• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1230-1237
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• 2009

In this paper, we develop a design methodology of Granular-based Radial Basis Function Neural Networks(GRBFNN) by context-based clustering. In contrast with the plethora of existing approaches, here we promote a development strategy in which a topology of the network is predominantly based upon a collection of information granules formed on a basis of available experimental data. The output space is granulated making use of the K-Means clustering while the input space is clustered with the aid of a so-called context-based fuzzy clustering. The number of information granules produced for each context is adjusted so that we satisfy a certain reconstructability criterion that helps us minimize an error between the original data and the ones resulting from their reconstruction involving prototypes of the clusters and the corresponding membership values. In contrast to "standard" Radial Basis Function neural networks, the output neuron of the network exhibits a certain functional nature as its connections are realized as local linear whose location is determined by the values of the context and the prototypes in the input space. The other parameters of these local functions are subject to further parametric optimization. Numeric examples involve some low dimensional synthetic data and selected data coming from the Machine Learning repository.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.426-431
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• 2007

In this paper we have studied the underwater vector channel modeling for MIMO(Multiple Input Multiple Output) to increase the performance and efficiency for ultrasound communication in underwater channel environments. Also we have analyzed the MIMO techniques using the proposed channel modeling. For underwater MIMO channel modeling. experiments were done in real channel environments and the data were analyzed to estimate parameters such as fading, Doppler, time delay, angle of arrival, and receiving power. These were used for modeling of underwater vector channel modeling for MIMO. Additionally, we have analyzed the performance of MIMO systems using our proposed channel models. As a result we could see that the BER has decreased severely with the same SNR when using the MIMO system.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1213-1216
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• 1987

In this paper, the application of AMFC(adaptive model - following-control) algorithm to the D.C motor speed control is investigated by using the 68000 microprocessor. Computer simulation in discrete AMFC algorithm shows that output errors caused by the external input and the variation of parameters in D.C motor are converged to zero.

• Proceedings of the KIPE Conference
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• 2018.11a
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• pp.175-176
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• 2018

This paper presents a method to estimate the parameter of permanent magnet synchronous motor using a least squares method. The approximate solution of the linear simultaneous equations is obtained by the pseudoinverse least squares method of the input current and output voltage data of the current controller. It is possible to obtain the current response of the same bandwidth to the general control target by using the Pole-zero Cancellation technique. This paper verifies the performance of the proposed method by comparing the results of estimation of parameters of different motors by simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.12
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• pp.1055-1060
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• 2016

Laser welding is a high-density energy welding method. Hence, deep penetration and high welding speed can be realized with lower heat input as compared with conventional welding. The heat input of a CW laser welding is determined by laser power and welding speed. In this study, bead and lap welding of $0.5mm^t$ pure titanium was performed using a fiber laser. Its weldability with laser power and welding speed was evaluated. Penetration, bead width, joining length, and bead shape were investigated, and the mechanical properties were examined through tensile-shear strength tests. Welds with sound joining length were obtained when the laser power and welding speed were respectively 0.5 kW and 2.5 m/min, and 1.5 kW and 6 m/min, and the weld obtained at low output presented better ductility than that obtained at high output.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6269-6273
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• 2015

Performance of the Alamouti algorithm based M-ary $2{\times}N$ OSTBC(Orthogonal Space Time Block Coded) MIMO(Multi Input Multi Output) system has been simulated varying two main parameters - the number of constellation(M), and the number of receiving antennas(N). Computer simulation has also been carried out using Matlab software for performance comparison between $2{\times}N$ MIMO and MRC(Maximal Ratio Combining) diversity antenna system to evaluate the degree of enhancement achieved through the use of Alamouti $2{\times}N$ MIMO. Under 10 dB EbNo QPSK scenario, $2{\times}1$ MIMO brought 4.2 dB BER improvement over single antenna system and $2{\times}2$ MIMO resulted in 7.4 dB BER improvement over $1{\times}2$ MRC.

• Design & Manufacturing
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• v.15 no.1
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• pp.48-56
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• 2021

The quality of products produced by injection molding process is greatly influenced by the process variables set on the injection molding machine during manufacturing. It is very difficult to predict the quality of injection molded product considering the stochastic nature of manufacturing process, because the process variables complexly affect the quality of the injection molded product. In the present study we predicted the quality of injection molded product using Artificial Neural Network (ANN) method specifically from Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) perspectives. In order to train the ANN model a systematic plan was prepared based on a combination of orthogonal sampling and random sampling methods to represent various and robust patterns with small number of experiments. According to the plan the injection molding experiments were conducted to generate data that was separated into training, validation and test data groups to optimize the parameters of the ANN model and evaluate predicting performance of 4 structures (MISO1-2, MIMO1-2). Based on the predicting performance test, it was confirmed that as the number of output variables were decreased, the predicting performance was improved. The results indicated that it is effective to use single output model when we need to predict the quality of injection molded product with high accuracy.

• Geotechnical Engineering
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• v.8 no.4
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• pp.41-50
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• 1992

In general, the conceptual lumped-parameter groundwater flow model to predict the groundwater fluctuations in hillside slopes has unknown model parameters to be estimated from the known input -output data. The purpose of this study is to estimate the optimal model parameters of the groundwater flow model developed by authors. The Mazilnum A Posteriori( MAP) estimation method is utilized for this purpose and it is applied to a site which shows the typical landslide in Korea. The result of application shows tllat the 반AP estimation method can estimate the unknown parameters properly well. The groundwater model developed along with estimation technique applied in this paper will be used for assessing risk of landslides.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.139-146
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• 2009

Parametric array for audio applications is analyzed by numerical modeling and analytical approximation. The nonlinear wave equations are used to provide design guidelines for the audio parametric array. A time domain finite difference code that accurately solves the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear parabolic wave equation is used to predict the response of the parametric array. The time domain code relates the source size and the carrier frequency to the audible signal response including the output level and beamwidth to considering the implementation issues for audio applications of the parametric array, the emphasis is given to the frequency response and distortion. We use the time domain code to find out the optimal parameters that will help produce the parametric array with highest achievable output in terms of the average power within the demodulated signal. Parameters such as primary input frequency, audio source radius and the modulation method are given utmost importance. The output effect of those parameters are demonstrated through the numerical simulation.

• Advances in nano research
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• v.12 no.4
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.