• Progress in Superconductivity and Cryogenics
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• v.24 no.3
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• pp.19-23
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• 2022

We have been developing a magnetic separation device that can be used in low magnetic fields for paramagnetic materials. Magnetic separation of paramagnetic particles with a small particle size is desired for volume reduction of contaminated soil in Fukushima or separation of iron scale from water supply system in power plants. However, the implementation of the system has been difficult due to the needed magnetic fields is high for paramagnetic materials. This is because there was a problem in installing such a magnet in the site. Therefore, we have developed a magnetic separation system that combines a selection tube and magnetic separation that can separate small sized paramagnetic particles in a low magnetic field. The selection tube is a technique for classifying the suspended particles by utilizing the phenomenon that the suspended particles come to rest when the gravity acting on the particles and the drag force are balanced when the suspension is flowed upward. In the balanced condition, they can be captured with even small magnetic forces. In this study, we calculated the particle size of paramagnetic particles trapped in a selection tube in a high gradient magnetic field. As a result, the combination of the selection tube and HGMS (High Gradient Magnetic Separation-system) can separate small sized paramagnetic particles under low magnetic field with high efficiency, and this paper shows its potential application.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.75-81
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• 2023

In this study, we design an optimized Graphics Processing Unit (GPU)-based GNSS signal processing technique with the goal of designing and implementing a GNSS Software Defined Receiver (SDR) that can operate in real time all-in-view mode under multi-constellation and multi-frequency signal environment. In the proposed structure the correlators of the existing GNSS SDR are processed by the GPU. We designed a memory structure and processing method that can minimize memory access bottlenecks and optimize the GPU memory resource distribution. The designed GNSS SDR can select and operate only the desired GNSS or desired satellite signals by user input. Also, parameters such as the number of quantization bits, sampling rate, and number of signal tracking arms can be selected. The computing capability of the designed GPU-based GNSS SDR was evaluated and it was confirmed that up to 2400 channels can be processed in real time. As a result, the GPU-based GNSS SDR has sufficient performance to operate in real-time all-in-view mode. In future studies, it will be used for more diverse GNSS signal processing and will be applied to multipath effect analysis using more tracking arms.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.518-528
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• 2022

Virtual Reality (VR) has been widely used in various applications to generate realistic virtual environments. A sense of immersion can be increased by providing additional stimuli such as tactile sensation to VR contents. However, it is still challenging to provide a realistic feel for the wind blowing over the whole body by smoothly controlling the airflow. To address this issue, we employ a household electric fan as a wind generating device to provide users with wind experience in VR environments. The wind generating device targets the whole body to mimic the wind we feel outside in our daily life. To do so, we present a low-cost method to smoothly control household fan speed using an Arduino microcontroller. Here, we use the Sinusoidal Pulse Width Modulation (SPWM) technique to generate the sinusoidal voltage required to drive the fan motor. Our experimental results show how Variable Voltage Variable Frequency (VVVF) is implemented at a low cost using our method for household fan speed control. The results can be applied to various VR applications to enhance the sense of immersion by providing users with realistic wind.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.194-202
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• 2022

The use of public Wi-Fi has increased in recent years with many people like to spend their time outside in malls or café shops which provide public Wi-Fi for their customers. However, since the public Wi-Fi can be accessed from any device the security of public Wi-Fi plays a big role to prevent the stealing of information by an attacker with methods and techniques such as WPA, WPA2 and WPA3. However, it is well known to the attackers that these methods are not difficult to get hacked by the attacker device to take the client precious information. Some researches were done in increasing the security of public Wi-Fi each with their own different technique or algorithm to provide more secure connection to the public Wi-Fi and prevent any unauthorized user to connect to avoid stealing the data of another legal user. Theses research paper are evaluated to learn which method excel in protecting the public Wi-Fi security by giving an analysis to the methods provided by the research paper with comparing the pros and cons of each algorithm. Moreover, the research displays that there are methods to actually provide security to the public Wi-Fi with each being very different in implementation.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.199-214
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• 2020

An important technique of the present invention is primarily to parallel light detection, self-pulse therapy after diagnosis. Herpes zoster is a disease caused by varicella zoster virus, and the virus that has been latent in the dorsal root ganglion that controls the skin segment loses its immune system and physically damages it. It is an acute skin disease in which acute pain and bullous rash occur along the sensory ganglia, which are rehab by inducers such as malignant tumors. Dorsal root ganglion after complete recovery of varicella, relapsed after incubation in brain ganglion, latent virus sometimes suppressed activity by cell mediated immunity, and in cell ganglion with reduced cellular immunity. It proliferates and destroys neurons, causing pain while forming a rash and blisters. This can reduce cell necrosis and increase the phagocytosis and enzymatic activity through the movement of ions through the cell membrane, depolarization and membrane potential change, growth factor secretion, calcium ion transfer, chondrocyte synthesis, etc., And may offer treatment options for lesions of herpes zoster and post-herpetic neuralgia (PHN).Therefore, according to the present research, the diagnosis and treatment device of treating paing for herpes zoster and post-herpetic pain can be implemented in the early stage of herpes zoster, and conventional analgesic regulation, anti-inflammatory effect, post-herpetic neuralgia.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.81-94
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• 2022

This study sets the research goal of reducing energy consumption which 'H' University Industry-University Cooperation Foundation and resident companies are concerned with, as well as conducting policy research and data analysis. We tried to present a solution to the problem using the technique. The algorithm showing the greatest reliability in the power of the model for the analysis algorithm of this paper was selected, and the power consumption trend curves per minute and hour were confirmed through predictive analysis while applying the algorithm, as well as confirming the singularity of excessive energy consumption. Through an additional sub-sensor analysis, the singularity of energy consumption of the unit was identified more precisely in the facility rather than in the building unit. Through this, this paper presents a system building model for real-time monitoring of campus power usage, and expands the data center and model for implementation. Furthermore, by presenting the possibility of expanding the field through research on the integration of mobile applications and IoT hardware, this study will provide school authorities and resident companies with specific solutions necessary to continuously solve data-based field problems.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.169-179
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• 2021

This study was conducted to develop and apply clinical nursing practice training simulation program using Standardized Patient for Nursing Students focused on infectious respiratory disease. This study is descriptive methodological study. Through prior consideration of documents and educational task of infectious respiratory disease was conducted with interview of clinical specialists of infection control managers. Development of educational task for infectious respiratory disease for Nursing Students went through the content validity. Finally, 10 educational tasks are developed 'knowledge of respiratory infections disease', 'hand washing', 'put on mask', 'lead to put on mask to patients and caregiver', 'intravenous injection via 3way', 'surgical aseptic technique', 'sterilization medical instrument', 'management of contaminated linen', 'infected personnel management manual'. The infectious respiratory disease simulation program was developed based on the ADDIE model and proceeded to 4 steps of analysis, design, development, implementation. The infection control education program included lectures (20 min), skill training (20 min), simulation using standardized patient (20 min), and debriefing (40 min), The collected data were analyzed by descriptive statistics with SPSS program for version 23.0. The results of this study confirmed that the clinical nursing practice training simulation program using standardized patients was effective in infectious respiratory disease of the nursing college students in knowledge of infectious respiratory disease and clinical nursing performance. we found this practical training program for nursing college students to improve knowledge and clinical competency of infection control. we expected that this developed program could be applied to practical training for various infectious control.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.163-168
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• 2023

In this paper, a novel platform for chemical sensing and biosensing is presented. The working principle is based on the coupling efficiency and interference properties of optical directional coupler (DC) and multimode interference coupler (MMIC). It has been realized using planar technology to allow integration on a silicon substrate. Firstly, the dispersion curves of DC and MMIC is described, and the design specification of an optimized slot optical waveguide to increase waveguide sensitivity is selected. Next, the sensor response to the refractive index change of sensing analyte is numerically simulated. The numerical results reveal that high effective index change per refractive index unit (RIU) change of analyte is obtained, and the sensitivity can be tuned using the DC and MMIC design technique.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.25-25
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• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4751-4758
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• 2022

Two-phase flow may almost exist in every branch of the energy industry. For the corresponding engineering design, it is very essential and crucial to monitor flow patterns and their transitions accurately. With the high-speed development and success of deep learning based on convolutional neural network (CNN), the study of flow pattern identification recently almost focused on this methodology. Additionally, the photographing technique has attractive implementation features as well, since it is normally considerably less expensive than other techniques. The development of such a two-phase flow pattern online monitoring system is the objective of this work, which seldom studied before. The ongoing preliminary engineering design (including hardware and software) of the system are introduced. The flow pattern identification method based on CNNs and transfer learning was discussed in detail. Several potential CNN candidates such as ALexNet, VggNet16 and ResNets were introduced and compared with each other based on a flow pattern dataset. According to the results, ResNet50 is the most promising CNN network for the system owing to its high precision, fast classification and strong robustness. This work can be a reference for the online monitoring system design in the energy system.