• Communications for Statistical Applications and Methods
• /
• v.19 no.2
• /
• pp.277-286
• /
• 2012

For credit assessment models, the ROC curves evaluate the classification performance using two univariate cumulative distribution functions of the false positive rate and true positive rate. In this paper, it is extended to two bivariate normal distribution functions of default and non-default borrowers; in addition, the bivariate ROC curves are proposed to represent the joint cumulative distribution functions by making use of the linear function that passes though the mean vectors of two score random variables. We explore the classification performance based on these ROC curves obtained from various bivariate normal distributions, and analyze with the corresponding AUROC. The optimal threshold could be derived from the bivariate ROC curve using many well known classification criteria and it is possible to establish an optimal cut-off criteria of bivariate mixture distribution functions.

• Journal of Korean Society of Steel Construction
• /
• v.15 no.3
• /
• pp.299-311
• /
• 2003

This paper presents a finite element procedure to estimate the ultimate strength of space frames considering spread of plasticity. The improved displacement field is introduced based on the inclusion of second-order terms of finite rotations. All the non-linear terms due to bending moment, torsional moment, and axial force are precisely considered. The concept of plastic hinges is introduced and the incremental load/displacement method is applied for elasto-plastic analyses. The initial yield surface is defined based on the residual stress, and the full plastification surface is considered under the combined action of axial forces, bending and torsional moments. The elasto-plastic stiffness matrices are derived using the flow rule and the normality condition of the limit function. Finite element solutions for the ultimate strength of space frames are compared with available solutions and experimental results.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.2 s.46
• /
• pp.63-70
• /
• 2007

The Data Encryption Standard (DES) is a block cipher that encrypts a 64 bit block of plaintext into a 64 bit block of ciphertext. The DES has been a worldwide standard for 20 years since it was adopted in 1976. strong. But, due to the rapid development of hardware techniques and cryptanalysis, the DES with 64-bit key is considered to be not secure at the present time. Therefore it became necessary to increase the security of DES. The NG-DES(New Generation DES)[1] is an encryption system which upgrades the encryption security of DES by the key extension and the usage of non-linear f function. It extends not only the size of plaintext and ciphertext to 128 bit but also the Fiestel structure used in each round. This structure has a weak point that the change of each bit of plaintext does not affect all bits of ciphertext simultaneously. In this paper, we propose a modified Fiestel structure of DES and thus increased confusion and diffusion by effectively cross-connecting between outputs in a round and inputs in next round.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.13 no.6
• /
• pp.538-545
• /
• 2002

In the orthogonal frequency division multiplexing (OFDM) system, the nonlinear distortion in the high power amplifier(HPA) degrades the system performance because of the high peak-to-average power ratio (PAPR). In this paper, a semi-analytical method is newly proposed for the performance evaluation of the nonlinearly distorted OFDM communication system. In the proposed method, at first, the probability density function (pdf) of the PAPR is generated by computer simulation. Then, mean and variance of the non-linear distortion noise process are computed. Next, the overall BER is found by the analytical method. When the equivalent SSPA model is applied in case of the QPSK/16-QAM and AWGN channel, the BER is calculated for the variation of the IBO(input back-off) and PAPR parameter. It is shown that the results by proposed method are very similar to those of the conventional Monte-Carlo method. The computation time can be considerably reduced than the conventional method that depends on the magnitudes of BER and IBO.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.3
• /
• pp.289-293
• /
• 2005

Pattern classification extracts various types of pattern information expressing objects in the real world and decides their class. The top priority of pattern classification technologies is to improve the performance of classification and, for this, many researches have tried various approaches for the last 40 years. Classification methods used in pattern classification include base classifier based on the probabilistic inference of patterns, decision tree, method based on distance function, neural network and clustering but they are not efficient in analyzing a large amount of multi-dimensional data. Thus, there are active researches on multiple classifier systems, which improve the performance of classification by combining problems using a number of mutually compensatory classifiers. The present study identifies problems in previous researches on multiple SVM classifiers, and proposes BORSE, a model that, based on 1:M policy in order to expand SVM to a multiple class classifier, regards each SVM output as a signal with non-linear pattern, trains the neural network for the pattern and combine the final results of classification performance.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.32 no.2
• /
• pp.165-169
• /
• 1999

Experiments were conducted to evaluate a experimental model developed for the protein removal by foam separation. The foam separator was operated in well-mixed tank which would be considered as a completely mixed condition. The feasibility of foam separation to remove protein from sea water was investigated. Protein removal characteristics of the foam separator were obtained by batch experiments. To find the effect of the operating parameter to protein removal rate, the foam separation was carried with variation of initial protein concentration and superficial air velocity. The result indicated that the protein removal efficiency was increased with increasing protein concentration and superficial air velocity. The relationship between operation parameters and protein removal rate were evaluated by non-linear regression as the form of exponential function, Using both relationships, the simplified model was determined. The simplified foam separator operation model was verified by the batch operation. The simulation results showed a good relationship with the experimental data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.6
• /
• pp.483-490
• /
• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.11
• /
• pp.73-82
• /
• 2014

The LM algorithm is used in solving the least square problem in a non linear system, and is used in various fields. However, in cases the applied field's target functionis complicated and high-dimensional, it takes a lot of time solving the inner matrix and vector operations. In such cases, the LM algorithm is unsuitable in embedded environment and requires a hardware accelerator. In this paper, we implemented the LM algorithm in hardware. In the implementation, we used pipeline stages to divide the target function operation, and reduced the period of data input of the matrix and vector operations in order to accelerate the speed. To measure the performance of the implemented hardware, we applied the refining fundamental matrix(RFM), which is a part of 3D reconstruction application. As a result, the implemented system showed similar performance compared to software, and the execution speed increased in a product of 74.3.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.28 no.5
• /
• pp.543-551
• /
• 2015

Polyurethane Foam(PUF), a outstanding thermal insulation material, is used for various structures as being composed with other materials. These days, PUF composed with glass fiber, Reinforced PUF(R-PUF), is used for a insulation system of LNG Carrier and performs function of not only the thermal insulation but also a structural member for compressive loads like a sloshing load. As PUF is a porous material made by mixing and foaming, mechanical properties depend on volume fraction of voids which is a dominant parameter on density. Thus, In this study, density is considered as the effect parameter on mechanical properties of Polyurethane Foam, and mechanical behavior for compression of the material is described by using modified Gurson damage model.

• Structural Engineering and Mechanics
• /
• v.12 no.5
• /
• pp.507-526
• /
• 2001

In standard finite element algorithms, the local stability conditions are not accounted for in the formulation of the tangent stiffness matrix. As a result, the loss of the local stability is not adequately related to the onset of the global instability. The phenomenon typically arises with material-type localizations, such as shear bands and plastic hinges. This paper addresses the problem in the context of the planar, finite-strain, rate-independent, materially non-linear beam theory, although the proposed technology is in principle not limited to beam structures. A weak formulation of Reissner's finite-strain beam theory is first presented, where the pseudocurvature of the deformed axis is the only unknown function. We further derive the local stability conditions for the large deformation case, and suggest various possible combinations of the interpolation and numerical integration schemes that trigger the simultaneous loss of the local and global instabilities of a statically determined beam. For practical applications, we advice on a procedure that uses a special numerical integration rule, where interpolation nodes and integration points are equal in number, but not in locations, except for the point of the local instability, where the interpolation node and the integration point coalesce. Provided that the point of instability is an end-point of the beam-a condition often met in engineering practice-the procedure simplifies substantially; one of such algorithms uses the combination of the Lagrangian interpolation and Lobatto's integration. The present paper uses the Galerkin finite element discretization, but a conceptually similar technology could be extended to other discretization methods.