• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.11
• /
• pp.1435-1441
• /
• 2018

Online signature verification is one of the simple and efficient methods of identity verification and has less resistance than other biometric technologies. To handle signature verification as a classification problem, it is necessary to gather forgery signatures, which is not easy in most practical applications. It is not easy to obtain a large number of genuine signatures either. In this paper, one class SVM is used to tackle the forgery signature problem and someone else's signatures are used as general handwriting data to solve the genuine signature problem. Someone else's signature does not share shape-based features with the signature to be verified, but it contains the general characteristics of a signature and useful in verification. Verification rate can be improved by using the general handwriting data, which can be confirmed through the experimental results.

• Journal of the Korean Society for Library and Information Science
• /
• v.26
• /
• pp.75-112
• /
• 1994

The purpose of this study is to investigate the problems concerning 780 music division of DDC. The object is especially arrangement of 780 music in the 20th edition of DDC which is the complete revision. The result is summarized as follows : 1. Although music is an important subject in humanities, especially in arts, it was classified as one division (780) not class. 2. The arrangement of 780 music is severely west-oriented music theory, vocal music and instrumental music. 3. Classification number of 780 music becomes longer because of the limitation of decimal notation. 4. 780 music division of DDC neglects music theory and emphasizes music practicing, especially performance. 5. The assignment of classification number is unbalanced, especially between theory and practice, composition and performance, and among sub-sections of vocal and instrumental music. 6. Many important subject are omitted in DDC music schedule, for example, musicology and branches of musicology, composition and traditional instruments of many countries. 7. Employment of terminology is often improper and inconsistant.

• Journal of the Korean Mathematical Society
• /
• v.48 no.2
• /
• pp.341-365
• /
• 2011

In this paper, we establish general stratawise higher jet evaluation transversality of J-holomorphic curves for a generic choice of almost complex structures J (tame to a given symplectic manifold (M, $\omega$)). Using this transversality result, we prove that there exists a subset $\cal{J}^{ram}_{\omega}\;{\subset}\;\cal{J}_{\omega}$ of second category such that for every $J\;{\in}\;\cal{J}^{ram}_{\omega}$, the dimension of the moduli space of (somewhere injective) J-holomorphic curves with a given ramication prole goes down by 2n or 2(n - 1) depending on whether the ramication degree goes up by one or a new ramication point is created. We also derive that for each $J\;{\in}\;\cal{J}^{ram}_{\omega}$ there are only a finite number of ramication profiles of J-holomorphic curves in a given homology class $\beta\;{\in}\;H_2$(M; $\mathbb{Z}$) and provide an explicit upper bound on the number of ramication proles in terms of $c_1(\beta)$ and the genus g of the domain surface.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2002.05a
• /
• pp.273-277
• /
• 2002

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region and synthetic image having four class using a newly proposed learning algorithm. Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) based on the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning (ETL) learning algorithm using the multilayer perceptron and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. The number of the required neurons in hidden layer can be reduced and fasted for learning pattern recognition.. The superiority of this NETLA to other algorithms was proved by simulation.

• East Asian mathematical journal
• /
• v.34 no.3
• /
• pp.295-303
• /
• 2018

Gautam et al. [9] introduced the multivariable A-function, which is very general, reduces to yield a number of special functions, in particular, the multivariable H-function. Here, first, we aim to establish two very general integral formulas involving product of the general class of Srivastava multivariable polynomials and the multivariable A-function. Then, using those integrals, we find a solution of partial differential equations of heat conduction at zero temperature with radiation at the ends in medium without source of thermal energy. The results presented here, being very general, are also pointed out to yield a number of relatively simple results, one of which is demonstrated to be connected with a known solution of the above-mentioned equation.

• Journal of the military operations research society of Korea
• /
• v.15 no.1
• /
• pp.14-27
• /
• 1989

This paper deals with the mission effectiveness of an airfleet, Airfleet operating system consists of a finite number of units performing the several mission types. Earlier works for the mission effectiveness of a fleet is limited to only one mission type and computer simulation approaches. The mission effectiveness. model of a fleet is constructed by three attributes - the mission readiness of the units, the mission reliability and capability of units. The environmental conditions and human factors affecting the mission success are considered together. The solution of the model is obtained by analytical technique. Especially, AOS is considered a closed queueing network with a finite number of units and a single job class. And then, the mission readiness of the units is found by the mean value analysis. The model would be a useful tool to readily evaluate mission effectiveness of a airfleet as it is and provide a criterion for determining the optimal operating policy.

• Journal for History of Mathematics
• /
• v.11 no.2
• /
• pp.63-76
• /
• 1998

When teaching the linear regression analysis in the class, the power transformation must be introduced to fit the linear regression model for nonlinear data. Box and Cox (1964) proposed the attractive power transformation technique which is so called Box-Cox transformation. In this paper, an effective algorithm selecting an appropriate value for Box-Cox transformation is developed which is considered to find a value minimizing error sum of squares. When the proposed algorithm is used to find a value for transformation, the number of iterations needs to be considered. Thus, the number of iterations is examined through simulation study. Since SAS is one of most widely used packages and does not provide the procedure that performs iterative Box-Cox transformation, a SAS program automatically choosing the value for transformation is developed. Hence, the students could learn how the Box-Cox transformation works, moreover, researchers can use this for analysis of data.

• The KIPS Transactions:PartD
• /
• v.15D no.6
• /
• pp.767-776
• /
• 2008

Microarray technology is extensively being used in experimental molecular biology field. Microarray experiments generate quantitative expression measurements for thousands of genes simultaneously, which is useful for the phenotype classification of many diseases. One of the two major problems in microarray data classification is that the number of genes exceeds the number of tissue samples. The other problem is that current methods generate classifiers that are accurate but difficult to interpret. Our paper addresses these two problems. We performed a direct integration of individual microarrays with same biological objectives by transforming an expression value into a rank value within a sample and generated rank-comparison decision rules with variable number of genes for cancer classification. Our classifier is an ensemble method which has k top scoring decision rules. Each rule contains a number of genes, a relationship among involved genes, and a class label. Current classifiers which are also ensemble methods consist of k top scoring decision rules. However these classifiers fix the number of genes in each rule as a pair or a triple. In this paper we generalized the number of genes involved in each rule. The number of genes in each rule is in the range of 2 to N respectively. Generalizing the number of genes increases the robustness and the reliability of the classifier for the class prediction of an independent sample. Also our classifier is readily interpretable, accurate with small number of genes, and shed a possibility of the use in a clinical setting.

• Journal of the military operations research society of Korea
• /
• v.17 no.1
• /
• pp.61-83
• /
• 1991

There has been a great deal of research dealing with the optimal replacement of stochastically deteriorating equipment and research in queueing systems with a finite calling population. However. there has been a lack of research which combines these two areas to deal with optimal replacement for a fixed number of machines and a limited number of repairmen. In this research, an optimal control policy for replacement involving two machines and one repairman is developed by investigating a class of age replacement policies in the context of controlling a G/M/1 queueing system with a finite calling population. The control policy to be imposed on this problem is an age-dependent control policy, described by the control limit $t^{\ast}$. The control limit is operational only when the repairman is idle; that is. if both machines are working, as soon as a machine reaches the age $t^{\ast}$ it is taken out of service for replacememt. We obtain the ${\epsilon}$-optimal control age which will minimize the long-run average system cost. An algorithm is developed that is applicable to general failure time distributions and cost functions. The algorithm does not require the condition of unimodality for implementation.

• Journal of The Korean Astronomical Society
• /
• v.47 no.6
• /
• pp.209-214
• /
• 2014

In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.