• Journal of radiological science and technology
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• v.45 no.5
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• pp.397-405
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• 2022

Computed radiography (CR) systems, which convert an analog signal recorded on a cassette into a digital image, combine the characteristics of analog and digital imaging systems. Compared to digital radiography (DR) systems, CR systems have presented difficulties in evaluating system performance because of their lower detective quantum efficiency, their lower signal-to-noise ratio (SNR), and lower modulation transfer function (MTF). During the step of energy-storing and reading out, a baseline offset occurs in the edge area and makes low-frequency overestimation. The low-frequency offset component in the line spread function (LSF) critically affects the MTF and other image-analysis or qualification processes. In this study, we developed the method of baseline correction using mathematical morphology to determine the LSF and MTF of CR systems accurately. We presented a baseline correction that used a morphological filter to effectively remove the low-frequency offset from the LSF. We also tried an MTF evaluation of the CR system to demonstrate the effectiveness of the baseline correction. The MTF with a 3-pixel structuring element (SE) fluctuated since it overestimated the low-frequency component. This overestimation led the algorithm to over-compensate in the low-frequency region so that high-frequency components appeared relatively strong. The MTFs with between 11- and 15-pixel SEs showed little variation. Compared to spatial or frequency filtering that eliminated baseline effects in the edge spread function, our algorithm performed better at precisely locating the edge position and the averaged LSF was narrower.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.5
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• pp.27-39
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• 2022

The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimate control can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better control of indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal air temperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climate and ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. The results indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99 and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracy with the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematical descriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction performances compared to the black-box machine learning models. Therefore, it was proven to be useful for intelligent microclimate control which would be developed in future studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.433-437
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• 2006

Recently, mathematical modeling for the activated sludge process is important to design and control of wastewater treatment plant. Nevertheless, there is a lack of information regarding the pathway of substrate utilization between external and internal substrates in biological nutrient removal (BNR). In this research, a new activated sludge model (step growth model) is proposed and compare with ASM No.3. This model structure is consist of five processes; aerobic storage, growth on external substrate and stored intercellular storage compounds (ISCs), endogenous respiration and aerobic respiration of ISCs. The predicted results by the step growth model were more good accordance with the results of oxygen utilization rate (OUR) and TCOD experiment than that of the ASM No.3.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.697-708
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• 2008

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems, or external events. The advanced measurement approach proposed by Basel committee uses loss distribution approach(LDA) which quantifies operational loss based on bank's own historical data and measurement system. LDA involves two distribution fittings(frequency and severity) and then generates aggregate loss distribution by employing mathematical convolution. An objective validation for the operational risk measurement is essential because the operational risk measurement allows flexibility and subjective judgement to calculate regulatory capital. However, the methodology to verify the soundness of the operational risk measurement was not fully developed because the internal operational loss data had been extremely sparse and the modeling of extreme tail was very difficult. In this paper, we propose a methodology for the validation of operational risk measurement based on bootstrap confidence intervals of operational VaR(value at risk). We derived two methods to generate confidence intervals of operational VaR.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1639-1645
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• 1991

Because of the important role LD converters play in the production of high quality steel, various dynamic models have been attempted in the past by many researchers not only to understand the complex chemical reactions that take place in the converter process but also to assist the converter operation itself using computers. And yet no single dynamic model was found to be completely satisfactory because of the complexity involved with the process. The process indeed involves dynamic energy and mass balances at high temperatures accompanied by complex chemical reactions and transport phenomena in the molten state. In the present study, a mathematical model describing the dynamic behavior of LD converter process has been developed. The dynamic model describes the time behavior of the temperature and the concentrations of chemical species in the hot metal bath and slag. The analysis was greatly facilitated by dividing the entire process into three zones according to the physical boundaries and reaction mechanisms. These three zones were hot metal (zone 1), slag (zone 2) and emulsion (zone 3) zones. The removal rate of Si, C, Mn and P and the rate of Fe oxidation in the hot metal bath, and the change of composition in the slag were obtained as functions of time, operating conditions and kinetic parameters. The temperature behavior in the metal bath and the slag was also obtained by considering the heat transfer between the mixing and the slag zones and the heat generated from chemical reactions involving oxygen blowing. To identify the unknown parameters in the equations and simulate the dynamic model, Hooke and Jeeves parttern search and Runge-Kutta integration algorithm were used. By testing and fitting the model with the data obtained from the operation of POSCO #2 steelmaking plant, the dynamic model was able to predict the characteristics of the main components in the LD converter. It was possible to predict the optimum CO gas recovery by computer simulation

• The Journal of Engineering Geology
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• v.23 no.4
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• pp.381-387
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• 2013

In compiling flood hazard maps for the case of dam-failure, a scenario-based numerical modeling approach is commonly used, involving the modeling of important parameters that capture peak discharge, such as breach formation and progress. In this study, an earth-dam-break model is constructed assuming an identical mechanism and hydraulic process for all dam-break processes. A focus of the analysis is estimation of the hydrograph at the outlet as a function of time. The constructed hydrograph then serves as an upper boundary condition in running the flood routing model downstream, although flood routing is not considered here. Validation was performed using the record of the Tangjishan dam-break in China. The results were satisfactory, with a coefficient of determination of 0.974, Nash-Sutcliffe Coefficient of Efficiency (NSC) of 0.94, and Root Mean Square Error (RMSE) of $610m^3/sec$. The proposed model will contribute to assessments of potential flood hazards caused by dam-break.

• Education of Primary School Mathematics
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• v.11 no.2
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• pp.121-139
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• 2008

This study analyzed problem presenting and solving activities in elementary school mathematics class to enhance insights of teachers in class for providing real meaning of learning. Following research problems were selected to provide basic information for improving to sound student oriented lesson rather than teacher oriented lessons. Protocols were made based on video information of 5th grade elementary school 'Na' level figure and measurement area 3. Congruence of figures, 4. Symmetry of figures, and 6. Areas and weight. Protocols were analyzed with numbering, comment, coding and categorizing processes. This study is an qualitative exploratory research held toward three teachers of 5th grade for problem solving activities analysis in problem presenting method, opportunity to providing method to solve problems and teachers' behavior in problem solving activities. Following conclusions were obtained through this study. First, problem presenting method, opportunity providing method to solve problems and teachers' behavior in problem solving activities were categorized in various types. Second, Effective problem presenting methods for understanding in mathematics problem solving activities are making problem solving method questions or explaining contents of problems. Then the students clearly recognize problems to solve and they can conduct searches and exploratory to solve problems. At this point, the students understood fully what their assignments were and were also able to search for methods to solve the problem. Third, actual opportunity providing method for problem solving is to provide opportunity to present activities results. Then students can experience expressing what they have explored and understood during problem solving activities as well as communications with others. At this point, the students independently completed their assignments, expressed their findings and understandings in the process, and communicated with others. Fourth, in order to direct the teachers' changes in behaviors towards a positive direction, the teacher must be able to firmly establish himself or herself as a teaching figure in order to promote students' independent actions.

• Journal of Gifted/Talented Education
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• v.15 no.2
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• pp.35-57
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• 2005

As the results of studies based on the Russian Activities-Oriented Theory, the gifted students in many fields have common insights for the true nature of the problem, or the actual state. From Russian Activities-Oriented Theory of view, gifted students have the ability to discern the essential elements involved in each actual state and change of state of things, and to solve the problem, based on these elements. Enhancing these abilities of the students, the educator can develop the average student into a gifted one. This study result of the Russian specialist suggests the possibility of a stream of education that can develop gifted students. Hence, this paper discussed the points and processes of formation of the Russian Activities-Oriented Theory, and inquired on what is the true nature of the problem or the meaning of actual state and how it affects the studies of the student. The paper also investigated the actual conditions of wrong learning about some mathematical concepts and discussed the role of insights to the true nature of the problem in the learning process of the student.

• Journal of Information Display
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• v.12 no.3
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• pp.145-152
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• 2011

Since the discovery of fullerenes as a class of nanostructure compounds, many potential applications have been suggested for their unusual structures and properties. The isolated pentagon rule (IPR) states that all pentagonal carbon rings are isolated in the most stable fullerene. Fullerenes $C_n$ are a class of spherical carbon allotrope group with unique properties. Electron transfer between fullerenes and other molecules is thought to involve the transfer of electrons between the molecules surrounding the fullerene cage. One class of electron transfer molecules is the methanofullerene derivatives ([6,6]-phenyl $C_{61}$-butyric acid methyl ester (PCBM), 4-(2-ethylhexyloxy)-[6,6]-phenyl $C_{61}$-butyric acid methyl ester (p-EHO-PCBM), and 4-(2-ethylhexyloxy)-[6,6]-phenyl $C_{61}$-butyric acid (p-EHO-PCBA), 10-12). It has been determined that $C_{60}$ does not obey IPR. Supramolecular complexes 1-9 and 10-12 are shown to possess a previously unreported host.guest interaction for electron transfer processes. The unsaturated, cis-geometry, thiocrown ethers, (1-9) (described as [X-UT-Y], where X and Y indicate the numbers of carbon and sulfur atoms, respectively), are a group of crown ethers that display interesting physiochemical properties in the light of their conformational restriction compared with a corresponding saturated system, as well as the sizes of their cavities. Topological indices have been successfully used to construct mathematical methods that relate structural data to various chemical and physical properties. To establish a good relationship between the structures of 1-9 with 10-12, a new index is introduced, ${\mu}_{cs}$. This index is the ratio of the sum of the number of carbon atoms ($n_c$) and the number of sulfur atoms ($n_s$) to the product of these two numbers for 1-9. In this study, the relationships between this index and oxidation potential ($^{ox}E_1$) of 1-9, as well as the first to third free energies of electron transfer (${\Delta}G_{et(n)}$, for n = 1-3, which is given by the Rehm-Weller equation) between 1-9 and PCBM, p-EHO-PCBM, and p-EHO-PCBA (10-12) as [X-UT-Y]@R(where R is the adduct PCBM, p-EHO-PCBM, and p-EHO-PCBA group) (13-15) supramolecular complexes are presented and investigated.