• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.50-55
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• 2019

Recently Ransomware attacks are continuously increasing, and new Ransomware, which is difficult to detect just with a basic vaccine, continuously has its upward trend. Various solutions for Ransomware have been developed and applied. However, due to the disadvantages and limitations of existing solutions, damage caused by Ransomware has not been reduced. Ransomware is attacking various platforms no matter what platform it is, such as Windows, Linux, servers, IoT devices, and block chains. However, most existing solutions for Ransomware are difficult to apply to various platforms, and there is a limit that they are dependent on only some specific platforms while operating. This study analyzes the problems of existing Ransomware detection solutions and proposes the onboard module based Ransomware detection system; after the system defines the function of necessary elements through analyzing requirements that can actually reduce the damage caused by the Ransomware from the viewpoint of users, it supports various OS without pre-installation and is able to restore data even after being infected. We checked the feasibility of each function of the proposed system through the analysis of the existing technology and verified the suitability of the proposed techniques to meet the user's requirements through the questionnaire survey of a total of 264 users of personal and corporate PC users. As a result of statistical analysis of the questionnaire results, it was found that the score of intent to introduce the system was at 6.3 or more which appeared to be good, and the score of intent to change from existing solution to the proposed system was at 6.0 which appeared to be very high.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.43-50
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• 2021

In this paper, we design and implement KITNESS, a windows application that feeds back the accuracy of fitness motions based on Kinect sensors. The feature of this application is to use Kinect's camera and joint recognition sensor to give feedback to the user to exercise in the correct fitness position. At this time, the distance between the user and the Kinect is measured using Kinect's IR Emitter and IR Depth Sensor, and the joint, which is the user's joint position, and the Skeleton data of each joint are measured. Using this data, a certain distance is calculated for each joint position and posture of the user, and the accuracy of the posture is determined. And it is implemented so that users can check their posture through Kinect's RGB camera. That is, if the user's posture is correct, the skeleton information is displayed as a green line, and if it is not correct, the inaccurate part is displayed as a red line to inform intuitively. Through this application, the user receives feedback on the accuracy of the exercise position, so he can exercise himself in the correct position. This application classifies the exercise area into three areas: neck, waist, and leg, and increases the recognition rate of Kinect by excluding positions that Kinect does not recognize due to overlapping joints in the position of each exercise area. And at the end of the application, the last exercise is shown as an image for 5 seconds to inspire a sense of accomplishment and to continuously exercise.

• Journal of the Korea Computer Graphics Society
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• v.27 no.1
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• pp.9-17
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• 2021

In this paper, we present a simple and fast supervised learning framework based on model predictive control so as to learn motion controllers for a physic-based character to track given example motions. The proposed framework is composed of two components: training data generation and offline learning. Given an example motion, the former component stochastically controls the character motion with an optimal controller while repeatedly updating the controller for tracking the example motion through model predictive control over a time window from the current state of the character to a near future state. The repeated update of the optimal controller and the stochastic control make it possible to effectively explore various states that the character may have while mimicking the example motion and collect useful training data for supervised learning. Once all the training data is generated, the latter component normalizes the data to remove the disparity for magnitude and units inherent in the data and trains an artificial neural network with a simple architecture for a controller. The experimental results for walking and running motions demonstrate how effectively and fast the proposed framework produces physics-based motion controllers.

• 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.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.3
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• pp.49-53
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• 2022

Ultra-thin glass (UTG) has been widely used in foldable display as a cover window for the protection of display and has a great potential for rollable display and various flexible electronics. The foldable display is under impact loading by bending and touch pen and exposed to other external impact loads such as drop while people are using it. These external impact loads can cause cracks or fracture to UTG because it is very thin under 100 ㎛ as well as brittle. Cracking and fracture lead to severe reliability problems for foldable smartphone. Thus, this study constructs finite element analysis (FEA) model for the pen drop test which can measure the impact resistance of UTG and conducts mechanical modeling to improve the reliability of UTG under impact loading. When a protective layer is placed to an upper layer or lower layer of UTG layer, stress mechanism which is applied to the UTG layer by pen drop is analyzed and an optimized structure is suggested for reliability improvement of UTG layer. Furthermore, maximum principal stress values applied at the UTG layer are analyzed according to pen drop height to obtain maximum pen drop height based on the strength of UTG.

• Korean Journal of Optics and Photonics
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• v.33 no.5
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• pp.210-217
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• 2022

In this paper, a study is conducted on the acceptable tolerance of an alignment device to reduce the optical loss caused by the alignment tolerance of a window hermetic optical connector. To increase the transmission distance of optical signals and fiber-optic communication systems, it is necessary to maintain and improve the high optical efficiency of the connectors used to bond optical fibers. In the case of the window hermetic optical connector, the optical system is aligned through an alignment device. At this time, since the two connectors are used together, each component is fixed, and further alignment is impossible. The alignment tolerance of the housing system and pin used to align the optical system of the connector causes optical loss, leading to serious problems in the fiber-optic communication system. Thus, to find the acceptable tolerance required for manufacturing the optical-connector alignment device, tolerance analysis is performed on the components of the optical connector, such as the ball lens and the window. We also implement single-mode and multimode optical-connector systems, respectively. Based on the results, we determine an acceptable tolerance value for the alignment device.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.131-139
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• 2023

In this study, we are purposed to find the educational effect of practical training using a 3D printed structure-based blind box on multidimensional radiographic image interpretation. The subjects were 83 (male: 49, female: 34) 2nd year radiological science students who participated in the digital medical imaging practice that was conducted for 3 years from 2020 to 2022. The learning method used 3D printing technology to print out the inside structure of the blind box designed by itself. After taking X-rays 3 times (x, y, z axis), the structure images in the blind box were analyzed for each small group. We made the 3D structure that was self-made with clay based on our 2D radiographic images. After taking X-rays of the 3D structure, it was compared whether it matches the structural image of the blind box. The educational effect for the practical training surveyed class faithfulness, radiographic image interpretation ability (attenuation concept, contrast concept, windowing concept, 3-dimensional reading ability), class satisfaction (interest, external recommendation, immersion) on a 5-point Likert scale as an anonymous student self-writing method. As a result, all evaluation items had high positive effects without significant differences between males and females. Practical education using blind boxes is a meaningful example of radiology education technology using 3D printing technology, and it is expected to be used as content to improve students' problem-solving skills and increase satisfaction with major subjects.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.6
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• pp.219-224
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• 2022

CaF₂ single crystal has a large band gap (12 eV), and it is used for optical windows, prisms, and lenses due to its excellent transmittance in a wide wavelength range and low refractive index. Moreover, it is expected to be one of the materials for ultraviolet transmissive laser optical components. CaF₂ belongs to the fluoride compounds and has a face-centered cubic (FCC) structure with three sub-lattices. The representative method for CaF₂ single crystal growth is Czochralski, which method has the advantages of high production efficiency and the ability to make large crystals. In this study, X-ray diffraction (XRD), X-ray rocking curves (XRC) measurement, and chemical etching were performed to analyze the crystallinity and defect density of the CaF₂ single crystals, grown by the Czochralski method. Fourier-transform infrared spectroscopy (FT-IR) and UV-VIS-NIR spectroscopy systems were used to investigate the optical properties of the CaF₂ crystal. The provability of various applications, including UV application, was systematically investigated with various analysis results.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

• 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.