• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.952-958
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• 2014

In this paper, we propose a parametric sparse recovery algorithm(SRA) applied to a radar signal model, based on the compressive sensing(CS), for the ISAR(Inverse Synthetic Aperture Radar) image reconstruction from an incomplete radar-cross-section(RCS) data and for the estimation of rotation rate of a target. As the SRA, the iteratively-reweighted-least-square(IRLS) is combined with the radar signal model including chirp components with unknown chirp rate in the cross-range direction. In addition, the particle swarm optimization(PSO) technique is considered for searching correct parameters related to the rotation rate. Therefore, the parametric SRA based on the IRLS can reconstruct ISAR image and estimate the rotation rate of a target efficiently, although there exists missing data in observed RCS data samples. The performance of the proposed method in terms of image entropy is also compared with that of the traditional interpolation methods for the incomplete RCS data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.475-481
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• 2019

The importance of performance-based design feedback is being emphasized when it comes to the potential impact that affects all the lifecycle of the building. However, the latency and disconnection of domain expert in the sector of AEC/FM remain current obstacles between design and performance feedback. It is hard to utilize performance feedback information for design exploration and support design decision making during the conceptual phase of design. Using parametric design, this paper proposes various design alternatives from a set of rules and constraints defined by algorithms for the geometric configurations of an Office Building. A Building Performance Analysis (BPA) was to developed using Autodesk® Revit® 2019 which integrates Autodesk® Green Building Studio® to predict its sufficient daylighting conditions of the LEED v4's Daylighting Autonomy (DA). The parametric-based performance feedback of this study outlines potential design improvements for further exploration in application to the early design process.

• Journal of Veterinary Clinics
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• v.27 no.1
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• pp.66-70
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• 2010

Reference interval is critical for interpreting laboratory results, monitoring response to therapy and predicting the prognosis of the patients in clinical settings. The aim of the present study was to update established reference intervals for routine hematologic and serum chemistry values for a population of clinically healthy dogs (range, 1-8 years) seen in an animal hospital. Blood was obtained by venipuncture while animals were physically restrained, and samples were analyzed for 9 chemistries on MS9-5H (Melot Schloesing Lab, France) and 6 hematology on Vet Test 8008 (IDEXX, USA). Data from 105 dogs (52 males and 53 females) for hematology and 113 dogs (37 males and 76 females) for chemistry were used to determine reference intervals using the parametric, nonparametric and bootstrap methods. Prior to analysis, all parameters were tested for normal distribution using Anderson-Darling criterion. Of the 9 biochemical analytes, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, creatinine, total protein, and glucose concentrations did not fit normal distribution for both original and transformed data. All but eosinophil count satisfied normal distribution for either original or transformed data. Parametric method can be used for original cholesterol concentrations, RBC, WBC, and neutrophil counts. This technique can also be used for power-transformed values of blood urea nitrogen concentrations and for logarithm of lymphocyte and monocyte counts. Non-parametric or bootstrap method was the preferred choice for the remaining 7 biochemical parameters and eosinophil count as they did not follow normal distributions. All three statistical techniques performed in similar reference intervals. When establishing reference intervals for clinical laboratory data, it is essential to assess the distribution of the original data to increase the accuracy of the interval, and non-parametric or bootstrap methods are of alternative for the data that do not fit normal distribution.

• Structural Engineering and Mechanics
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• v.56 no.5
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• pp.813-833
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• 2015

Spherical reticulated shells are widely applied in structural engineering due to their good bearing capability and attractive appearance. Parametric modeling of spherical reticulated shells is the basis of internal analysis and optimization design. In the present study, generation methods of nodes and the corresponding connection methods of rod elements are proposed. Modeling programs are compiled by adopting the ANSYS Parametric Design Language (APDL). A shape optimization method based on the two-stage algorithm is presented, and the corresponding optimization program is compiled in FORTRAN environment. Shape optimization is carried out based on the objective function of the minimum total steel consumption and the restriction condition of strength, stiffness, slenderness ratio, stability. The shape optimization of four typical Schwedler spherical reticulated shells is calculated with the span of 30 m~80 m and rise to span ratio of 1/7~1/2. Compared with the shape optimization results, the variation rules of total steel consumption along with the span and rise to span ratio are discussed. The results show that: (1) The left and right rod-Schwedler spherical reticulated shell is the most optimized and should be preferentially adopted in structural engineering. (2) The left diagonal rod-Schwedler spherical reticulated shell is second only to left and right rod regarding the mechanical behavior and optimized results. It can be applied to medium and small-span structures. (3) Double slash rod-Schwedler spherical reticulated shell is advantageous in mechanical behavior but with the largest total weight. Thus, this type can be used in large-span structures as far as possible. (4) The mechanical performance of no latitudinal rod-Schwedler spherical reticulated shell is the worst and with the second largest weight. Thus, this spherical reticulated shell should not be adopted generally in engineering.

• Journal of the Korean Geosynthetics Society
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• v.13 no.4
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• pp.109-117
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• 2014

Using the finite element analysis model presented in accompanying paper, parametric study was performed in this paper. Various parameters were considered such as the width of wheel loads-induced permanent plastic deformation, backfill, equivalent thickness and orthogonal characteristic of steel mats. The effects of these parameters were analyzed for vertical and rotational displacements, maximum moment and tensile stress. From the parametric studies, it is found that great vertical deflection and tensile stress above allowable flexural tensile strength are developed in steel mats by the wheel loads-induced permanent plastic deformation. Backfill or increasing the thickness of steel mats is a feasible solution on this problem.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.259-264
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• 2023

In this study, we devised a parametric analysis workflow for efficiently analyzing the material properties of 3D woven materials. The parametric model uses wire spacing in the woven materials as a design parameter; we generated 2,500 numerical models with various combinations of these design parameters. Using MATLAB and ANSYS software, we obtained various material properties, such as bulk modulus, thermal conductivity, and fluid permeability of the woven materials, through a parametric batch analysis. We then used this large dataset of material properties to perform a regression analysis to validate the relationship between design variables and material properties, as well as the accuracy of numerical analysis. Furthermore, we constructed an artificial neural network capable of predicting the material properties of 3D woven materials on the basis of the obtained material database. The trained network can accurately estimate the material properties of the woven materials with arbitrary design parameters, without the need for numerical analyses.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.393-400
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• 2015

This study proposes a method to create and combine a superstructure module by parametric modeling, in order to improve the production efficiency of information model for modular steel bridge superstructure that can be used in planning, design and construction phase. Compound classification was performed in order to derive elements to apply the parametric modeling, and according to assembly condition, the classified elements were grouped into 13 types. In addition, three assembly conditions were derived for production of stable superstructure through combination of superstructure module, which is a production unit for modular steel bridge factory. Parameter that reflects assembly condition in compound shape when producing superstructure module through parametric modeling was deducted. Superstructure module compounds were produced according to type and parameter using interface generation based on Building Information Model(BIM) software that was developed in this study. The superstructure module produced reflects information to combine into a superstructure. To verify this, information model based on Industry Foundation Classes(IFC) was built and confirmed the application in production of superstructure by identifying the reflected property information.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.105-115
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• 2018

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results of frequency based snowfall depth show that most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. According to the results, observed data and Bootstrap method showed a difference of -19.2% to 3.9%, and the Bootstrap method and SIR(Sampling Importance Resampling) algorithm showed a difference of -7.7 to 137.8%. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.1-25
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• 2016

This study investigated the variability of WTP estimates(i.e. mean or median) with ad hoc assumptions of specific parametric probability distributions(i.e. normal, logistic, lognormal, and exponential distribution) to estimate WTP function using dichotomous choice CV data on mortality risk reduction. From the perspective of policy decision, the variability of these WTP estimates are intolerable in comparison with those of Turnbull nonparametric estimation method which is free from ad hoc distribution assumptions. The Turnbull nonparametric estimation can avoid a kind of misspecification bias due to ad hoc assumption of specific parametric distributions. Furthermore, the WTP estimates by Turnbull nonparametric estimation are robust because the similar estimates are elicited from a dichotomous choice or double dichotomous choice CV data, and the statistically significant WTP estimates can be obtained even though it is not possible by parametric estimation methods. If there are considerable variability among those WTP estimates by parametric estimation methods in condition with no criteria of model adequacy, the mean WTPs from Turnbull nonparametric estimation can be the robust estimates without ad hoc assumptions, which can avoid controversial issues in the perspective of policy decisions.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.297-302
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• 2007

Although just developed in recent years, curved box girder has widely used in modern highway system due to their load resistance capacity as well as aesthetic considerations. According to recent literature reviews on curved box girder designs, distortional load was not considered as much as it deserves to be. In practice, the effect of distortional force is very small in straight bridge systems but yet unknown how it is in curved bridge systems. For the reason, this paper will show an extensive parametric study on distortional behavior. Based on Dabrowski formulas, using finite element method, various bridges were investigated. In this study, following parameters will be included: span length, curvature radius, section height, section width, and internal section angle (web slope). From the obtained results, some initial geometric parameters are proposed for curved box girder bridges.