• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.2
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• pp.168-177
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• 2003

The performance sensitivity analysis due to manufacturing/alignment errors is performed for the Ku-band offset parabola antenna of the domestic Communications and Broadcasting Satellite. The performance variations due to reflector random surface error, which inevitably happens during reflector manufacturing, are statistically analyzed using RMS error and correlation interval. The impact on the antenna performance of the fred hem's position and angular errors is investigated, and the sensitive directions are identified. When the target tolerances are applied, the performance degradations are found to be within the loss budget or corresponding performance margins.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.10a
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• pp.16.1-16.1
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• 2011

Gas sensor properties of $WO_3$ nanowire structures have been studied. The sensing layer was prepared by deposition of tungsten metal on porous single wall carbon nanotubes followed by thermal oxidation. The morphology and crystalline quality of $WO_3$ material was investigated by SEM, TEM, XRD and Raman analysis. A highly porous $WO_3$ nanowire structure with a mean diameter of 82 nm was obtained. Response to CO, $NH_3$ and $H_2$ gases diluted in air were investigated in the temperature range of $100{\sim}340^{\circ}C$ The sensor exhibited low response to CO gas and quite high response to $NH_3$ and $H_2$ gases. The highest sensitivity was observed at $250^{\circ}C$ for $NH_3$ and $300^{\circ}C$ for $H_2$. The effect of the diameters of $WO_3$ nanowires on the sensor performance was also studied. The $WO_3$ nanowires sensor with diameter of 40 nm showed quite high sensitivity, fast response and recovery times to $H_2$ diluted in dry air. The sensitivity as a function of detecting gas concentrations and gas sensing mechanism was discussed. The effect of dilution carrier gases, dry air and nitrogen, was examined.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.11
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• pp.831-836
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• 2010

In this paper, Plasma Enhanced Chemical Vapor Deposition (PECVD) $SiO_2$ film properties are modeled using statistical analysis and neural networks. For systemic analysis, Box-Behnken's 3 factor design of experiments (DOE) with response surface method are used. For characterization, deposited film thickness and film stress are considered as film properties and three process input factors including plasma RF power, flow rate of $N_2O$ gas, and flow rate of 5% $SiH_4$ gas contained at $N_2$ gas are considered for modeling. For film thickness characterization, regression based model showed only 0.71% of root mean squared (RMS) error. Also, for film stress model case, both regression model and neural prediction model showed acceptable RMS error. For sensitivity analysis, compare to conventional fixed mid point based analysis, proposed sensitivity analysis for entire range of interest support more process information to optimize process recipes to satisfy specific film characteristic requirements.

• Tribology and Lubricants
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• v.30 no.1
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• pp.15-20
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• 2014

A more accurate expression for effective viscosity is obtained using a linear regression of the data from Fukui-Kaneko's model, which are obtained through numerical calculations based on the linearized Boltzmann equation. Veijola and Turowski's expression is adopted as a base function for effective viscosity. The four coefficients in that equation are optimized, and sensitivity analysis is conducted for these coefficients. The results show that the coefficient for the first-order Knudsen number is the most accurate, whereas the coefficient in the exponential of the Knudsen number is the least accurate compared with Fukui-Kaneko's results. The expression for effective viscosity is accurate within 0.02% rms of Fukui-Kaneko's results for the inverse Knudsen numbers from 0.01 to 100 and surface accommodation coefficients ranging from 0.7 to 1.

• Korean Journal of Environmental Biology
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• v.30 no.4
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• pp.307-313
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• 2012

The Oriental White Stork (Ciconia boyciana) is a representative wetland species distributed across East Asia. The species has been declined to face the threat of species extinctions with estimation of at about 3000 individuals. In order to re-introduce the endangered storks in the field, we developed a baseline model using the program VORTEX, performed sensitivity test, and finally suggested an ideal model based on results of the sensitivity test. The baseline model predicted 12.5% extinction probability with mean time to first extinction of 82.0 year. Sensitivity test revealed that two demographic variables (first-year mortality and percent of adult female breeding) had the greatest impacts on population persistence. Thus, corrected model improved the population persistence, where the extinction probability decreased to 1.0% in 100 years by changing values of two variables within a range of applicable to the population. Our models for stork re-introduction suggest this population will be stable by improving first-year mortality and adult female fecundity.

• The Korean Journal of Nuclear Medicine
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• v.17 no.2
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• pp.19-24
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• 1983

The purpose of this study was to develop a method by which the sensitivity of radionuclide liver imaging for detection of liver cirrhosis could be enhanced. Dynamic blood flow scan were performed 21 cases of liver cirrhosis patients by using computerized gamma camera named arterialization index. The results were as follows: 1) Arterialization index were higher in liver cirrhosis comparing to normal value 0.33 and its mean is 2. 02. 2) Comparing to static liver scan, higher sensitivity in dynamic hepatic blood flow scan for detection of liver cirrhosis. Sensitivity for detection of liver cirrhosis is over 90%. 3) There are no correlation between arterialization index and serum albumin level. The use of hepatic dynamic blood flow scan proved effective in detection of liver cirrhosis. However, the test may be used as an aid in distinguishing between normal and pathologic livers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1854-1862
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• 2000

Input shaping method is to convolute input shaper, which is sequence of impulses, with reference input command not to excite the natural frequency of system. To reduce residual vibration for the ch ange of frequency, the number of impulses should be increased. Until now, amplitudes and time interval of those has been searched from the derivative of residual vibration. However, if time interval of impulses is fixed as the half of vibration period of system, input shaper H(z) in z-domain becomes (I-pz-1)n/K in which increasing n is the mean that robustness for change of parameter is improved. Also, design of many types of input shapers in z-domain is very easy because sensitivity curve is displayed with $\mid$H(z)zn$\mid$$\times$100. In the z-domain, EI(Extra-Insensitive) input shaper could be designed without solving nonlinear simultaneous equations as design in continuous time domain. In addition to, the design possibility of input shaper for a damped system was shown.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.8
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• pp.581-588
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• 2020

The aging characteristics of exploding foil initiator (EFI) are studied. In order to observe the aging characteristics, the main components of the exploding foil initiator were classified and the failure mechanism was defined. The aging characteristics were defined in terms of power and sensitivity, and the accelerated aging test plan was established based on the activation energy calculated by HFC (Heat Flow Calorimetry) and Arrhenius theory. The performance variation was observed using the sensitivity test (Neyer test) and power test (Dent test) for the aged samples. The aging characteristic was observed on the mean exploding point of the sensitivity test, but long-enough life span was predicted considering the related specification.

• Journal of Home Health Care Nursing
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• v.29 no.2
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• pp.175-182
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• 2022

Purpose: The study examined the effects of ethical sensitivity and person-environment fit on person-centered care of nurses in long-term care hospitals. Methods: The participants were 111 nurses. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis with the SPSS program. Results: The mean of person-centered care was 2.95±0.62 out of 5. There were significant differences in person-centered care in terms of age, shift pattern, total clinical career, and educational experience of person-centered care. Person-centered care and ethical sensitivity, person-centered care and person-environment fit showed a positive correlation. Factors affecting the person-centered care were the age (20-29), shift pattern (three shift), person-environment fit. The explanatory power was 42%. Conclusion: These results can be used to increase the person-environment fit and adopt a differented approach based on age and shift pattern in order to enhance person-centered care. Therefore, it is necessary to develop and apply an person-centered care program for nurses in long-term care hospitals.

• Journal of Wind Energy
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• v.15 no.2
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• pp.10-22
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• 2024

This research is a comprehensive analysis of wind power prediction sensitivity using a Long Short-Term Memory (LSTM) deep learning neural network model, accounting for the inherent uncertainties in wind speed estimation. Utilizing a year's worth of operational data from an operational wind farm, the study forecasts the power output of both individual wind turbines and the farm collectively. Predictions were made daily at intervals of 10 minutes and 1 hour over a span of three months. The model's forecast accuracy was evaluated by comparing the root mean square error (RMSE), normalized RMSE (NRMSE), and correlation coefficients with actual power output data. Moreover, the research investigated how inaccuracies in wind speed inputs affect the power prediction sensitivity of the model. By simulating wind speed errors within a normal distribution range of 1% to 15%, the study analyzed their influence on the accuracy of power predictions. This investigation provided insights into the required wind speed prediction error rate to achieve an 8% power prediction error threshold, meeting the incentive standards for forecasting systems in renewable energy generation.