• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.5 no.1
• /
• pp.29-33
• /
• 2004

In this paper, I'm tying to define the connection of the Device Characteristics and the Error Terms, and yield maximum estimated value of the mismatching errors by modeling the individual devices with signal-flow graph, and by seeking the transfer function of the system with the mismatching error in the combination of the devices using the Signal-flow Graph Gain Formula.

• KIISE Transactions on Computing Practices
• /
• v.22 no.11
• /
• pp.559-566
• /
• 2016

Excel is a commercially available computer program that is used worldwide. Excel is widely utilized; it is helpful in household ledgers, corporate tax calculations, management of academic grades or reports, etc. However from the beginning, inaccuracies and errors in calculations have constantly been identified, so the program is updated regularly. Decimal-to-binary conversion is a simple and repetitive task. So, use of a computer program to do this calculation is suitable. Errors in decimal-to-binary conversion are surprising and are not easily understood. Therefore, it is important to identify the flaws in Excel, which unfortunately still exist today. It is necessary to determine the cause of this type of error, and I hope for a fix to be implemented quickly.

• Journal of the Korea Safety Management & Science
• /
• v.18 no.1
• /
• pp.141-145
• /
• 2016

This study was to improve to utilization of non dosimetry measurements for X-ray radiography. Experiments was passed off varying the X-ray tube voltage and the thickness of the aluminum filter by actual dose. Calculated results was set to the first beam quality factors, calculated first correction coefficient by the Microsoft Excel program was set as the second beam quality factors. To make the non dosimetry measurements simply, the Excel program apply to the new beam quality factors, the error was compared to the previous studies, and the results verify the calculated value of smaller errors.

• Knowledge Management Research
• /
• v.13 no.2
• /
• pp.37-52
• /
• 2012

A spreadsheet is a office automation software which has been widely used in almost all areas in business. A spreadsheet is used for calculation, data analysis, model building and so on. As a result, spreadsheet is a very important tool for generating knowlege in a firm. Errors in a spreadsheet model can cause a serious financial damage in a corporation. However in Korea few researches for reducing errors have been performed. Neither serious efforts to reduce errors have been executed by corporations. In this research we provided summarized the results from a survey for spreadsheet usage, summarized researches on errors in spreadsheet up to now, and suggested a rules and structured development method for reducing errors in a spreadsheet. Errors in spreadsheets are prevalent. To solve this serious problem, we need much more attention on this problem in research area. Corporations must put more efforts on setting policies and rules. And also we need the government's concern and support.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.20 no.2
• /
• pp.69-74
• /
• 2016

Purpose Using a regression formula of the trendline near the coefficient of determination (R2) "1" by substituting the dependent variable of the standard curve to calculate the values of the independent variable. To determine the suitability of a regression equation by comparing the difference between the independent variables of the standard curve and the predicted independent variables. Materials and Methods Perkin Elmer Gamma-Counter machine was used for Standard curve of regression methods. TSH. TG-Ag (Thyroglobulin Antigen), Insulin that used materials and method test to compare the result from the Excel trendline of the regression formula. Results Each of the value of coefficient of determination ($R^2$) and Trendline $R^2=1$, Polynomial Trendline for TSH, $R^2=1$, Polynomial Trendline for TG-Ag, $R^2=0.9994$, Polynomial Trendline for Insulin. Conclusion We confirmed that IRMA immune method is found to the nearest trends elected a standard curve using polynomial trendline. The independent variables to predict the trend by using a polynomial trendline formula containing the error was a limitation.

• Journal of Korean Society of Water and Wastewater
• /
• v.28 no.6
• /
• pp.735-745
• /
• 2014

This paper presents PKES(PuKyung -Excel based Simulator) for WWTPs(wastewater treatment plants) by using MS Excel and VBA(Visual Basic for Application). PKES is a user-friendly simulator for the design and optimization of the whole plant including biological and physico-chemical processes for the wastewater and sludge treatment. PKES calculates the performance under steady or dynamic state and allows changing the mathematical model by the user. Mathematical model implemented in PKES is a improved integration model based on ASM2d and ADM1 for simulation of AS(activated sludge) and AD(anaerobic digestion). Gaseous components of $N_2$, $N_2O$, $CO_2$ and $CH_4$ are added for estimation of GHGs(greenhouse gases) emission. The simulation results for comparison between PKES and Aquasim(EAWAG) showed about the same effluent concentrations. As a result of verification using by measured data of BOD, TSS, TN and TP for 2 years of operation, calculated effluent concentrations were similar to measured effluent concentrations. The values of average RMSE(root mean square error) were 1.9, 0.8, 1.6 and 0.2 mg/L for BOD, TSS, TN and TP, respectively. Total GHGs emission of WWTP calculated by PKES was 138.5 ton-$CO_2$/day and GHGs emissions of $N_2O$, $CO_2$ and $CH_4$ were calculated at 21.7, 28.9 and 87.9 ton-$CO_2$/day, respectively. GHGs emission of activated sludge was 32.5 % and that of anaerobic digestion was 67.5 %.

• Journal of Educational Research in Mathematics
• /
• v.15 no.1
• /
• pp.75-105
• /
• 2005

This study explored a mathematical modeling flow and the effect of interactions among students and between a student and Excel on modeling in a small group modeling environment with Excel. This is a case study of three 8th graders' modeling activity using Excel during their extra lessons. The conclusions drawn from this study are as follows: First, small group modeling using Excel was formed by formulating 4∼10 modeling cycles in each task. Students mainly formed tables and graphs and refined and simplified these models. Second, students mainly formed tables, algebraic formulas and graphs and refined tables considering each variable in detail by obtaining new data with inserting rows. In tables, students mainly explored many expected cases by changing the values of the parameters. In Graphs, students mainly identified a solution or confirmed the solution founded in a table. Meanwhile, students sometimes constructed graphs without a purpose and explored the problem situations by graphs mainly as related with searching a solution, identifying solutions that are found in the tables. Thus, the teacher's intervention is needed to help students use diverse representations properly in problem situations and explore floatingly and interactively using multi-representations that are connected numerically, symbolically and graphically. Sometimes students also perform unnecessary activities in producing data by dragging, searching a solution by 'trial and error' and exploring 'what if' modeling. It is considered that these unnecessary activities were caused by over-reliance on the Excel environment. Thus, the teacher's intervention is needed to complement the Excel environment and the paper-and-pencil environment properly.

• Journal of Environmental Science International
• /
• v.26 no.4
• /
• pp.421-432
• /
• 2017

In this study, we examined the suitability of ten disinfection models for predicting the inactivation of Artemia sp. via single or combined physical and chemical treatments. The effect of Hydraulic Retention Time (HRT) on the inactivation of Artemia sp. was examined experimentally. Disinfection models were fitted to the experimental data by using the GInaFiT plug-in for Microsoft Excel. The inactivation model were evaluated on the basis of RMSE (Root Mean Square Error), SSE (mean Sum Square Error) and $r^2$. An inactivation model with the lowest RMSE, SSE and $r^2$ close to 1 was considered the best. The Weibull+Tail model was found to be the most appropriate for predicting the inactivation of Artemia sp. via electrolytic treatment and electrolytic-ultrasonic combined treatment. The Log-linear+Tail model was the most appropriate for modeling inactivation via homogenization and combined electrolytic-homogenization treatment. The double Weibull disinfection model was the most suitable for the predicting inactivation via ultrasonic treatment.

• Journal of the Korea Society for Simulation
• /
• v.23 no.4
• /
• pp.21-29
• /
• 2014

In general, a simulation project requires much time and money since we should develop a model that works similarly to the system at a level consistent with the project purposes. Therefore, more active research studies are required to reduce the time needed for the modeling process. This is achievable by minimizing the possible trial and error during the model development process through the appropriate conceptual model design and the automated generation of the simulation model. This paper presents a tool automatically generating an Arena model after developing a conceptual simulation model. Because our proposed tool is based on the popular Microsoft Excel and Visio, it is expected to be practically used at many industrial sites. Finally, we showed the effectiveness of the newly suggested tool by applying it to an imaginary simulation project.

• Journal of Environmental Science International
• /
• v.24 no.11
• /
• pp.1393-1404
• /
• 2015

Ten empirical disinfection models for the plasma process were used to find an optimum model. The variation of model parameters in each model according to the operating conditions (first voltage, second voltage, air flow rate, pH, incubation water concentration) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Phytophthora capsici which cause wilt in tomato plantation. Optimum disinfection models were chosen among ten models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), $r^2$ values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum models were shown as Log-linear+Tail model, Double Weibull model and Biphasic model. Three models were applied to the experimental data according to the variation of the operating conditions. In Log-linear+Tail model, $Log_{10}(N_o)$, $Log_{10}(N_{res})$ and $k_{max}$ values were examined. In Double Weibull model, $Log_{10}(N_o)$, $Log_{10}(N_{res})$, ${\alpha}$, ${\delta}_1$, ${\delta}_2$, p values were calculated and examined. In Biphasic model, $Log_{10}(N_o)$, f, $k_{max1}$ and $k_{max2}$ values were used. The appropriate model parameters for the calculation of optimum operating conditions were $k_{max}$, ${\alpha}$, $k_{max1}$ at each model, respectively.