• Journal of Digital Contents Society
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• v.18 no.4
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• pp.777-785
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• 2017

In the modern real world, we can extract and recognize some texts to get a lot of information from the scene containing them, so the techniques for extracting and recognizing text areas from a scene are constantly evolving. They can be largely divided into texture-based method, connected component method, and mixture of both. Texture-based method finds and extracts text based on the fact that text and others have different values such as image color and brightness. Connected component method is determined by using the geometrical properties after making similar pixels adjacent to each pixel to the connection element. In this paper, we propose a method to adaptively change to improve the accuracy of text region extraction, detect and correct the slope of the image using edge and image segmentation. The method only extracts the exact area containing the text by correcting the slope of the image, so that the extracting rate is 15% more accurate than MSER and 10% more accurate than EEMSER.

• Korean Journal of Plant Tissue Culture
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• v.24 no.5
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• pp.273-277
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• 1997

The sesquiterpene cyclase (SC) was induced and its products were accumulated in the culture media of Hyoscyamus muticus hairy roots by addition of Rhizoctonia solani extracts. The cumulative production of solavetivone was nearly doubled by integrated extraction of the products from the media during the 24 h accumulation period. Western blots with monoclonal antibodies against SC show that the enzyme levels are the same for both extracted and non-extracted cultures. SC activities measured in vitro with radioactive substrate are not significantly different. These results suggest that productivity is controlled by substrate availability within the terpenoid pathway, and feedback regulation precedes the branch-point enzyme sesquiterpene cyclase.

• Archives of Pharmacal Research
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• v.9 no.3
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• pp.131-138
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• 1986

A specific and sensitive gas chromatographic (GC) procedure with the flame photometric detector (FPD) was developed for determination of barbiturates such as barbital, allobarbital, secobarbital, phenobarbital and thiopental in plasma. In order to evaluate the performance of the FPD, the results were campared with those of the flame ionization detector (FID). After extraction of barbiturates from plasma, the barbiturates were quantitatively N, N-dimethylthiometyl (MTM)-derivatized with methylthiomethyl chloride in 1, 8-diazabicyclo [5, 4, 0] undec-7-ene catalyst. The data indicate that the FPD is about 4 times more sensitive than the FID for barbiturates, although it is less reproducible. The FPD also produced chromatogram with less back ground for extracted plasma sample. The FPD also produced chromatogram with less background for extracted plasma sample. The minimum detectable amount of MTM-thiopental on 3% OV-225 column was 4, 4fmol and that of other MTM-barbiturate was about 10.0fmol.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.1
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• pp.65-73
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• 2007

Pattern classification of single and multiple discharge sources was applied using a wavelet image signal method in which a feature extraction was applied using a hidden sub-image. A feature extracting method that used vertical and horizontal images using an MSD method was applied to an averaging process for the scale of pulses for the phase. A feature extracting process for the preprocessing of the input of a neural network was performed using an inverse transformation of the horizontal, vertical, and diagonal sub-images. A back propagation algorithm in a neural network was used to classify defective signals. An algorithm for wavelet image processing was developed. In addition, the defective signal was classified using the extracted value that was quantified for the input of a neural network.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.49-60
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• 2004

While the World-Wide Web offers an incredibly rich base of information, organized as a hypertext it does not provide a uniform and efficient way to retrieve specific information. Therefore, it is needed to develop an efficient web crawler for gathering useful information in acceptable amount of time. In this paper, we studied the order in which the web crawler visit URLs to rapidly obtain more important web pages. We also developed an internet agent for efficient web crawling using hyperlink structure and fitness of hypertext documents. As a result of experiment on a website. it is shown that proposed agent outperforms other web crawlers using BackLink and PageRank algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.8-13
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• 2009

LED BLU(Back Light Unit), based on MCPCB(Metal Core Printed Circuit Board) with anodizing oxide dielectric layer and improved thermal dissipation property, are presented. Reflecting cups were also formed on the surface of the MCPCB such that optical coupling between neighboring chips were minimized for improving the photon extraction efficiency. LED chips were directly attached on the MCPCB by using the COB (Chip On Board) scheme.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.147-159
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• 2002

This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.84-92
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• 2001

In this papers, we proposed the new method in order to diagnosis aging state of transformers. For wavelet transform, Daubechies filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion skewness, kurtosis) about each acoustic emission signal. Also, these coefficients are used to identify normal and fault signal of internal partial discharge in transformer. As improved method for classification use neural network. Extracted statistical parameters are input into an back-propagation neural network. The number of neurons of hidden layer are obtained through Result of Cross-Validation. The network, after training, can decide whether the test signal is early aging state, alst aging state or normal state. In quantity analysis, capability of proposed method is superior to compared that of classical method.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.354-356
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• 2000

This paper describes the strategy of a daily optimal operational scheduling on cogeneration systems with each other generation mode. The cogeneration systems consists of three generators. auxiiiary devices which are three auxiliary boilers, two waste boilers and three sludge incinerators. One unit that using the back pressure turbin generates the electrical and the thermal energy. The other two units that using the extraction condensing turbine generate the energy. Auxiliary devices operate to supplement the thermal energy to the thermal load with three units. The cogeneration system has a large capacity which is able to supply enough the thermal energy to the thermal load, however the electric power generated is insufficient to satisfy the electrical load. Therefore the insufficient electric energy is supplemented by buying electrical energy from the utility. Simulation was carried out using optimization toolbox. The result reveals that the proposed modeling and strategy can be effectively applied to cogeneration systems with each other generation mode.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2101-2102
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• 2006

In this paper, a new digital audio watermarking algorithm is presented. The proposed algorithm embeds watermark into audio signal based on human auditory system (HAS). This algorithm is a blind audio watermarking method, which does not require any prior information during watermark extraction process. This algorithm finds watermarking position using time-domain masking effect. First we insert the watermark into wavelet domain, and then we use a back-propagation neural network (BPN) to learn the characteristics of relationship between the watermark and the watermarked audio. Due to the teaming and adaptive capabilities of the BPN, the false recovery of the watermark can be greatly reduced by the trained BPN. Experimental results show that the proposed method has good inaudibility and high robustness to common audio processing attacks.