• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.411-418
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• 2020

In the field of information security, IDS(Intrusion Detection System) is normally classified in two different categories: signature-based IDS and anomaly-based IDS. Many studies in anomaly-based IDS have been conducted that analyze network traffic data generated in cyberspace by machine learning algorithms. In this paper, we studied pre-processing methods to overcome performance degradation problems cashed by rare classes. We experimented classification performance of a Machine Learning algorithm by reconstructing data set based on rare classes and semi rare classes. After reconstructing data into three different sets, wrapper and filter feature selection methods are applied continuously. Each data set is regularized by a quantile scaler. Depp neural network model is used for learning and validation. The evaluation results are compared by true positive values and false negative values. We acquired improved classification performances on all of three data sets.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.251-267
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• 2003

In order to satisfy the needs of an intelligent information system, it is necessary to have more intelligent query processing in an object-oriented database. In this paper, we present a method to apply intelligent query processing in object-oriented databases using deductive approach. Using this method, we generate intelligent answers to represent the answer-set abstractly for a given query in object-oriented databases. Our approach consists of few stages: rule representation, rule reformation pre-resolution, and resolution. In rule representation, a set of deductive rules is generated based on an object-oriented database schema. In rule reformation, we eliminate the recursion in rules. In pre-resolution, rule transformation is done to get unique intensional literals. In resolution, we use SLD-resolution to generate intensional answers.

• Journal of the Korean Society of Systems Engineering
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• v.1 no.2
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• pp.26-33
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• 2005

In this paper, an algorithm is presented to recognize road based on unpaved test courses image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, gray level slicing, masking and identification of unpaved test courses. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing unpaved road. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning or assistance system.

• ETRI Journal
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• v.32 no.3
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• pp.395-405
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• 2010

A novel multiclassifier system (MCS) strategy is proposed and applied to a text-dependent speaker verification task. The presented scheme optimizes the linear combination of classifiers on an on-line basis. In contrast to ordinary MCS approaches, neither a priori distributions nor pre-tuned parameters are required. The idea is to improve the most accurate classifier by making use of the incremental information provided by the second classifier. The on-line multiclassifier optimization approach is applicable to any pattern recognition problem. The proposed method needs neither a priori distributions nor pre-estimated weights, and does not make use of any consideration about training/testing matching conditions. Results with Yoho database show that the presented approach can lead to reductions in equal error rate as high as 28%, when compared with the most accurate classifier, and 11% against a standard method for the optimization of linear combination of classifiers.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.124-132
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• 2018

This paper presents a shelf life assessment for K-1 military gas masks in the Republic of Korea using test data of Chemical Materiels Stockpile Reliability Program(CSRP). For the shelf life assessment, over 2,500 samples between 2006 and 2015 were collected from field tests and analyzed to estimate a probability of proper and improper functionality using Bayesian estimation. For this, three stages were considered; a pre-processing, a processing and an assessment. In the pre-processing, major components which directly influence the shelf life of the mask were statistically analyzed and selected by applying principal component analysis from all test components. In the processing, with the major components chosen in the previous stage, both proper and improper probability of gas masks were computed by applying Bayesian estimation. In the assessment, the probability model of the mask shelf life was analyzed with respect to storage periods between 0 and 29 years resulting in between 66.1 % and 100 % performances in accuracy, sensitivity, positive predictive value, and negative predictive value.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.235-245
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• 2018

Recently panoramic image overcomes camera limited viewing angle and offers wide viewing angle by stitching plenty of images. In this paper, we propose pre-processing and post-processing algorithm which makes speed and accuracy improvements when making panoramic images. In pre-processing, we can get camera sensor information and use three-dimensional rotation angle to find RoI(Region of Interest) image. Finding RoI images can reduce time when extracting feature point. In post-processing, we propose weighted minimal error boundary cut blending algorithm to improve accuracy. This paper explains our algorithm and shows experimental results comparing with existing algorithms.

• Journal of the Korean Chemical Society
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• v.43 no.3
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• pp.307-314
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• 1999

Ml RNA, the RNA component of RNase P from Escherichia coli, is produced by 3' processing of pre-Ml RNA, a major primary transcript of the rnpB gene. The enzyme fraction containing the processing activity was partially purified and characterized. Since exposure of the active fraction to the high salt condition results in the inactivation of the processing activity, the processing enzyme seems to be an enzyme complex composed of multiple enzymes. The enzyme fraction loses the processing activity when treated with the chemical nuclease lead(II) ion, but regains its activity by the addition of RNA isolated from the enzyme fraction itself, suggesting that an RNA molecule(s) may be essential for the processing activity. Analysis of cleavage sites produced by the partially purified enzyme fraction also implies that the 3' processing occurs by multiple enzymes and at least in two distinct pathways.

• Journal of the Korean GEO-environmental Society
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• v.13 no.11
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• pp.69-79
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• 2012

This pre-supported nail method is able to decrease ground displacements more than NATM because this method reinforces ground with grouted steels before tunnel excavation. Therefore this method has advantage of being able to increase the stability and workability. This study presents applicability of pre-supported nail method with case of site measurement for shallow tunnel composed with high groundwater level and unconsolidated soil, performs this research the mechanism of new supporting system is compared with the conventional existing supporting system in terms of soil reinforcement. NATM has characteristics that construction stage displacement of the apparent height difference is observed in the step of divided excavation processing. Otherwise it is analyzed that pre-supported nail method is not sensitive in the displacement problem of excavation processing in comparison to NATM. It is found that this method is very applicable in shallow depth tunnel such as portal area, tunnel in soil and weak zone without arching effect.

• Journal of Sensor Science and Technology
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• v.12 no.3
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• pp.121-127
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• 2003

In this study, we carried out a study for implementation of the pre-amplifier and the digital signal processing part for the potable EEG biofeedback system. As we consider characteristics of the EEG signal, we designed the pre-amplifier to obtain the EEG signal to be reduced noise signal. Because the EEG signal include EOG, EMG, ECG signals etc, it is difficult to analyze of the EEG signal. Therefore, we developed DSP board and operation program which was embed the LMS adaptive filter algorithm and operate with the pre-amplifier in the real time. The simulation signal and pure EEG signal is used in the experiment. As the result, we confirmed good efficiency of developed system and possibility of application to the portable EEG biofeedback system.

• Transactions of Materials Processing
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• v.8 no.4
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• pp.356-363
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• 1999

This paper discusses some techniques for the determination of optimum blank size and pre-form design for multi-stepped deep drawing of oval shell. The deep drawing process of oval shape has been regarded as more difficult than that of cylindrical shell because of its complicated behavior of plastic deformation. But there is insufficient information in this area to carry out successful deep drawing work of irregular products such as oval, rectangular, and square shapes. In order to find the optimum conditions, the drawing apparatus for two kinds of pre-form design are built, a series of drawing experiments performed, and thickness stain distributions measured. From the results of thess suggested experiments, various optimum process variables are observed and discussed.