• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.52-57
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• 2018

The purpose of this paper is to develop simulations that can be used for virtual education in dentistry. The virtual education to be developed will be developed with clinical training and actual case data of tooth extraction. This development goal is to allow dental students to learn the necessary surgical techniques at the point of their choice, not going into the operating room, away from time, space, and physical limits. I want to develop content using VR. Oculus Rift HMD, Optical Based Outside-in Tracking System, Oculus Touch Motion Controller, and Headset as Input / Output Device. In this configuration, the optimization method is applied convergent, and when the operation of the VR contents is performed, the content data is extracted from the interaction analysis formed in the VR engine, and the data is processed by the content algorithm. It also computes events and dental operations generated within the 3D engine programming and generates corresponding events through data processing according to the input signal. The visualization information is output to the HMD using the rendering information. In addition, the operating room environment was constructed by studying lighting and material for actual operating room environment. We applied the ratio of actual space to virtual space and the ratio between character and actual person to create a spatial composition at a similar rate to actual space.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.89-99
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• 2018

Downtime and malfunction of industrial rotor machines represents a crucial cost burden and productivity loss. Fault diagnosis of this equipment has recently been carried out to detect their fault(s) and cause(s) by using fault classification methods. However, these methods are of limited use in detecting rotor faults because of their hypersensitivity to unexpected and different equipment conditions individually. These limitations tend to affect the accuracy of fault classification since fault-related features calculated from vibration signal are moved to other regions or changed. To improve the limited diagnosis accuracy of existing methods, we propose a new approach for fault diagnosis of rotor machines based on the model generated by supervised learning. Our work is based on feature residual values from vibration signals as fault indices. Our diagnostic model is a robust and flexible process that, once learned from historical data only one time, allows it to apply to different target systems without optimization of algorithms. The performance of the proposed method was evaluated by comparing its results with conventional methods for fault diagnosis of rotor machines. The experimental results show that the proposed method can be used to achieve better fault diagnosis, even when applied to systems with different normal-state signals, scales, and structures, without tuning or the use of a complementary algorithm. The effectiveness of the method was assessed by simulation using various rotor machine models.

• Journal of Power Electronics
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• v.19 no.1
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• pp.119-133
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• 2019

Although the dual modulation wave method can solve the low-frequency neutral point potential (NPP) fluctuation problem for three-level neutral point clamped converters, it also increases the switching frequency and limits the zero-sequence voltage. That makes it harmful when dealing with the NPP drift problem if the converter suffers from a long dead time or asymmetric loads. By introducing two degrees of freedom (2-DOF), an NPP control based on a search optimization method can demonstrate its ability to cope with the above mentioned two types of NPP problems. However, the amount of calculations for obtaining an optimal 2-DOF is so large that the method cannot be applied to certain industrial applications with an inexpensive digital signal processor. In this paper, a novel optimal 2-DOF-based NPP control is proposed. The relationships between the NPP and the 2-DOF are analyzed and a method for directly determining the optimal 2-DOF is also discussed. Using a direct calculation method, the amount of calculations is significantly reduced. In addition, the proposed method is able to maintain the strongest control ability for the two types of NPP problems. Finally, some experimental results are given to confirm the validity and feasibility of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5898-5916
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• 2018

In this paper, the downlink performance of multi-cell distributed antenna systems (DAS) with a single user in each cell is investigated. Assuming the channel state information is available at the transmitter, four transmission modes are formulated as combinations of remote antenna units (RAUs) selection and cooperative transmission, namely, non-cooperative transmission without RAU selection (NCT), cooperative transmission without RAU selection (CT), non-cooperative transmission with RAU selection (NCT_RAUS), and cooperative transmission with RAU selection (CT_RAUS). By using probability theory, the cumulative distribution function (CDF) of a user's signal to interference plus noise ratio (SINR) and the system ergodic capacity under the above four modes are determined, and their closed-form expressions are obtained. Furthermore, the system energy efficiency (EE) is studied by introducing a realistic power consumption model of DAS. An expression for determining EE is formulated, and the closed-form tradeoff relationship between spectral efficiency (SE) and EE is derived as well. Simulation results demonstrate their consistency with the theoretical analysis and reveal the factors constraining system EE, which provide a scientific basis for future design and optimization of DAS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2668-2717
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• 2021

Demands for high-speed wireless data services grow rapidly. It is a big challenge to increasing the network capacity operating on licensed spectrum resources. Unlicensed spectrum cellular networks have been proposed as a solution in response to severe spectrum shortage. Licensed Assisted Access (LAA) was standardized by 3GPP, aiming to deliver data services through unlicensed 5 GHz spectrum. Furthermore, the 3GPP proposed 5G New Radio-Unlicensed (NR-U) study item. On the other hand, artificial intelligence (AI) has attracted enormous attention to implement 5G and beyond systems, which is known as Intelligent Radio (IR). To tackle the challenges of unlicensed spectrum networks in 4G/5G/B5G systems, a lot of works have been done, focusing on using Machine Learning (ML) to support resource allocation in LTE-LAA/NR-U and Wi-Fi coexistence environments. Generally speaking, ML techniques are used in IR based on statistical models established for solving specific optimization problems. In this paper, we aim to conduct a comprehensive survey on the recent research efforts related to unlicensed cellular networks and IR technologies, which work jointly to implement 5G and beyond wireless networks. Furthermore, we introduce a positioning assisted LTE-LAA system based on the difference in received signal strength (DRSS) to allocate resources among UEs. We will also discuss some open issues and challenges for future research on the IR applications in unlicensed cellular networks.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.1-12
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• 2021

Reactor Coolant Pump (RCP) is core part of nuclear power plant to provide the forced circulation of reactor coolant for the removal of core heat. Properly monitoring vibration of RCP is a key activity of a successful predictive maintenance and can lead to a decrease in failure, optimization of machine performance, and a reduction of repair and maintenance costs. Here, we developed real-time RCP Vibration Analysis System (VAS) that web based platform using NoSQL DB (Mongo DB) to handle vibration data of RCP. In this paper, we explain how to implement digital signal process of vibration data from time domain to frequency domain using Fast Fourier transform and how to design NoSQL DB structure, how to implement web service using Java spring framework, JavaScript, High-Chart. We have implement various plot according to standard of the American Society of Mechanical Engineers (ASME) and it can show on web browser based on HTML 5. This data analysis platform shows a upgraded method to real-time analyze vibration data and easily uses without specialist. Furthermore to get better precision we have plan apply to additional machine learning technology.

• ETRI Journal
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• v.43 no.1
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• pp.7-16
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• 2021

Noncontiguous orthogonal frequency division multiplexing (NC-OFDM)-based cognitive radio (CR) systems achieve highly efficient spectrum utilization by transmitting unlicensed users' data on subcarriers of licensed users' data when they are free. However, there are two disadvantages to the NC-OFDM system: out-of-band power (OBP) and a high peak-to-average power ratio (PAPR). OBP arises due to side lobes of an NC-OFDM signal in the frequency domain, and it interferes with the spectrum for unlicensed users. A high PAPR occurs due to the inverse fast Fourier transform (IFFT) block used in an NC-OFDM system, and it induces nonlinear effects in power amplifiers. In this study, we propose an algorithm called "Alternative Projections onto Convex and Non-Convex Sets" that reduces the OBP and PAPR simultaneously. The alternate projections are performed onto these sets to form an iteration, and it converges to the specified limits of in-band-power, peak amplitude, and OBP. Furthermore, simulations show that the bit error rate performance is not degraded while reducing OBP and PAPR.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.41-49
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• 2021

In electronic warfare, beamforming using multiple antennas is applied for effective transmission of electronic attack signals. In order to perform an electronic attack against multiple threats using the same frequency resource, it is necessary to apply a multi-beam transmission algorithm that has been studied in wireless communication systems. For electronic attacks against multiple threats, this paper presents an MMSE(Minimum Mean-Squared Error) beam-forming technique based on the prior location information of threats and an optimization method for power allocation. In addition, the performance of the proposed method is evaluated and received signals of multiple threats are compared and analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3780-3797
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• 2022

The estimation of radio map (RM) is a fundamental and critical task for the network planning and optimization performance of mobile communication. In this paper, a RM estimation method is proposed based on a deep dual learning structure. This method can simultaneously and accurately reconstruct the urban building map (UBM) and estimate the RM of the whole cell by only part of the measured reference signal receiving power (RSRP). Our proposed method implements UBM reconstruction task and RM estimation task by constructing a dual U-Net-based structure, which is named RadioCycle. RadioCycle jointly trains two symmetric generators of the dual structure. Further, to solve the problem of interference negative transfer in generators trained jointly for two different tasks, RadioCycle introduces a dynamic weighted averaging method to dynamically balance the learning rate of these two generators in the joint training. Eventually, the experiments demonstrate that on the UBM reconstruction task, RadioCycle achieves an F1 score of 0.950, and on the RM estimation task, RadioCycle achieves a root mean square error of 0.069. Therefore, RadioCycle can estimate both the RM and the UBM in a cell with measured RSRP for only 20% of the whole cell.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.307-310
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• 2021

In the recent years, studies using Computer-Aided Diagnostics(CAD) have been actively conducted, such as signal and image processing technology using breast ultrasound images, automatic image optimization technology, and automatic detection and classification of breast masses. As computer diagnostic technology is developed, it is expected that early detection of cancer will proceed accurately and quickly, reducing health insurance and test ice for patients, and eliminating anxiety about biopsy. In this paper, a quantitative analysis of tumors was conducted in ultrasound images using a gray level co-occurrence matrix(GLCM) to experiment with the possibility of use for computer assistance diagnosis.