• Journal of Korea Technical Association of The Pulp and Paper Industry
• /
• v.29 no.2
• /
• pp.36-45
• /
• 1997

Newly bleaching sequence using oxygen, ozone and hydrogen peroxide has introduced to avoid pollution hazards from chlorinated organic compounds, because chlorine dioxide substitution bleaching was produced a little chlorinated organic substance. Oxygen-type chemicals replaced for chlorine has attracted much research attention. Bleachability of ozone was improved at low temperature and high pulp consistency. In third bleaching followed OZ bleaching, addition of O2 and NaBH4 in alkali extraction was effective than only alkali extraction. Bleachability of pulps in ozone bleaching(Z) was improved at higher consistency and lower temperature The addition O2 and NaBH4 in alkali extraction after OZ bleaching sequence improved brightness, when compared to those obtained by only alkaline extraction. Pulps bleached by ECF bleaching sequences such as OZEoD and OZEopD was obtained by 90% ISO brightness. The brightness of pulp bleached by TCF sequences with the ozone dosage of 1.6% was approached to target brightness (88~90%ISO). Pulps bleached Z stage combined bleaching sequence was reduced the viscosity to a little greater extent. However, physical properties of pulps was not great different compared to those bleached by conventional bleaching sequences. A pollution index of bleaching effluente by ozone combined bleaching sequences was lower than by conventional bleaching sequence, but somewhat higher than multistage bleaching sequences combined C/D stage.

• Environmental Engineering Research
• /
• v.23 no.2
• /
• pp.175-180
• /
• 2018

Box-Behnken Design (BBD) under response surface methodology (RSM) was implemented to optimization the operating parameters and assess the removal and recovery efficiencies of crude oil from contaminated soil using subcritical water extraction. The effects of temperature, extraction time and water flow rate were explored, and the results indicate that temperature has a great impact on crude oil removal and recovery. The correlation coefficients for oil removal ($R^2=0.74$) and recovery ($R^2=0.98$) suggest that the proposed quadratic model is useful. When setting the target removal and recovery (>99%), BBD-RSM determined the optimum condition to be a temperature of $250^{\circ}C$, extraction time of 120 min, and water flow rate of 1 mL/min. An experiment was carried out to confirm the results, with removal and recovery efficiencies of 99.69% and 87.33%, respectively. This result indicates that BBD is a suitable method to optimize the process variables for crude oil removal and recovery from contaminated soil.

• Fisheries and Aquatic Sciences
• /
• v.4 no.1
• /
• pp.1-9
• /
• 2001

This paper describes a procedure extracting feature vector of a target cell more precisely in the case of identifying specified cell. The classification of object type is based on feature vector such as area, complexity, centroid, rotation angle, effective diameter, perimeter, width and height of the object So, the feature vector plays very important role in classifying objects. Because the feature vectors is affected by noises and holes, it is necessary to remove noises contaminated in original image to get feature vector extraction exactly. In this paper, we propose the following method to do to get feature vector extraction exactly. First, by Otsu's optimal threshold selection method and morphological filters such as cleaning, filling and opening filters, we separate objects from background an get rid of isolated particles. After the labeling step by 4-adjacent neighborhood, the labeled image is filtered by the area filter. From this area-filtered image, feature vector such as area, complexity, centroid, rotation angle, effective diameter, the perimeter based on chain code and the width and height based on rotation matrix are extracted. To prove the effectiveness, the proposed method is applied for yeast Zygosaccharomyces rouxn. It is also shown that the experimental results from the proposed method is more efficient in measuring feature vectors than from only Otsu's optimal threshold detection method.

• Proceedings of the CALSEC Conference
• /
• 2005.03a
• /
• pp.55-61
• /
• 2005

We will introduce a new web-based knowledge management system in progress, in which XML-based web information extraction and our structuring knowledge technologies are combined using ontology-based natural language processing. Our aim is to provide efficient access to heterogeneous information on the web, enabling users to use a wide range of textual and non textual resources, such as newspapers and databases, effortlessly to accelerate knowledge acquisition from such knowledge sources. In order to achieve the efficient knowledge management, we propose at first an XML-based Web information extraction which contains a sophisticated control language to extract data from Web pages. With using standard XML Technologies in the system, our approach can make extracting information easy because of a) detaching rules from processing, b) restricting target for processing, c) Interactive operations for developing extracting rules. Then we propose a structuring knowledge system which includes, 1) automatic term recognition, 2) domain oriented automatic term clustering, 3) similarity-based document retrieval, 4) real-time document clustering, and 5) visualization. The system supports integrating different types of databases (textual and non textual) and retrieving different types of information simultaneously. Through further explanation to the specification and the implementation technique of the system, we will demonstrate how the system can accelerate knowledge acquisition on the Web even for novice users of the field.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2002.09a
• /
• pp.40-43
• /
• 2002

Electrokinetic remediation was studied for the removal of toxic heavy metals from tailing soils. This study emphasized the dependency of removal efficiency upon heavy metal speciation, as demonstrated by different extraction methods (sequential extraction, total digestion, and 0.1 N HC1 extraction). The tailing soils examined showed different physicochemical characteristics, in view of initial pH, particle size distribution, and major mineral constituents, and contained high concentrations of target metal contaminants in various forms. The electrokinetic removal efficiency of heavy metals was significantly influenced by their partitioning prior to treatment, and by the pHs of the tailing soils. The mobile and weakly bound fractions of heavy metals, such as exchangeable fraction, were easily removed by electrokinetic treatment (more than 90% in removal efficiency), whereas immobile and strongly bound fractions, such as organically bound and residual fractions, were not effectively removed (less than 20% in removal efficiency).

• Journal of Digital Convergence
• /
• v.11 no.10
• /
• pp.453-458
• /
• 2013

HMM Speech recognition systems have a few weaknesses, including failure to recognize speech due to the mixing of environment noise other voices. In this paper, we propose a speech feature extraction methode using CHMM for extracting selected target voice from mixture of voices and noises. we make use of channel similarity and correlate relation for the selective speech extraction composes. This proposed method was validated by showing that the average distortion of separation of the technique decreased by 0.430 dB. It was shown that the performance of the selective feature extraction is better than another system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.8
• /
• pp.1802-1808
• /
• 2003

In this paper, we propose a method about the extraction of the pedestrian tracking trajectory in the road and we used the method of mosaic background extraction and adaptive neural network for automatic pedestrian tracking system. We used mosaic background extraction to overcome ghost phenomenon. And we detected pedestrian using differential image analysis. We used adaptive neural network for multiple pedestrian tracking that non­rigid form moving. The ART2 network is capable of detecting the mass­centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment show promising results.

• The KIPS Transactions:PartB
• /
• v.10B no.1
• /
• pp.81-86
• /
• 2003

In this paper, we propose the tracking method of moving object which use extracted object by difference between background image and target image in fixed domain. As a extraction method of object, calculate not pixel of full image but predefined some edge pixel of image to get a position of new object. Since the center area Is excluded from calculation, the extraction time is efficiently reduced. To extract object in the predefined area, get a starting point in advance and then extract size of width and height of object. Central coordinate is used to track moved object.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.5
• /
• pp.915-920
• /
• 2007

Using the existing algorithms that estimate the background noise, the detection probability for the week tonals is low and for the even week tonals, there is a limit not detected. Therefore it is required to algorithms which can improve the performance of the tonal extraction. Recently, many researches using artificial neural networks in sonar signal processing are performed. We propose a neural network with double feedback that can remove automatically the background noise and detect the even week tonals buried in background noise, therefore not detected by growing the week tonals lastingly for a certain time. For the real underwater target, experiments for the tonal extraction are performed by using the existing algorithms that estimate the background noise and the proposed neural network. As a result of the experiment, a method using the proposed neural network showed the better performance of the tonal extraction in comparison with the existing algorithms.

• The KIPS Transactions:PartB
• /
• v.13B no.1 s.104
• /
• pp.71-76
• /
• 2006

To obtain a correctly translated sentence in a machine translation system, we must select target words that not only reflect an appropriate meaning in a source sentence but also make a fluent sentence in a target language. This paper points out that a source language word has various senses and each sense can be mapped into multiple target words, and proposes a new translation disambiguation method based on this 'word-to-sense and sense-to-word' relationship. In my method target words are chosen through disambiguation of a source word sense and selection of a target word. Most of translation disambiguation methods are based on a 'word-to-word' relationship that means they translate a source word directly into a target wort so they require complicate knowledge sources that directly link a source words to target words, which are hard to obtain like bilingual aligned corpora. By combining two sub-problems for each language, knowledge for translation disambiguation can be automatically extracted from knowledge sources for each language that are easy to obtain. In addition, disambiguation results satisfy both fidelity and intelligibility because selected target words have correct meaning and generate naturally composed target sentences.