• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.55-63
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• 2019

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.

• Journal of IKEEE
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• v.24 no.4
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• pp.1022-1027
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• 2020

In this paper, SVM-based speaker classification is experimented with GMM-supervector. To create a speaker cluster, conventional speaker change detection is performed with the KL distance using the SNR-based weighting function. SVM-based speaker classification consists of two steps. In the first step, SVM-based classification between UBM and speaker models is performed, speaker information is indexed in each cluster, and then grouped by speaker. In the second step, the SVM-based classification between UBM and speaker models is performed by inputting the speaker cluster group. Linear and RBF are applied as kernel functions for SVM-based classification. As a result, in the first step, the case of applying the linear kernel showed better performance than RBF with 148 speaker clusters, MDR 0, FAR 47.3, and ER 50.7. The second step experiment result also showed the best performance with 109 speaker clusters, MDR 1.3, FAR 28.4, and ER 32.1 when the linear kernel was applied.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.337-343
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• 2014

This paper presents a continuum-based shape design sensitivity analysis(DSA) method for crack propagation problems using a reproducing kernel method(RKM), which facilitates the remeshing problem required for finite element analysis(FEA) and provides the higher order shape functions by increasing the continuity of the kernel functions. A linear elasticity is considered to obtain the required stress field around the crack tip for the evaluation of J-integral. The sensitivity of displacement field and stress intensity factor(SIF) with respect to shape design variables are derived using a material derivative approach. For efficient computation of design sensitivity, an adjoint variable method is employed tather than the direct differentiation method. Through numerical examples, The mesh-free and the DSA methods show excellent agreement with finite difference results. The DSA results are further extended to a shape optimization of crack propagation problems to control the propagation path.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.36-44
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• 2010

Recently, as new weapons are being developed, test equipments to test their functions inevitably require real-time features. However, since test equipments based on Windows can not support real-time requirements, we have no choice but to use third-party solutions such as RTX or INtime. This leads to increase the development cost of each test equipment. This paper suggests an real-time implemented kernel(RTiK) which operates as a device driver on Windows. RTiK provides another timer using the Local APIC of x86 microprocessors. It supports real-time requirements by periodically executing the required services using Windows-independent timer interrupts to guarantee task deadlines. To reduce the interrupt latency, we used deferred procedure calls provided by Windows. We also used the export driver to implement and modify user-defined functions without accessing the RTiK internals. Using an oscilloscope, we prove that the RTiK kernel proposed in this paper guarantees up to 0.1ms periods.

• Food Science of Animal Resources
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• v.29 no.1
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• pp.132-139
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• 2009

The objective of this study was to investigate the most effective analysis methods for palatability grading of Hanwoo beef by comparing the results of discriminant analysis with sensory data. The sensory data were obtained from sensory testing by 1,300 consumers evaluated tenderness, juiciness, flavor-likeness and overall acceptability of Hanwoo beef samples prepared by boiling, roasting and grilling cooking methods. For the discriminant analysis with one factor, overall acceptability, the linear discriminant functions and the non-parametric discriminant function with the Gaussian kernel were estimated. The linear discriminant functions were simple and easy to understand while the non-parametric discriminant functions were not explicit and had the problem of selection of kernel function and bandwidth. With the three palatability factors such as tenderness, juiciness and flavor-likeness, the canonical discriminant analysis was used and the ability of classification was calculated with the accurate classification rate and the error rate. The canonical discriminant analysis did not need the specific distributional assumptions and only used the principal component and canonical correlation. Also, it contained the function of 3 factors (tenderness, juiciness and flavor-likeness) and accurate classification rate was similar with the other discriminant methods. Therefore, the canonical discriminant analysis was the most proper method to analyze the palatability grading of Hanwoo beef.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.703-707
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• 2008

This paper designs and implements a software prober to support a more effective power analysis for Linux-based embedded systems by using power consumption data measured in hardware. The proposed software prober, which is included in a target system as a module, collects power data and provides a service to discover major power consumers in user functions of applications or kernel functions through time synchronization between the power data measured in hardware and software. In addition, we verified usefulness of the implemented software prober by running user applications on target systems.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.1-6
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• 2017

For the algorithm of cross-information potential with delta functions (CIPD) which has superior performance in impulsive noise environments, a new method of employing the information of power variations of magnitude controlled input (MCI) in the weight update equation of the CIPD is proposed in this paper where the input of CIPD is modified by the Gaussian kernel of error. To prove its effectiveness compared to the conventionalCIPD algorithm, the distance between the current weight vector and its previous one is analyzed and compared under impulsive noise. In the simulation results the proposed method shows a two-fold improvement in steady state stability, faster convergence speed by 1.8 times, and 2 dB - lower minimum MSE in the impulsive noise situation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1353-1360
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• 2005

Injection-molded products serve a wide range of applications in our modem lives and their significance is ever increasing. However, difficulty of communication among related companies under the present system results in increase of lead time and decrease of production efficiency. The objective of this paper is the development of a web-based draft verification system in mold design processes. Although several commercial CAD systems offer draft verification functions, those systems are very expensive and inadequate to perform collaborative works. For collaborative work under the distributed environment, the proposed system uses native file transforming of CAD data into optimal format by using the ACIS kernel and InterOp. Functions of draft verification modules are constructed over the ActiveX control using the visual C++ and OpenGL. Therefore, collaborators related to the development of a new product are able to verify the draft and undercut over the Internet without commercial CAD systems. The system helps to reduce production cost, errors and lead-time to the market. Performance of the system is confirmed through various case studies.

• Earthquakes and Structures
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• v.22 no.2
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• pp.157-168
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• 2022

A moment-independent importance measure analysis approach was introduced to quantify the effects of structural uncertainty parameters on probabilistic seismic demands of simply supported girder bridges. Based on the probability distributions of main uncertainty parameters in bridges, conditional and unconditional bridge samples were constructed with Monte-Carlo sampling and analyzed in the OpenSees platform with a series of real seismic ground motion records. Conditional and unconditional probability density functions were developed using kernel density estimation with the results of nonlinear time history analysis of the bridge samples. Moment-independent importance measures of these uncertainty parameters were derived by numerical integrations with the conditional and unconditional probability density functions, and the uncertainty parameters were ranked in descending order of their importance. Different from Tornado diagram approach, the impacts of uncertainty parameters on the whole probability distributions of bridge seismic demands and the interactions of uncertainty parameters were considered simultaneously in the importance measure analysis approach. Results show that the interaction of uncertainty parameters had significant impacts on the seismic demand of components, and in some cases, it changed the most significant parameters for piers, bearings and abutments.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1993-1998
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• 2004

This paper proposes a new framework for control system design, called the data-based control approach or data space approach, in which the input and output data of a dynamical system is directly and solely used to analyze or design a control system without the employment of any mathematical models like transfer functions, state space equations, and kernel representations. Since, in this approach, most of the analysis and design processes are carried out in the domain of the data space, we introduce some notions of geometrical objects, e.g., the openloop and closed-loop data spaces, which serve as the system representations in the data space. In addition, we establish a relationship between the open-loop and closed-loop data spaces that the closed-loop data space is contained in the open-loop data space as one of its subspaces. By using this relationship, we can derive the data-based stabilization condition for a linear time-invariant discrete-time system, which leads to a linear matrix inequality with a rank constraint.