• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.4
• /
• pp.711-725
• /
• 2013

A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

• The Journal of the Acoustical Society of Korea
• /
• v.38 no.4
• /
• pp.415-426
• /
• 2019

In this paper, we discussed automatic target tracking algorithms for diver detection sonar that observes penetration forces of coastal military installations and major infrastructures. First of all, we analyzed sea trial data in diver detection sonar and composed automatic target tracking algorithms based on track existence probability as track quality measure in clutter environment. In particular, these are presented track management algorithms which include track initiation, confirmation, termination, merging and target tracking algorithms which include single target tracking IPDAF (Integrated Probabilistic Data Association Filter) and multitarget tracking LMIPDAF (Linear Multi-target Integrated Probabilistic Data Association Filter). And we analyzed performances of automatic target tracking algorithms using sea trial data and monte carlo simulation data.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2000.03b
• /
• pp.125-132
• /
• 2000

This study presents the application of genetic algorithms(GA) to the back analysis of tunnels. GA based on the theory of natural evolution, and have been evaluated very effective for their robust performances, particularly for optimizing structure problems. In the back analysis method, the selection of initial value and uncertainty of field measurements influence significantly on the analysis result. GA can improve this problems through a probabilistic approach. Besides, this technique have two other advantages over the back analysis. One is that it is not significantly affected by the form of problems. Another one is that it can consider two known parameter simultaneously. The propriety of this study is verified as the comparison in the same condition of the back analysis(Gens et al, 1987). In this study, it was performed to estimated the geotechnical parameters in the case of weak rock mass at the Kyung Bu Express railway tunnel. GA have been shown for effective application to a geotechnical engineering.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.667-670
• /
• 2001

For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PEM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. For the verification of this analysis, a comparison study of th PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Proceedings of the KSME Conference
• /
• 2001.06a
• /
• pp.459-464
• /
• 2001

For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.10
• /
• pp.154-160
• /
• 2001

For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. for the verification of this analysis, a comparison study of the PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.6
• /
• pp.513-519
• /
• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Steel and Composite Structures
• /
• v.15 no.1
• /
• pp.15-39
• /
• 2013

The sensitivities of a structural response due to variation of its design parameters are prerequisite in the majority of the algorithms used for fundamental problems in engineering as system uncertainties, identification and probabilistic assessments etc. The paper presents the concept of probabilistic sensitivity of suspension bridges with respect to near-fault ground motion. In near field earthquake ground motions, large amplitude spectral accelerations can occur at long periods where many suspension bridges have significant structural response modes. Two different types of suspension bridges, which are Bosporus and Humber bridges, are selected to investigate the near-fault ground motion effects on suspension bridges random response sensitivity analysis. The modulus of elasticity is selected as random design variable. Strong ground motion records of Kocaeli, Northridge and Erzincan earthquakes are selected for the analyses. The stochastic sensitivity displacements and internal forces are determined by using the stochastic sensitivity finite element method and Monte Carlo simulation method. The stochastic sensitivity displacements and responses obtained from the two different suspension bridges subjected to these near-fault strong-ground motions are compared with each other. It is seen from the results that near-fault ground motions have different impacts stochastic sensitivity responses of suspension bridges. The stochastic sensitivity information provides a deeper insight into the structural design and it can be used as a basis for decision-making.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1682-1685
• /
• 2005

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.275-282
• /
• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.