• Proceedings of the Membrane Society of Korea Conference
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• 2004.05a
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• pp.179-182
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• 2004

This study reports the extraction behavior of $\alpha$-lactalbumin using bis(2-ethylhexyl) sulfosuccinate sodium (AOT) reverse micelles. Forward extraction of $\alpha$-lactalbumin in the reverse micellar organic phase from aqueous feed solutions was strongly dependent on the AOT concentration and the complete forward extraction of 0.03 mM $\alpha$-lactalbumin was successfully achieved at an AOT concentration of ca. 100 mM. A similar dependency of the forward extraction on the AOT concentration was obtained in isooctane, n-hexane, and n-octane systems. In the backward extraction from the micellar organic phase, the recovery of the protein as high as ca. 90% was obtained with pH control and/or salt addition.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.47-50
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• 2000

DC Gummel-Poon SPICE model parameter extraction program has been implemented. This program extracts the parameters from measured data using Levenberg-Marquardt algorithm. Measured data consist of forward and reverse Gummel plot, forward and reverse output characteristics and RE and RC measurements.

• Food Science and Biotechnology
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• v.14 no.1
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• pp.131-136
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• 2005

The selective extraction behavior of lactoferrin (Lf) from whey protein mixture was examined using reverse micelles formed by the cationic surfactant, cetyldimethylammonium bromide (CDAB). The major whey proteins, including ${\beta}$-lactoglobulin, ${\alpha}$-lactalbumin and bovine serum albumin, were solubilized from aqueous phase to organic phase while Lf was recovered in the aqueous phase. The solubilization behaviors of the proteins were manipulated by the process parameters such as the pH and salt concentration of the aqueous phase and the surfactant concentration in the organic phase. Efficient forward extraction was achieved with sodium borate buffer (50 mM, pH 9) containing 50 mM KCl and organic phase containing 100 mM CDAB. Based on SDS-PAGE and densitometry, about 96% of the initial Lf remained in the aqueous phase after forward extraction. The dialyzed Lf fully maintained its bacteriostatic activity against E. coli O157:H7.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.439-444
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• 2016

The method for extracting the SPICE model parameter of Schottky diode under DC forward bias is proposed. A method for improving the accuracy of the SPICE model parameter at various temperatures is proposed. Three analysis steps according to the magnitude of the current is used in order to extract the parameters effectively. At each analysis step, initial parameters are calculated by using the current-voltage equations and the Levenberg-Marquardt analysis is proceeded. To verify the validity of the proposed method, the SPICE model parameters for the BAT45 and FSV1045 under DC forward bias is extracted. Schottky diode currents obtained from the proposed method shows the average relative error of 6.1% and 9% compared with the measured data for the BAT45 and FSV1045 sample at various temperatures.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.665-671
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• 2010

This paper propose the DDEGST(divergent-direction-emphasis generalized symmetry transform) which emphasis the symmetry of divergent intensity orientation for effective target extraction in FLIR(forward looking infra-red) images. In the proposed method, we use the exponential function instead of cosine function as a phase weight function in the generalized symmetry transform for effective target extraction in FLIR images which contain a target with higher intensity than a background intensity. To evaluate the performance of the proposed method, we compare the proposed mehtod with conventional GST method in experiments. We prove that the proposed method have better performance in IR images.

• KSBB Journal
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• v.14 no.6
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• pp.661-664
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• 1999

Proteins were extracted from an aqueous phase with reversed micelles. The effect of pH, and salt concentration on the solubilization of lysozyme in AOT/isooctane solution was studied to explore the potential for employing this solvent system in the large-scale recovery and concentration of proteins using liquid extraction. For pH values below the isoelectric point, pl of the protein, solubilization was high, probably owing to strong electrostatic interactions between the positively charged proteins and the anionic surfactant heads forming the inner micelle wall. At low ionic strength complete solubilization of the protein was observed. A pH higher than the pl of lysozyme and a salt concentration lower than that of the water pool were required for the recovery aqueous phase to ensure the back extraction of lysozyme from the AOT reversed micelles.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.125-134
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• 2018

Lamport firstly suggested password base authentication scheme and then, similar authentication schemes have been studied. Due to the development of Internet network technology, remote user authentication using smart card has been studied. Li et al. analyzed authentication scheme of Chen et al. and then, Li et al. found out the security weakness of Chen et al.'s scheme such forward secrecy and the wrong password login problem, and proposed an a new smart card based user password authentication scheme. But Liu et al. found out that Li et al.'s scheme still had security problems such an insider attack and man-in-the-middle attack and then Liu et al. proposed an efficient and secure smart card based password authentication scheme. This paper analyzed Liu et al.'s authentication and found out that Liu et al.'s authentication has security weakness such as no perfect forward secrecy, off-line password guessing attack, smart-card loss attack, and no anonymity. And then, this paper proposed security enhanced efficient smart card based password authentication scheme using fuzzy extraction technology.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.313-314
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• 2007

In this paper, we suggest robust object extraction algorithm taking advantage of efficient Belief Propagation method. It does not get a disparity information because of uniform region and occlusion region etc. on initial depth map that use forward direction disparity information although is object area. Therefore, We run parallel backward disparity information and brightness information for certain object extraction.