• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.217-223
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• 2014

With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

• Genomics & Informatics
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• v.7 no.3
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• pp.148-151
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• 2009

Generally, larger sample size leads to a greater statistical power to detect a significant difference. We may increase the sample size for both case and control in order to obtain greater power. However, it is often the case that increasing sample size for case is not feasible for a variety of reasons. In order to look at change in power as the ratio of control to case varies (1:1 to 4:1), we conduct association tests with simulated data generated by PLINK. The simulated data consist of 50 disease SNPs and 300 non-disease SNPs and we compute powers for disease SNPs. Genetic Power Calculator was used for computing powers with varying the ratio of control to case (1:1, 2:1, 3:1, 4:1). In this study, we show that gains in statistical power resulting from increasing the ratio of control to case are substantial for the simulated data. Similar results might be expected for real data.

• Nuclear Engineering and Technology
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• v.37 no.5
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• pp.491-502
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• 2005

Reliable human performance is a prerequisite in securing the safety of complicated process systems such as nuclear power plants. However, the amount of available knowledge that can explain why operators deviate from an expected performance level is so small because of the infrequency of real accidents. Therefore, in this study, a database that contains a set of useful information extracted from simulated emergencies was developed in order to provide important clues for understanding the change of operators' performance under stressful conditions (i.e., real accidents). The database was developed under Microsoft Windows TM environment using Microsoft Access $97^{TM}$ and Microsoft Visual Basic $6.0^{TM}$. In the database, operators' performance data obtained from the analysis of over 100 audio-visual records for simulated emergencies were stored using twenty kinds of distinctive data fields. A total of ten kinds of operators' performance data are available from the developed database. Although it is still difficult to predict operators' performance under stressful conditions based on the results of simulated emergencies, simulation studies remain the most feasible way to scrutinize performance. Accordingly, it is expected that the performance data of this study will provide a concrete foundation for understanding the change of operators' performance in emergency situations.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.353-358
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• 1998

GRASS-AGNPS model integrated with GIS was applied to rural watersheds having complex land use characteristics and evaluated for its applicability through calibration using observed data. The analyses of raster encoding accuracy and model behavior to runoff, sediment yields and nutrient loads for different cell-size showed that 150 m cell size indicated reasonable applicability of the model. Simulated runoff was in a good agreement with the observed data and simulated peak runoff rate was larger than the observed data. The sediment yield simulated by modified AGNPS model using irregular cell for forest area were less than that of the regular cell method. In predicting sediment yields, the result showed a different trend at each representative rural watershed. Nutrient loads simulated by the model were significantly different from the observed data.

• Atmosphere
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• v.22 no.4
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• pp.387-400
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• 2012

This study aims at examining the sensitivity of numerical simulations to the resolution of initial and boundary data, and to an application of WRF (Weather Research and Forecasting) 3DVAR (Three Dimension Variational data Assimilation). To do this, we ran the WRF model by using GDAS (Global Data Assimilation System) FNL (Final analyses) and the KLAPS (Korea Local Analysis and Prediction System) analyses as the WRF's initial and boundary data, and by using an initial field made by assimilating the radar data to the KLAPS analyses. For the sensitivity experiment, we selected a heavy rainfall case of 21 September 2010, where there was localized torrential rain, which was recorded as 259.5 mm precipitation in a day at Seoul. The result of the simulation using the FNL as initial and boundary data (FNL exp) showed that the localized heavy rainfall area was not accurately simulated and that the simulated amount of precipitation was about 4% of the observed accumulated precipitation. That of the simulation using KLAPS analyses as initial and boundary data (KLAPC exp) showed that the localized heavy rainfall area was simulated on the northern area of Seoul-Gyeonggi area, which renders rather difference in location, and that the simulated amount was underestimated as about 6.4% of the precipitation. Finally, that of the simulation using an initial field made by assimilating the radar data to the KLAPS using 3DVAR system (KLAP3D exp) showed that the localized heavy rainfall area was located properly on Seoul-Gyeonggi area, but still the amount itself was underestimated as about 29% of the precipitation. Even though KLAP3D exp still showed an underestimation in the precipitation, it showed the best result among them. Even if it is difficult to generalize the effect of data assimilation by one case, this study showed that the radar data assimilation can somewhat improve the accuracy of the simulated precipitation.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.933-939
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• 2009

The bivariate data in clinical research fields often has two types of failure times, which are mark variable for the first failure time and the final failure time. This paper showed how to generate bootstrap data to get Bayesian estimation for the joint distribution of bivariate survival times. The observed data was generated by Frank's family and the fake date is simulated with the Gamma prior of survival time. The bootstrap data was obtained by combining the mimic data with the observed data and the simulated fake data from the observed data.

• International Journal of High-Rise Buildings
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• v.8 no.2
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• pp.101-106
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• 2019

Assessing the energy performance of supertall buildings often does not consider variations in energy consumption due to the change of environmental conditions such as temperature, pressure, and wind speed associated with differing elevations. Some modelers account for these changing conditions by using a conventional temperature lapse rate, but not many studies confirm to the appropriateness of applying it to tall buildings. This paper presents and discusses simulated annual energy consumption results from a 600 m tall skyscraper floor plate located in Dubai, UAE, assessed using ground level weather data, a conventional temperature lapse rate of $6.5^{\circ}C/km$, and more accurate simulated 600 m weather data. A typical office floorplate, with ASHRAE 90.1-2010 standards and systems applied, was evaluated using the EnergyPlus engine through the OpenStudio graphical user interface. The results presented in this paper indicate that by using ground level weather data, energy consumption at the top of the building can be overestimated by upwards of 4%. Furthermore, by only using a lapse rate, heating energy is overestimated by up to 96% due to local weather phenomenon such as temperature inversion, which can only be conveyed using simulated weather data. In addition, sizing and energy consumption of fans, which are dependent both on wind and atmospheric pressure, are not accurately captured using a temperature lapse rate. These results show that that it is important, with the ever increasing construction of supertall buildings, to be able to account for variations in climatic conditions along the height of the building. Adequately modeling these conditions using simulated weather data will help designers and engineers correctly size mechanical systems, potentially decreasing overall building energy consumption, and ensuring that these systems are able to provide the necessary indoor conditions to maintain occupant comfort levels.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• The KSFM Journal of Fluid Machinery
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• v.9 no.6 s.39
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• pp.22-28
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• 2006

Operation of a microturbine was simulated on the basis of component characteristic parameters obtained from performance test. Characteristic parameters, such as compressor and turbine efficiencies, recuperator effectiveness as well as turbine inlet temperature, were obtained for a wide operation range. Component characteristics including performance maps and characteristic curves were generated using measured data. Based on the component characteristics, a simulation program was constructed and operation of the microturbine was simulated, and the simulated results were compared with the measured data to verify the program. Also, influence of variation in the power control scheme on the operating characteristic and performance of the engine was simulated. The simulation program can be used for predicting operation of both healthy and degraded engine conditions.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.87-92
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• 2002

By using the signal error test, model structure of total antilock braking system consisting of electromagnetic system and hydraulic system is determined as 9th order system. For determining parameters of the ABS, using time discrete model of parametric method, parameters in time discrete model are searched by least square method. By bilinear transform, we have found the model of ABS in s domain. Afterward, experimental output data is compared with simulated output data by MATLAB haying identified parameter. As the result, experimental data is agreed with simulated data very well.