• Journal of Korean Society of Water and Wastewater
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• v.31 no.4
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• pp.289-296
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• 2017

Pulp and paper industry produces large volumes of wastewater and residual sludge waste, resulting in many issues in relation to wastewater treatment and sludge disposal. Contaminants in pulp and paper wastewater include effluent solids, sediments, chemical oxygen demand (COD), and biological oxygen demand (BOD), which should be treated by wastewater treatment processes such as coagulation and biological treatment. However, few works have been attempted to predict the treatment efficiency of pulp and paper wastewater. Accordingly, this study presented empirical models based on experimental data in laboratory-scale coagulation tests and compared them with statistical models such as artificial neural network (ANN). Results showed that the water quality parameters such as turbidity, suspended solids, COD, and UVA can be predicted using either linear or expoential regression models. Nevertheless, the accuracies for turbidity and UVA predictions were relatively lower than those for SS and COD. On the other hand, ANN showed higher accuracies than the emprical models for all water parameters. However, it seems that two kinds of models should be used together to provide more accurate information on the treatment efficiency of pulp and paper wastewater.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.85-98
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• 2004

The adsorption equilibrium data for the binary gas mixture system from the pure gas adsorption data of carbon dioxide and ethylene on ZSM-5 prepared were predicted. The binary gas mixture adsorption data have been examined against predicted values by two models-the vacancy solution model(VSM) and the statistical thermodynamic model(STM), using parameters obtained from the single component isotherm. The binary gas mixture data for the carbon dioxide-ethylene system were obtained for cation exchanged forms of ZSM-5 for the gas phase carbon dioxide mole fraction of 0.752 at $37^{\circ}C$ and 1 atm. The experimental adsorption phase diagrams were obtained for carbon dioxide-ethylene on sodium form ZSM-5 synthesized. The single component adsorption isotherms for carbon dioxide and ethylene were also obtained for this zeolite. The single component data were used to obtain parameters derived in two models. These parameters were, in turn, used to predict the binary mixture isotherms for this zeolite. Both the vacancy solution and the statistical thermodynamic models give satisfactory predictions of adsorption phase diagrams for the binary gas mixtures of carbon dioxide and ethylene on sodium exchanged ZSM-5. Also the correlation between the experimental data and the predicted values is generally in good agreement. The system appears to show ideal behavior with a relatively constant separation factor. The slight increase in adsorption capacity with an increase in ionic radius is due, in part, to the higher polarizability associated with larger cations.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.119-134
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• 2021

Lung cancer is one of the leading causes of cancer deaths in the world. Investigation of mortality rates is pivotal to adequately understand the determinants causing this disease, allocate public health resources, and apply different control measures. Our study aims to analyze and forecast age-specific US lung cancer mortality trends. We report functions of mortality rates for different age groups by incorporating functional principal component analysis to understand the underlying mortality trend with respect to time. The mortality rates of lung cancer have been higher in men than in women. These rates have been decreasing for all age groups since 1990 in men. The same pattern is observed for women since 2000 except for the age group 85 and above. No significant changes in mortality rates in lower age groups have been reported for both gender. Lung cancer mortality rates for males are relatively higher than females. Ten-year predictions of mortality rates depict a continuous decline for both gender with no apparent change for lower age groups (below 40).

• Applied Chemistry for Engineering
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• v.35 no.4
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• pp.346-351
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• 2024

Chemical reduction using catalysts and NaBH₄ presents a promising approach for reducing 4-nitrophenol contamination while generating valuable byproducts. Covalent organic frameworks (COFs) emerge as a versatile platform for supporting catalysts due to their unique properties, such as high surface area and tunable pore structures. This study employs design of experiments (DOE) to systematically optimize the synthesis of Cu embedded COF (Cu/COF) catalysts for the reduction of 4-nitrophenol. Through a series of experimental designs, including definitive screening, mixture method, and central composition design, the main synthesis parameters influencing Cu/COF formation are identified and optimized: MEL:TPA:DMSO = 0.31:0.36:0.33. Furthermore, the optimal synthesis temperature and time were predicted to be 195 ℃ and 14.7 h. Statistical analyses reveal significant factors affecting Cu/COF synthesis, facilitating the development of tailored nanostructures with enhanced catalytic performance. The catalytic efficacy of the optimized Cu/COF materials is evaluated in the reduction of 4-nitrophenol, demonstrating promising results in line with the predictions from DOE.

• Animal cells and systems
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• v.5 no.4
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• pp.313-317
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• 2001

The sequential assessment model describes a fight between two conspecific as an ongoing statistical sampling process, which makes it possible to predict fight length or repetition number of a behavioral element depending on relative RHP (resource holding potential: e.g. weight or fighting ability). We staged contests between males of common freshwater gobies to test some predictions of this model. Fights proceeded in a consistent sequence of phases. Most contests began with two contestants adopting lateral display, and then escalated to intense physical contacts. The length of contests was negatively correlated with weight difference between the contestants. The duration of complete phases was, however, independent of weight, and the prior information gained during complete phases did not appear to affect subsequent phases of the fight. Our results show that the contests of common freshwater gobies are well predicted by the sequential assessment model.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.166-172
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• 2014

Caspases, a family of cysteinyl aspartate-specific proteases plays a central role in the regulation and the execution of apoptotic cell death. Activation of caspases-3 stimulates a signaling pathway that ultimately leads to the death of the cell. Hence, caspase-3 has been proven to be an effective target for reducing the amount of cellular and tissue damage. In this work, comparative molecular field analysis (CoMFA) was performed on a series of 3, 4-dihydropyrimidoindolones derivatives which are inhibitors of caspase-3. The best predictions were obtained for CoMFA model ($q^2=0.676$, $r^2=0.990$). The predictive ability of test set ($r^2_{pred}$) was 0.688. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. Our theoretical results could be useful to design novel and more potent caspase-3 derivatives.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.25-49
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• 2007

An important assumption of the classical linear regression model is that the disturbances appearing in the population regression function are homoskedastic; that is, they all have the same variance. If we persist in using the usual testing procedures despite heteroskedasticity, what ever conclusions we draw or inferences we make be very misleading. The contribution of this paper will be to the concrete procedure of the proper estimation when the heteroskedasticity does exist in the data, because the quality of dependent variable predictions, i.e., the estimated variance of the dependent variable, can be improved by giving consideration to the issues of regional homogeneity and/or heteroskedasticity across the research area. With respect to estimation, specific attention should be paid to the selection of the appropriate strategy in terms of the auxiliary regression model. The paper shows that by testing for heteroskedasticity, and by using robust methods in the presence of with and without heteroskedasticity, more efficient statistical inferences are provided.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.74-82
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• 1998

To evaluate the reliability against fatigue failure of offshore structures, a fatigue reliability analysis model based on the probabilistic approach has been developed. In this model, the simplified method is adopted as a fatigue analysis method. The uncertainties included in the fatigue analysis are considered as random variables and their statistical properties are evaluated as quantitatively as possible using existing data. As an example, the developed fatigue reliability model is applied to the jacket. And then the relative significance of each uncertainty on the probability of fatigue failure is surveyed.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.675-682
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• 2013

Reliability analysis and prediction of next failure time is critical to sustain weapon systems, concerning scheduled maintenance, spare parts replacement and maintenance interventions, etc. Since 1981, many methodology derived from various probabilistic and statistical theories has been suggested to do that activity. Nowadays, many A.I. tools have been used to support these predictions. Support Vector Regression(SVR) is a nonlinear regression technique extended from support vector machine. SVR can fit data flexibly and it has a wide variety of applications. This paper utilizes SVM and SVR with combining time series to predict the next failure time based on historical failure data. A numerical case using failure data from the military equipment is presented to demonstrate the performance of the proposed approach. Finally, the proposed approach is proved meaningful to predict next failure point and to estimate instantaneous failure rate and MTBF.

• Environmental Engineering Research
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• v.14 no.1
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• pp.13-18
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• 2009

In this study, specific pollutant releases during the Asian monsoon season were estimated and the information was applied to the non-point pollutant sources management from two forested watersheds of the Soyang Lake. The two watersheds are part of the 2,703 km2 Soyang Lake watershed in the northern region of the Han River. The outlets of the two watersheds were respectively analyzed for continuous water quality concentration and for discharge during various single rainfall events. Statistical power function methods are utilized to compare stream discharge and pollutant flux release during the study period. Based on the monitoring data during the study period, the specific load flux method using simulated discharge was conducted and validated in the two watersheds. The model predictions corresponded well with the measured and calculated pollutant releases. The modeling approach taken in this study was found to be applicable for the two forested watersheds.