• Journal of Biosystems Engineering
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• 제12권3호
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• pp.17-29
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• 1987

A 10-degree of freedom mathematical model of motion for power tiller-trailer system was developed. This model can predict motion characteristics of power tiller trailer system while travelling over smooth and irregular ground surfaces under various operating conditions. The model provide, the fundamental data needed to improve the stability of power tiller-trailer systems.

• International Journal of Automotive Technology
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• 제7권7호
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• pp.833-839
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• 2006

In this paper, roll behavior of three planar half car models are compared. The first model is a simple model whose contact point between a wheel and the ground is assumed to be fixed with a revolute joint. The second model is a modified model of the fIrst model, whose wheel tread width can vary. In this model, the instant center of a wheel with respect to the ground, which is crucial to find the roll center, is assumed to be at the contact point of a wheel and the ground. The last model uses the pole of a wheel with respect to the ground for small displacement as the instant center of a wheel with respect to the ground. Loci of the center of gravity point, the fixed and the moving centrodes which are traces of roll center position in the ground and the body frame respectively, wheel contact points, and instant centers of a wheel with respect to the ground are calculated.

• Electronics and Telecommunications Trends
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• 제33권5호
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• pp.103-110
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• 2018

Studies on artificial intelligence have been developed for the past couple of decades. After a few periods of prosperity and recession, a new machine learning method, so-called Deep Learning, has been introduced. This is the result of high-quality big- data, an increase in computing power, and the development of new algorithms. The main targets for deep learning are 1D audio and 2D images. The application domain is being extended from a discriminative model, such as classification/segmentation, to a generative model. Currently, deep learning is used for processing 3D data. However, unlike 2D, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become more popular owing to advances in 3D vision technology, the generation/acquisition of 3D data remains a very difficult problem. Moreover, it is not easy to directly apply an existing network model, such as a convolution network, owing to the variety of 3D data representations. In this paper, we summarize the 3D deep learning technology that have started to be developed within the last 2 years.

• Electronics and Telecommunications Trends
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• 제33권4호
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• pp.1-13
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• 2018

Deep learning (DL) models have been widely applied to AI applications such image recognition and language translation with big data. Recently, DL models have becomes larger and more complicated, and have merged together. For the accelerated training of a large-scale deep learning model, model parallelism that partitions the model parameters for non-shared parallel access and updates across multiple machines was provided by a few distributed deep learning frameworks. Model parallelism as a training acceleration method, however, is not as commonly used as data parallelism owing to the difficulty of efficient model parallelism. This paper provides a comprehensive survey of the state of the art in model parallelism by comparing the implementation technologies in several deep learning frameworks that support model parallelism, and suggests a future research directions for improving model parallelism technology.

• Proceedings of the KIEE Conference
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• 대한전기학회 2002년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.286-293
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• 2002

Photovoltaic systems normally use a maximum power point tracking (MPPT) technique to continuously deliver the highest possible power to the load when variations in the insolation and temperature occur. A simple method of tracking the maximum power points (MPPs) and forcing the boost converter system to operate close to these Points is presented through deriving small-signal model and transfer function of boost converter. This paper aims at modeling boost converter including equivalent series resistance of input reservoir capacitor by state-space-averaging method and PWM switch model. In the future, properly designed controller for compensation will be constructed in real system for maximum photovoltaic power tracking control.

• Proceedings of the KIEE Conference
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.83-85
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• 2003

This paper presents a correction technique of missing load data. In this paper, the ARIMA(Autoregressive Integrated Moving Average) model and Piecewise Cubic Interpolation are applied to seek the missing parameters. The new model has been tested under a variety of conditions and it is shown in this paper to produce excellent results. It is helpful for operators to designed the load duration curve.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제35권1호
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• pp.1-8
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• 2022

This study proposes a penetration model in soil considering the wake separation and reattachment based on the integrated force law (IFL). Rigid body dynamics, the IFL, and semi-empirical resistance function about soil are utilized to formulate the motion of the hard projectile. The model can predict the trajectory in soil considering the spherical cavity expansion phenomenon under various oblique angles and angles of attack (AOA). The Mohr-Coulomb yield model is utilized as the resistance function of the soil. To confirm the feasibility of the proposed model, a comparative study is conducted with experimental results described in the open literature. From the comparative study, the penetration depth estimated from the proposed model had about 13.4% error compared to that of the experimental results. In general, the finite element method is widely used to predict the trajectory in soil for a projectile. However, it takes considerable time to construct the computational model for the projectile and perform the numerical simulation. The proposed model only needs to the dimension of the projectile and can predict the trajectory of the projectile in a few seconds.

• Transactions of the Korean Society of Machine Tool Engineers
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• 제16권4호
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• pp.87-92
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• 2007

The full automation welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an neural network model to predict the weld top-bead height as a function of key process parameters in the welding. and to compare the developed models using three different training algorithms in order to select an adequate neural network model for prediction of top-bead height.

• Journal of Distribution Research
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• 제15권4호
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown