• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.1
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• pp.61-67
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• 2020

This study deals with the modulation index (MI) of a voltage source converter (VSC) HVDC system based on a modular multilevel converter (MMC). In the two-level converter, the purpose of the MI is to maximize the achievable AC voltage of the converter from a fixed DC voltage. Unlike that in a two-level converter, the MI in the MMC topology plays a role in making the converter a voltage source using a capacitor. The circulating current in the MMC distorts the AC voltage reference, and the distortion affects the MI. In addition, the AC network conditions, such as AC voltage variation and reactive power, affect the MI. Therefore, the MI should be optimized with consideration of internal and external factors. This study proposes a method to optimize the MI of an MMC HVDC system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05c
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• pp.41-44
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• 2003

As the device feature size is reduced to the deep sub-micron regime, the chemical mechanical polishing (CMP) technology is widely recognized as the most promising method to achieve the global planarization of the multilevel interconnection for ULSI applications. However, cost of ownership (COO) and cost of consumables (COC) were relatively increased because of expensive slurry. In this paper, the effects of different slurry composition on the oxide CMP characteristics were investigated to obtain the higher removal rate and lower non-uniformity. We prepared the various kinds of slurry. In order to save the costs of slurry, the original slurry was diluted by de-ionized water (DIW). And then, alunima abrasives were added in the diluted slurry in order to promote the mechanical force of diluted slurry.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1240-1242
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• 1996

In a still mill, the effective surface defect inspection algorithm is necessary. For this purpose, this paper proposed the preprocessing algorithm for surface defect inspection of cold mill strip. This consists of live steps. They are edge detection, binarizing, noise deletion, combining of fragmented defect and selecting the largest defect. Especially, binarizing is a critical problem. Bemuse the performance of the preprocessing is largely depend on the binarized image. So, we develope the adaptive thresholding method, which is multilevel thresholding. The thresholding value is varied according to the mean graylevel value of each test image. To investigate the performance of the proposed algorithm, we classified the detected defect using neural network. The test image is 20 defect images captured at German Sick Co. This algorithm is proved to have good property in cold mill strip surface inspection.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• Current Optics and Photonics
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• v.2 no.6
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• pp.532-539
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• 2018

Multiple LED arrays can be utilized in visible-light communication (VLC) to improve communication efficiency, while maintaining smart illumination functionality through dimming control. This paper proposes a modulation scheme called "Spatial Intensity Modulation" (SIM), where the effective number of turned-on LEDs is employed for data modulation and dimming control in VLC systems. Unlike the conventional pulse-amplitude modulation (PAM), symbol intensity levels are not determined by the amplitude levels of a VLC signal from each LED, but by counting the number of turned-on LEDs, illuminating with a single amplitude level. Because the intensity of a SIM symbol and the target dimming level are determined solely in the spatial domain, the problems of conventional PAM-based VLC and related MIMO VLC schemes, such as unstable dimming control, non uniform illumination functionality, and burdens of channel prediction, can be solved. By varying the number and formation of turned-on LEDs around the target dimming level in time, the proposed SIM scheme guarantees homogeneous illumination over a target area. An analysis of the dimming capacity, which is the achievable communication rate under the target dimming level in VLC, is provided by deriving the turn-on probability to maximize the entropy of the SIM-based VLC system. In addition, a practical design of dimmable SIM scheme applying the multilevel inverse source coding (MISC) method is proposed. The simulation results under a range of parameters provide baseline data to verify the performance of the proposed dimmable SIM scheme and applications in real systems.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.989-998
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• 2020

Recently, demands for large-capacity electronic loads are increasing in various industries such as a reliability test for the performance of a DC power supply device or a dummy-load for improving the stability of an independent microgrid to be actively built in the future. The electronic load required in these various fields requires an operation such as a continuously variable resistance load while minimizing the switching harmonic component generated in the electric load current in order to reduce the influence of interference from the load peripheral device. Electronic loads require a system that minimizes switching current ripple for load control. Therefore, in this paper, we propose a three-level module converter structure to reduce the current ripple of an electronic load, and a multilevel interleaved power converter topology to reduce the current ripple. The validity of the proposed electronic load, 3-level 6 interleaver converter, was verified by simulation and experiment. In addition, the user's convenience was provided by applying the emotional command curve interface method.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.6
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• pp.498-506
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• 2022

This study proposes a design methodology for bidirectional, series-resonant, dual-active bridge (SRDAB) converters. The circuit parameters of the SRDAB converters are designed by considering the output power and efficiency of the converter. The proposed method can be used to design a high-power, high-efficiency SRDAB converter. A voltage controller is employed to manipulate the output voltage of the converter, and the controller gains are selected using the transfer function and frequency response of the controller. Simulation results show that the output power of the designed SRDAB converter is 2 kW per converter module as designed. In addition, the performance of the voltage controller is evaluated using the simulation and experimental results. The output voltage follows the reference voltage within 10 ms under the step change of the reference command. The output voltage also follows the reference voltage under the step load change. The efficiency of the designed SRDAB converter is 95.6%.

• Child Health Nursing Research
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• v.29 no.1
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• pp.84-95
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• 2023

Purpose: This study aimed to conduct a concept analysis of health-related quality of life in children with epilepsy to promote conceptual clarification and facilitate mutual understanding of the concept. Methods: Walker and Avant's concept analysis method was adopted. Results: Health-related quality of life in children with epilepsy consists of six attributes: health status, inner strength, close relationships, resource-rich community, social acceptance, and changeability. According to the ecological system paradigm, these attributes are structured into five dimensions: organism, microsystem, macrosystem, exosystem, and chronosystem. These dimensions provide a comprehensive approach to the relationship between children with epilepsy and their environment. Epilepsy and interactions with multilevel ecological systems that are directly and indirectly related to children with epilepsy precede the concept, followed by positive and negative affective responses. Conclusion: The findings of this study may support effective communication in various practice settings, thereby contributing to the health and well-being of children with epilepsy, as well as the development and expansion of interventions to improve their health-related quality of life.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4408-4425
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• 2023

Alarm flood due to abnormality propagation is the most difficult alarm overloading problem in nuclear power plants (NPPs). Root-cause analysis is suggested to help operators in understand emergency events and plant status. Multilevel Flow Modeling (MFM) has been extensively applied in alarm management by virtue of the capability of explaining causal dependencies among alarms. However, there has never been a technique that can identify the actual root cause for complex alarm situations. This paper presents an automated root-cause analysis system based on MFM. The causal reasoning algorithm is first applied to identify several possible root causes that can lead to massive alarms. A novel root-cause ranking algorithm can subsequently be used to isolate the most likely faults from the other root-cause candidates. The proposed method is validated on a pressurized water reactor (PWR) simulator at HAMMLAB. The results show that the actual root cause is accurately identified for every tested operating scenario. The automation of root-cause identification and ranking affords the opportunity of real-time alarm analysis. It is believed that the study can further improve the situation awareness of operators in the alarm flooding situation.