• 대한전기학회논문지
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• 제41권6호
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• pp.600-606
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• 1992

The series connection of power switching semiconductor elements is essential when a high voltage converter is made, so researches are being conducted to further develop this technology. In the series connection of power switching semiconductor elements, the main problem is that simultaneous conduction at turn-on and simultaneous blocking at turn-off together with voltage balancing are unattainable because of the difference of their switching characteristics. In this paper a novel series connection algorithm is proposed, which can implement not only the synchronization of the points of turn-on and turn-off time but the dynamic voltage balancing in spite of the difference of each switching characteristics. The proposed method is that the compensated control signal is attained from the voltage feedback signal and applied to the series-connected power transistors independently. Computer simulation and experimental results verify its validity.

• 대한수학회논문집
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• 제20권2호
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• pp.395-403
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• 2005

The authors aim mainly at giving fifteen three-term contiguous relations for the basic hypergeometric series $series\;_2{\phi}_1$ corresponding to Gauss's contiguous relations for the hypergeometric series $series\;_2F_1$ given in Rainville([6], p.71). They also apply them to obtain two summation formulas closely related to a known q-analogue of Kummer's theorem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.195-197
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• 1998

The large scale industry needs high voltage converters. Therefore series connection of power semiconductor devices is necessary. It is important to prevent a device induced the overvoltage above ratings by proper voltage balancing in the field of IGBT series connection. In addition, the overvoltage induced by a stray inductance has to be limited in the high power circuit. This paper proposes a new gate control scheme which can balance the voltage properly and limit the overshoot by control the slope of collector voltage under series connected IGBT turn-off transient. The propose gate control scheme limits the overvoltage by sensing the collector voltage and controlling the gate signal actively. The new series connected IGBT gate driver is made and its validity is verified by the experimental results for series connected IGBT circuit.

• 한국전기전자재료학회논문지
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• 제25권11호
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• pp.930-937
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• 2012

Newly developed Series hybrid low-floor articulated vehicle which can meet both road and railway running conditions. It has the rated driving speed of 80 km/h and three driving modes with hybrid(engine+battery) driving mode, engine driving mode, battery driving mode. The battery driving mode requires the several 10 km running without additional charging operation. The vehicle has been equipped with LPB (lithium polymer battery) pack for the series hybrid propulsion system. LPB pack consists of 168 cells (3.7 V in a cell, 80 Ah) in series, DC Circuit breaker, mechanical rack, BMS (battery management system). This paper has shown the design process of LPB pack and application to the vehicle. Driving results in the road was successful to be satisfied with the requirement of the series hybrid vehicle.

• 전력전자학회논문지
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• 제26권1호
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• pp.32-37
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• 2021

This study proposes a DC series arc fault detector using a frequency analysis method called the discrete wavelet transform (DWT), in which the processing speed of the DWT algorithm is improved effectively. The processing time can be shortened because of the time characteristic of the DWT result. The performance of the developed DC series arc fault detector for a large photovoltaic system is verified with various DC series arc generation conditions. Successful DC series arc detection and improved calculation time were both demonstrated through the measured actual arc experimental result.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.185-192
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• 2022

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.

• Mycobiology
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• 제50권1호
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• pp.96-98
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• 2022

The Aspergilli of the section Nidulantes series Versicolores are among the most recurrent molds in indoor environments. These species cause damage to the quality of air. Indeed, they are responsible for allergies, aggravation of asthma and can even cause infections in immunocompromised patients. Molds belonging to the Versicolores series also produce sterigmatocystin, a mycotoxin classified as potential human carcinogen by the International Agency for Research on Cancer (group 2B). Here, we provide for the first time the genome of three species of the series Versicolores: Aspergillus creber, Aspergillus jensenii and Aspergillus protuberus which are the most abundant species of this series in bioaerosols. The genomes of these three species could be assembled with a percentage of completeness of 97.02%, 96.21% and 95.35% for Aspergillus creber, A. jensenii and A. protuberus respectively. These data will allow to study the genes and gene clusters responsible for the expression of virulence factors, the biosynthesis of mycotoxins and the proliferation of these ubiquitous and recurrent molds.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.85-88
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• 2021

제조 설비에서 짧은 주기로 수집된 제조 데이터는 시간 간격이 일정하지 않은 불규칙 샘플링 시계열이고 값이 불안정하여 큰 분산을 가지는 경우가 많다. 본 논문에서는 단순이동평균법을 이용하여 불규칙 시계열의 시간 간격을 일정하게 보정함과 동시에 값의 분산을 줄이는 보정 기법을 제안하고, 제안된 보정 기법이 생산 설비의 이상탐지의 성능 향상에 효과가 있음을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.210-212
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• 2022

제조업에서 생산 설비의 상태를 모니터링하기 위해 각종 센서를 부착하고 있으며, 이를 통해 획득된 데이터의 경우 시계열 데이터인 경우가 많다. 생산 설비의 이상 여부를 판단하기 위해서는시계열 데이터로부터 패턴을 추출하는 과정이 선행되어야 하며 다양한 방법이 연구되고 있다. 본 논문에서는 수집된 다변량 시계열 데이터로부터 패턴을 추출하기 위해 매트릭스 프로파일 알고리즘을 적용하였으며, 이를 통해 현재 CNC 머신으로부터 수집 중인 다중 센서 데이터의 패턴을 추출하였다.

• Journal of applied mathematics & informatics
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• 제41권5호
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• pp.1057-1069
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• 2023

In this paper, we have determined the degree of approximation of function belonging of Lipschitz class by using Deferred-Generalized Nörlund (D^𝛾_𝛽.N_pq) means of Fourier series and conjugate series of Fourier series, where {p_n} and {q_n} is a non-increasing sequence. So that results of DEGER and BAYINDIR [23] become special cases of our results.