• International Journal of CAD/CAM
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• v.3 no.1_2
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• pp.67-75
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• 2003

Viewpoint-dependent feature-based modelling in computer-aided design is developed for the purposes of supporting engineering design representation and automation. The approach of this paper uses a combination of a multi-level modelling approach. This has two stages of mapping between models, and the multi-level model approach is implemented in three-level architecture. Top of this level is a feature-based description for each viewpoint, comprising a combination of form features and other features such as loads and constraints for analysis. The middle level is an executable representation of the feature model. The bottom of this multi-level modelling is a evaluation of a feature-based CAD model obtained by executable feature representations defined in the middle level. The mappings involved in the system comprise firstly, mapping between the top level feature representations associated with different viewpoints, for example for the geometric simplification and addition of boundary conditions associated with moving from a design model to an analysis model, and secondly mapping between the top level and the middle level representations in which the feature model is transformed into the executable representation. Because an executable representation is used as the intermediate layer, the low level evaluation can be active. The example will be implemented with an analysis model which is evaluated and for which results are output. This multi-level modelling approach will be investigated within the framework aimed for the design automation with a feature-based model.

• Journal of the military operations research society of Korea
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• v.8 no.1
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• pp.71-76
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• 1982

A procedure is established for combining a regression model and a time series model to fit to a set of autocorrelated data. This procedure is based on an iterative method to compute regression parameter estimates and time series parameter estimates simultaneously. The time series model which is discussed is basically AR(p) model, since MA(q) model or ARMA(p,q) model can be inverted to AR({$\infty$) model which can be approximated by AR(p) model. The procedure discussed in this articled is applied in general to any combination of regression model and time series model.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.282-290
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• 2013

The effects of the combination of blade number for forward and after propeller on the propeller shaft forces of a contra-rotating propeller (CRP) system are presented in the paper. The research is performed through the numerical simulations based on the Reynolds-Averaged Navier-Stokes equations (RANS). The simulation results of the present method in open water condition are validated comparing with the experimental data as well as the other numerical simulation results based on the potential method for 4-0-4 CRP (3686+3687A) and 4-0-5 CRP (3686+3849) of DTNSRDC. Two sets of CRP are designed and simulated to study the effect of the combination of blade number in behind-hull condition. One set consists of 3-blade and 4-blade, while the other is 4-blade and 4-blade. A full hull body submerged under the free surface is modeled in the computational domain to simulate directly the wake field of the ship at the propeller plane. From the simulation results, the fluctuations of axial force and moment are dominant in the case of same blade numbers for forward and after propellers, whereas the fluctuations of horizontal and vertical forces and moments are very large in the case of different blade numbers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.655-657
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• 2021

It is challenging to find breast ultrasound image training dataset to develop an accurate machine learning model due to various regulations, personal information issues, and expensiveness of acquiring the images. However, studies targeting transfer learning for ultrasound breast cancer images classification have not been able to achieve high performance compared to radiologists. Here, we propose an improved transfer learning model for ultrasound breast cancer classification using publicly available dataset. We argue that with a proper combination of ImageNet pre-trained model and optimizer, a better performing model for ultrasound breast cancer image classification can be achieved. The proposed model provided a preliminary test accuracy of 99.5%. With more experiments involving various hyperparameters, the model is expected to achieve higher performance when subjected to new instances.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.83-91
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• 2008

This study establishes the model to estimate a work time and a machine equipment combination in a NATM tunnel. Also it includes the increasing rate of haulage distance in the model for to make near to reality model. A simulation model focuses on the mucking process which affects the work effectiveness very highly to plan of machine use in tunneling operation. With the analysis of work effectiveness through tunnel simulation model, it is defined the problem of planning phase. Also it shows the optimal working time and efficiency of machine used through change the number of dump truck and haulage distance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.706-711
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• 2005

Torsional oscillations of a system incorporating a Hooke's joint are investigated by studying a simple similar nonlinear 2-degree-of-freedom model, which has linear and quadratic nonlinear parametric excitations. The simple system is identified to have the possibilities of primary, sub harmonic and combination resonances. The case of simultaneous primary and combination resonances is selected for perturbation analysis to have the reduced amplitude-equations of motion. The same procedure is applied to the system incorporating a Hooke's joint.

• Structural Engineering and Mechanics
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• v.75 no.1
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• pp.87-100
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• 2020

The present paper investigates the combination resonance behavior of imperfect spiral stiffened functionally graded (SSFG) cylindrical shells with internal and external functionally graded stiffeners under two-term large amplitude excitations. The structure is embedded within a generalized nonlinear viscoelastic foundation, which is composed of a two-parameter Winkler-Pasternak foundation augmented by a Kelvin-Voigt viscoelastic model with a nonlinear cubic stiffness, to account for the vibration hardening/softening phenomena and damping considerations. With regard to classical plate theory of shells, von-Kármán equation and Hook law, the relations of stress-strain are derived for shell and stiffeners. The spiral stiffeners of the cylindrical shell are modeled according to the smeared stiffener technique. According to the Galerkin method, the discretized motion equation is obtained. The combination resonance is obtained by using the multiple scales method. Finally, the influences of the stiffeners angles, foundation type, the nonlinear elastic foundation coefficients, material distribution, and excitation amplitude on the system resonances are investigated comprehensively.

• Structural Engineering and Mechanics
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• v.7 no.2
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• pp.217-224
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• 1999

A semi-stochastic process model of reliability was established for hyperbolic cooling towers subjected to combined loadings of wind force, self-weight, temperature loading. Effect of the soil-structure interaction on reliability was evaluated. By involving the gust factor, an equivalent static scheme was employed to convert the dynamic model to static model. The TR combination rule was used to consider relations between load responses. An analysis example was made on the 90M cooling tower of Maoming, Guangdong of China. Numerical results show that the design not including interaction turns to be conservative.

• Environmental Engineering Research
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• v.23 no.1
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• pp.107-113
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• 2018

Air quality and pollution have recently become a major concern; vehicle emissions significantly pollute the air, especially in large and crowded cities. There are various factors that affect vehicle emissions; this research aims to find the most influential factors affecting $CO_2$ and $NO_x$ emissions using Adaptive Neural Fuzzy Inference System (ANFIS) as well as a systematic approach. The modified ANFIS (MANFIS) was developed to enhance modelling and Root Mean Square Error was used to evaluate the model performance. The results show that percentages of $CO_2$ from trucks represent the best input combination to model. While for $NO_x$ modelling, the best pair combination is the vehicle delay and percentage of heavy trucks. However, the final MANFIS structure involves two inputs, three membership functions and nine rules. For $CO_2$ modelling the triangular membership function is the best, while for $NO_x$ the membership function is two-sided Gaussian.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.643-648
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• 2001

The direct simulation Monte Carlo(DSMC) method is applied to investigate steady and unsteady flow fields of a single-stage disk-type drag pump. Two different kinds of pumps are considered: the first one is a rotor-rotor combination, and the second one is a rotor-stator combination. The pumping channels are cut on a rotor and stator. The rotor and stator have 10 Archimedes' spiral blades, respectively. In the present DSMC method, the variable hard sphere model is used as a molecular model, and the no time counter method is employed as a collision sampling technique. For simulation of diatomic gas flows, the Borgnakke-Larsen phenomenological model is adopted to redistribute the translational and internal energies. The DSMC results are in good agreement with the experimental data.