• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.876-883
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• 2003

In this paper, we propose an algorithm for organ recognition in ultrasound images using log power spectrum. The main procedure of the algorithm consists of feature extraction and feature classification. In the feature extraction, as a translation invariant feature, log power spectrum is used for extracting the information on echo of the organs tissue from a preprocessed input image. In the feature classification, Mahalanobis distance is used as a measure of the similarity between the feature of an input image and the representative feature of each class. Experimental results for real ultrasound images show that the proposed algorithm yields the improvement of maximum 30% recognition rate than the recognition algorithm using power spectrum and Euclidean distance, and results in better recognition rate of 10-40% than the recognition algorithm using weighted quefrency complex cepstrum.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.95-104
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• 2015

Recently, collecting and analyzing method of users location has been studied due to the development of mobile devices. There is analyzing method using Semantic Location History in order to identify of characteristics and extract pattern and predict trajectory of users. We should extraction of Stay Point in order to use Semantic Location History. The Conventional extraction method of Stay Point is not accuracy of location of Stay Points because it does not specify the GPS log of users. Also, Conventional extraction method of Stay Point cannot distinguish indoors and outdoors. In this paper, we implement extraction method of Stay Point in which specify the GPS log of users and extraction of Stay Point at indoors only. Stay Point(nearSP) specifies the nearest GPS log of users from generated Stay Point by conventional extraction method. And, Stay Point(indoorSP) specifies the GPS log of users that user get into the building. Our experimental results, accuracy of Stay Point is improved, and capacity of output data decrease than Conventional extraction method. Also, we were able to distinguish Stay Point of indoors and outdoors.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2E
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• pp.31-38
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• 1999

This paper focuses on extracting formants from transfer function, derived from linear prediction analysis of speech signal. The second derivative of the log magnitude spectrum of the transfer function, the first and third derivatives of the phase spectrum of the transfer function in the z-plane are discussed. Their resolutions of detecting formants are analyzed and some comparisons are given. Theoretical analyses and experimental results show that the third derivative of the phase spectrum decays more rapidly around the formant locations than the first derivative of the phase spectrum and the second derivative of the log magnitude spectrum. Compared with the second derivative of the log spectrum and the first derivative of the phase spectrum, the third derivative of the phase spectrum has higher resolution in frequency domain and provides more accurate formant extraction.

• Analytical Science and Technology
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• v.7 no.2
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• pp.225-232
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• 1994

The podands I-VII, acyclic polyethers, expected high extractability for $Ag^+$ against $Pb^{2+}$ were designed and synthesized with high yields. Using podands I-VII as extractants, the %extraction(%Ex) of $Ag^+$ and $Pb^{2+}$ as picrates were determined in water/chloroform systems. The stability constants(log K) for the complexation of $Ag^+$ with podands I-VII were also determined by potentiometry. %Ex($Ag^+$) were proportional to the numbers of substituted sulfur donor atoms. Podand VI(log K : 7.65) having 3 substituted sulfur and podand VII(log K : 9.15) having 4 substituted sulfur, however, exhibited almost 100% of extractability, respectively. In %Ex($Ag^+/Pb^{2+}$, oxygen-sulfur mixed donor podands(IV-VII) showed the higher values. Otherwise, the values of log K and %Ex($Ag^+$) largely depended on the variation of donor-site of sulfur. From the results of NMR experiments, it seems that it is due to the ${\pi}-{\pi}$ stacking interaction between the aromatic end-groups.

• MALSORI
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• no.59
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• pp.13-25
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• 2006

In previous study, the linlog(linear log) RASTA(J-RASTA) approach based on PLP was proposed to deal with both the channel effect and the additive noise. The extraction of PLP required generally more steps and computation than the extraction of widely used MFCC. Thus, in this paper, we apply the linlog function to the MFCC for investigating the possibility of simple compensation method that removes both distortion. With the experimental results, the proposed method shows the similar tendency to the linlog RASTA-PLP_ When the J value is set to le-6, the best ERR(Error Reduction Rate) of 33% is obtained. For applying the linlog function to the feature extraction process, the J value plays a very important role in compensating the corruption. Thus, the study for the adaptive J or noise dependent J estimation is further required.

• Journal of Environmental Science International
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• v.8 no.3
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• pp.371-377
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• 1999

The effects of benzamidoxime concentration, solvents and temperature on the degree of metal extraction were investigated to apply benzamidoxime to heavy metal extraction as chelating agent. Benzamidoxime was synthesized from benzonitrile with hydroxylamine. The chemical structure of benzamidoxime was identified. The degree of heavy metal extraction was increased with increasing the concentration of benzamidoxime and decreasing the extraction temperature. Benzamidoxime was found to be an concentration of benzamidoxime and decreasing the extraction temperature. Benzamidoxime was found to be an effective extractant for Cu-extraction by benzene or chloroform. The relationship between the thermodynamic overall equilibrium constant and absolute temperature was expressed as log K = -5.56 ＋ $855T^{-1}$. Heat of extraction, $$\Delta$H^0$ were calculated from overall equilibrium constants at various temperature and the extraction reactionby benzamidoxime was found to be exthothermic.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.231-241
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• 2019

Web Usage Mining (WUM) is one part of Web mining and also the application of data mining technique. Web mining technology is used to identify and analyze user's access patterns by using web server log data generated by web users when users access web site. So first of all, it is important that the data should be acquired in a reasonable way before applying data mining techniques to discover user access patterns from web log. The main task of data acquisition is to efficiently obtain users' detailed click behavior in the process of users' visiting Web site. This paper mainly focuses on data acquisition stage before the first stage of web usage mining data process with activities like data acquisition strategy and field extraction algorithm. Field extraction algorithm performs the process of separating fields from the single line of the log files, and they are also well used in practical application for a large amount of user data.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.335-340
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• 2018

Commercialized speech recognition systems that have an accuracy recognition rates are used a learning model from a type of speaker dependent isolated data. However, it has a problem that shows a decrease in the speech recognition performance according to the quantity of data in noise environments. In this paper, we proposed the vector quantization based speech recognition performance improvement using maximum log likelihood in Gaussian distribution. The proposed method is the best learning model configuration method for increasing the accuracy of speech recognition for similar speech using the vector quantization and Maximum Log Likelihood with speech characteristic extraction method. It is used a method of extracting a speech feature based on the hidden markov model. It can improve the accuracy of inaccurate speech model for speech models been produced at the existing system with the use of the proposed system may constitute a robust model for speech recognition. The proposed method shows the improved recognition accuracy in a speech recognition system.

• Analytical Science and Technology
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• v.5 no.1
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• pp.63-71
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• 1992

Liquid chromatographic behavior of Pd(II), Ni(II) and Co(III) in N-Alkylisonitrosoacetylacetone imine(HIAA-NR) chelates was investigated by reversed phase high perfomance liquid chromatography. The optimum conditions for the separation of IAA-NR-metal chelates were examined respect to the flow rate and mobile phase strength. The metal-N-Alkylisonitrosoacetylacetone imine chelates in solution were successfully separated on Novapak $C_{18}$ column using acetonitrile/water mixture as mobile phase. The elution order of chelates is methyl>ethyl>propyl>butyl as N-alkyl group for ligand is varied. It was found that all IAA-NR-metal chelates were eluted in an acceptable range of capacity factor value($0{\leq}log\;k^{\prime}{\leq}1$). The dependence of log k' on the volume fraction of water in the binary mobile phase was examined. Also, the dependence of k' on the liquid-liquid extraction distribution ratio(Dc) in acetonitrile-water-alkane extraction system was investigated for IAA-NR-metal chelate. Both kinds of dependence are linear, which suggests that the retention of the electroneutral metal chelates on Novapak $C_{18}$ column is largely due to the hydrophobic effect.

• ETRI Journal
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• v.26 no.3
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• pp.273-276
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• 2004

We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.