• Journal of the Korean Institute of Gas
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• v.17 no.6
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• pp.39-45
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• 2013

The gas generated from the fire which is continuous until material is completely burned. We can analyze usual gas using chromatography analysis but it can not be applicated to analyze for the gas from the fire because which gas is enormously generated. Besides, chromatography analysis has the disadvantage that it can not continuously analyze the sample's representativness, gas from the fire, Fourier transform infrared spectroscopy, FT-IR, has been utilized for effective combustion gas analysis method in small-scale combustion and on-line analysis has been attempted continuously. However, continuous sampling of 3.5l/min can not be representativness of sample if the gas caused by a massive fire and space. And the gas sampling is practically impossible in such a case. In this study, we attempted remote analysis while overcoming the disadvantages of the current gas analysis by using an Open-Path Infrared Analyzer without pre-treatment of the sampling. For the remote analysis, quantitative analysis method was established regarding each combustion toxic gases. And we measured the gases from the fire that occurs in the real case.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.46-55
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• 2020

The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.809-817
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• 2002

This paper describes a new face detection method that is a pre-processing algorithm for on-line face recognition. To complement the weakness of using only edge or rotor features from previous face detection method, we propose the two types of face detection method. The one is a combined method with edge and color features and the other is a center area color sampling method. To prevent connecting the people's face area and the background area, which have same colors, we propose a new adaptive edge detection algorithm firstly. The adaptive edge detection algorithm is robust to illumination variance so that it extracts lots of edges and breakouts edges steadily in border between background and face areas. Because of strong edge detection, face area appears one or multi regions. We can merge these isolated regions using color information and get the final face area as a MBR (Minimum Bounding Rectangle) form. If the size of final face area is under or upper threshold, color sampling method in center area from input image is used to detect new face area. To evaluate the proposed method, we have experimented with 2,100 face images. A high face detection rate of 96.3% has been obtained.

• The Journal of Bigdata
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• v.3 no.2
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• pp.71-78
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• 2018

The study is based on machine learning techniques to increase the accuracy of the forest fire predictive model. It used 14 years of data from 2003 to 2016 in Gang-won-do where forest fire were the most frequent. To reduce weather data errors, Gang-won-do was divided into nine areas and weather data from each region was used. However, dividing the forest fire forecast model into nine zones would make a large difference between the date of occurrence and the date of not occurring. Imbalance issues can degrade model performance. To address this, several sampling methods were applied. To increase the accuracy of the model, five indices in the Canadian Frost Fire Weather Index (FWI) were used as derived variable. The modeling method used statistical methods for logistic regression and machine learning methods for random forest and xgboost. The selection criteria for each zone's final model were set in consideration of accuracy, sensitivity and specificity, and the prediction of the nine zones resulted in 80 of the 104 fires that occurred, and 7426 of the 9758 non-fires. Overall accuracy was 76.1%.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.89-92
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• 1999

인식기 훈련과정에서 발생하지 않았던 잡음이 인식과정에서 신호를 손상할 경우 인식률의 저하가 발생한다. 본 논문에서는 음성의 질을 떨어뜨리는 이러한 잡음을 Wavelet Packets을 이용하여 전처리함으로서 인식률을 향상시키는 방법을 제안한다. 인식기로는 Hidden Markov Model을 사용하였고, 시스템에 사용된 특징 파라미터로는 15차 Cepstrum을 사용하였다. 11 kHz로 샘플링된 숫자음에 Additive White Gaussian Noise를 첨가한 손상된 음성신호를 인식실험에 사용하였다. 화자독립으로 진행된 실험에서 잡음에 의해 손상된 SNR 20dB의 음성신호에 대하여 Wavelet Packets로 잡음을 제거한 후 복원된 음성신호 의 인식률은 약 $10\%$ 향상됨을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.14-19
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• 2008

대규모로 유전자 발현정도를 동시에 측정하는 마이크로어레이 실험은 많은 양의 데이터를 생성하기 때문에, 자동화된 효과적인 분석기법이 필요하다. 이 논문에서는 약물의 영향 분석을 위해 약물의 투여량 및 투여후의 시간대별로 샘플을 추출하여, 마이크로어레이를 이용하여 유전자의 발현량을 분석하는 경우에, 약물에 대해서 반응하는 유전자를 추출하는 데이터마이닝 기법을 제안한다. 제안한 방법에서는 유전자의 발현 정도값을 이전 비교대상의 값을 기준값으로 하여 증가, 감소, 답보에 해당하는 기호로 매핑하여, 분석자가 원하는 패턴을 보이는 유전자를 추천한다. 한편, 유전자의 상호간에 많은 영향을 주고받기 때문에 특정 약물을 투여할 때, 이에 직접적인 영향을 받는 것도 있지만, 이와는 전혀 상관없이 동작하는 것도 있기 때문에, 제안한 방법에서는 이러한 약물 투여와 유의성이 있을 가능성이 있는 유전자만을 전처리과정을 통해서 필터링하는 기법을 활용한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.127-136
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• 2017

This paper investigates improved stability and stabilization criteria for sampled-data control systems. By using a suitable and newly constructed augmented Lyapunov-Krasovskii functional and some recent mathematic techniques such as auxiliary function-based integral inequalities, sufficient conditions for stability and stabilization conditions are derived within the framework of linear matrix inequalities(LMI) form. The superiority and validity of the proposed results are illustrated by three numerical examples.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.419-428
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• 2003

Recently, digital watermarking has been proposed as a viable solution to the need of copyright protection and authentication of multimedia data. A robust wavelet-based watermark casting scheme and a watermark retrieval technique are suggested in this paper. We present a method which can add the watermark to the significant coefficients in the DWT domain, and does not require the original image in the detection process. In adaptive watermark casting method is developed to select perceptually significant coefficients for each subband using multiple threshold. In the proposed method, an adaptive multiple threshold scheme is used to reflect characteristics of each subband and complexity of image. The watermark is adaptively weighted in different subbands to achieve robustness as well as high perceptual quality. The watermark, Gaussian random sequence is added to the large coefficients but not in the lowest subband in the DWT domain. Experimental results show that the proposed algorithm produced visually very good watermarked image which has good invisibility to human eyes and very robust against various image processing and compression attacks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2074-2084
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• 2001

la this paper, a new digital watermarking algorithm using wavelet transform in frequency domain is suggested. The wavelet coefficients of low frequency subband are utilized to embed the watermark, After the original image is transformed using discrete wavelet transform, their coefficients are transformed into efficient1y in Sequency domain. DCT and FFT transforms are utilized in this processing. Watermark image of general image format is transformed using DCT and the hiding watermark into wavelet coefficients is equally distributed in frequency domain. Next, these wavelet coefficients are performed with inverse transform. The detection process of watermark is performed with reverse direction to insertion process. In this paper, we developed core watermark technologies which are a data hiding technology to hide unique logo mark which symbolizes the copyright and a robust protection technology to protect logo data from external attack like as compression, filtering, resampling, cropping. The experimental results show that two suggested watermarking technologies are invisible and robust.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.109-122
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• 2019

The expansion of double-income households is increasing the social interest in child care. In particular, children's entrance into elementary school is considered to be the main cause of women's career break as well as childbirth. This study proposes an optimal location selection method for caring facilities for elementary school students. As a candidate for care facilities, we selected existing child care facilities. We proposed a dual structure evaluation method that considers locational characteristics as well as mathematical optimization when selecting the optimal location. The experiment was conducted in Songpa-gu, Seoul. A total of 36 optimal locations were selected from a total of 258 candidate facilities. First, the evaluation criteria were established using public data, and the primary candidate facilities were selected by ranking the location scores. At this time mesh resampling method was used to integrate various public data into one. Next, the final care facilities were selected using the p-median method. The results chosen are not only the optimal location considering total distance but also satisfy various location criteria considering the characteristics of the care facility. We expect that the proposed method will contribute to public data convergence or utilization and it will be helpful for policy decision when selecting the optimal location for public facilities.