• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7549-7554
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• 2015

The aim of this study was to develop gastric retentive bi-layered tablet using floating drug delivery technique. Metformin was selected as a model drug due to its narrow absorption window as well as very highly water solubility. These properties of metformin led to be difficult controlling the drug release. The bi-layered tablet was prepared with bi-layered compression machine to minimize interference between floating part and controlling part. The tablet weight, appearance and hardness were evaluated after compression process. The times of 'time to floating' and 'Floating duration' were tested for floating ability and drug release study was also carried out to understand drug release behavior. Furthermore, the drug release of bi-layered tablet was compared with marketed metformin tablet with sustained release pattern (Glucopharge XR$^{(R)}$).The floating ability and drug release behaviors were well controlled by changing amounts of $NaHCO_3$ (floating substance) and hydroxypropyl methylcellulose (HPMC; release control material). Bi-layered tablet had 13s of time to float, over 10h of floating duration and very similar drug release behavior compared with Glucopharge XR$^{(R)}$($f_2$: 89.6). Consequently, the bi-layered tablet with floating ability was successfully prepared and these properties can maximize the efficacy of metformin.

• Proceedings of the Korean Society of Rheology Conference
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• 2006.06a
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• pp.81-84
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• 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.

• Journal of IKEEE
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• v.25 no.3
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• pp.501-505
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• 2021

In this study, we fabricated amorphous indium-tin-gallium-zinc-oxide thin-film transistors (a-ITGZO TFTs) with gate dielectrics of HfO₂ and the mixed layers of HfO₂ and Al₂O₃, and investigated the effect of gate dielectric on electrical characteristics of a-ITGZO TFTs. When only HfO₂ was used as the gate dielectric, the mobility and subthreshold swing (SS) were 32.3 cm²/Vs and 206 mV/dec. For the a-ITGZO TFTs with gate dielectric made of HfO₂ and Al₂O (2:1, 1:1), the mobilities and SS were 26.4 cm²/Vs (2:1), 16.8 cm²/Vs(1:1), 160 mV/dec (2:1) and 173 mV/dec (1:1). On the other hand, the hysteresis window shown in transfer curves of the a-ITGZO TFTs was lessened from 0.60 to 0.09 V by the increase of Al₂O₃ ratio in gate dielectric, indicating that the interface trap density between the gate dielectric and channel layer decreases due to Al₂O₃.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.52-60
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• 2019

The APR1400 is a 1400MWe nuclear power plant developed through national technology development project over a period about 10years. Approximately 65,000 design drawings are produced for APR1400 construction. In order to maintain consistency among numerous drawings, the highest level of design bases drawings (DBDs) are created according to design bases and this is used in the subsequent design. However, DBDs are produced and managed on a document basis and they are managed various field, it was difficult to accurately reflect the design bases information in the subsequent design. Therefore, this study recognizes limitations of the document based DBDs and develops a system that can accurately reflect the design bases information to subsequent design by adopting BIM based design bases integrated information system. Especially, by introducing DBIL(Design Bases Information Layer) concept, DBIL was created and analyzed based on five design bases(Physical protection, Fire protection, Internal missile protection, Internal flood protection, Radiation protection) applied to APR1400. In the final result DBIL set and Datasheet are integrated of room, design bases information, building data(wall, slab, door, window, penetrations). So it can be used for subsequent design automation and design verification. Furthermore, it is expected that APR1400 DBILs data can be used extensively in constructability and design economics analysis through comparison with next generation nuclear power plant.

• Journal of the Korean Chemical Society
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• v.66 no.3
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• pp.209-217
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• 2022

We have developed photosensitive electrochromic smart windows that does not require any transparent conducting oxide (TCO) substrate. In our previous study, we demonstrated that a flexible film-type device made with a low temperature curing WO₃ sol and TiO₂ sol could show a reversible and rapid switching between colored and bleached state via incorporation of platinum catalysts on the surface of WO₃ layer. However, when these devices were exposed to sunlight over 4 hour, it was confirmed that they did not return to fully bleached state in the darkened state due to their overcoloring process. In this study, we added 4-hydroxy-(2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPOL) as an additive to the electrolyte of photosensitive electrochromic device to effectively prevent the undesired overcoloring process. The resulting device with TEMPOL indeed did not undergo excessive coloration and showed great reversibility even after being exposed to sunlight for over 4 hours. Various concentrations of TEMPOL were applied to compare changes in the visible transmittance and coloring/bleaching kinetics of devices. In terms of energetic point of view, we proposed a plausible mechanism of TEMPOL to prevent excessive coloration.

• The Journal of the Acoustical Society of Korea
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• v.42 no.2
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• pp.102-111
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• 2023

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.

• Cartoon and Animation Studies
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• s.27
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• pp.1-30
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• 2012

Oshii Mamoru attempts to project the perception of reality about his own modern world as it is through animation. The precedent studies on Oshii Mamoru put their focus on the point that his works have a tendency to represent the devastation of reality as the image of 'a ruin.' In addition, they gave an impression that Oshii Mamoru's animation has gradually developed to expose the 'realistic taste[beauty]' from the design perspective. However, this study is going to put its focus on the point that Mamoru's works were created as an attempt at finding the subversive possibility of the suppressed modern world under the modern capitalism in the aspect of 'everyday life' of the modern world. First, for its analytical purpose, this study intends to do that by dividing the work into the three layers such as space, body and everyday life. In Chapter II, this study, in relation with the issue of 'space' representation, analyzed the space in into the modern, mechanical, compactly capitalized space and also the space just like a closed circuit having the nature of 'repetition.' In Chapter III, this analyzed that suggests the body moving freely between a human named 'Kildren' and the inhuman from the aspect of character's body, through which Mamoru represents the capitalized, reified body of the modern world. In addition, this analyzed the extreme anxiety facing the body into the reflection of the phenomena of 'anxiety' and 'placelessness' consequent on the labor flexibility of the modern world. In Chapter IV, this study, on the basis of the analysis of layers of space & body, analyzed that the 'everyday life' of the modern world was represented in the respects of 'memory' and 'habit', and in the aspects of Mise-en-Sc$\grave{e}$ne, design and direction. In Chapter V, this rooted out the fact that Mamoru suggested the attempt at 'appropriation' based on his perception of reality about such a modern world. Such a finding includes unearthing the fact that Oshii Mamoru's work is raising a question about how to desert and appropriate the modern space. In conclusion of Chapter VI, this drew the conclusion that Oshii Mamoru's work represented the layer of 'everyday life' while dealing with the post-modern themes shown by the existing modern SF genre, provided the 'window' through which people can perceive the 'modern world radically by recommending an attempt at 'appropriation', and blazed a trail in a new realm of creation for animations.

• Radiation Oncology Journal
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• v.18 no.4
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• pp.345-354
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• 2000

Purpose : Conventional radiation therapy Portal images gives low contrast images. The purpose of this study was to enhance image contrast of a linacgram by developing a low-cost image processing method. Materials and Methods : Chest linacgram was obtained by irradiating humanoid Phantom and scanned using Diagnostic-Pro scanner for image processing. Several types of scan method were used in scanning. These include optical density scan, histogram equalized scan, linear histogram based scan, linear histogram independent scan, linear optical density scan, logarithmic scan, and power square root scan. The histogram distribution of the scanned images were plotted and the ranges of the gray scale were compared among various scan types. The scanned images were then transformed to the gray window by pallette fitting method and the contrast of the reprocessed portal images were evaluated for image improvement. Portal images of patients were also taken at various anatomic sites and the images were processed by Gray Scale Expansion (GSE) method. The patient images were analyzed to examine the feasibility of using the GSE technique in clinic. Results :The histogram distribution showed that minimum and maximum gray scale ranges of 3192 and 21940 were obtained when the image was scanned using logarithmic method and square root method, respectively. Out of 256 gray scale, only 7 to 30$\%$ of the steps were used. After expanding the gray scale to full range, contrast of the portal images were improved. Experiment peformed with patient image showed that improved identification of organs were achieved by GSE in portal images of knee joint, head and neck, lung, and pelvis. Conclusion :Phantom study demonstrated that the GSE technique improved image contrast of a linacgram. This indicates that the decrease in image quality resulting from the dual exposure, could be improved by expanding the gray scale. As a result, the improved technique will make it possible to compare the digitally reconstructed radiographs (DRR) and simulation image for evaluating the patient positioning error.

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.