• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.77-82
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• 1994

In speech signal processing, it is very important to detect the pitch exactly. Although various methods for detecting the pitch of speech signals have been developed, it is difficult to exactly extract the pitch for wide range of speakers and various utterances. Thus we propose a new pitch detection algorithm which takes advantage of the G-peak extraction. It is a method to detect the pitch period of the voiced signals by finding MZCI (maximum zero-crossing interval) of the G-peak which is defined as cut-off bandwidth rate of LPF (low pass filter). This algorithm performs robustly with a gross error rate of 3.63% even in 0 dB SNR environement. The gross error rate for clean speech is only 0.18%. Also it is able to process all courses with high speed.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.18-26
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• 2015

Geometric distortion and shadow effect due to capturing angle could be included in document copy images that are captured by a camera in stead of a scanner. In this paper, a clean black and white document image generation algorithm by distortion correction and shadow elimination based on a camera, is proposed. In order to correct geometric distortion such as straightening un-straight boundary lines occurred by camera lens radial distortion and eliminating outlying area included by camera direction, second derivative filter based document boundary detection method is developed. Black and white images have been generated by adaptive binarization method by eliminating shadow effect. Experimental results of the black and white document image generation algorithm by recovering geometrical distortion and eliminating shadow effect for the document images captured by smart phone camera, shows very good processing results.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.119-131
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• 2016

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.6
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• pp.696-703
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• 2003

A photovoltaic power generation system is an infinite and clean energy system. Recently. because of the realization of high efficiency and low cost PV modules, the studies on the PV system have extensively increased. In this paper. we present an online scheme for parameter estimation of solar cell, based on the model adjustment technique and a real-coded genetic algorithm(RCGA). The ideal diode model and the diode model with series and shunt resistors are used to estimate their parameters, Simulation works using field data in the form of a V-I characteristic curve are carried out to demonstrate the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.121-128
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• 2005

On the research field for speech signal, neural network mainly uses for the category classification in speech recognition and applies to signal processing. Accordingly, this paper proposes a noise reduction system using a time-delay neural network, which implements the mapping from the space of speech signal degraded by noise to the space of clean speech signal. It is confirmed that this method is effective for speech degraded not only by white noise but also by colored noise using the noise reduction system, which restores the amplitude component of fast Fourier transform.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.897-902
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• 2001

SBOS(Soot blower Optimum System) analyzes the accumulated fouling rate of a coal-fired boiler plant at short intervals, compares it with a reference data, and determines the optimal time of soot blowing. In this paper, ANFIS algorithm which is an optimal algorithm to detect variation of boiler performance with time, updating the reference data and to eliminate the effects of noise in field signal is used to clean heating surface and to reduce steam needed to blow the soot.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.289-293
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• 2007

낸드 플래시 메모리는 특성상 덮어 쓰기가 불가능하기 때문에 유효하지 않는 데이터가 저장된 더티(Dirty) 상태의 페이지를 삭제 연산을 통해 클린(Clean) 상태로 만든 후 데이터를 써야 한다. 더티 페이지가 낸드 플래시 메모리에 많이 존재하면 파일을 쓸 때 많은 블록을 삭제해야 하기 때문에 쓰기 지연 시간이 길어지는 문제가 발생한다. 따라서 본 논문에서는 일정한 쓰기 지연 시간을 보장하는 새로운 페이지 할당 및 회수 기법을 제안한다. 파일이 삭제될 때 더티 상태인 페이지를 삭제함으로써 클린 상태로 변경하여 낸드 플래시 메모리에 쓰기 지연 시간을 길게 만드는 더티 페이지가 없는 상태로 유지한다. 또한 삭제 연산은 블록 단위로 수행되므로 삭제할 블록의 유효한 페이지를 다른 블록으로 복사해야 하기 때문에, 페이지를 할당할 때 한 블록에 가급적 적은 개수의 파일을 저장하는 알고리즘을 제시한다.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.4-7
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• 2022

기존 합성곱 신경망 기반의 잡음 제거 네트워크들은 학습을 위한 noisy-clean 데이터 쌍을 필요로 한다. 하지만 실제 카메라 잡음의 경우, 잡음에 대한 깨끗한 원본 영상을 얻는 것은 불가능하거나 많은 비용이 소모된다. 따라서 이러한 방법을 해결하기 위하여 원본 영상 없이 잡음 영상만으로만 잡음 제거 네트워크를 학습하는 방법들이 제안되어왔다. 그 중 카메라 잡음 영상을 처리하기 위한 대표적인 방법으로 학습과 추론에서 비대칭적인 downsampling을 사용하는 AP-BSN이 제안되었다. 본 논문에서는 Functional neural network를 AP-BSN 알고리즘에 적용하여 다양한 downsampling ratio에 대응되는 하나의 네트워크를 학습하였다. 이를 통해 기존 hyperparameter로 사용되던 downsampling ratio에 대한 결과를 하나의 네트워크에서 분석 및 확인하였다. 또한 해당 파라미터를 조절함으로써 다양한 잡음 제거 후보들을 추출하고 사용자가 원하는 잡음 제거 정도를 조정할 수 있도록 하였다.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.