• Journal for History of Mathematics
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• v.11 no.2
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• pp.63-76
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• 1998

When teaching the linear regression analysis in the class, the power transformation must be introduced to fit the linear regression model for nonlinear data. Box and Cox (1964) proposed the attractive power transformation technique which is so called Box-Cox transformation. In this paper, an effective algorithm selecting an appropriate value for Box-Cox transformation is developed which is considered to find a value minimizing error sum of squares. When the proposed algorithm is used to find a value for transformation, the number of iterations needs to be considered. Thus, the number of iterations is examined through simulation study. Since SAS is one of most widely used packages and does not provide the procedure that performs iterative Box-Cox transformation, a SAS program automatically choosing the value for transformation is developed. Hence, the students could learn how the Box-Cox transformation works, moreover, researchers can use this for analysis of data.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.57-66
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• 2001

This study was performed to determine adsorption equilibrium moisture contents of rough rice, brown rice, white rice and rice hull grown in Korea. EMC values were measured by static method using saturated salt solutions at three temperature levels of 20$\^{C}$, 30$\^{C}$ and 40$\^{C}$, and eight relative humidity levels in the range from 11.2% to 85.0%. The measured EMC values were fitted to modified Henderson, Chung-Pfost, and modified Oswin models by using nonlinear regression analysis. The results of comparing root mean square errors for three models showed that modified Henderson and Chung-Pfost models could serve as good models, and that modified Oswin model could not be applicable to rough rice, brown rice, white rice and rice hull.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.187-189
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• 2004

This paper investigates the effect of weather factors(such as winds, rain, snows, temperature, clouds and humidity) on transmission line outages. The result shows that weather variables have significant effects on the transmission line historical outages and the relationship between them is nonlinear. Multiple regression analysis using Logit model is proved to be appropriate in forecasting line failure rate in KEPCO systems. It could also provide system operators with useful informations about system operation and planing.

• Coupled systems mechanics
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• v.6 no.1
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• pp.55-74
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• 2017

The evaluation of torsional effects on multistory buildings remains an open issue, despite considerable research efforts and numerous publications. In this study, a large number of multiple test structures are considered with normally distributed topological attributes, in order to quantify the statistically derived relationships between the torsional criteria and response parameters. The linear regression analysis results, depict that the center of twist and the ratio of torsion (ROT) index proved numerically to be the most reliable criteria for the prediction of the modal rotation and displacements, however the residuals distribution and R-squared derived for the ductility demands prediction, was not constant and low respectively. Thus, the assessment of the torsional parameters' contribution to the nonlinear structural response was investigated using artificial neural networks. Utilizing the connection weights approach, the Center of Strength, Torsional Stiffness and the Base Shear Torque curves were found to exhibit the highest impact numerically, while all the other torsional indices' contribution was investigated and quantified.

• Journal of Environmental Impact Assessment
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• v.16 no.1
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• pp.79-87
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• 2007

The performance of a stream water quality analysis model depends upon many factors attributed to the geological characteristics of a watershed as well as the distribution behaviors of pollutant itself on a surface of watershed. Because the model run has to import the pollution load from the watershed as a boundary condition along an interface between a stream water body and a watershed, it has been used to introduce a pollution delivery coefficient to behalf of the boundary condition of load importation. Although a nonlinear regression model (NRM) was developed to cope with the limitation of a conventional empirical way, this an up-to-date study has also a limitation that it can't be applied where the pollution load washed off (assumed at a source) is less than that delivered (observed) in a stream. The objective of this study is to identify what causes the limitation of NRM and to suggest how we can purify the process to evaluate a pollution delivery coefficient using many field observed cases. As a major result, it was found what causes the pollution load delivered to becomes bigger than that assumed at the source. In addition, the pollution load discharged to a stream water body from a specific watershed was calculated more accurately.

• Journal of Life Science
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• v.16 no.7 s.80
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• pp.1225-1228
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• 2006

Cyclic AMP receptor protein (CRP) complexed with cAMP binds to DNA and induces sharp DNA bending around ${\sim}90$ degree. Previous publication (5), however, reported that mutant CRP:cGMP complex showed high migration rate relative to mutant CRP:cAMP complex on native polyacrylamide gel. To confirm DNA structural change in the presence of CRP and cyclic nucleotide, molar cyclization factor $(j_M)$ [13] was measured with 6 constructed DNA fragments. Nonlinear regression analysis of $j_M$ data indicated that mutant CRP did not induce DNA bending in the presence of cGMP but bent DNA in the presence of cAMP without any helical twist change in DNA.

• Applied Chemistry for Engineering
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• v.32 no.5
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• pp.581-588
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• 2021

In this study, soil slurry bioreactors were used to treat soils containing 16 polycyclic aromatic hydrocarbons (PAHs) for 35 days. Five different soil samples were taken from manufactured gas plant (MGP) and coal tar disposal sites. Soil properties, such as carbon content and particle distribution, were measured. These properties were significantly correlated with percent biodegradation and degradation rate. The cumulative amount of PAH degraded (P), degradation rate (K_m), and lag phase (𝜆) constants of PAHs in different MGP soils for 16 PAHs were successfully obtained from nonlinear regression analysis using the Gompertz equation, but only those of naphthalene, anthracene, acenaphthene, fluoranthene, chrysene, benzo[k]fluoranthene, benzo(a)pyrene, and benzo(g,h,i)perylene are presented in this study. A comparison between total non-carcinogenic and carcinogenic PAHs indicated higher maximum amounts of PAH degraded in the former than that in the latter owing to lower partition coefficients and higher water solubilities (S). The degradation rates of total non-carcinogenic compounds for all soils were more than four times higher than those of total carcinogenic compounds. Carcinogenic PAHs have the highest partitioning coefficients (K_oc), resulting in lower bioavailability as the molecular weight (MW) increases. Good linear relationships of K_m, 𝜆, and P with the octanol-water partitioning coefficient (K_ow), MW, and S were used to estimate PAH remaining, lag time, and biodegradation rate for other PAHs.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.437-448
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• 2022

Alluvial soil is challenging to work with due to its high compressibility. Thus, consolidation settlement of this type of soil should be accurately estimated. Accurate estimation of the consolidation settlement of alluvial soil requires accurate prediction of compressibility parameters. Geotechnical engineers usually use empirical correlations to estimate these compressibility parameters. However, no attempts have been made to develop correlations to estimate compressibility parameters of alluvial soil. Thus, this paper aims to develop new models to predict the compression and recompression indices (Cc and Cr) of alluvial soils. As part of the study, geotechnical laboratory tests have been conducted on large number of undisturbed samples of local alluvial soil. The obtained results from these tests in addition to available results from the literature from different parts in the world have been compiled to form the database of this study. This database is then employed to examine the accuracy of the available empirical correlations of the compressibility parameters and to develop the new models to estimate the compressibility parameters using the nonlinear regression analysis. The accuracy of the new models has been accessed using mean absolute error, root mean square error, mean, percentage of predictions with error range of ±20%, percentage of predictions with error range of ±30%, and coefficient of determination. It was found that the new models outperform the available correlations. Thus, these models can be used by geotechnical engineers with more confidence to predict Cc and Cr.

• Steel and Composite Structures
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• v.19 no.6
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• pp.1449-1466
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• 2015

Mixed structures consist of two parts: a lower part and an upper part. The lower part is usually made of concrete while the upper part is made of steel. Analyzing these structures is complicated and code-based design of them has many associated problems. In this research, the seismic behavior of mixed structures which have reinforced concrete frames and shear walls in their lower storeys and steel frames with bracing in their upper storeys were studied. For this purpose, seventeen structures in three groups of 5, 9 and 15 storey structures with different numbers of concrete and steel storeys were designed. Static pushover analysis, linear dynamic analysis and incremental dynamic analysis (IDA) using 15 earthquake records were performed by OpenSees software. Seismic parameters such as period, response modification factor and ductility factor were then obtained for the mixed (hybrid) structures using more than 4600 nonlinear dynamic analysis and used in the regression analysis for achieving proper formula. Finally, some formulas, effective in designing such structures, are presented for the mentioned parameters. According to the results obtained from this research, the response modification factor values of mixed structures are lower compared to those of steel or concrete ones with the same heights. This fact might be due to the irregularities of stiffness, mass, etc., at different heights of the structure. It should be mentioned that for the first time, the performance and seismic response of such structures were studied against real earthquake accelerations using nonlinear dynamic analysis, andresponse modification factor was obtained by IDA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.103-108
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• 2022

In this paper, we propose a new image analysis method based on regression manifold 3-D PCA. The proposed method is a new image analysis method consisting of a regression analysis algorithm with a structure designed based on an autoencoder capable of nonlinear expansion of manifold 3-D PCA and PCA for efficient dimension reduction when entering large-capacity image data. With the configuration of an autoencoder, a regression manifold 3-DPCA, which derives the best hyperplane through three-dimensional rotation of image pixel values, and a Bayesian rule structure similar to a deep learning structure, are applied. Experiments are performed to verify performance. The image is improved by utilizing the fine dust image, and accuracy performance evaluation is performed through the classification model. As a result, it can be confirmed that it is effective for deep learning performance.