• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.584-592
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• 2008

In this paper, we propose a new model of the magnetic control force exerted on the levitation object in magnetic levitation systems. The model assumes that the magnetic force is a function of the voltage applied to an electromagnet and the position of a levitation object. The function is not explicitly expressed but represented through a 2D lookup table constructed from the experimentally measured data. Unlike the conventional model that reveals only local characteristics of the magnetic force, the proposed model shows global characteristics satisfactorily. Specially devised measurement equipment is utilized in order to gather the data required for model construction. An experimental procedure to construct the model is presented. We apply the proposed model to designing a sliding mode controller for a lab-built magnetic system. The validity of the proposed model is illustrated by comparing the performances of the controller adopting the conventional model with that of the controller adopting the proposed model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1414-1430
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• 2022

Due to the Internet of Things popularity, many agricultural data are collected by sensors automatically. The abundance of agricultural data makes precise prediction of rice yield possible. Because the climate factors have an essential effect on the rice yield, we considered the climate factors in the prediction model. Accordingly, this paper proposes a machine learning model for rice yield prediction in Taiwan, including the genetic algorithm and support vector regression model. The dataset of this study includes the meteorological data from the Central Weather Bureau and rice yield of Taiwan from 2003 to 2019. The experimental results show the performance of the proposed model is nearly 30% better than MARS, RF, ANN, and SVR models. The most important climate factors affecting the rice yield are the total sunshine hours, the number of rainfall days, and the temperature.The proposed model also offers three advantages: (a) the proposed model can be used in different geographical regions with high prediction accuracies; (b) the proposed model has a high explanatory ability because it could select the important climate factors which affect rice yield; (c) the proposed model is more suitable for predicting rice yield because it provides higher reliability and stability for predicting. The proposed model can assist the government in making sustainable agricultural policies.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.119-130
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• 2022

Crime is a common social problem that affects the quality of life. As the number of crimes increases, it is necessary to build a model to predict the number of crimes that may occur in a given period, identify the characteristics of a person who may commit a particular crime, and identify places where a particular crime may occur. Data privacy is the main challenge that organizations face when building this type of predictive models. Federated learning (FL) is a promising approach that overcomes data security and privacy challenges, as it enables organizations to build a machine learning model based on distributed datasets without sharing raw data or violating data privacy. In this paper, a federated long short- term memory (LSTM) model is proposed and compared with a traditional LSTM model. Proposed model is developed using TensorFlow Federated (TFF) and the Keras API to predict the number of crimes. The proposed model is applied on the Boston crime dataset. The proposed model's parameters are fine tuned to obtain minimum loss and maximum accuracy. The proposed federated LSTM model is compared with the traditional LSTM model and found that the federated LSTM model achieved lower loss, better accuracy, and higher training time than the traditional LSTM model.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.137-140
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• 2000

In this paper, we have proposed an efficient test generation method for asynchronous circuits. The test generation is based on specification level, especially on Signal Transition Graph(STG)〔1〕 which is a kind of specification method for asynchronous circuits. To conduct a high-level test generation, we have defined a high-level fault model, called single State Transition Fault(STF) model on STG and proposed a test generation algorithm for STF model. The effectiveness of the proposed fault model and its test generation algorithm is shown by experimental results on a set of benchmarks given in the form of STG. Experimental results show that the generated test for the proposed fault model achieves high fault coverage over single input stuck-at fault model with low cost. We have also proposed extended STF model with additional gate-level information to achieve higher fault coverage in cost of longer execution time.

• Journal of KSNVE
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• v.10 no.1
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• pp.144-152
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• 2000

The identification of a nonlinear vibration system based on the time domain parametric model has been widely studied in recent years. In most of the studies, the NARMAX model has been used for the identification of a nonlinear system. However, the computational load for the identification with this model is quite heavy. In this paper, a new modeling procedure for nonlinear system identification in discrete time domain is proposed. The proposed model has less initial nonlinear terms than NARMAX model, and the terms in the proposed model are derived from physically meaningful way. The performance of the proposed method is evaluated through the simulation, and the result shows that the proposed model can identify the nonlinear characteristics of the vibration system very will less computational effort.

• Journal of Ship and Ocean Technology
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• v.10 no.2
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• pp.11-23
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• 2006

The model exchange from CAD system to CAE system in valid and effective manner is the major issue of automatic analysis modelling of ship structure. However, model exchange approaches based on the neutral CAD file have resulted in invalid model exchange that could not properly reflect the characteristics of CAD model and CAE model of ship structure. This paper presents the new approach of n-to-n mapping to exchange ship structure model in heterogeneous CAD/CAE environments. In this study, the common model called 'unified ship model for analysis' to directly extract proper information from different CAD systems for ship structural analysis is proposed. Moreover, a command language based model interfacing technique to construct an idealized model for analysis job is also proposed. The proposed approach has been actually implemented in DSME CAD/CAE environment of ship structure such as TRIBON system, PATRAN system and FLUENT system. The applicability and effectiveness of the proposed approach was verified by applying it to the real analysis project for fore-body of ship and block lifting. This application results show that the proposed approach can be effectively used for heterogeneous CAD/CAE environment.

• Journal of KSNVE
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• v.10 no.3
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• pp.451-456
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• 2000

In this paper a discrete time model for the identification of nonlinear vibration system with stick-slip friction is proposed. The proposed model can handle the highly nonlinear behavior of the friction such as stick-slip phenomenon and Stribeck effect. The basic idea of the proposed model is as follows : If the nonlinearity of the system can be predicted as a simple function then this nonlinear function term cab be directly used in the discrete time model. By doing this the number of nonlinear terms in the model can be much less than those of NARMAX model which is widely used nonlinear discrete model. The simulation result shows that the proposed model can estimate the response of the nonlinear vibration system with stick-slip friction very well with less computational effort.

• Computers and Concrete
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• v.5 no.3
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• pp.217-241
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• 2008

In this paper, a total strain-based hysteretic material model based on MCFT is proposed for non-linear finite element analysis of reinforced concrete structures. Although many concrete models have been proposed for simulating behavior of structures under cyclic loading conditions, accurate simulations remain challenging due to uncertainties in materials, pitfalls of crude assumptions of existing models, and limited understanding of failure mechanisms. The proposed model is equipped with a fully generalized hysteresis rule and is formulated for 2D plane stress non-linear finite element analysis. The proposed model has been formulated in a tangent stiffness-based finite element scheme so that it can be used for most general finite element analysis packages. Moreover, it eliminates the need to check that tensile stresses can be transmitted across a crack. The tension stiffening model is a function of the bar orientation and any orientation can be accommodated. The proposed model has been verified with a series of experimental results of 2D RC planar panels. This study also demonstrates how parameters of the proposed model associated with cyclic damage modeling influences the pinched cyclic shear behavior.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.318-322
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• 1996

In this study, a controller design method is proposed for controlling the discrete-time chaotic systems efficiently. Our proposed control method is based on Generalized Predictive Control and uses NARMAX models as a controlled model. In order to evaluate the performance of our proposed controller design method, a proposed controller is applied to Henon system which is a discrete-time chaotic system, and then the control performance of the proposed controller are compared with those of the previous model-based controllers through computer simulations. Through simulations, it is shown that the control performance of the proposed controller is superior to that of the conventional model-based controller.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.1-42
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• 2002

A model to predict population by sex, age and district over a long-range period is proposed based on fuzzy theories. First, a fuzzy model is described. Second, a method to estimate the social increase by sex and age in each district is proposed based on a fuzzy clustering method for dealing with long-range socioeconomic changes in population migration. By the proposed methods, it became possible to predict the population by sex, age and district over a long-range period. Third, the structure and characteristics of the three models of employment model, time distance model, and land use model constructed to predict various socioeconomic indicators, which are require...