• Computers and Concrete
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• v.9 no.3
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• pp.179-193
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• 2012

The hydration of cement contributes to the performance characteristics of concrete, such as strength and durability. In order to improve the utilization efficiency of cement and its early properties, the particle size distribution (PSD) of cement varies considerably, and the effects of the particle size distribution of cement on the hydration process should be considered. In order to evaluate effects of PSD separately, experiments testing the isothermal heat generated during the hydration of cements with different particle size distributions but the same chemical composition have been carried out. The measurable hydration depth for cement hydration was proposed and deduced based on the experimental results, and a PSD hydration model was developed in this paper for simulating the effects of particle size distribution on the hydration process of cement. First, a reference hydration rate was derived from the isothermal heat generated by the hydration of ordinary Portland cement. Then, the model was extended to take into account the effect of water-to-cement ratio, hereinafter which was referred to as PSD hydration model. Finally, the PSD hydration model was applied to simulate experiments measuring the isothermal heat generated by the hydration of cement with different particle size distributions at different water-to-cement ratios. This showed that the PSD hydration model had simulated the effects of particle size distribution and water-to-cement ratio on the hydration process of cement with satisfactory accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.145-153
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• 2015

This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density

• The Journal of Information Systems
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• v.28 no.1
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• pp.133-153
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• 2019

Purpose The purpose of this study is to design a regional electricity planning model rather than the existing single region ones and verify its usefulness. The regional electricity planning model is to determine both electricity distribution among regions and power plant planning at the same time satisfying regional demands and distribution networks. Design/methodology/approach This study made a regional electricity planning model by integrating power plant planning and electricity distribution among regions. The regional electricity planning model is formulated into a linear programming problem, and coded and run using the OSeMOSYS, one of open source energy systems. Findings According to the empirical analysis result, this study confirmed that the regional electricity planning model proposed in this study deducts the unfairness among regions in view of electricity and green house gas. In addition, the model is expected to be used in evaluating and developing the national policies concerning fine dust and/or green house gas.

• Computers and Concrete
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• v.33 no.2
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• pp.147-162
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• 2024

This study presents a random-aggregate mesoscale model integrating the random distribution of the coarse aggerates and the damage mechanics of the mortar and interfacial transition zone (ITZ). This mesoscale model can generate the random distribution of the coarse aggregates according to the prescribed particle size distribution which enables the automation of the current methodology with different coarse aggregates' distribution. The main innovation of this work is to propose the "correction factor" to eliminate the dimensionally dependent mesh sensitivity of the concrete damaged plasticity (CDP) model. After implementing the correction factor through the user-defined subroutine in the randomly meshed mesoscale model, the predicted fracture resistance is in good agreement with the average experimental results of a series of geometrically similar single-edge-notched beams (SENB) concrete specimens. The simulated cracking pattern is also more realistic than the conventional concrete material models. The proposed random-aggregate mesoscale model hence demonstrates its validity in the application of concrete fracture failure and statistical size effect analysis.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.274-281
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• 2019

Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.159-170
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• 2005

This paper presents the design and development of a scaled down physical model for power Distribution Automation (DA) system simulation. The developed DA system simulator is useful in providing hands-on experience to utility engineers / managers to familiarize with the DA system and gain confidence in managing the power distribution system from the computer aided distribution control center. The distribution automation system simulator can be effectively used to carry out further research work in this area. This also helps the undergraduate and graduate students to understands the power distribution automation technology in the laboratory environment. The developed DA simulator has become an integral part of a distribution automation lab in the Electrical Engineering Department at Indian Institute of Technology Kanpur in India.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.797-805
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• 2012

Many circular distributions are known to be not only asymmetric but also bimodal. Hidden truncation method of generating asymmetric distribution is applied to a bivariate circular distribution to generate an asymmetric circular distribution. While many other existing asymmetric circular distributions can only model an asymmetric data, this new circular model has great flexibility in terms of asymmetry and bi-modality. Some properties of the new model, such as the trigonometric moment generating function, and asymptotic inference about the truncation parameter are presented. Simulation and real data examples are provided at the end to demonstrate the utility of the novel distribution.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.645-650
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• 2018

Software stability is the possibility of operating without any malfunction in the operating environment over time. In a finite failure NHPP for software failure analysis, the failure occurrence rate may be constant, monotonically increasing, or monotonically decreasing. In this study, based on the NHPP model and based on the software failure time data, we compared and analyzed the attributes of the software development cost model using the exponential distribution Rayleigh distribution and inverse exponential distribution considering the shape parameter of the Weibull distribution as the life distribution. The results of this study show that the Rayleigh model is the fastest release time and has the economic cost compared to the inverse-exponential model and the Goel-Okumoto model. Using the results of this study, it can be expected that software developers and operators will be able to predict the optimal release time and economic development cost.

• Journal of Distribution Science
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• v.20 no.6
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• pp.1-10
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• 2022

Purpose: This research proposes a new modified Recency-Frequency-Monetary (RFM) model by extending the model with spatial analysis for supporting decision-makers in discovering the promotional target market. Research design, data and methodology: This quantitative research utilizes data-mining techniques and the RFM model to cluster a university's provider schools. The RFM model was modified by adapting its variables to the university's marketing context and adding a district's potential (D) variable based on heatmap analysis using Geographic Information System (GIS) and K-means clustering. The K-prototype algorithm and the Elbow method were applied to find provider school clusters using the proposed RFM-D model. After profiling the clusters, the target segment was assigned. The model was validated using empirical data from an Indonesian university, and its performance was compared to the Customer Lifetime Value (CLV)-based RFM utilizing accuracy, precision, recall, and F1-score metrics. Results: This research identified five clusters. The target segment was chosen from the highest-value and high-value clusters that comprised 17.80% of provider schools but can contribute 75.77% of students. Conclusions: The proposed model recommended more targeted schools in higher-potential districts and predicted the target segment with 0.99 accuracies, outperforming the CLV-based model. The empirical findings help university management determine the promotion location and allocate resources for promotional information distribution and student recruitment.

• Journal of the Korean earth science society
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• v.35 no.7
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• pp.518-528
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• 2014

In this study, a model of rainfall drop-size distribution was modified using PARSIVEL-retrieved rainfall drop-size distribution over Daegwanryeong mountainous area. A prototype model (Modified ${\Gamma}$ distribution model) applicable for this area was decided through the comparative analysis between results from models proposed by preceding research and PARSIVEL-retrieved data over Daegwanryeong mountainous area. In order to apply the prototype model for Daegwanryeong region, the parameters (${\alpha}$, A, B) were made via sensitivity experiments and models of the rainfall drop-size distributions for five cases of rainfall rate were proposed. Results from the proposed five models showed high correlations with PARSIVEL-retrieved data ($R^2=0.975$). In order to suggest a generalized form of rainfall drop-size distribution, interaction equations between rainfall rates and parameters (${\alpha}$, A, B) were investigated. The generalized model of the rainfall drop-size distribution was highly correlated with PARSIVEL-retrieved data ($R^2=0.953$), which means that the proposed model from this study was effective for simulating the rainfall drop-size distribution over Daegwanryeong region. However, the proposed model was optimized for rainfall drop-size distribution over Daegwanryeong region. Therefore, broad observations of other regions are necessary in order to develop the representative model of the Korean peninsula.