• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.786-789
• /
• 2002

A recurrent artificial neural network (ANN) model is developed to simulate hydrocarbon recovery process at petroleum-contaminated site. The groundwater extraction rate, vacuum pressure, and saturation hydraulic conductivity are selected as the input variables, while the cumulative hydrocarbon recovery volume is considered as the output variable. The experimental data fer establishing the ANN model are from implementation of a multiphase flow model for dual phase remediation process under different input variable conditions. The complex nonlinear and dynamic relationship between input and output data sets are then identified through the developed ANN model. Reasonable agreements between modeling results and experimental data are observed, which reveals high effectiveness and efficiency of the neural network approach in modeling complex hydrocarbon recovery behavior.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.6
• /
• pp.20-27
• /
• 1993

The white-balance system for color tevision is characterized by 5 input-5 output nonlinear process. A design strategy of fuzzy control rules is treated in which it can be adopted to the white balance adjustment for color television. A fuzzy rule based on an expert's knowledge is constructed, and then a multivariable fuzzy control rule is designed. Since human has just two hands, he can manipulate two variables simutaneously. In case when the process to be controlled has more than three control variables, expert's control rule is much different from the multivariable control rule. A multivariable fuzzy control rule is constructed by utilizing the expert' knowledge and rough relations between input and output variables, and its usefulness is shown by experiments.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.8
• /
• pp.883-892
• /
• 1992

In order to remove the assumption of full state availability which is one of the major difficulties with the practical realization of variable structure control system (VSCS), an output feedback variable structure control scheme for multivariable systems is proposed. The proposed output feedback VSCS is composed of a switching surfaces with dynamic structure and a new output feedback control input that can be constructed by using conventional output feedback control input design methodologies. With the proposed scheme, the practical realization of VSCS for the systems with unmeasurable states and for high order systems that conventional schemes cannot be applied is possible. Simulation results show that proposed scheme is a viable method to achieve the desired control performance, for example, good transient response, robustness against process parameter variations and external disturbance without measuring all the state variables.

• Journal of Welding and Joining
• /
• v.26 no.1
• /
• pp.63-68
• /
• 2008

This paper has aimed to prevent excessive heat input by controlling arc distribution and heat input capacity with pulse GTAW in order to improve weld quality in 0.08mm pressure gauge diaphragm and flange welding parts. A design of experiment was designed using Box-Behnken method to optimize a welding process. The pulse GTAW parameters such as pulse current, base current, pulse duty, frequency and welding speed were set to input variables while hydraulic pressure that represents welding characteristics in diaphragm and flange joint were set to output variables. Based on the test result, a second regression equation was obtained between input and output variables and turned out significant. Besides, an influence of parameters has been confirmed through response surface analysis using the second-order regression equation and optimum welding condition was obtained through a grid-search method. The optimum welding condition was set to pulse current 84.4(A), base current 29.6(A), pulse duty 58.8(%), frequency 10(%), and welding speed 596(mm/min). Then, decent bead shape was acquired with no excessive heat input under the $2.3kgf/cm^2$ of hydrostatic pressure.

• Journal of Information Technology Applications and Management
• /
• v.23 no.4
• /
• pp.83-100
• /
• 2016

In this paper, we present the DEA (Data Envelopment Analysis) application case study to investigate the regionally distinctive telco management characteristics of the Asia-Pacific countries. This study attempts to exploit the implications of DEA for the assessments of core process capabilities of telcos. Accordingly, we extract input variables of CAPEX (capital expenditure), operating expense, marketing expense, and number of employees, each to reflect the competitiveness of the core processes such as fixed asset utilization, operation & sales efficiency, and white collar productivity. In conjunction with the input variables, the output variables are chosen as EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization), ARPU (Average Revenue per User), and number of subscribers. The computational testing results, conducted with total 37 telcos of the 12 Asia-Pacific countries, are analyzed in various ways to understand the distinctive performance characteristics across the region. The managerial implication captured from this study provides useful insight for using DEA as the international telco management purpose.

• Journal of Korea Technology Innovation Society
• /
• v.14 no.3
• /
• pp.552-577
• /
• 2011

We have analyzed technology transfer and commercialization process and factors affecting the outcomes of technology commercialization of public research institutes in Korea. A technology commercialization process model was presented as an input, intermediate outcomes/capabilities, output (outcome) structure using the structural equation model. Input variables include R&D input, technology commercialization strategy/support, collaboration, social capital. The model also includes R&D capabilities and technology commercialization performance as intermediate variable and output variable respectively. The technology commercialization performance was measured as the number of technology transfer and spin-off. We conducted survey and 88 institutes responded. Empirical results show that R&D input influence R&D capabilities and R&D capabilities influence the output of technology transfer and commercialization. Collaboration activities and social capital also appear to have a positive effect on the output. However, the effect of strategy and support on the output appear to be not statistically significant.

• Journal of the Korean Mathematical Society
• /
• v.49 no.3
• /
• pp.641-658
• /
• 2012

The goal of this paper is to develop a nonlinear observer-based control strategy for a multi-variables continuous stirred tank reactor (CSTR). A new robust nonlinear observer is constructed to estimate the whole process state variables. The observer is coupled with a nonlinear controller, designed based on the input-output linearization for controlling the concentration and reactor temperature. The closed loop system is shown to be globally asymptotically stable based on Lyapunov arguments. Finally, computer simulations are developed for showing the performance of the proposed controller.

• Proceedings of the KWS Conference
• /
• 1997.10a
• /
• pp.205-209
• /
• 1997

One of the major important tasks in the robotic $CO_2$ arc welding process is to understand how process variables affected bead geometry and to subsequently develop the mathematical models to predict the desired bead dimensions. Experiment results are compared to outputs obtained using a set of published formulae relating input variables to output parameters and also investigated process variables on bead geometry for robotic $CO_2$ arc welding process The university of results obtained using empirical equations taken from existing models provided to be limited in predicting experimental bead shapes.

• Journal of Powder Materials
• /
• v.29 no.6
• /
• pp.459-467
• /
• 2022

Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.337-339
• /
• 2004

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.