• Title/Summary/Keyword: statistical engineering

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Review on the Application of Statistical Methods to Maritime Traffic Safety Assessment

  • Gong, In-Young
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.35-40
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    • 2006
  • For the maritime traffic safety assessment of vessels navigating in harbor or fairway, simulation techniques by using shiphandling simulator system have been traditionally used. When designing the simulation experiments and when analyzing the simulation results, however, there has been a little systematic method. Ship-handling simulations can be regarded as a kind of statistical experiment by using ship-handling simulator system, which means that shiphandling simulation conditions should be designed statistically and that the simulation results should be statistically analyzed as well. For the safe and economic design of harbor and fairway, reasonable decisions based upon the scientific analysis of shiphandling simulation results are indispensable. In this paper, various statistical methods, such as Bayes theorem, statistical hypothesis testing, and probability distributions, are reviewed with a view to application to maritime traffic safety assessment. It is expected that more reasonable decisions on harbor and fairway design can be made from shiphandlers' view point by using statistical methods.

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Modulation Recognition of MIMO Systems Based on Dimensional Interactive Lightweight Network

  • Aer, Sileng;Zhang, Xiaolin;Wang, Zhenduo;Wang, Kailin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.10
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    • pp.3458-3478
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    • 2022
  • Automatic modulation recognition is the core algorithm in the field of modulation classification in communication systems. Our investigations show that deep learning (DL) based modulation recognition techniques have achieved effective progress for multiple-input multiple-output (MIMO) systems. However, network complexity is always an additional burden for high-accuracy classifications, which makes it impractical. Therefore, in this paper, we propose a low-complexity dimensional interactive lightweight network (DilNet) for MIMO systems. Specifically, the signals received by different antennas are cooperatively input into the network, and the network calculation amount is reduced through the depth-wise separable convolution. A two-dimensional interactive attention (TDIA) module is designed to extract interactive information of different dimensions, and improve the effectiveness of the cooperation features. In addition, the TDIA module ensures low complexity through compressing the convolution dimension, and the computational burden after inserting TDIA is also acceptable. Finally, the network is trained with a penalized statistical entropy loss function. Simulation results show that compared to existing modulation recognition methods, the proposed DilNet dramatically reduces the model complexity. The dimensional interactive lightweight network trained by penalized statistical entropy also performs better for recognition accuracy in MIMO systems.

Development of a Method for Detecting Unstable Behaviors in Flume Tests using a Univariate Statistical Approach

  • Kim, Seul-Bi;Seo, Yong-Seok;Kim, Hyeong-Sin;Chae, Byung-Gon;Choi, Jung-Hae;Kim, Ji-Soo
    • The Journal of Engineering Geology
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    • v.24 no.2
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    • pp.191-199
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    • 2014
  • We describe a method for detecting slope instability in flume tests using pore pressure and water content data in conjunction with a statistical control chart analysis. Specifically, we conducted univariate statistical analysis on x-MR control chart data (pore pressure and water content) collected at several points along the flume slope, which we separated into three parts: upper, middle, and lower. To assess our results in the context of landslide forecasting and warning systems, we applied control limit lines at $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$ levels of uncertainty. In doing so, we observed that dispersion time varies depending on the control limit line used. Moreover, the detection of instabilities is highly dependent on the position and type of sensor. Our findings indicate that different characteristics of the data on various factors predict slope failure differently and these characteristics can be identified by univariate statistical analysis. Therefore, we suggest that a univariate statistical approach is an effective method for the early detection of slope instability.

Prediction of Effective Horsepower for G/T 4 ton Class Coast Fishing Boat Using Statistical Analysis (통계해석에 의한 G/T 4톤급 연안어선의 유효마력 추정)

  • Park, Chung-Hwan;Shim, Sang-Mog;Jo, Hyo-Jae
    • Journal of Ocean Engineering and Technology
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    • v.23 no.6
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    • pp.71-76
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    • 2009
  • This paper describes a statistical analysis method for predicting a coast fishing boat's effective horsepower. The EHP estimation method for small coast fishing boats was developed, based on a statistical regression analysis of model test results in a circulating water channel. The statistical regression formula of a fishing boat's effective horsepower is determined from the regression analysis of the resistance test results for 15 actual coast fishing boats. This method was applied to the effective horsepower prediction of a G/T 4 ton class coast fishing boat. From the estimation of the effective horsepower using this regression formula and the experimental model test of the G/T 4 ton class coast fishing boat, the estimation accuracy was verified under 10 percent of the design speed. However, the effective horsepower prediction method for coast fishing boats using the regression formula will be used at the initial design and hull-form development stage.

Statistical analysis of parameter estimation of a probabilistic crack initiation model for Alloy 182 weld considering right-censored data and the covariate effect

  • Park, Jae Phil;Park, Chanseok;Oh, Young-Jin;Kim, Ji Hyun;Bahn, Chi Bum
    • Nuclear Engineering and Technology
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    • v.50 no.1
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    • pp.107-115
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    • 2018
  • To ensure the structural integrity of nuclear power plants, it is essential to predict the lifetime of Alloy 182 weld, which is used for welding in nuclear reactors. The lifetime of Alloy 182 weld is directly related to the crack initiation time. Owing to the large time scatter in most crack initiation tests, a probabilistic model, such as the Weibull distribution, has mainly been adopted for prediction. However, since statistically more advanced methods than current typical methods may be applied, we suggest a statistical procedure for parameter estimation of the crack initiation time of Alloy 182 weld, considering right-censored data and the covariate effect. Furthermore, we suggest a procedure for uncertainty evaluation of the estimators based on the bootstrap method. The suggested statistical procedure can be applied not only to Alloy 182 weld but also to any material degradation data set including right-censored data with covariate effect.

Beyond robust design: an example of synergy between statistics and advanced engineering design

  • Barone, Stefano;Erto, Pasquale;Lanzotti, Antonio
    • International Journal of Quality Innovation
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    • v.3 no.2
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    • pp.13-28
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    • 2002
  • Higher efficiency and effectiveness of Research & Development phases can be attained using advanced statistical methodologies. In this work statistical methodologies are combined with a deterministic approach to engineering design. In order to show the potentiality of such integration, a simple but effective example is presented. It concerns the problem of optimising the performances of a paper helicopter. The design of this simple device is not new in quality engineering literature and has been mainly used for educational purposes. Taking full advantage of fundamental engineering knowledge, an aerodynamic model is originally formulated in order to describe the flight of the helicopter. Screening experiments were necessary to get first estimates of model parameters. Subsequently, deterministic evaluations based on this model were necessary to set up further experimental phases needed to search (or a better design. Thanks to this integration of statistical and deterministic phases, a significant performance improvement is obtained. Moreover, the engineering knowledge かms out to be developed since an explanation of the “why” of better performances, although approximate, is achieved. The final design solution is robust in a broader sense, being both validated by experimental evidence and closely examined by engineering knowledge.

Statistical analysis of S-N type environmental fatigue data of Ni-base alloy welds using weibull distribution

  • Jae Phil Park;Junhyuk Ham;Subhasish Mohanty;Dayu Fajrul Falaakh;Ji Hyun Kim;Chi Bum Bahn
    • Nuclear Engineering and Technology
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    • v.55 no.5
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    • pp.1924-1934
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    • 2023
  • In this study, the probabilistic fatigue life model for Ni-base alloys was developed based on the Weibull distribution using statistical analysis of fatigue data reported in NUREG/CR-6909 and the new fatigue data of Alloy 52M/152 and 82/182. The developed Weibull model can consider right-censored data (i.e., non-failed data) and quantify the improved safety (or reliability) based on the level of failure probability. The overall margin in the current fatigue design limit model (ASME design curve + NUREG/CR-6909 Fen model) is similar to that of the Weibull model with a cumulative failure probability of approximately 2.5%. The margin in the current fatigue design limit model demonstrated inconsistencies for the Ni-base alloy weld data, whereas the Weibull model showed a consistent margin. Therefore, the Weibull model can systematically mitigate the excessive safety margin.

Efficient Sequential Estimation in a Compound Poisson Process

  • Bai, Do-Sun;Kim, Myung-Soo;Jang, Joong-Soon
    • Journal of the Korean Statistical Society
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    • v.15 no.2
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    • pp.87-96
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    • 1986
  • Sequential estimation of parameters in a compound Poisson process whose jump sizes are one-parameter exponential class random variables is discussed. Cramer-Rao type information inequality is used as an efficiency cirterion. Unbiased estimators for certain parametric functions whose variance attain the lower bound are all characterized with the corresponding sampling plans.

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Analysis of Structural Reliability under Model and Statistical Uncertainties: a Bayesian Approach

  • Kiureghian, Armen-Der
    • Computational Structural Engineering : An International Journal
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    • v.1 no.2
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    • pp.81-87
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    • 2001
  • A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.

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