• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.273-276
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• 2002

In this paper, we propose a bias random vector generator which can verify functions of microprocessor effectively. This generator is a pre-processor of assembly program, and defines pre-processor instructions which create random vector only in the pall which the designer wants to verify. Therefore, this generator shows higher detection ration than any other generators. And, we can cut down design costs because of shortening a Period for verifying function.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.121-124
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• 2002

In this paper, we propose a bias random vector generator which can verify functions of microprocessor effectively. This generator is a pre-processor of assembly program, and defines pre-processor instructions which create random vector only in the part which the designer wants to verify. Therefore, this generator shows higher detection ration than any other generators. And, we can cut down design costs because of shortening a period for verifying function.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.33-44
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• 2023

Entrepreneurial self-efficacy is an important variable that explains people's attitudes and behaviors toward start-ups. In this study, we focused on individual psychological characteristics variables such as luck in belief and positive cognitive bias that affect entrepreneurial self-efficacy. Among these variables, we paid particular attention to luck in belief. The belief that business success depends on luck is widespread, but scientific verification about it has not been much. The reason for the academic indifference is that luck is a kind of superstition, related to precognition or extrasensory perception, and randomly caused by the external environment. The study of luck began in earnest as a measure to measure luck as an individual characteristic variable such as personality was developed. The purpose of this study is to examine the existing studies on luck in belief and to examine the effect of this luck in belief on positive cognitive bias and entrepreneurial self-efficacy through empirical analysis. For empirical analysis, this study conducted an on-line survey of 400 ordinary people and conducted a structural equation model analysis using AMOS 21.0 to verify the hypothesis. As a result of hypothesis testing, all hypotheses that luck in belief would have a positive effect on positive cognitive bias(self-enhancement bias, illusion of control bias, unrealism optimistic bias) were adopted. The hypothesis that positive cognitive bias(self-enhancement bias, illusion of control bias, unrealistic optimism bias) will have a positive effect on entrepreneurial self-efficacy was also adopted. Additional analysis was conducted to examine the mediating role of positive cognitive bias in the relationship between luck in belief and entrepreneurial self-efficacy, which showed that 'luck in belief→positive cognitive bias →entrepreneurial self-efficacy' were statistically significant. Through this, we confirmed the mediating effect of positive cognitive bias in the relationship between luck in belief and entrepreneurial self-efficacy. In the conclusion, the implications and limitations of the study were presented based on the results of this study.

• Atmosphere
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• v.18 no.3
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• pp.237-248
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• 2008

A thermal index which considers metabolic heat generation of human body is proposed for operational forecasting. The new thermal index, Perceived Temperature (PT), is forecasted using Weather Research and Forecasting (WRF) mesoscale model and validated. Forecasted PT shows the characteristics of diurnal variation and topographic and latitudinal effect. Statistical skill scores such as correlation, bias, and RMSE are employed for objective verification of PT and input meteorological variables which are used for calculating PT. Verification result indicates that the accuracy of air temperature and wind forecast is higher in the initial forecast time, while relative humidity is improved as the forecast time increases. The forecasted PT during 2007 summer is lower than PT calculated by observation data. The predicted PT has a minimum Root-Mean-Square-Error (RMSE) of $7-8^{\circ}C$ at 9-18 hour forecast. Spatial distribution of PT shows that it is overestimated in western region, while PT in middle-eastern region is underestimated due to strong wind and low temperature forecast. Underestimation of wind speed and overestimation of relative humidity have caused higher PT than observation in southern region. The predicted PT from the mesoscale model gives appropriate information as a thermal index forecast. This study suggests that forecasted PT is applicable to the prediction of health warning based on the relationship between PT and mortality.

• Nuclear Engineering and Technology
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• v.26 no.3
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• pp.367-373
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• 1994

It is necessary to adopt a simple signal validation for avoiding the complexity of algorithm and verification in the design process of the instrumentation and control system in nuclear plants. This paper suggests a signal validation method developed on the basis of consistency checking for the multi-channel measurement system without any analytic process model. It includes a simplified algorithm for estimating the fixed bias error of each channel and a weighted averaging method. The weighting factor of each channel is updated according to its calculated bias error. The developed method has been tested to verify its performance through several input scenarios.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.277-283
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• 2016

A high-precision force-feedback 3-axes accelerometer developed in Korea has been investigated and studied for the verification of feasibility in the computational analysis and health monitoring of civil infrastructures. Through a series of experiment, the nonlinearity, bandwidth, low-frequency signal measurement accuracy and bias characteristics of the accelerometer has been thoroughly compared to those of two accelerometers produced by two market leaders in domestic and global accelerometer market. The experiment results shows that the overall measurement performance of the accelerometer has superiority over the performance of the two accelerometers from global market leader companies. Especially, the accelerometer shows a better low-frequency signal measurement accuracy and constant bias characteristic, which are mostly required in the computational analysis and the long-term health monitoring of large-scale civil infrastructures.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.333-342
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• 2012

We studied the characteristics of spatial distribution of global wave height and carried out the modelsensitivity test by changing the input field, model resolution and physical factor (effective wind factor) since the spatial and temporal resolution in wind wave forecasting is one of most important factors. Comparisons among the different cases, and also between model, buoy and satellite data have been made. As a results of the wind-wave model run using the high resolution wind field, the bias of significant wave height showed the positive tendency and the Root-Mean Square Error(RMSE) was a bit decreased based on the comparison with buoy data. When the model resolution was changed to higher, the bias and RMSE was increased, and as the effective wind factor was smaller than default value(= 1.4) the bias and RMSE showed also decreasing pattern.

• Atmosphere
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• v.33 no.4
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• pp.423-440
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• 2023

The updated version of Global Ocean Data Assimilation and Prediction System (GODAPS) in the NIMS/KMA (National Institute of Meteorological Sciences/Korea Meteorological Administration), which has been in operation since December 2021, is being introduced. This technical note on GODAPS2 describes main progress and updates to the previous version of GODAPS, a software tool for the operating system, and its improvements. GODAPS2 is based on Forecasting Ocean Assimilation Model (FOAM) vn14.1, instead of previous version, FOAM vn13. The southern limit of the model domain has been extended from 77°S to 85°S, allowing the modelling of the circulation under ice shelves in Antarctica. The adoption of non-linear free surface and variable volume layers, the update of vertical mixing parameterization, and the adjustment of isopycnal diffusion coefficient for the ocean model decrease the model biases. For the sea-ice model, four vertical ice layers and an additional snow layer on top of the ice layers are being used instead of previous single ice and snow layers. The changes for data assimilation include the updated treatment for background error covariance, a newly added bias scheme combined with observation bias, the application of a new bias correction for sea level anomaly, an extension of the assimilation window from 1 day to 2 days, and separate assimilations for ocean and sea-ice. For comparison, we present the difference between GODAPS and GODAPS2. The verification results show that GODAPS2 yields an overall improved simulation compared to GODAPS.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2112-2124
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• 2023

With the rise of economic and safety standards for nuclear reactors, new concepts of Gen-IV reactors and modular reactors showed more complex designs that challenge current tools for reactor physics analysis. A Monte Carlo (MC) two-step method was proposed in this work. This calculation scheme uses the continuous-energy MC method to generate multi-group cross-sections from heterogeneous models. The multi-group MC method, which can adapt locally-heterogeneous models, is used in the core calculation step. This calculation scheme is verified using a Gen-IV modular lead-based fast reactor (LFR) benchmark case. The influence of homogenized patterns, scatter approximations, flux separable approximation, and local heterogeneity in core calculation on simulation results are investigated. Results showed that the cross-sections generated using the 3D assembly model with a locally heterogeneous representation of control rods lead to an accurate estimation with less than 270 pcm bias in core reactivity, 0.5% bias in control rod worth, and 1.5% bias on power distribution. The study verified the applicability of multi-group cross-sections generated with the MC method for LFR analysis. The study also proved the feasibility of multi-group MC in core calculation with local heterogeneity, which saves 85% time compared to the continuous-energy MC.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.832-839
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• 2009

Since construction of the estuarine barrage at the mouth of the Nakdong River, eutrophication and increased abundance of phytoplankton have occurred mainly due to the increased retention time in the reach. However, during the spring, there is a decrease in chlorophyll-a, as a result of an increase in zooplankton number, which preys upon phytoplankton and affects the value of chlorophyll-a. In order to emphasize the importance of zooplankton data in water quality simulation, zooplankton community data were used to simulate water quality and eutrophication at Mulgeum located in 27 km upstream from the barrage. WASP 7.2 was used as the water quality model for the river, using a monthly data set from 2003 to 2005 for model calibration and verification. The results showed that chlorophyll-a, DO, and total nitrogen in the river were simulated well during the verification period. The results of water quality simulation using zooplankton community data in the model were better than those with phytoplankton death rate, in terms of the absolute value of percent bias, root mean square error, and Nash-Sutcliffe efficiency. Those results indicate the use of zooplankton data provides more accurate simulation results for chlorophyll-a and eutrophication.