• Atmosphere
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• v.23 no.4
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• pp.453-470
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• 2013

As a part of the KIAPS Observation Processing System (KOPS), we have developed the modules of satellite radiance data pre-processing and quality control, which include observation operators to interpolate model state variables into radiances in observation space. AMSU-A (Advanced Microwave Sounding Unit-A) level-1d radiance data have been extracted using the BUFR (Binary Universal Form for the Representation of meteorological data) decoder and a first guess has been calculated with RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder) version 10.2. For initial quality checks, the pixels contaminated by large amounts of cloud liquid water, heavy precipitation, and sea ice have been removed. Channels for assimilation, rejection, or monitoring have been respectively selected for different surface types since the errors from the skin temperature are caused by inaccurate surface emissivity. Correcting the bias caused by errors in the instruments and radiative transfer model is crucial in radiance data pre-processing. We have developed bias correction modules in two steps based on 30-day innovation statistics (observed radiance minus background; O-B). The scan bias correction has been calculated individually for each channel, satellite, and scan position. Then a multiple linear regression of the scan-bias-corrected innovations with several predictors has been employed to correct the airmass bias.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.370-376
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• 2023

In the underwater image, it is not clear to distinguish the shape of the target due to underwater noise and low resolution. In addition, as an input of deep learning, underwater images require pre-processing and segmentation must be preceded. Even after pre-processing, the target is not clear, and the performance of detection and identification by deep learning may not be high. Therefore, it is necessary to distinguish and clarify the target. In this study, the importance of target shadows is confirmed in underwater images, object detection and target area acquisition by shadows, and data containing only the shape of targets and shadows without underwater background are generated. We present the process of converting the shadow image into a 3-mode image in which the target is white, the shadow is black, and the background is gray. Through this, it is possible to provide an image that is clearly pre-processed and easily discriminated as an input of deep learning. In addition, if the image processing code using Open Source Computer Vision (OpenCV)Library was used for processing, the processing speed was also suitable for real-time processing.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.2
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• pp.8-18
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• 1993

A multi-font, multi-size and high speed character recognition system is designed. The design principles are simpilcity of algorithm, adaptibility, learnability, hierachical data processing and attention by feed back. For the multi-size character recognition, the extracted character images are normalized. A hierachical classifier classifies the feature vectors. Feature is extracted by applying the directional receptive field after the directional dege filter processing. The hierachical classifier is consist of two pre-classifiers and one decision making classifier. The effect of two pre-classifiers is prediction to the final decision making classifier. With the pre-classifiers, the time to compute the distance of the final classifier is reduced. Recognition rate is 95% for the three documents printed in three kinds of fonts, total 1,700 characters. For high speed implemention, a multiprocessor system with the ring structure of four transputers is implemented, and the recognition speed of 30 characters per second is aquired.

• Annual Conference of KIPS
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• 2005.05a
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• pp.1169-1172
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• 2005

컴퓨터 포렌식절차에서 증거물 획득은 중요한 부분이다. 컴퓨터 포렌식의 여러 원칙 중 신속성의 원칙은 휘발성 정보의 획득유무와 관계가 있다. 기존 통합보안관리시스템(ESM: Enterprise Security Management) 은 보안이벤트중심으로 정보를 수집한다. 컴퓨터 포렌식에서 중요한 휘발성 시스템 포렌식 정보와 네트웍 포렌식 정보는 수집하지 않는다. 본 논문에서는 통합보안관리시스템에 Pre-Forensic 정책을 도입하여 기존 보안경보기능에 포렌식 데이터 수집 대응방안을 추가한 새로운 통합 보안관리시스템 모델을 제안한다. 제안 시스템은 무결성이 보장되는 많은 증거를 수집할 수 있으며 향상된 컴퓨터 포렌식 증거물 획득 방법을 제시한다.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.70-76
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• 1996

In this paper, we have proposed a band stop filter (BSF) for pre-processing of image sequences before encoding. By pixel-wise temporal filtering of the image sequences using the BSF, the bandwidth and noise of the signal are reduced, while preserving the image quality in view of human visual perceptions. As a result, when compared to the original image sequences, te pre-filtered image sequence requires lower bit-rates for encoding, while there is not much degradation in quality. Also, it has been shown that the proposed BSF causes less smearing and blurring than the conventional recursive low pass filter for bandwidth and noise reductions.

• Annual Conference of KIPS
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• 2024.05a
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• pp.843-845
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• 2024

도메인 적응 사전 훈련(Domain-Adaptive Pre-training, DAPT)을 활용한 한국어 문서 요약 연구에서는 특정 도메인의 문서에 대한 이해도와 요약 성능을 향상시키기 위해 DAPT 기법을 적용했다. 이 연구는 사전 훈련된 언어 모델이 일반적인 언어 이해 능력을 넘어 특정 도메인에 최적화된 성능을 발휘할 수 있도록 도메인 특화 데이터셋을 사용하여 추가적인 사전 훈련을 진행한다. 구체적으로, 의료, 법률, 기술 등 다양한 도메인에서 수집한 한국어 텍스트 데이터를 이용하여 모델을 미세 조정하며, 이를 통해 얻은 모델은 도메인에 특화된 용어와 문맥을 효과적으로 처리할 수 있음을 보여준다. 성능 평가에서는 기존 사전 훈련 모델과 DAPT를 적용한 모델을 비교하여 DAPT의 효과를 검증했다. 연구 결과, DAPT를 적용한 모델은 도메인 특화 문서 요약 작업에서 성능 향상을 보였으며, 이는 실제 도메인별 활용에서도 유용할 것으로 기대된다.

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.337-342
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• 2007

This paper proposes Electronic Credit Card(EMV) processing procedures for a credit payment method which can be applied to Korean ETCS(Electrical Toll Collection System). In Korea, Korea Highway Corporation services contactless ETCS's called by Hi-Pass and Touch-Pass system at present. These systems operate on a pre-paid payment method similar to electronic money. On the other side, a credit payment method based on credit card has an advantage which does not require pre-paid. The introduction of credit payment method to ETCS is in preparation. In this paper, we propose EMV processing methods based on a credit payment method which can be applied on ETCS.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.324-333
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• 2011

This study was accomplished for the purpose of developing a textile processing ingredient that is harmless to the human body and environment. The research method consists of dyeing cotton textiles by extracting the dye solution from ginseng. Then, chrominance, after treatment, antibacterial ratio and deodorization ratio of cotton fabrics dyed with ginseng extracts were tested and results were examined. The research procedure involved first extracting the dye solution from the ginseng's by-product (fine roots) and then dyeing was effectuated differently according to the test samples temperature and dyeing time requirements. Brightness in all dye substances was lower in pre-mordanting. Beige color could be extracted from pre-mordanted samples. And dark orange from postmordanted samples. Color-festness was high in all samples. Most of samples show a big antibacterial ratio and deodorization ratio. Through this research it has been discovered that, when applied to textiles, Korea's ginseng extract possessed reproducibility features as a natural dye and a possibility to be used in cutting which plays a crucial role in hygienic processing. In addition, by using ginseng's by-product for dyeing processing as the dye solution, efficient application of resources and occurrences of no water waste damages were demonstrated and thus, proved to be environmentally-friendly. Specifically, through this experiment, it was found that saponin, ginseng's special characteristics, possessed excellent antibacterial odor repelling functions to clothing as well as the capability to prevent skin disease.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• Journal of Broadcast Engineering
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• v.6 no.2
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• pp.139-147
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• 2001

Since various noises degrade not only image quality but also compression efficiency in MPEG and H.263, pre-processing is necessary to reduce spatial and temporal noise and to increase ceding efficiency as well. In this paper, we propose a simplified method for noise detection, spatial and temporal noise reduction. Noise detection is based on correlation of the current pixel with its neighboring 4 pixels. Spatial noose reduction utilizes a non-rectangular median filter that is less complex than the conventional rectangular median filter. The proposed temporal filter is an IIR average filter using LUT(Look-up Table) to enhance subjective video quality. The proposed pre-processing method is very simple and efficient.