• Journal of Welding and Joining
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• v.32 no.6
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• pp.8-13
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• 2014

One of the main challenges of the automatic arc welding process which has been widely used in various constructions such as steel structures, bridges, autos, motorcycles, construction machinery, ships, offshore structures, pressure vessels, and pipelines is to create specific welding knowledge and techniques with high quality and productivity of the production-based industry. Commercially available automated arc welding systems use simple control techniques that focus on linear system models with a small subset of the larger set of welding parameters, thereby limiting the number of applications that can be automated. However, the correlations of welding parameters and bead geometry as welding quality have mostly been linked by a trial and error method to adjust the welding parameters. In addition, the systematic correlation between these parameters have not been identified yet. To solve such problems, a new or modified models to determine the welding parameters for tandem GMA (Gas Metal Arc) welding process is required. In this study, A new predictive model called STACO model, has been proposed. Based on the experimental results, STACO model was developed with the help of a standard statistical package program, MINITAB software and MATLAB software. Cross-comparative analysis has been applied to verify the reliability of the developed model.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.16-21
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• 2001

In this paper a virtual form of 3 dimensional face is synthesized from the two sheets of 2 dimensional photographs In this case two sheets of 2D face photographs, the front and the side photographs are used First of all a standard model for a general face is created and from this model the feature points which represents a construction of face are densely defined on part of ears. eyes, a nose and a lip but the other parts. for example, forehead, chin and hair are roughly determined because of flat region or the less individual points. Thereafter the side photograph is connected symmetrically on the left and right sides of the front image and it is gradually synthesized by use of affine transformation method. In order to remove the difference of color and brightness from the junction part, a linear interpolation method is used. As a result it is confirmed that the proposed model which general model of a face can be obtain the 3D virtual image of the individual face.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.555-565
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• 1999

The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.59-74
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• 2015

This study aims to estimate optimal harvesting production, fishing efforts, and stock levels of yellow croaker caught by the offshore Stow Net and the offshore Gill Net fisheries using the current value Hamiltonian method and the surplus production model. As analyzing processes, firstly, this study uses the Gavaris general linear model to estimate standardized fishing efforts of yellow croaker caught by the above multiple fisheries. Secondly, this study applies the Clarke Yoshimoto Pooley(CY&P) model among the various exponential growth models to estimate intrinsic growth rate(r), environmental carrying capacity(K), and catchability coefficient(q) of yellow croaker which inhabits in offshore area of Korea. Thirdly, the study determines optimal harvesting production, fishing efforts, and stock levels of yellow croaker using the current value Hamiltonian method which is including average landing price of yellow croaker, average unit cost of fishing efforts, and social discount rate based on standard of the Korean Development Institute. Finally, this study tries sensitivity analysis to understand changes in optimal harvesting production, fishing efforts, and stock levels of yellow croaker caused by changes in economic and biological parameters. As results drawn by the current value Hamiltonian model, the optimal harvesting production, fishing efforts, and stock levels of yellow croaker caught by the multiple fisheries were estimated as 19,173 ton, 101,644 horse power, and 146,144 ton respectively. In addition, as results of sensitivity analysis, firstly, if the social discount rate and the average landing price of yellow croaker continuously increase, the optimal harvesting production of yellow croaker increases at decreasing rate and then finally slightly decreases due to decreases in stock levels of yellow croaker. Secondly, if the average unit cost of fishing efforts continuously increases, the optimal fishing efforts of the multiple fisheries decreases, but the optimal stock level of yellow croaker increases. The optimal harvest starts climbing and then continuously decreases due to increases in the average unit cost. Thirdly, when the intrinsic growth rate of yellow croaker increases, the optimal harvest, fishing efforts, and stock level all continuously increase. In conclusion, this study suggests that the optimal harvesting production and fishing efforts were much less than actual harvesting production(35,279 ton) and estimated standardized fishing efforts(175,512 horse power) in 2013. This result implies that yellow croaker has been overfished due to excessive fishing efforts. Efficient management and conservative policy on stock of yellow croaker need to be urgently implemented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.197-208
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• 2022

The existence of shallow bedrock and the desire to use underground space necessitate the use of blasting methods. The standard blasting method under water after drilling is associated with certain technical difficulties, including reduced detonation power, the use of a fixed charge per delay, and decoupling. However, there is no blasting method to replace the existing blasting method. In this paper, a dry hole charged with ANFO blasting is assessed while employing a dry hole pumping system to remove water from the drill borehole. Additional standard blasting is also utilized to compare the blasting performances of the two methods. The least-squares linear regression method is adopted to analyze the blasting vibration velocity quantitatively using the measured vibration velocity for each blasting method and the vibration velocity model as a function of the scaled distance. The results show that the dry hole charged with ANFO blasting will lead to greater damping of the blasting vibration, more energy dissipation to crush the surrounding rock, and closer distances for the allowable velocity of the blasting vibration. Also, standard blasting shows much longer influencing distances and a wider range of the blasting pattern. The pilot test confirms the blasting efficiency of dry hole charged with ANFO blasting.

• The Journal of Engineering Geology
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• v.16 no.4 s.50
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• pp.393-402
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• 2006

The contamination characteristics of BTEX and TPH components in silty soils with the oil leakage event from point source were studied. The over ratios of three soil pollution standard for TPH component were $1.5{\sim}1.7$ times higher than that of BTEX component. The mean and maximum values of BTEX and TPH components with sample points were B-zone > A-zone > C-zone, and the highest concentrations were measured at $1{\sim}2m$ depth below surface. BTEX and TPH components were increased with linear distance in zone within 120 m and 80 m from point source. For the zone more than 120 m, BTEX and TPH concentrations were under soil pollution standard. The cutoff values of indicator kriging using BTEX and TPH components were defined as confirmative limit, warn- ing limit and counterplan limit. The variograms of indicator-transformed data were selected linear model. The contamination ranges of BTEX and TPH components using confirmative limit and warning limit were estimated similar, but the contamination range of those using counterplan limit was much reduced. The maximum contamination probabilities were estimated by probability maps usinB confirmative limit, warning limit and counterplan limit. The maximum contamination probabilities with three soil pollution standard were estimated 26%, 26% and 13% for BTEX component, and 44%, 38% and 26% for TPH component.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.3
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• pp.65-73
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• 2004

The bolier systems of coal fired power plants are large, non-linear systems with numerous interactions between its component parts. In the analysis of such complex systems, dynamic simulation is recognized as a powerful method of keeping track of the myriad of interactions. The boiler system consists of air/gas system and water/steam system. Due to recent reinforcement of environmental regulation on pollutant discharge and requirements of design validation on properites of boiler, the commercial programs are used for the analysis of boiler system. This paper addressed to the development of model using MMS(Modular Modeling System) developed by EPRI(Electric Power Research Institute) as the simulation tool. The developed model using MMS is tested for the design and local data on boiler combustion system of korea standard coal fired power plant boiler. The simulation results show that the developed model well reproduces responses of the combustion system with less than ${\pm}$5% error under steady state and transient state conditions. The developed model for analysis of the combustion system in this paper is general and applicable to any type of coal fired power plant.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.653-664
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• 2015

TPLMS (Total water pollutant load management system) that is the most powerful water-quality protection program have been implemented since 2004. In the implementation of TPLMS, target water-quality and permissible discharged load from each unit watershed can be decided by water-quality modeling. And NPS (Non-point sources) discharge coefficients associated with certain (standard) flow are used on estimation of input data for model. National Institute of Environmental Research (NIER) recommend NPS discharge coefficients as 0.15 (Q₂₇₅) and 0.50 (Q₁₈₅) in common for whole watershed in Korea. But, uniform coefficient is difficult to reflect various NPS characteristics of individual watershed. Monthly NPS discharge coefficients were predicted and estimated using surface flow and water-quality from HSPF watershed model in this study. Those coefficients were plotted in flow duration curve of study area (Palger stream and Geumho C watershed) with monthly average flow. Linear regression analysis was performed about NPS discharge coefficients of BOD, T-N and T-P associated with flow, and R² of regression were distributed in 0.893~0.930 (Palger stream) and 0.939~0.959 (Geumho C). NPS Discharge coefficient through regression can be estimated flexibly according to flow, and be considered characteristics of watershed with watershed model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.575-594
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• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• Current Optics and Photonics
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• v.6 no.5
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• pp.489-496
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• 2022

Our previous study on monitoring cerebral oxygenation with a variation of isoflurane concentration in a rat model showed that near-infrared spectroscopy (NIRS) signals have potential as a new depth of anesthesia (DOA) index. However, that study obtained results from the brain in a completely invasive way, which is inappropriate for clinical application. Therefore, in this follow-up study, it was investigated whether the NIRS signals measured in a minimally invasive model including the skull and cerebrospinal fluid layer (CSFL) are similar to the previous study used as a gold standard. The experimental method was the same as the previous study, and only the subject model was different. We continuously collected NIRS signals before, during, and after isoflurane anesthesia. The isoflurane concentration started at 2.5% (v/v) and decreased to 1.0% by 0.5% every 5 min. The results showed a positive linear correlation between isoflurane concentration and ratio of reflectance intensity (RRI) increase, which is based on NIRS signals. This indicates that the quality of NIRS signals passed through the skull and CSFL in the minimally invasive model is as good as the signal obtained directly from the brain. Therefore, we believe that the results of this study can be easily applied to clinics as a potential indicator to monitor DOA.