• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.81-86
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• 2019

In X-ray image, the role of filtration through the filter is to reduce the exposure of the patient by using photon which is useful in formation of the image, and at the same time, enhance the contrast of the image. During interaction between photon and object, low energy X-rays are absorbed from the site of a few cm of the first patient's tissue, and high energy X-rays are the one which form the image. Therefore, the radiation filter absorbs low energy X-ray in order to lower the exposure of the patient and improve the quality of the image. The purpose of this study is to compare the effect on the image quality by differences of added filter through simulation image and actual radiation image. For that purpose, we used Geant4 Application for Tomographic Emission (GATE) as a tool for Monte Carlo simulation. We set actual size, shape and material of Polymethylmethacrylate (PMMA) Phantom on GATE and differentiated the parameter of added filter. Also, we took image of PMMA phantom with same parameter of added filter by digital radiography (DR). Than we performed contrast-to-noise ratio (CNR) evaluation on both simulation image and actual DR image by Image J. Finally, we observed the effect on image quality due to different thickness of added filter, and compared two images' CNR evaluation's transitions of change. The result of this experiment showed decreasing in the progress of CNR on both DR and simulation image. It is ultimately caused by decreasing in contrast on image. In theory, contrast decrease with kVp increased. Given that condition, this study found out that filter makes not only decreasing total dose by absorbing low energy of X-ray, but also increasing average energy of X-ray.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.157-175
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• 2012

It is difficult to evaluate the performance of process innovation of e-procurement which has large scale and complex processes. The existing evaluation methods for measuring the effects of process innovation have been mainly done with statistically quantitative methods by analyzing operational data or with qualitative methods by conducting surveys and interviews. However, these methods have some limitations to evaluate the effects because the performance evaluation of e-procurement process innovation should consider the interactions among participants who are active either directly or indirectly through the processes. This study considers the e-procurement process as a complex system and develops a simulation model based on MAS(Multi-Agent System) to evaluate the effects of e-procurement process innovation. Multi-agent based simulation allows observing interaction patterns of objects in virtual world through relationship among objects and their behavioral mechanism. Agent-based simulation is suitable especially for complex business problems. In this study, we used Netlogo Version 4.1.3 as a MAS simulation tool which was developed in Northwestern University. To do this, we developed a interaction model of agents in MAS environment. We defined process agents and task agents, and assigned their behavioral characteristics. The developed simulation model was applied to G2B system (KONEPS: Korea ON-line E-Procurement System) of Public Procurement Service (PPS) in Korea and used to evaluate the innovation effects of the G2B system. KONEPS is a successfully established e-procurement system started in the year 2002. KONEPS is a representative e-Procurement system which integrates characteristics of e-commerce into government for business procurement activities. KONEPS deserves the international recognition considering the annual transaction volume of 56 billion dollars, daily exchanges of electronic documents, users consisted of 121,000 suppliers and 37,000 public organizations, and the 4.5 billion dollars of cost saving. For the simulation, we analyzed the e-procurement of process of KONEPS into eight sub processes such as 'process 1: search products and acquisition of proposal', 'process 2 : review the methods of contracts and item features', 'process 3 : a notice of bid', 'process 4 : registration and confirmation of qualification', 'process 5 : bidding', 'process 6 : a screening test', 'process 7 : contracts', and 'process 8 : invoice and payment'. For the parameter settings of the agents behavior, we collected some data from the transactional database of PPS and some information by conducting a survey. The used data for the simulation are 'participants (government organizations, local government organizations and public institutions)', 'the number of bidding per year', 'the number of total contracts', 'the number of shopping mall transactions', 'the rate of contracts between bidding and shopping mall', 'the successful bidding ratio', and the estimated time for each process. The comparison was done for the difference of time consumption between 'before the innovation (As-was)' and 'after the innovation (As-is).' The results showed that there were productivity improvements in every eight sub processes. The decrease ratio of 'average number of task processing' was 92.7% and the decrease ratio of 'average time of task processing' was 95.4% in entire processes when we use G2B system comparing to the conventional method. Also, this study found that the process innovation effect will be enhanced if the task process related to the 'contract' can be improved. This study shows the usability and possibility of using MAS in process innovation evaluation and its modeling.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.7
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• pp.523-528
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• 2020

A lateral type MEMS inertial switch was designed on the same principle as spring-mass system. The MEMS switch is used for arming mechanism of the arm-fire device by sensing the applied acceleration. We analyzed the switching capability of the MEMS switch under various acceleration conditions via performance model. Simulation results showed that the MEMS switch works very well at 10 g when the applied acceleration slope does not exceed 10 g/msec. On the other hand, the threshold operating acceleration level simulation exceeded the requirement (10±2 g) due to the width and length of the spring by considering 10% tolerance of the design values. Design modification of doubling the width of the spring, which is difficult to reduce less than 10% tolerance in fabrication process, was proposed after confirming the simulation results comply the requirement.

• The Journal of Engineering Geology
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• v.24 no.4
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• pp.511-523
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• 2014

Limit equilibrium analysis and finite difference analysis were used to evaluate slope stability in the in Gohan, Korea, which is affected by large-scale tensile cracks and uplift. There is a thick colluvial layer in the study area and predicting ground behavior is problematic because the presence of clay makes it difficult to determine the strength parameters of the soil. Consequently, a numerical model able to reflect the collapse properties of the site was required that applied the modified boundary layer model and calculated the strength parameters using back analysis. The numerical simulation results that consider the strength parameter one does with the present situation the establishment of the pile is completed, and the simulation is able to asses ground stability in complex terrain in a reliable manner. Also the somewhat it judges with the fact that it will be able to provide the fundamental data which secures the stability of the segment where it is unstable.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.6
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• pp.30-36
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• 2011

The current test methods are insufficient to evaluate and ensure the safety and reliability of vehicle system for all possible dynamic situation including the worst case such as rollover, spin-out and so on. Although the known NHTSA Sine with dwell steering maneuvers are applied for the vehicle performance assessment, they aren't enough to estimate other possible worst case scenarios. Therefore, it is crucial for us to verify the various worst cases including the existing severe steering maneuvers. This paper includes useful worst case based upon the existing worst case scenarios mentioned above and worst case evaluation for vehicle dynamic controller in simulation basis and UCC HILS. The only human steering angle is selected as a design parameter here and optimized to maximize the index function to be expressed in terms of both yaw rate and side slip angle. The obtained scenarios were enough to generate the worst case to meet NHTSA worst case definition. It has been concluded that the new procedure in this paper is adequate to create other feasible worst case scenarios for a vehicle dynamic control system.

• Journal of radiological science and technology
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• v.44 no.5
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• pp.459-464
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• 2021

The detector performance is important role in acquiring the gamma rays from patients. Among parameters of detector performances, there is density, which relates to respond to gamma rays. Therefore, we confirm the detection efficiency according to various detector materials based on the density parameter using GATE (geant4 application for emission tomography) simulation tool. The NaI (density: 3.67 g/cm³), CZT (Cadimium Zinc Telluride) (density: 5.80 g/cm³), CdTe (Cadmium Telluride) (5.85 g/cm³), and GAGG (Gadoinium Aluminum Gallium Garnet) (density g/cm³) were used as detector materials. In addition, the point source and quadrant bar phantom, which is modeled for 0.5, 1.0, 1.5, and 2.0 mm thicknesses, were modeled to confirm the quatitative analysis using sensitivity (cps/MBq) and the full width at half maximum (FWHM, mm) at the 2.0 mm bar thickness containing visual evaluation. Based on the results, the sensitivity for NaI, CZT, CdTe, and GAGG detector materials were 0.12, 0.15, 0.16, and 0.18 cps/MBq. In addition, the FWHM for quadrant bar phantom in the 2.0 mm bar thickness is 3.72, 3.69, 3.70, and 3.73 mm for NaI, CZT, CdTe, and GAGG materials, respectively. Compared with performance of detector materials according to density, the high density can improve detection efficiency in terms of sensitivity and mean count. Among these detector materials, the GAGG material is efficient for detection of gamma rays.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.77-86
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• 2018

For the past few years, KISTI has been servicing an online simulation execution platform, called EDISON, allowing users to conduct simulations on various scientific applications supplied by diverse computational science and engineering disciplines. Typically, these simulations accompany large-scale computation and accordingly produce a huge volume of output data. One critical issue arising when conducting those simulations on an online platform stems from the fact that a number of users simultaneously submit to the platform their simulation requests (or jobs) with the same (or almost unchanging) input parameters or files, resulting in charging a significant burden on the platform. In other words, the same computing jobs lead to duplicate consumption computing and storage resources at an undesirably fast pace. To overcome excessive resource usage by such identical simulation requests, in this paper we introduce a novel framework, called IceSheet, to efficiently manage simulation data based on execution metadata, that is, provenance. The IceSheet framework captures and stores each provenance associated with a conducted simulation. The collected provenance records are utilized for not only inspecting duplicate simulation requests but also performing search on existing simulation results via an open-source search engine, ElasticSearch. In particular, this paper elaborates on the core components in the IceSheet framework to support the search and reuse on the stored simulation results. We implemented as prototype the proposed framework using the engine in conjunction with the online simulation execution platform. Our evaluation of the framework was performed on the real simulation execution-provenance records collected on the platform. Once the prototyped IceSheet framework fully functions with the platform, users can quickly search for past parameter values entered into desired simulation software and receive existing results on the same input parameter values on the software if any. Therefore, we expect that the proposed framework contributes to eliminating duplicate resource consumption and significantly reducing execution time on the same requests as previously-executed simulations.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1011-1027
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• 2010

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.217-217
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• 2015

The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1180-1193
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• 2023

Most carcass and meat quality traits are moderate to highly heritable, indicating that they can be improved through selection. Genetic evaluation for these types of traits is performed using performance data obtained from commercial and progeny testing evaluation. The performance data from commercial farms are available in large volume, however, some drawbacks have been observed. The drawback of the commercial data is mainly due to sorting of animals based on live weight prior to slaughter, and this could lead to bias in the genetic evaluation of later measured traits such as carcass traits. The current study has two components to address the drawback of the commercial data. The first component of the study aimed to estimate genetic parameters for carcass and meat quality traits in Korean Hanwoo cattle using a large sample size of industry-based carcass performance records (n = 469,002). The second component of the study aimed to describe the impact of sorting animals into different contemporary groups based on an early measured trait and then examine the effect on the genetic evaluation of subsequently measured traits. To demonstrate our objectives, we used real performance data to estimate genetic parameters and simulated data was used to assess the bias in genetic evaluation. The results of our first study showed that commercial data obtained from slaughterhouses is a potential source of carcass performance data and useful for genetic evaluation of carcass traits to improve beef cattle performance. However, we observed some harvesting effect which leads to bias in genetic evaluation of carcass traits. This is mainly due to the selection of animal based on their body weight before arrival to slaughterhouse. Overall, the non-random allocation of animals into a contemporary group leads to a biased estimated breeding value in genetic evaluation, the severity of which increases when the evaluation traits are highly correlated.