized along c-axis.
The characteristics of the Asian summer monsoon have been investigated for the periods of 1993/1994, the contrasting years in a view of the summer monsoon precipitation. In order to investigate the monsoon features over the eastern Asian monsoon region, the cloudiness(using the extensive data derived by the geostationary meteorological satellite), the condition of underlying surface including sea-surface temperature, and the summer rainfall are analyzed and some comparisons with 1993 and 1994 are also made and the characteristic differences are discussed. An analysis of the 2-degree latitude-longitude gridded 5-day mean high cloud amount data shows the detailed movement and persistence of the convective activities. In order to describe the spatial and temporal structures of the intraseasonal oscillation for the movement and evolution of the monsoon cloud, the extended empirical orthogonal fnction analysis with the twenty-day window size is used for the each year. Also, in order to find out the periodicity of the equatorial convective cluster, Fourier harmonic analysis is applied to the each year. The most prevailing intraseasonal oscillations of high cloud amount are 61 day mode and 15day mode in the equatorial and the subtropical oceans. However it was found that the most prevailing modes over the equatorial western Pacific and Indian Ocean were different for each year, hence raising the possibillity that the contrasting monsoon presipitation may be more fundamentally related to the interaction of intraseasonal oscillations and seasonal variation of convective activities over the lower latitude ocean.
The current increasing size of container vessels affects the container port's situation. The containerization has changed the inter-modal handling process, which brought more flexibility and comfortableness in the shipping industry sector. Thus, it is very crucial to analyze the efficiency of container ports in the regional sphere. Such kind of efficiency analysis provide a powerful management tool for port operators and shipping managers in the Mediterranean market, and it also helps to form an information for planning new regional and national port operations. This paper aims to analyze the ports' technical efficiency of Mediterranean major container ports. It is conducted to establish the model of port performance and efficiency through the empirical test of the various factors. Regarding to the panel data collected from the 48 DMUs (decision making units), this study attempts to provide the empirical basis of the port efficiency relative to another factors in the total port performance. Due to the complexity of the various activities carried out at container ports, the study focuses only on the technical efficiency at the level of the Mediterranean container port. Unlike the practice of cross-sectional data analysis, originally established by Charnes et al. (1985), the panel data in DEA window analysis applications are used. The main focus of this study is the relative technical efficiency of 12 container ports from 7 countries in the Mediterranean market. The selection of ports under study is based on their high handling capability and rankings in World Top 100 (Containerization International, 2018).
A multi-view display is regarded as the most practical technology to provide a three-dimensional effect to a viewer because it can provide an appropriate viewpoint according to the observer's position. But, most multi-view displays with flat shapes have a disadvantage in that a viewer watches 3D images only within a limited front viewing angle. In this paper, we proposed a spherical display using a ball lens with spherical symmetry that provides perfect parallax by extending the viewing zone to 360 degrees. In the proposed system, each projection lens is designed to be packaged into a small modular array, and the module array is arranged in a spherical shape around a ball lens to provide vertical and horizontal parallax. Through the applied optical module, the image is formed in the center of the ball lens, and 3D contents are clearly imaged with the size of about 0.65 times the diameter of the ball lens when the viewer watches them within the viewing window. Therefore, the feasibility of a 360-degree full parallax display that overcomes the spherical aberration of a ball lens and provides a wide field of view is confirmed experimentally.
Automatic Music Transcription (AMT) is a task that detects and recognizes musical note events from a given audio recording. In this paper, we focus on reducing the latency of real-time AMT systems on piano music. Although neural AMT models have been adapted for real-time piano transcription, they suffer from high latency, which hinders their usefulness in interactive scenarios. To tackle this issue, we explore several techniques for reducing the intrinsic latency of a neural network for piano transcription, including reducing window and hop sizes of Fast Fourier Transformation (FFT), modifying convolutional layer's kernel size, and shifting the label in the time-axis to train the model to predict onset earlier. Our experiments demonstrate that combining these approaches can lower latency while maintaining high transcription accuracy. Specifically, our modified model achieved note F1 scores of 92.67 % and 90.51 % with latencies of 96 ms and 64 ms, respectively, compared to the baseline model's note F1 score of 93.43 % with a latency of 160 ms. This methodology has potential for training AMT models for various interactive scenarios, including providing real-time feedback for piano education.
In gated radiation therapy (gRT), due to residual motion, beam delivery is intended to irradiate not only the true extent of disease, but also neighboring normal tissues. It is desired that the delivery covers the true extent (i.e. clinical target volume or CTV) as a minimum, although target moves under dose delivery. The objectives of our study are to validate if the intended dose is surely delivered to the true target in gRT and to quantitatively understand the trend of dose delivery on it and neighboring normal tissues when gating window (GW), motion amplitude (MA), and CTV size changes. To fulfill the objectives, experimental and computational studies have been designed and performed. A custom-made phantom with rectangle- and pyramid-shaped targets (CTVs) on a moving platform was scanned for four-dimensional imaging. Various GWs were selected and image integration was performed to generate targets (internal target volume or ITV) for planning that included the CTVs and internal margins (IM). The planning was done conventionally for the rectangle target and IMRT optimization was done for the pyramid target. Dose evaluation was then performed on a diode array aligned perpendicularly to the gated beams through measurements and computational modeling of dose delivery under motion. This study has quantitatively demonstrated and analytically interpreted the impact of residual motion including penumbral broadening for both targets, perturbed but secured dose coverage on the CTV, and significant doses delivered in the neighboring normal tissues. Dose volume histogram analyses also demonstrated and interpreted the trend of dose coverage: for ITV, it increased as GW or MA decreased or CTV size increased; for IM, it increased as GW or MA decreased; for the neighboring normal tissue, opposite trend to that of IM was observed. This study has provided a clear understanding on the impact of the residual motion and proved that if breathing is reproducible gRT is secure despite discontinuous delivery and target motion. The procedures and computational model can be used for commissioning, routine quality assurance, and patient-specific validation of gRT. More work needs to be done for patient-specific dose reconstruction on CT images.
The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.
Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.
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