• Korean Journal of Radiology
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• v.22 no.7
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• pp.1194-1202
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• 2021

Objective: To investigate the age-dependent changes in regional cerebral blood flow (CBF) in healthy adults by fitting mathematical models to imaging data. Materials and Methods: In this prospective study, 90 healthy adults underwent pseudo-continuous arterial spin labeling imaging of the brain. Regional CBF values were extracted from the arterial spin labeling images of each subject. Multivariable regression with the Akaike information criterion, link test, and F test (Ramsey's regression equation specification error test) was performed for 7 models in every brain region to determine the best mathematical model for fitting the relationship between CBF and age. Results: Of all 87 brain regions, 68 brain regions were best fitted by cubic models, 9 brain regions were best fitted by quadratic models, and 10 brain regions were best fitted by linear models. In most brain regions (global gray matter and the other 65 brain regions), CBF decreased nonlinearly with aging, and the rate of CBF reduction decreased with aging, gradually approaching 0 after approximately 60. CBF in some regions of the frontal, parietal, and occipital lobes increased nonlinearly with aging before age 30, approximately, and decreased nonlinearly with aging for the rest of life. Conclusion: In adults, the age-related perfusion patterns in most brain regions were best fitted by the cubic models, and age-dependent CBF changes were nonlinear.

• Transactions of the Korean hydrogen and new energy society
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• v.35 no.1
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• pp.83-89
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• 2024

In order to confirm the safety against vibration of high-pressure fittings for mobile hydrogen charging devices, the natural frequency was confirmed through ANSYS, and vibration data occurring during driving was applied to utilize the vehicle's operating power spectral density data specified in MIL-STD-810H regulations. Fatigue analysis and resonance were confirmed, and as a result, it was confirmed that the sum of the pure phase ratios was less than 1 for the driving history presented in the standard, and there was no risk of resonance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.624-627
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• 1992

Mathematical modeling is majorly divided into three parts: the derivation of models, the fitting of models to data, and the simulation of data from models. This paper focuses on the parameter optimization which is necessary for the fitting of models to data. The method of simulated annealing(SA) is a technique that has recently attracted significant attention as suitable for optimization problem of very large scale. If the temperature is too high, then some of the structure created by the heuristic will be destroyed and unnecessary extra work will be done. If it is too low then solution is lost, similar to the case of a quenching cooling schedule in the SA phase. In this study, therfore, we propose a technique of determination of the starting temperature and cooling schedule for SA phase.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1988.10a
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• pp.7-12
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• 1988

This study presents rational methods for probability-based estimates of basic design wind speeds in Korea and develops a risk-bases nation-wide map of design wind speeds. The paper examines the fitting of the Type-I extreme model to maximum yearly non-typhoon wind data from long-term records based on the conventional method and to maximum monthly nod-typhoon wind data from short-term records following Grigorin's approach. The paper also reviews the applicability of the method using short records of about 5 years. The basic design wind speeds for typhoon and non-typhoon wind at a station are made to be obtained from a mixed model which is given as a product of typhoon and non-typhoon extreme wind distributions. A practical method which is based on the fitting of the Type I model to records or typhoon and non-typhoon mixed wind data at a station is also preposed in this study.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.920-924
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• 2002

This paper presents the reverse design of a cam mechanism using NURBS(Nonuniform Rational B-spline curve). Cam is very difficult to make the accurate shape on the design and the manufacture. Because the cam shape is commonly made in order to move in special functions. The reverse design can be used to check accuracy between the designed data and the manufactured data of the cam shape and also reproduce the cam without the design data. The reverse design procedures consist of motion analysis and curve fitting. The motion analysis is used the central difference method and the relative velocity method to find the displacement and velocity. The curve fitting is used NURBS to develope the whole curve. The central difference method is derived in the 3 dimensional space.

• Computers and Concrete
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• v.9 no.4
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• pp.293-310
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• 2012

This paper discusses a new constitutive model called the high-rate brittle microplane (HRBM) model and also presents the details of a new software package called the Virtual Materials Laboratory (VML). The VML software package was developed to address the challenges of fitting complex material models such as the HRBM model to material property test data and to study the behavior of those models under a wide variety of stress- and strain-paths. VML employs Continuous Evolutionary Algorithms (CEA) in conjunction with gradient search methods to create automatic fitting algorithms to determine constitutive model parameters. The VML code is used to fit the new HRBM model to a well-characterized conventional strength concrete called WES5000. Finally, the ability of the new HRBM model to provide high-fidelity simulations of material property experiments is demonstrated by comparing HRBM simulations to laboratory material property data.

• Food Science and Biotechnology
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• v.17 no.6
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• pp.1352-1356
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• 2008

Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.

• Proceedings of the Korean Vacuum Society Conference
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• 1996.02a
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• pp.171-171
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• 1996

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.57-65
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• 2018

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS : For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS : The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination ($R^2$) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as $R^2$ had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.97-103
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• 2011

LiDAR system has become a popular tool for generating 3D surface data such as Digital Surface Model. Extraction of valuable information, such as digital building models, from LiDAR data has been an attractive research subject. This research addresses to extract planar patches from LiDAR data. Planar patches are important primitives consisting of man-made objects such as buildings. In order to determine the best fitted planes, this research proposed a method to reduce/eliminate the impact of the outliers and the intersection areas of two planes. After finishing plane fitting, planar patches are segmented by pseudo color values which are calculated by determined three plane parameters for each LiDAR point. In addition, a segmentation procedure is conducted using the pseudo color values to find planar patches. This paper evaluates the feasibility of the proposed method using both airborne and terrestrial LiDAR data.