• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.59-66
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• 2002

This paper presents accelerated life tests for Type I censoring data under probabilistic stresses. Probabilistic stress, S, is the random variable for stress influenced by test environments, test equipments, sampling devices and use conditions. The hazard rate, $\theta$ is a random variable of environments and a function of probabilistic stress. In detail, it is assumed that the hazard rate is linear function of the stress, the general stress distribution is a gamma distribution and the life distribution for the given hazard rate, $\theta$is an exponential distribution. Maximum likelihood estimators of model parameters are obtained, and the mean life in use stress condition is estimated. A hypothetical example is given to show its applicability.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.311-316
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• 2003

The compressive strength of concrete is a criterion to produce concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of Concrete at the Construction site. Therefore, strength prediction before the placement of concrete is highly desirable. This study presents the probabilistic technique for predicting the compressive strength of concrete on the basis of concrete mix proportions. The estimation of the strength is based on the probabilistic neural network, and show that the present methods are very efficient and reasonable in predicting the compressive strength of concrete probabilistically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1659-1673
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• 2019

Android platform provides In-app Billing service for purchasing valuable items inside mobile applications. However, it has become a major target for attackers to achieve valuable items without actual payment. Especially, application developers suffer from automated attacks targeting all the applications in the device, not a specific application. In this paper, we propose a novel scheme detecting automated attacks with probabilistic tests. The scheme tests the signature verification method in a non-deterministic way, and if the method was replaced by the automated attack, the scheme detects it with very high probability. Both the analysis and the experiment result show that the developers can prevent their applications from automated attacks securely and efficiently by using of the proposed scheme.

• Journal of Advanced Navigation Technology
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• v.1 no.1
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• pp.35-46
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• 1997

Over last decade Multiple Target Tracking (MTT) has been the subject of numerous presentations and conferences [1979-1900]. Various approaches have been proposed to solve the problem. Representative works in the problem are Nearest Neighbor (NN) method based on non-probabilistic data association (DA), Multiple Hypothesis Test (MHT) and Joint Probabilistic Data Association (JPDA) as the probabilistic approaches. These techniques have their own advantages and limitations in computational requirements and in the tracking performances. In this paper, the three promising algorithms based on the NN standard filter, MHT and JPDA methods are presented and their performances against simulated multiple maneuvering targets are compared through numerical simulations.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.15-38
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• 2010

In order to predict the shear strengths of reinforced concrete beams, many deterministic models have been developed based on rules of mechanics and on experimental test results. While the constant and variable angle truss models are known to provide reliable bases and to give reasonable predictions for the shear strengths of members with shear reinforcement, in the case of members without shear reinforcement, even advanced models with complicated procedures may show lack of accuracy or lead to fairly different predictions from other similar models. For this reason, many research efforts have been made for more accurate predictions, which resulted in important recent publications. This paper develops probabilistic shear strength models for reinforced concrete beams without shear reinforcement based on deterministic shear strength models, understanding of shear transfer mechanisms and influential parameters, and experimental test results reported in the literature. Using a Bayesian parameter estimation method, the biases of base deterministic models are identified as algebraic functions of input parameters and the errors of the developed models remaining after the bias-correction are quantified in a stochastic manner. The proposed probabilistic models predict the shear strengths with improved accuracy and help incorporate the model uncertainties into vulnerability estimations and risk-quantified designs.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.11 s.254
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• pp.1417-1424
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• 2006

In order to evaluate variation of fatigue life of mechanical components including engineering plastics, it is important to estimate probabilistic strain-life curves to accurately define the variation of fatigue characteristics. This paper intends to provide new assessment of P-$\varepsilon$-N (probabilistic strain-life curves) for considering the variation of fatigue characteristics in polyacetal. The fatigue strain controlled tests were conducted under constant 50% humidity and room temperature condition by a universal testing machine at strain ratio, R=0. A practical procedure is introduced to evaluate probabilistic strain-life curves. Three probabilistic distributions were used for generating P-$\varepsilon$-N curves such as normal, 2-parameter and 3-parameter Weibull. In this study, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue characteristic were examined using chi-square and Kolmogorov-Smirnov test. The more appropriate P-$\varepsilon$-N curves for these materials are generated by the proposed method considering 3-parameter Weibull distribution.

• International Journal of Concrete Structures and Materials
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• v.19 no.1E
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• pp.11-16
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• 2007

Recently, probabilistic neural network (PNN) has been proposed to predict the compressive strength of concrete for the known effect of improvement on PNN by the iteration method. However, an empirical method has been incorporated in the PNN technique to specify its smoothing parameter, which causes significant uncertainty in predicting the compressive strength of concrete. In this study, a modified probabilistic neural network (MPNN) approach is hence proposed. The global probability density function (PDF) of variables is reflected by summing the heterogeneous local PDFs which are automatically determined by the individual standard deviation of each variable. The proposed MPNN is applied to predict the compressive strength of concrete using actual test data from a concrete company. The estimated results of MPNN are compared with those of the conventional PNN. MPNN showed better results than the conventional PNN in predicting the compressive strength of concrete and provided promising results for the probabilistic approach to predict the concrete strength by using the individual standard deviation of a variable.

• Geomechanics and Engineering
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• v.18 no.6
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.

• Journal of KIISE
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• v.44 no.3
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• pp.239-245
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• 2017

Probabilistic grammar is used in natural language processing, and the parse result of the grammar has to preserve the probability of the original grammar. As for the representative parsing method, LL parsing and LR parsing, the former preserves the probability information of the original grammar, but the latter does not. A characteristic of a probabilistic parsing automaton has been studied; but, currently, the generating model of probabilistic parsing automata has not been known. The paper provides a model of probabilistic parsing automata based on the single state parsing automata. The generated automaton preserves the probability of the original grammar, so it is not necessary to test whether or not the automaton is probabilistic parsing automaton; defining a probability function for the automaton is not required. Additionally, an efficient automaton can be constructed by choosing an appropriate parameter.

• Journal of The Korean Association For Science Education
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• v.25 no.7
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• pp.787-793
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• 2005

The purposes of this study were to investigate the development of probabilistic thinking in relation to the cognitive level of elementary school students and to analyze the effects of probability activities in Thinking Science(TS) program on the development of probabilistic thinking. 152 6th grade elementary school students compiled the sample group which was divided into an experimental group and a control group. Probability activities in TS program were used with the experimental group, while the normal curriculum was conducted with the control group. Both the experimental and control group were assessed with Science Reasoning Task II and a probabilistic thinking test before execution of this investigation and were post-tested with probabilistic thinking test after the project period was complete. Results of this study showed that the students in the concrete operational stage and transitional stage used subjective strategy together with quantitative strategy in probability problem-solving, and students in the early formal operational stage used quantitative strategy in probability problem-solving. It was also found that the higher the cognitive level of students, the higher the probabilistic thinking level. The probability activities of the TS program influenced the development of probabilistic thinking of elementary school students. Assessing the development of probabilistic thinking on the basis of the cognitive level found that the level of effectiveness was significantly higher for students in the early concrete operational stage and transitional stage than students in any other stage.