• IE interfaces
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• v.14 no.3
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• pp.227-235
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• 2001

There is a rapidly growing demand for wireless telecommunication. However, the number of usable channel is very limited. Therefore, the problem of channel assignment becomes more and more important to use channels as efficiently as possible. The objective of this paper is to develop an evolution program (EP) to find an efficient dynamic channel assignment method for minimum interference among the channels within reasonable time. The series of specific channel number is used as a representation of chromosome. The only changed chromosomes by crossover and mutation are evaluated in each generation to save computation time and memory for the progress of improved EP. We can easily differentiate the fitness value of each chromosome using proposed evaluation function. We also control the weighting factor of the mutation rate and the used number of elitist chromosomes for the speed of convergence to the optimal solution.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.420-423
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• 2001

In this paper, the Multi-FNNs(Fuzzy-Neural Networks) architecture is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNNs architecture uses simplified inference and linear inference as fuzzy inference method and error back propagation algorithm as learning rules. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNNs according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNNs model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model we use the time series data for gas furnace and the NOx emission process data of gas turbine power plant.

• Architectural research
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• v.16 no.4
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• pp.131-137
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• 2014

Recently, the development of sustainable building assessment tools as means to invigorate the dissemination of sustainable buildings has been actively progressed. However, many assessment tools involve various problems in terms of assessment method and system framework, which greatly impede their credibility and applicability. If these problems persist over time, the role of sustainable building assessment tools as decision making measures during the design stage will be greatly limited. The objective of the study is to suggest a systematic model for sus- tainable building assessment tools by establishing a logical system of performance assessment framework. For this purpose, the Environmen- tal Impact Assessment(EIA) framework used in selected and modified to fit the building performance assessment. The analysis of performance assessment tools for sustainable buildings was conducted using the EIA framework. Based on the results of the analysis, a framework for the performance assessment of sustainable buildings was established.

• The Journal of the Acoustical Society of Korea
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• v.7 no.2
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• pp.5-19
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• 1988

The feedback controllers for the active vibration control of elastic systems are developed using optimal regulator, optimal tracking, time optimal and noise observer algorithms. Using the modal analysis of the elastic systems, the effects of the actuator positions, the input weighting factor and the magnitude of the constraint of the actuator force are investigated.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.864-869
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• 2004

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of 'NARMAX' form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.104-108
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• 2001

In this paper, the 3-D measurement method of moving object with a laser and one camera system for image processing method is presented. The method of segmentation image in conventional method, the error are generated by the threshold values. In this paper, to improve these problem for segmentation image, the calculation of weighting factor using brightness distribution by histogram of stored images are proposed. Therefore the image erosion and spread are improved, the correct and reliable informations can be measured. In this paper, the system of 3-D extracting information using the proposed algorithm can be applied to manufactory automation, building automation, security guard system, and detecting information system for all of the industry areas.

• Journal of Power Electronics
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• v.13 no.5
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• pp.814-828
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• 2013

The LCL resonant inductive power transfer (IPT) system is increasingly used because of its harmonic filtering capabilities, high efficiency at light load, and unity power factor feature. However, the modeling and controller design of this system become extremely difficult because of parameter uncertainty, high-order property, and switching nonlinear property. This paper proposes a frequency and load uncertainty modeling method for the LCL resonant IPT system. By using the linear fractional transformation method, we detach the uncertain part from the system model. A robust control structure with weighting functions is introduced, and a control method using structured singular values is used to enhance the system performance of perturbation rejection and reference tracking. Analysis of the controller performance is provided. The simulation and experimental results verify the robust control method and analysis results. The control method not only guarantees system stability but also improves performance under perturbation.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.153-160
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• 1997

The purpose of this paper is to present design recommendations intended to reduce the risk of cumulative trauma disorders(CTD) at the Osram Slvania, Inc. The CTD risk index score is a method which quantifies the risk factors to CTD incidence, namely extreme postures, high force elements, frequent damaging hand motions, and other miscellaneous factors. The risk index score quantified the jobs as a single composite value by weighting the scores for each risk factor. Jobs were prioritized for capital outlays in workstation redesign, and the factors of highest risk within each job could be identified. Three jobs which presented the greatest risk of CTD incidence were redesigned ergonomically.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.255-264
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• 2005

In this paper, a practical bushing model is proposed to improve the accuracy of the vehicle dynamic analysis. The results of the rubber bushing are used to develop an empirical bushing model with an artificial neural network. A back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra algorithm of 'NARMAX' form is employed to consider these effects. A numerical example is carried out to verify the developed bushing model. Then, a full car dynamic model with artificial neural network bushings is simulated to show the feasibility of the proposed bushing model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.3
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• pp.46-52
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• 2012

During the past decades, energy and Green House Gas(GHG) emissions has risen as a global issue. This paper is about the energy intensity and the GHG intensity in a university campus using the weighting factor of total occupied time to the members of the university. Through this analysis, we could separately estimate GHG intensity per full-time and part-time members under the situation that the measuring data is not perfect. This analyzing procedure could be applied to other non-manufacturing institutions such as school, hospital, governmental institute, office building etc.