• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.6
• /
• pp.155-166
• /
• 2016

It is important to configure capacitance(C) of the capacitor and the induction coefficient(L) of the work coil on the resonant circuit design stage in order to induce heating on the object by a precise and constant frequency components in the electromagnetic induction heating equipment. Work coil conducts a direct induction heating according to heating point and area of the object which has a fixed heat factor so that work coil is designed to has fixed value. On the other hands, Capacitor should be designed to be changed in order to be the higher the utilization of the entire equipment. It is extracted the samples by variation of single electrode capacity from the selection stage of raw materials for capacity to the stage of process design for output of the high frequency LC resonance of 700kHz on 1000 VAC maximum voltage and current to $200I_{MAX}$. It is suggested fundamental experiment results in order to prove relation for the optimal design of HF-LC resonance conduction-cooled capacitor based on the response of frequency characteristics and results of output parameters according to variation of the capacitance size.

• Journal of Soil and Groundwater Environment
• /
• v.18 no.1
• /
• pp.26-35
• /
• 2013

Outbreak of animal infectious diseases such as foot-and-mouth disease, avian influenza are becoming prevalent worldwide. For prevent the further infection, tremendous numbers of the infected or culled stocks are buried around farm. This burial method can generate a wide range of detrimental components such as leachate, nutrient, salt, and pathogenic bacteria, consequently. In this study, for the stabilization of livestock carcasses leachate, advanced oxidation processes utilizing the Fenton reaction was investigated in lab-scale experiments for the treatment for $COD_{Cr}$ of livestock carcass leachate. $COD_{Cr}$ reduction by the Fenton oxidation was investigated response surface methodology using the Box-Begnken methods were applied to the experimental results. A central composite design was used to investigate the effects of the independent variables of pH ($x_1$), dosage of $FeCl_2{\cdot}4H_2O$ ($x_2$) and dosage of $H_2O_2$ ($x_3$) on the dependent variables $COD_{Cr}$ concentration ($y_1$). A 1 M NaOH and $H_2SO_4$ was using for pH control, $FeCl_2{\cdot}4H_2O$ was used as iron catalyst and NaOH was used for Fenton reaction. The optimal conditions for Fenton oxidation process were determined: pH, dosage of $FeCl_2{\cdot}4H_2O$ and dosage of $H_2O_2$ were 3, 0.6 g (0.0151 M) and 7 mL(0.259 M), respectively. Statistical results showed the order of significance of the independent variables to be pH > initial concentration of ferrous ion > initial concentration of hydrogen peroxide.

• Asian Spine Journal
• /
• v.12 no.6
• /
• pp.1085-1091
• /
• 2018

Study Design: Case-control. Purpose: To determine optimal cut-off value for body mass index (BMI) in predicting surgical success in patients with lumbar spinal canal stenosis (LSCS). Overview of Literature: BMI is an essential variable in the assessment of patients with LSCS. Methods: We conducted a prospective study with obese and non-obese LSCS surgical patients and analyzed data on age, sex, duration of symptoms, walking distance, morphologic grade of stenosis, BMI, postoperative complications, and functional disability. Obesity was defined as BMI of ${\geq}30kg/m^2$. Patients completed the Oswestry Disability Index (ODI) questionnaire before surgery and 2 years after surgery. Surgical success was defined as ${\geq}30%$ improvement from the baseline ODI score. Receiver operating characteristic (ROC) analysis was used to estimate the optimal cut-off values of BMI to predict surgical success. In addition, correlation was assessed between BMI and stenosis grade based on morphology as defined by Schizas and colleague in total, 189 patients were eligible to enter the study. Results: Mean age of patients was $61.5{\pm}9.6years$. Mean follow-up was $36{\pm}12months$. Most patients (88.4%) were classified with grades C (severe stenosis) and D (extreme stenosis). Post-surgical success was 85.7% at the 2-year follow-up. A weak correlation was observed between morphologic grade of stenosis and BMI. Rates of postoperative complications were similar between patients who were obese and those who were non-obese. Both cohorts had similar degree of improvement in the ODI at the 2-year followup. However, patients who were non-obese presented significantly higher surgical success than those who were obese. In ROC curve analysis, a cut-off value of ${\leq}29.1kg/m^2$ for BMI in patients with LSCS was suggestive of surgical success, with 81.1% sensitivity and 82.2% specificity (area under the curve, 0.857; 95% confidence interval, 0.788-0.927). Conclusion: This study showed that the BMI can be considered a parameter for predicting surgical success in patients with LSCS and can be useful in clinical practice.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.2
• /
• pp.236-242
• /
• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.76-91
• /
• 2017

The Area of a domestic railway station is designed based on the 4-step traffic demand forecasting model with the average daily passenger count as one of its parameter. However, nowadays, due to increasing rate of railway station's function, the non-passengers are increasing. In order to consider those non-passengers who aren't using trains, assumed volume are added to the average daily passenger count of station to estimate the area, but the criteria being applied has no concrete basis. Therefore, this study aimed to recalculate the increasing non-passenger rate based on actual survey data of station users in any type of railway station to obtain the optimum area. Subsequently, the the design area was performed through pedestrian simulation. According to the result of the simulation, it was found that the total space of the exciting railway stations can be reduced up to 45% and will still satisfy the level of service(LOS) requirement.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.241-254
• /
• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Applied Biological Chemistry
• /
• v.47 no.1
• /
• pp.96-106
• /
• 2004

Response surface methodology (RSM) was applied in roasting processes of perilla leaves to develop a high quality perilla leaf tea. The Hunter color parameters and electron donating ability were monitored to optimize organoleptic properties of perilla leaf tea. The roasting processes were based on the central composite design with primary variables-roasting temperature $(140{\sim}220^{\circ}C)$, time $(5{\sim}25)$, and reaction variables-sensory test, electron donating ability. From the variables, the roasting condition was optimized using statistical analysis system (SAS) program as developing the functional tea using perilla leaf. Hunter color L and b values of the powdered samples increased with the roasting processes, but Hunter color a value decreased. Electron donating ability was influenced by roasting temperature (p<0.01) and time (p<0.01), and optimum condition selected was at $220^{\circ}C$ for 15 min with coefficient of determinations $(R^2)$ above 0.98. After preference test of perilla leaf tea using parameter of taste, color, and flavor, we can estimate that the optimal roasting condition of preilla leaf for function tea manufacturing are $210{\sim}220^{\circ}C$ for $10{\sim}20$ min by response surface methodology (RSM). Tyrosinase, xanthine oxidase and electron donating ability were 10.14, 14.37 and 59.19% of perilla leaf tea.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.12
• /
• pp.3626-3631
• /
• 2009

This study has provided some of the first experimental results of NMOSFET hot-carrier degradation for the analog circuit application. After hot-carrier stress under the whole range of gate voltage, the degradation of NMOSFET characteristics is measured in saturation region. In addition to interface states, the evidences of hole and electron traps are found near drain depending on the biased gate voltage, which is believed to the cause for the variation of the transconductance($g_m$) and the output conductance($g_{ds}$). And it is found that hole trap is a dominant mechanism of device degradation in a low-gate voltage saturation region, The parameter degradation is sensitive to the channel length of devices. As the channel length is shortened, the influence of hole trap on the channel conductance is increased. Because the magnitude of $g_m$ and $g_{ds}$ are increased or decreased depending on analog operation conditions and analog device structures, careful transistor design including the level of the biased gate voltage and the channel length is therefore required for optimal voltage gain ($A_V=g_m/g_{ds}$) in analog circuit.

• Korean Journal of Remote Sensing
• /
• v.34 no.3
• /
• pp.481-494
• /
• 2018

The accurate radiative transfer model simulation is essential for an accurate ozone profile retrieval using optimal estimation from backscattered ultraviolet (BUV) measurement. The input parameters of the radiative transfer model are the main factors that determine the model accuracy. In particular, meteorological parameters such as temperature and surface pressure have a direct effect on simulating radiation spectrum as a component for calculating ozone absorption cross section and Rayleigh scattering. Hence, a sensitivity of UV ozone profile retrievals to these parameters has been investigated using radiative transfer model. The surface pressure shows an average error within 100 hPa in the daily / monthly climatological data based on the numerical weather prediction model, and the calculated ozone retrieval error is less than 0.2 DU for each layer. On the other hand, the temperature shows an error of 1-7K depending on the observation station and altitude for the same daily / monthly climatological data, and the calculated ozone retrieval error is about 4 DU for each layer. These results can help to understand the obtained vertical ozone information from satellite. In addition, they are expected to be used effectively in selecting the meteorological input data and establishing the system design direction in the process of applying the algorithm to satellite operation.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.43 no.9
• /
• pp.1462-1466
• /
• 2014

In this study, an attempt was made to produce oat protein concentrates from defatted oat groat by alkali extraction. Independent variables formulated by D-optimal design were NaOH concentration (X1, 0.005~0.06 N) for extraction and precipitation pH (X2, pH 4.0~6.0), and the dependent variable was extraction yield (Y1, %). Experimental results were analyzed by response surface methodology to determine optimized extraction conditions. Extraction yield increased both with an increase in NaOH concentration of the extraction solution and when approaching a precipitation pH of 4.9, and NaOH concentrations were a major influencing parameter. Solubility of oat protein concentrates showed a minimum value (i.e., 0.1%) at pH 5 and increased substantially at pH values in the range of ${\leq}$ pH 3 or ${\geq}$ pH 7, reaching a maximum value at pH 11 (i.e., 76%). Regression equation coincided well with the results of the experiment. Optimized extraction conditions to maximize extraction yield were 0.06 N NaOH (X1) for extraction and pH 4.7 (X2) for precipitation.