• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1610-1612
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• 2005

In this paper, the inductive power collector using electromagnetic induction for vehicle such as the PRT(Personal Rapid Transit) system is suggested and some ideas for power collector design to improve the power transfer performance are presented. The proposed the inductive power collector is used for the PRT system, which has a large air-gap and demands a large electrical power capability. But, low output power is generated due to a loosely coupled characteristic of the large air-gap. Therefore, double layer construction of secondary winding, which was divided in half to increase both output current and output voltage was suggested. Also, a model of power collector and parallel winding structure and a model of concentration/decentralization winding are presented, in addition, the performance of inductive power collector to alignment condition between the primary power line and the inductive power transformer was verified by computer simulation of 2kW model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.71-74
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• 2005

This experimental study describes the propagation characteristics and reduction of impulse noises emitted from a high voltage COS(Cut Out Switch) fuse of a transformer. When a high voltage COS fuse becomes a short circuit by the over current. The peak sound Pressure above 150dB(A) is generated. In this study, an impulse noise generator is designed for generating the impulse noises similar to the noise level of COS fuse, which is utilized to test the noise reduction of a reactive silencer. The reactive silencers have been tested for 10 different types with each different porosity, hole diameter and length. From the experimental results, it is found that the reactive silencer has an excellent performance to greatly suppress the impulse noise and that its performance is closely connected with the porosity and hole diameter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.3795-3801
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• 2011

The mathematical simulation of voltage and current waveform of the discharge lamp is useful for the analysis and design of ballasting circuits. This paper proposes a mathematical model which has lamp power and negative voltage drop in discharge lamp. Simulation applying the proposed model has been done, and the results are compared with the experimental results. Furthermore, in the paper, the ballast components(core, transformer) was designed such that high intensity discharge could be optimized for the automotive, by applying a method simulation based design.

• ETRI Journal
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• v.43 no.2
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• pp.299-312
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• 2021

It is necessary to achieve high performance in the task of zero anaphora resolution (ZAR) for completely understanding the texts in Korean, Japanese, Chinese, and various other languages. Deep-learning-based models are being employed for building ZAR systems, owing to the success of deep learning in the recent years. However, the objective of building a high-quality ZAR system is far from being achieved even using these models. To enhance the current ZAR techniques, we fine-tuned a pretrained bidirectional encoder representations from transformers (BERT). Notably, BERT is a general language representation model that enables systems to utilize deep bidirectional contextual information in a natural language text. It extensively exploits the attention mechanism based upon the sequence-transduction model Transformer. In our model, classification is simultaneously performed for all the words in the input word sequence to decide whether each word can be an antecedent. We seek end-to-end learning by disallowing any use of hand-crafted or dependency-parsing features. Experimental results show that compared with other models, our approach can significantly improve the performance of ZAR.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.11-13
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• 2019

This paper proposes a novel high step-up non-isolated DC-DC converter, suitable for regulating dc bus in various inherent low voltage micro sources especially for photovoltaic (PV) and fuel cell sources. This novel high voltage Non-isolated Boost DC-DC converter topology is best replacement, where high voltage conversion ratio is required without the transformer and also need continuous input current. Since the proposed topology utilizes the stack-based structure, the voltage gain, and the efficiency are higher than other conventional non-isolated converters. Switches in this topology is easier to control since its control signal is grounding reference. Also, there is no need of extra gate driver and extra power supply for driver circuit, which reduces the cost and size of system. In order to show the feasibility and practicality of the proposed topology principle operation, steady state analysis and simulation result is presented and analyzed in detail. To verify the performance of proposed converter and theoretical analysis 360W laboratory prototype is implemented.

• Journal of Power Electronics
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• v.19 no.2
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• pp.380-393
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• 2019

Traditional boost converters have difficulty realizing high efficiency and high voltage gain conversion due to 1) extremely large duty cycles, 2) high voltage and current stresses on devices, and 3) low conversion efficiency. Therefore, a function decoupling high voltage gain DC/DC converter composed of a DC transformer (DCX) and an auxiliary converter is proposed. The role of DCX is to realize fixed gain conversion with high efficiency, whereas the role of the auxiliary converter is to regulate the output voltage. In this study, different forms of combined high voltage gain converters are compared and analyzed, and a structure is selected for the function decoupling high voltage gain converter. Then, topologies and control strategies for the DCX and auxiliary converter are discussed. On the basis of the discussion, an optimal design method for circuit parameters is proposed, and design procedures for the DCX are described in detail. Finally, a 400 W experimental prototype based on the proposed optimal design method is built to verify the accuracy of the theoretical analysis. The measured maximum conversion efficiency at rated power is 95.56%.

• Journal of Advanced Engineering and Technology
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• v.11 no.4
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• pp.267-271
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• 2018

A high-frequency therapy device with improved output by modifying a high-frequency stimulator was fabricated. The details of the design include generating part design, high-frequency transformer design, large output FET installation, DC voltage input part design and gate input driver design. Based on the real test using the pork meat, the temperature distributions according to the current electric transfer method, penetration depth, electrode diameter size were measured. In the CET method, the penetration depth was 0.5 cm and in the RET method, the penetration depth was 20 cm or more. In addition, it was confirmed that the temperature rise according to the penetration depth in the RET system was substantially constant, and the temperature rise was remarkable as the electrode diameter was small. As a result, it has been confirmed that the high frequency therapy device is highly affected by various conditions of the electrode.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.5
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• pp.372-375
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• 2021

A three-leg inverter-type isolated DC-DC Converter that can use 220 and 440 V grid input voltages is introduced. The secondary circuit structure of the proposed topology is center-tap, which is the same as the conventional phase-shifted full-bridge converter. However, the primary circuit structure is composed of a three-leg inverter structure and a transformer, in which two primary windings are connected in series. The proposed circuit structure has a wider input voltage range than the conventional phase-shifted full-bridge converter, and the circulating-current on the primary-side is reduced. In addition, the voltage stress at the secondary rectifier is greatly improved, and high efficiency can be achieved at a high input voltage by removing the snubber circuit added to the conventional converter. Prototype converters with input DC of 311 V, output of 622 V, and 50 V and 6 kW class specifications were designed and manufactured to verify the validity of the proposed topology; the experimental results are presented.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.411-427
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• 2022

Digging historical and cultural information from seals in ancient books is of great significance. However, ancient Chinese seal samples are scarce and carving methods are diverse, and traditional digital image processing methods based on greyscale have difficulty achieving superior segmentation and recognition performance. Recently, some deep learning algorithms have been proposed to address this problem; however, current neural networks are difficult to train owing to the lack of datasets. To solve the afore-mentioned problems, we proposed an SEL-RefineMask which combines selector of feature pyramid network (SEL-FPN) with RefineMask to segment and recognize seals. We designed an SEL-FPN to intelligently select a specific layer which represents different scales in the FPN and reduces the number of anchor frames. We performed experiments on some instance segmentation networks as the baseline method, and the top-1 segmentation result of 64.93% is 5.73% higher than that of humans. The top-1 result of the SEL-RefineMask network reached 67.96% which surpassed the baseline results. After segmentation, a vision transformer was used to recognize the segmentation output, and the accuracy reached 91%. Furthermore, a dataset of seals in ancient Chinese books (SACB) for segmentation and small seal font (SSF) for recognition were established which are publicly available on the website.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.