• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.6
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• pp.380-386
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• 2000

This paper presents the mathematical modelling analysis of Brushless Synchronous Motor(BLSM). The dynamic and the steady state characteristics of BLSM are simulated and analyzed : electromagnetic torque, speed, line voltage, and current. We used mathematical modelling to model of BLSM with sinusoidal back EMF, namely the shaft transformation referencing rotor frame from a, b, c three to produce constant torque like synchronous motor. The experiment result has already similar to compare with simulation result : torque error about 7%, speed error about 5%. The validity of proposed modelling and analysis was confirmed by the experimental result.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.2
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• pp.156-173
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• 2004

Business process should support the execution of collaboration process with agility and flexibility through the integration of enterprise inner or outer applications and human resources from the collaborative workflow view. Although the dependency of enterprise activities to the automated system has been increasing, human role is as important as ever. In the workflow modelling this human role is emphasized and the structure to control human error by analysing decision-making itself is needed. Also, through the collaboration of activities agile and effective communication should be constructed, eventually by the combination and coordination of activities to the aimed process the product quality should be improved. This paper classifies human errors can be occurred in collaborative workflow by applying GEMS(Generic Error Modelling System) to control them, and suggests human error control method through hybrid based modelling as well. On this base collaborative workflow modeling tool is designed and implemented. Using this modelling methodology it is possible to workflow modeling could be supported considering human characteristics has a tendency of human error to be controlled.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.110-116
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• 2003

A catchment modelling system is the summation of the numerous hydrologic, hydraulic and other process models necessary to simulate the response of a catchment to a storm event. Differences between the recorded catchment response and that predicted by a catchment modelling system can arise from structural errors within the catchment modelling system, evaluation errors in the control parameters, or measurement errors in the recorded data being used to assess the reliability of the evaluation of the control parameters. Presented herein is an investigation of the potential measurement errors within the recorded information, which was considered to occur from instrument error in the ultra sonic flow monitor. This investigation was undertaken using three available rating curves at the Musgrave Avenue Stormwater System in Centennial Park, Sydney, developed by Abustan (1997), Water Board (1994), and using Manning's equation.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2827-2830
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• 2003

Tele manipulator is distingushed from industrial robot by iterating same specified work. Manipulator operator is included in control loop for controlling the telemanipulator because he decide directly during the work and order controllabily reducing the modelling error of telemanipulator which depend on the PID controller. But position-force control method of bidirectional control impose unsafety of vibiration and Analytic Hierachy Method can stabilize for reducing nonlinear modelling error by expert operator because of transformation empirical control rule to linear model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.304-310
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• 2020

The technology in 3D modelling have advanced not only maps, heritages, constructions but also trees modelling. By laser scanning(Faro s350) and photogrammetry software(Pix4d) for 3D modelling, this study compared with real coniferous tree and both technology's results about characteristics of shape, texture, and dimensions. As a result, both technologies all showed high reproducibility. The scanning technique showed very good results in the reproduction about bark and leaves. Comparing the detailed dimensions on it, the error between the actual tree and modelling with scanning was 1.7~2.2%, and the scanning result was larger than the actual tree. The error between the actual tree and photogrammetry was only 0.2~0.5%, which was larger than the actual tree. On the other hand, the dark areas's modelling was not fully processed. This study is meaningful as a basic research that can be used for tree DB on BIM for the landscape architecture, landscape design and analysis with AR technology, historical tree and heritage also.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.137-149
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• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.294-298
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• 2009

In this study, we proposes the method to improve the quality of the image through the edge extraction more delicately. Our method is named ESII(Edge Sensitive Image Interpolation) and doesn't use the fixed parameter of the interpolation kernel. However, it changes the parameter of pixel which is interpolated to the high definition image using the proper information from the surrounding pixels. It reconstructs the image by using the LSE(Least Square Error) and determining the pixel values to make the CME(Camera Modelling Error) minimized. Compared to the conventional methods, suggested method shows the higher quality of subjective and objective image definition and lessons the computational complexity by separating the image into 1-D data.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1144-1148
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• 1996

This paper presents WMR modelling and path tracking algorithm using Inertial Navigation System. The error models of gyroscope and accelerometers in INS are derived by Gauss-Newton method which is nonlinear regression model. Then, to test availability of error model, we pursue the fitness diagnosis about probability characteristic for real data and estimated data. Performance of inertial sensor with error model and Kalman filter is pursued by comparing with one without them. The computer simulation shows that position error remarkably decrease when error compensation is applied.

• Journal of Ocean Engineering and Technology
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• v.10 no.1
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• pp.65-74
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• 1996

Up to now, the existing crack growth modelling has used a mathematical approximation but an assumed function have a great influence on this method. Especially, crack growth behavior that shows very strong nonlinearity needed complicated function which has difficulty in setting parameter of it. The main characteristics of neural network modelling to engineering field are simple calculations and absence of assumed function. In this paper, after discussing learning and generalization of neural networks, we performed crack growth modelling on the basis of above learning algorithms. J'-da/dt relation predicted by neural networks shows that test condition with unlearned data is simulated well within estimated mean error(5%).