• Journal of the Korean Chemical Society
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• v.43 no.4
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• pp.412-417
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• 1999

The analytical results obtained by microwave digestion and acid digestion methods for sample pretreatment to determine metal impurities in silicon wafer by inductively coupled plasma-mass spectrometry (ICP-MS) were compared. In order to decompose the silicon wafer, a mixed solution of $HNO_3$ and HF was added to the sample and the metal elements were determined after removing the silicon matrix by evaporating silicon in the form of Si-F. The recovery percentages of Ni,Cr and Fe were found to be 95∼106% for both microwave digestion and acid digestion methods. The recovery percentage of Cu obtained by the acid digestion method was higher than that obtained by the microwave digestion method. For Zn, however, the microwave digestion method gave better result than the acid digestion method. Fe was added to a silicon wafer using a spin coater. The concentration of Fe in this sample was determined by lCP-MS, and the same results were obtained in the two pretreatment methods.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.41-51
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• 2024

In this paper, we explore the enhancement of target detection accuracy in the guided weapon using deep learning object detection on infrared (IR) images. Due to the characteristics of IR images being influenced by factors such as time and temperature, it's crucial to ensure a consistent representation of object features in various environments when training the model. A simple way to address this is by emphasizing the features of target objects and reducing noise within the infrared images through appropriate pre-processing techniques. However, in previous studies, there has not been sufficient discussion on pre-processing methods in learning deep learning models based on infrared images. In this paper, we aim to investigate the impact of image pre-processing techniques on infrared image-based training for object detection. To achieve this, we analyze the pre-processing results on infrared images that utilized global or local information from the video and the image. In addition, in order to confirm the impact of images converted by each pre-processing technique on object detector training, we learn the YOLOX target detector for images processed by various pre-processing methods and analyze them. In particular, the results of the experiments using the CLAHE (Contrast Limited Adaptive Histogram Equalization) shows the highest detection accuracy with a mean average precision (mAP) of 81.9%.

• Journal of Bio-Environment Control
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• v.21 no.3
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• pp.170-179
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• 2012

We examined pretreatment methods eliminating potassium and sodium efficiently for coir bag used in hydroponics by analyzing drainage coming from coir bags. In the first experiment we investigated for six coir bags with the high market shares. The three types of pretreatment were washing coir bags with only water for 7 days (W7S0), washing with water for 4 days and further with nutrient solution for 3 days (W4S3), and washing with only nutrient solution for 7 days (W0S7). In the second experiment we tested reproducibility of the experiment results for Bio Grow and coco Mix among six coir bags used in the first experiment to verify the results. As a result, the best pretreatments for the pH stabilization were W4S3 and W0S7. The EC value of the drainage was stabilized to less than 1.0 that is the same as EC of the supply solution on the fourth day in all treatments. The nutrients of the drainage in W7S0 was stabilized in 3~4 days but calcium and magnesium were depleted. We assessed that washing longer than 4 days was waste of water. The stabilization of coir bags in W0S7 was similar to it in W4S3, but washing with the nutrient solution for 7 days seemed to be uneconomical. The reproducibility experiment for two coir bags ensured the results in the first experiment. Therefore, the pretreatment method, which is the most simple to implement and economic, seems to wash with water for 3 days and then with the nutrient solution for 1 day before planting on coir bag.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.4
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• pp.361-368
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• 2002

The aim of this study was to investigate the effect of preprocessing the transmitted energy spectrum data on development of a robust model to predict the sugar content in intact apples. The spectrum data were measured from 120 Fuji apple samples conveying at the speed of 2 apples per second. Computer algorithms of preprocessing methods such as MSC, SNV, first derivative, OSC and their combinations were developed and applied to the raw spectrum data set. The results indicated that correlation coefficients between the transmitted energy values at each wavelength and sugar contents of apples were significantly improved by the preprocessing of MSC and SNV in particular as compared with those of no-preprocessing. SEPs of the prediction models showed great difference depending on the preprocessing method of the raw spectrum data, the largest of 1.265%brix and the smallest of 0.507% brix. Such a result means that an appropriate preprocessing method corresponding to the characteristics of the spectrum data set should be found or developed for minimizing the prediction errors. It was observed that MSC and SNV are closely related to prediction accuracy, OSC is to number of PLS factors and the first derivative resulted in decrease of the prediction accuracy. A robust calibration model could be d3eveloped by the combined preprocessing of MSC and OSC, which showed that SEP=0.507%brix, bias=0.0327 and R2=0.8823.

• Food Science and Preservation
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• v.14 no.5
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• pp.462-468
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• 2007

In this study, the quality effect of soaking in alum water, soaking in electrolyzed oxidizing water, and freezing during storage, on peeled chestnuts, were analyzed. When soaked in 0.1% (w/v) alum water, peeled chestnuts showed good characteristics in terms of weight loss, decomposition, and color preservation. However, texture and taste qualities rapidly decreased with increases in storage time. When soaked in twice their own weight of electrolyzed oxidizing water(pH 2.61, ORP 1,142 mV) for 10 min, the samples were preserved in an optimally edible condition. When frozen at $-10^{\circ}C$ for 5 min, the samples were suitable for use as material for processed chestnut produce, as was also the case when pretreatment with electrolyzed oxidizing water was employed.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.165-172
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• 2020

Recently, due to exponential growth of access information on the web, the importance of predicting a user's next web page use has been increasing. One of the methods that can be used for predicting user's next web page is deep learning. To predict next web page, web logs are analyzed by data preprocessing and then a user's next web page is predicted on the output of the analyzed web logs using a deep learning algorithm. In this paper, we propose a framework for web page prediction that includes methods for web log preprocessing followed by deep learning techniques for web prediction. To increase the speed of preprocessing of large web log, a Hadoop based MapReduce programming model is used. In addition, we present a web prediction system that uses an efficient deep learning technique on the output of web log preprocessing for training and prediction. Through experiment, we show the performance improvement of our proposed method over traditional methods. We also show the accuracy of our prediction.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.106.1-106.1
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• 2010

본 연구는 팜 부산물로부터 바이오 에탄올을 생산하는 전처리-당화-발효 공정의 첫 번째 단계인 전처리 공정에서 팜 부산물을 NaOH를 이용하여 효율적으로 전처리하고자 하였다. 암모니아 침지법과 NaOH 침출법을 비교한 결과 팜 부산물에 대해서는 암모니아 침지에 의한 탈리그닌 효과가 적으며 NaOH 전처리가 적합한 방법임을 알 수 있었다. 40-100 mesh 크기의 팜 부산물을 이용하여 반응온도(110, 130, $150^{\circ}C$), 반응시간(20, 40, 60분) 및 NaOH 농도(5%, 11%)의 변화에 따른 팜 부산물의 탈리그닌율과 글루코스 및 자일로스 회수율 간의 상호관계를 확인하였다. $150^{\circ}C$까지의 온도 조건에서 온도에 의한 자일로스의 분해는 일어나지 않는 것으로 확인되었다. 팜 부산물의 탈리그닌율은 시간이 증가할수록 증가하였으며, 높은 NaOH 농도에서 더 높은 것으로 나타났다. 그러나 글루코스 및 자일로스의 회수율은 높은 농도에서 낮게 나타났으며, 시간이 지날수록 감소하여 손실이 많은 것으로 나타났다. 따라서 NaOH 농도가 낮을수록 당 회수율은 높게 나타나지만, 탈리그닌율이 낮아 당화 효율이 떨어지므로 효소 당화 후에 최종 당 회수율이 높은 NaOH 농도 조건을 결정하여야 하겠다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.357-361
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• 2006

매일 새롭게 생기는 웹 페이지 수가 수천만 개, 온라인 문서들의 수가 수십억 개에 이르게 되자, 웹 사이트를 설계함에 있어서 웹 서버 로그 파일에 기록된 사용자의 행동을 분석하는 것이 중요한 부분이 되어가고 있다. 분석가들은 전체 웹 사이트에서 사용자 행동의 완전한 개요를 알기 원하기 때문에 고객이 방문했던 모든 다른 웹 서버를 통하여 사용자의 패스(path)를 다시 수집해야만 한다. 본 연구에서는 모든 로그 파일을 연결해서 방문했던 곳을 재구성하는 향상된 데이터 전처리 방법에 의하여 실험을 하여 로그 파일 크기를 감소시키게 되어 데이터 전처리의 성능이 향상되었음을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.586-588
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• 2003

현재 많이 연구되는 영상융합(Image fusion)에서는 필히 두 영상의 정합(alignment)이 이루어져야만 수행된다. 각기 다른 특징을 갖는 센서(EO.IR.Radar등)로부터 얻는 영상에서는 각각 다른 특징점 정보를 가지므로, 특징점을 이용한 영상 정합 구현에는 전처리 과정이 매우 복잡하고 까다롭게 이루어져야 한다. 본 논문에서는 Correlation에 대한 통계적 상관 관계를 이용하여. 전처리 과정을 단순하게 수행 하여도 매우 강건한 영상 정합이 이루어지도록 구현 하였다. 또한, 통계적 기법에 적합하도록, 효율적인 전처리 과정을 통해 계산량이 적어 지는 방법을 제안 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2527-2533
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• 2011

In this paper we propose a new pre-processing algorithm applied to multi-view video coding using color compensation algorithm based on image features. Multi-view images have a difference between neighboring frames according to illumination and different camera characteristics. To compensate this color difference, first we model the characteristics of cameras based on frame's feature from each camera and then correct the color difference. To extract corresponding features from each frame, we use Harris corner detection algorithm and characteristic coefficients used in the model is estimated by using Gauss-Newton algorithm. In this algorithm, we compensate RGB components of target images, separately from the reference image. The experimental results with many test images show that the proposed algorithm peformed better than the histogram based algorithm as much as 14 % of bit reduction and 0.5 dB ~ 0.8dB of PSNR enhancement.