• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.04a
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• pp.73-81
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• 1995

In Korea, the pilot construction of the first high-speed railroad on the Seoul-Pusan has already started 2 years ago. In the thesis, an attempt is made to develop reliability-based integrity-assessment models for the computer-aided control and maintenance of high-speed railroad bridges. The strength limit state models for PC railroad bridges encompass the bending and shear strengths as well as the strength interaction equations which simultaneously take into the element and system reliablities of the proposed limit states and reliability models. Then, the actual load carrying capacity and the realistic safety of bridges are evaluated using the system reliability-based equivalent strength, and the results are compared with those of the element reliability-based or conventional methods. Various parametric studies are performed for the proposed reliability-based safety and integrity-assessment models using the actual PC box girder bridges used in the pilot construction. And the sensitivity analyses are performed for the basic random variables included in strength limit state models. It is concluded that proposed models may be practically applied for the rational assessment of safety and integrity of high speed railroad bridges.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.96-107
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• 2009

Worm attacks can greatly distort network performance, and countering infections can exact a heavy toll on economic and technical resources. Worm modeling helps us to better understand the spread and propagation of worms through a network, and combining effective types of mitigation techniques helps prevent and mitigate the effects of worm attacks. In this paper, we propose a mathematical model which combines both dynamic quarantine and passive benign worms. This Passive Worm Dynamic Quarantine (PWDQ) model departs from previous models in that infected hosts will be recovered either by passive benign worms or quarantine measure. Computer simulation shows that the performance of our proposed model is significantly better than existing models, in terms of decreasing the number of infectious hosts and reducing the worm propagation speed.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.193-199
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• 2014

As the requirement on the quality of the system has increased, the reliability is very important part in terms of enhance stability and to provide high quality services to customers. Many statistical models have been developed in the past years for the estimation of software reliability. We consider the functions for NHPP software reliability model and time series model in software failure data. We estimate parameters for the proposed models from three data sets. The values of SSE and MSE is presented from three data sets. We compare the predicted number of faults with the actual three data sets using the NHPP software reliability model and time series model.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.671-675
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• 2011

DVC (Distributed Video Coding) and FRUC (Frame Rate Up Conversion) techniques need to have an efficient motion compensated frame interpolation algorithms. Conventional works of these applications have mainly focused on the performance improvement of overall system. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame matches the original frame. For this aim, this paper deals with the modeling methods for evaluating the block-based matching cost. First, several matching criteria, which have already been dealt with the motion compensated frame interpolation, are introduced and then combined to make estimate models for the size of MSE (Mean Square Error) noise of the MCI frame to original one. Through computer simulations, it is shown that the block-based matching criteria are evaluated and the proposed model can be effectively used for estimating the MSE noise.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1796-1816
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• 2020

The health and safety of elderly and disabled patients who cannot live alone is an important issue. Timely detection of sudden events is necessary to protect these people, and anomaly detection in smart homes is an efficient approach to extracting such information. In the real world, there is a causal relationship between an occupant's behaviour and the order in which appliances are used in the home. Bayesian networks are appropriate tools for assessing the probability of an effect due to the occurrence of its causes, and vice versa. This paper defines different subsets of random variables on the basis of sensory data from a smart home, and it presents an anomaly detection system based on various models of Bayesian networks and drawing upon these variables. We examine different models to obtain the best network, one that has higher assessment scores and a smaller size. Experimental evaluations of real datasets show the effectiveness of the proposed method.

• Computers and Concrete
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• v.4 no.4
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• pp.259-272
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• 2007

A method based on the lower-bound theorem of limit analysis is presented for the capacity assessment of nodal zones in strut-and-tie models. The idealized geometry of the nodal zones is formed by the intersection of effective widths of the framing struts and ties. The stress distribution is estimated by dividing the nodal zones into constant stress triangles separated by lines of stress discontinuity. The strength adequacy is verified by comparing the biaxial stress field in each triangle with the corresponding failure criteria. The approach has been implemented in a computer-based strut-and-tie tool called CAST (Computer-Aided Strut-and-Tie). An application example is also presented to illustrate the approach.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1025-1030
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• 2005

This paper deals with the emotional model of the software-robot. The software-robot requires several capabilities such as sensing, perceiving, acting, communicating, and surviving. and so on. There are already many studies about the emotional model like KISMET and AIBO. The new emotional model using the modified friendship scheme is proposed in this paper. Quite often, the available emotional models have time invariant human respond architectures. Conventional emotional models make the sociable robot get around with humans, and obey human commands during robot operation. This behavior makes the robot very different from real pets. Similar to real pets, the proposed emotional model with the modified friendship capability has time varying property depending on interaction between human and robot.

• Genomics & Informatics
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• v.1 no.1
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• pp.32-39
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• 2003

We present a latent variable model-based approach to the analysis of gene expression patterns, coupled with topographic clustering. Aspect model, a latent variable model for dyadic data, is applied to extract latent patterns underlying complex variations of gene expression levels. Then a topographic clustering is performed to find coherent groups of genes, based on the extracted latent patterns as well as individual gene expression behaviors. Applied to cell cycle­regulated genes of the yeast Saccharomyces cerevisiae, the proposed method could discover biologically meaningful patterns related with characteristic expression behavior in particular cell cycle phases. In addition, the display of the variation in the composition of these latent patterns on the cluster map provided more facilitated interpretation of the resulting cluster structure. From this, we argue that latent variable models, coupled with topographic clustering, are a promising tool for explorative analysis of gene expression data.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.996-1003
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• 1990

We present algebraic algorithms for collision-avoidance robot motion planning problems with planar geometric models. By decomposing the collision-free space into horizontal vertex visibility cells and connecting these cells into a connectivity graph, we represent the global topological structure of collision-free space. Using the C-space obstacle boundaries and this connectivity graph we generate exact (non-heuristic) compliant and gross motion paths of planar curved objects moving with a fixed orientation amidst similar obstacles. The gross motion planning algorithm is further extended (though using approximations) to the case of objects moving with both translational and rotational degrees of freedom by taking slices of the overall orientations into finite segments.