• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.2111-2111
• /
• 2001

A chemoinfometrical method for evaluating the quantitative determination of crystallinity one polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the and compared with the conventional powder X-ray diffraction method was performed. [Method] The pPure a and g forms of indomethacin (IMC) were prepared by reportedusing published methods. Six kinds of standard samples obtained by physically mixing of a and g forms. After the powder X-ray diffraction profiles of samples have been measured, the intensity values were normalized to against the intensity of silicon powder as the as an external standard. The calibration curves for quantification of crystal content were based upon the total relative intensity of four diffraction peaks from of the form g crystal. FT-NIR spectra of six calibration sample sets were recorded 5 times with the NIR spectrometer (BRAN+LUEBBE). Chemoinfometric analysis was performed on the NIR spectral data sets by applying the principal component regression (PCR). [Results] The relation between the actual and predicted polymorphic contents of form g IMC measured using by the X-ray diffraction method shows a good straight linen linear relation., and it has slope of 0.023, an intercept of 0.131 and a correlation coefficient of 0.986. PCR analyses wereis was performed based on normalized NIR spectra sets offer standard samples of known content of IMC g form. IMC. A calibration equation was determined to minimize the root mean square error of the predictionthe prediction. Figure 1 shows a plot of the calibration data obtained by NIR method between the actual and predicted contents of form g IMC. The predicted values were reproducible and had a smaller standard deviation. Figure 2 shows that the plot for the predicted transformation rate (%) of form a IMC to form g as measured by X-ray diffractomeoy against to those as measured by NIR method. The plot has a slope of 1.296, an intercept of 1,109, and a correlation coefficient of 0.992. The line represents a satisfactory correlation between the two predicted values of form g IMC content. Thus NIR spectroscopy is an effective method for the evaluation to the pharmaceutical products of quantitative of polymorph.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1244-1244
• /
• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1042-1042
• /
• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.22 no.1
• /
• pp.11-26
• /
• 2011

The expectation and the role for the university are rising due to the national competitiveness and change of environment in higher education in the knowledge based society, and the role to realize the effective lifelong study is also underlined in lifelong study society. And the social awareness is also diffused that the university should share the specialized substantial information resource with the community, and ensure the access right to knowledge and information to local inhabitant. Like this, the roll as an information center that the university can develop the local society as the component of the community according to the diffusion of lifelong study and the change of civic awareness. To check the open state of university libraries to community, this study surveyed and analyzed the open state of 4-year-course university libraries in Seoul and Gyoenggi region. On this base, this study emphasized that the university should open its libraries and positively offer the abundant specialized data of university libraries to the local residents. And this study suggested the way that the university libraries can cooperate connecting with the local public libraries and the school libraries as a positive service way of university libraries. Also this study accentuated that the university libraries should establish an open-door policy of its libraries and enlarge the service for the local residents by using the university conditions to maximum with the positive support of the university libraries of government and the university's bureaucracy.

• Korean Journal of Environment and Ecology
• /
• v.23 no.6
• /
• pp.603-612
• /
• 2009

This study was conducted to provide information which will be useful for establishing and implementing effective management policy for Baekdudaegan Trail and user satisfaction by investigating the characteristics of trail use and users' perceptions of the environmental impacts on the trail. For this purpose, a questionnaire survey was employed in Baekdudaegan trail by three topological types. With this classification, the characteristics of the way the trails used and users' perceptions of the impacts were analysed in terms of ecological, physical and social environments. The result showed that the Baekdudaegan trail was used mainly for mountaineering rather vacation or travel, and found no differences in the characteristics of the trail use by the types. Ecological environment showed no significant relation with user satisfaction, however changes in physical environmental factors such as a trail width functioned as a negative component to decrease use experience. In addition, the satisfaction of the users had little to do with social environment, when the level of using the trail was relatively low. To present, the levels of impacts on ecological, physical and social environments and the users' satisfaction level regarding the Baekdudaegan trail appear to be positive. However, the increase of use level is expected in the future, and therefore systematic managerial measures need to be implemented to monitor the changes of the trails and interactions of the environmental impacts.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.7B
• /
• pp.1313-1321
• /
• 1999

The two-phase locking protocol(2PL) is the most widely-used concurrency control mechanism for guaranteeing logical consistency of data in a database environment where a number of transactions perform concurrently. The problem inherent in the 2PL protocol is a deadlock, where a set of transactions holding some locks indefinitely wait an additional lock that is already held by other transactions in the set. The deadlock detector is a DBMS sub-component that examines periodically whether a system is in a deadlock state based on lock waiting information of transactions. The deadlock detector and transactions execute concurrently in a DBMS and read and/or write the lock waiting information simultaneously. Since the lock waiting information is a shared one, we need an efficient method guaranteeing its physical consistency by using mutual exclusion. The efficiency of the mutual exclusion method is crucial especially in a main memory DBMS with high performance since it seriously affects the performance of an entire system. In this paper, we propose a new method that effectively guarantees physical consistency of lock waiting information. Two primary goals of our method are to minimize the processing overhead and to maximize system concurrency.

• The KIPS Transactions:PartC
• /
• v.8C no.5
• /
• pp.573-584
• /
• 2001

Policy-Based Network Management (PBNM) architecture is to meet various needs of network users and to provide effective management facilities in distributed and large scale networks to network managers. In PBNM, network managers perform network management operations by stipulating a set of rules rather than control each network component. On the other hand, providing security services such as authentication, privacy of messages as well as a new flexible and extensible administration framework, SNMPv3 enables network managers to monitor and control the operation of network components more secure way than ever before. Despite of its enhanced security services, SNMPv3 has difficulties in managing distributed, large-scaled network because it does not provide centralized security management facilities. In this paper, we propose a new security model called Role-based Security Management model (RSM) with security management policy to support scalable and centralized security management for SNMP-based networks. Also, the structure and the operation of the security system as well as the efficiency analysis of RSM in terms of security management are also described.

• Investigative Magnetic Resonance Imaging
• /
• v.8 no.1
• /
• pp.1-8
• /
• 2004

Purpose : Information about electrical activity inside the brain during fMRl scans is very useful in monitoring physiological function of the patient or locating the spatial position of the activated region in the brain. However, many additional noises appear in the EEG signal acquired during the MRI scan. Gradient induced noise is the biggest one among the noises. In this work, we propose a gradient noise reduction method using the independent component analysis (ICA) method. Materials and Methods : We used a 29-channel MR-compatible EEG measurement system and a 3.0 Tesla MRI system. We measured EEG signals on a subject lying inside the magnet during EPI scans. We selectively removed the gradient noise from the measured EEG signal using the ICA method. We compared the results with the ones obtained with conventional averaging method and PCA method. Results : All the noise reduction methods including the averaging and PCA methods were effective in removing the noise in some extent. However, the proposed ICA method was found to be superior to the other methods. Conclusion : Gradient noise in EEG signals acquired during fMRI scans can be effectively reduced by the ICA method. The noise-reduced EEG signal can be used in fMRI studies of epileptic patients or combinatory studies of fMRI and EEG.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.34 no.3
• /
• pp.220-225
• /
• 2014

Generally, the nonlinearity of ultrasonic waves is measured using a nonlinear parameter ${\beta}$, which is defined as the ratio of the second harmonic's magnitude to the power of the fundamental frequency component after the ultrasonic wave propagates through a material. Nonlinear parameter ${\beta}$ is recognized as an effective parameter for evaluating material degradation. In this paper, we evaluated the nonlinear parameter of Al6061-T6 which had been subjected to an artificial aging heat treatment. The measurement was using the transmitted signal obtained from contact-type transducers. After the ultrasonic test, a micro Vickers hardness test was conducted. From the result of the ultrasonic nonlinear parameter, the microstructural changes resulting from the heat treatment were estimated and the hardness test proved that these estimates were reasonable. Experimental results showed a correlation between the ultrasonic nonlinear parameter and microstructural changes produced by precipitation behavior in the material. These results suggest that the evaluation of mechanical properties using ultrasonic nonlinear parameter ${\beta}$ can be used to monitor variations in the mechanical hardness of aluminum alloys in response to an artificial aging heat-treatment.

• Microbiology and Biotechnology Letters
• /
• v.33 no.4
• /
• pp.274-280
• /
• 2005

Pasteurella multocida is known to cause widespread infections in husbandry. To induce homologous and heterologous immunity against the infections, outer membrane proteins (OMPs) in the envelope of P. multocida are thought to be attractive vaccine candidates. Outer membrane protein H is considered as the major component of OMPs. In this study, a gene for OmpH was isolated from pathogenic P. multocida serogroup A. The gene was composed of 1,047 nucleotides coding 348 amino acids with signal peptide of 20 amino acids. The amino acid composition showed about 80 to 98 per cent sequence homologies among other 10 strains of P. multocida serogroup A, reported so far. A recombinant ompH, from which signal peptide was truncated, was generated using pRSET A to name 'pRSET A/OmpH-F2'. The pRSET A/OmpH-F2 was well expressed in E. coli BL21(DE3). The truncated OmpH was purified using nickel-nitrilotriacetic acid (Ni-NTA) affinity column chromatography. Its molecular weight was registered to be 40 kDa on SDS-PAGE gel. In order to generate immunesera against the OmpH, 50 ug of the protein was intraperitoneally injected into mice three times. The anti-OmpH immuneserum recognized about $5{\times}10^{-2}$ng quantity of the purified OmpH. It can be used for an effective vaccine production to prevent fowl cholera caused by pathogenic P. multocida (Serogroup A).