• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.103-108
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• 2003

The effect of equivalence ratio and fuel/air mixing quality on the phase-resolved gas temperatures at different phases of the oscillating pressure cycle was experimentally investigated. An atmospheric pressure, optically accessible and laboratory-scale dump combustor operating on methane with heat release rate of 1.59kW was used. Temperature measurements were made using coherent anti-Stokes Raman spectroscopy (CARS) at several spatial locations for typical unstable combustion conditions. Analysis was conducted using parameters such as phase-resolved averaged temperature, normalized standard deviation and temperature probability distribution functions (PDFs). Also the probability on the occurrence of high temperature (over 1900K) was investigated to get the information on the perturbation of equivalence ratio and NOx emission characteristics. It was shown that most of temperature histograms exhibit Gaussian profile which has short breadth of temperature fluctuation at equivalence ratio of 0.6, while beta profile was predominant for the cases of other equivalence ratios (${\Phi}$=0.55, 0.50). The characteristics on the occurrence of high temperature also displayed periodic wave form which is very similar to the pressure signal. And the amplitude of this profile goes larger as the fuel/air mixing quality become poorer. These also provided additional information on the perturbation of equivalence ratio at flame as well as NOx emission characteristics.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.29-37
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• 2017

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises' sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.391-404
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• 2022

Aron Gohr proposed a cryptanalysis method based on deep learning technology for the lightweight block cipher Speck. This is a method that enables a chosen plaintext attack with higher accuracy than the classical differential cryptanalysis. In this paper, by using the probability distribution, we analyze the mechanism of such deep learning based cryptanalysis and propose the results applied to the lightweight block cipher Simon. In addition, we examine that the probability distributions of the predicted values of the neural networks within the cryptanalysis working processes are different depending upon the characteristics of round functions of Speck and Simon, and suggest a direction to improve the efficiency of the neural distinguisher which is the core technology of Aron Gohr's cryptanalysis.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.1
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• pp.11-19
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• 2013

As the temperature data show a distribution pattern with a number of peaks, assumption of normal distribution will result in a serious bias in the analysis. In this study, the Gaussian Mixture Distribution (GMD), a type of bimodal distribution, is presumed as a frequency distribution for the water temperature, in order to estimate the optimal parameter and to carry out the relation analysis between the optimal parameter and the basic statistical information such as mean and variance on the data. By the way, an estimation formulae to compute the frequency distribution of the data is developed by computing the parameters of GMD (i.e. ${\alpha}_1$, ${\mu}_1$, ${\sigma}_1$, ${\alpha}_2$, ${\mu}_2$, ${\sigma}_2$) by means of the major characteristic values, such as mean, standard deviation and skewness of the data. The formulae shows an excellent coincidence with the result from the observation data, in the RMS limit accuracy of 5%.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.63-72
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• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.223-232
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• 2017

Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.

• Journal of Korea Water Resources Association
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• v.40 no.2 s.175
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• pp.159-170
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• 2007

This study evaluated the parameters of Clark unit hydrograph (UH) estimated using the rainfall-runoff measurements and evaluated their variability. This also includes the quantification of basin and meteorological factors using probability density functions, selection of storm events with mean affecting factors, and derivation of average parameters of the Clark UH from storm events selected. Summarizing the results from this procedure are as follows. (1) It is not easy to avoid much uncertainty on the decision of runoff characteristics (that is, the concentration time and storage coefficient) even with some rainfall-runoff events are available. (2) As the distribution function of concentration time is very skewed, a simple arithmetic mean may lead a biased estimate. That is, the arithmetic mean based on the normal distribution can not be representative anymore. The mode may well be the representative in this case. On the other hand, the storage coefficient shows a symmetric distribution function, so the arithmetic mean may be used use for its representative. For the basin in this study, the concentration time in this study is estimated to be about 7 hours, and the storage coefficient about 22 hours.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.10
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• pp.1184-1192
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• 2004

Experimental investigations were carried out in an atmospheric pressure, optically accessible and laboratory-scale dump combustor operating on methane gas. The objective of this study was to obtain the phase-resolved gas temperatures at different phases of the oscillating pressure cycle during unstable combustion. CARS temperature measurements were made at several spatial locations under lean premixed conditions to get the information on temperature field within the combustor. Also the effect of incomplete fuel-air mixing on phase-resolved temperature fluctuation was investigated. Results including phase-resolved averaged temperature, normalized standard deviation and temperature probability distribution functions (PDFs) were provided in this paper. Temperature PDFs gave an insight on the flame behavior. And strong correlation between phase-resolved temperature profile and pressure cycle was observed. Results of the phase-resolved high temperature gave an additional information on the perturbation of equivalence ratio at flame as well as the effect of mixing quality on NOx emission characteristics.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.78-87
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• 1994

In this paper, we have addressed a new approach to encode the DCT coefficients efficiently by exploiting the structural differences among the probability distribution functions of them. We have proved analytically that if signals are separated according to their source models, the entropy of the separated signals decreases below that of the unseparated signals. And simulation results show that the average codelength decrease when each (runlength, level) symbol is encoded adaptively according to the index associated with the symbol.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.1-6
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• 2012

In the paper, an information divergence called Kullback-Leiber divergence, which measures the average of the logarithmic difference between two probability density functions, is utilized to derive a novel method for spectrum sensing in cognitive radio systems. In the proposed sensing method, we test whether the observed samples are drawn from the noise distribution by using Kullback-Leiber divergence. It is shown by numerical results that under the same conditions, the proposed Kullback-Leiber divergence-based spectrum sensing always outperforms the energy detection based spectrum sensing significantly, especially in low SNR regime and in fading circumstance.