• Bulletin of the Korean Chemical Society
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• v.30 no.1
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• pp.67-76
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• 2009

The development of a variety of methods like AM1, PM3, PM5 and DFT now allows the calculation of atomic and molecular properties with high precision as well as the treatment of large molecules with predictive power. In this paper, these methods have been used to calculate a number of quantum chemical descriptors (like Klopman atomic softness in terms of $E_n^{\ddag}\;and\;E_m^{\ddag}$, chemical hardness, global softness, electronegativity, chemical potential, electrophilicity index, heat of formation, total energy etc.) for 75 alkanes to predict their boiling point values. The 3D modeling, geometry optimization and semiempirical & DFT calculations of all the alkanes have been made with the help of CAChe software. The calculated quantum chemical descriptors have been correlated with observed boiling point by using multiple linear regression (MLR) analysis. The predicted values of boiling point are very close to the observed values. The values of correlation coefficient ($r^2$) and cross validation coefficient ($r_{cv}^2$) also indicates the generated QSPR models are valuable and the comparison of all the methods indicate that the DFT method is most reliable while the addition of Klopman atomic softness $E_n^{\ddag}$ in DFT method improves the result and provides best correlation.

• Computers and Concrete
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• v.15 no.4
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• pp.485-501
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• 2015

Cooling by the flow of water through an embedded cooling pipe has become a common and effective artificial thermal control measure for massive concrete structures. However, an extreme thermal gradient induces significant thermal stress, resulting in thermal cracking. Using a mesoscopic finite-element (FE) mesh, three-phase composites of concrete namely aggregate, mortar matrix and interfacial transition zone (ITZ) are modeled. An equivalent probabilistic model is presented for failure study of concrete by assuming that the material properties conform to the Weibull distribution law. Meanwhile, the correlation coefficient introduced by the statistical method is incorporated into the Weibull distribution formula. Subsequently, a series of numerical analyses are used for investigating the influence of the correlation coefficient on tensile strength and the failure process of concrete based on the equivalent probabilistic model. Finally, as an engineering application, damage and failure behavior of concrete cracks induced by a water-cooling pipe are analyzed in-depth by the presented model. Results show that the random distribution of concrete mechanical parameters and the temperature gradient near water-cooling pipe have a significant influence on the pattern and failure progress of temperature-induced micro-cracking in concrete.

• The Journal of Korean Academic Society of Nursing Education
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• v.19 no.3
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• pp.455-464
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• 2013

Purpose: The goal of the study was to investigate nursing students' knowledge and compliance with hand hygiene to find out the variables associated with compliance with hand hygiene. Methods: The participants were 1,020 nursing college students located in Seoul, Ansan and Suncheon. The variables analyzed in this study were; hand hygiene knowledge, hand hygiene compliance, hand washing habits, hand hygiene education with emphasis in school, emphasis on hand washing and role modeling in hospital, and hand hygiene beliefs. Data were analyzed by frequency, $x^2$-test, t-test and Pearson correlation coefficient. Results: 1. The correct answer average percentage of hand hygiene knowledge was 78.4%. 2. The average rates of hand hygiene compliance rate was 78.0% 3. Compliance rate had significant correlation with variables such as hand washing habit, hand hygiene education with emphasis in school, emphasis on hand washing and role modeling in hospital, and hand hygiene belief. Conclusion: 1. It is nessassery for nursing students to receive proper educational on hand hygiene knowledge during practices in nursing school curriculum. 2. Nurses should be encouraged to be a good mentor to nursing students on appropriate hand hygiene compliance in clinical practice.

• Analytical Science and Technology
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• v.9 no.1
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• pp.98-106
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• 1996

The concentration of sulfur dioxide in Wonju City was predicted using TCM (Texas Climatological Model). We have studied the transportation and wet deposition of $SO_2$ using the TCM and the analysis of rainfalls. The results are as follows : At the Hak-Sung Dong site in Wonju city, the correlation coefficient between the measured and calculated concentrations were 0.904. Sulfur dioxide was washed out by wet deposition. The wet deposition ratio to total amount of emitted sulfur dioxide was higher in summer than in autumn and winter seasons due to heavy rainfall in summer. The correlation coefficient between the precipitation and wet deposition of sulfur dioxide was 0.68. The months with greater rainfall showed that the measured concentrations of sulfur dioxide were much lower than the predicted ones. Although the amount of precipitation in April was smaller than in summer, the wet deposition ratio in April was much higher than any other months, due to the sulfur dioxide that was adsorbed on particulate matter and moisture was transported during the period of yellow sand phenomena from China.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.2
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• pp.167-172
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• 2011

A three-dimensional ecological model (EMT-3D) was applied to Tokyo Bay to simulate 4,4'-bis (2-sulfostyryl)biphenyl (DSBP). The simulated results were in good agreement with the observed values, with a correlation coefficient of R=0.8431 and a coefficient of determination of $R^2$=0.7108. The sensitivity analysis indicated that the photolysis rate is the most important factor. Therefore, the parameters must be considered carefully in modeling. The mass balance results showed that the standing stock of DSBP in water and in particulate organic carbon was 621.2 and 19.5 kg, respectively, and the effluent flux to the open sea was 2.63 and 0.055 kg/day, respectively.

• Bioinformatics and Biosystems
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• v.1 no.1
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• pp.82-87
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• 2006

The most popular protein structure prediction method is comparative modeling. To guarantee accurate comparative modeling, the sequence alignment between a query protein and a template should be accurate. Although choosing the best template based on the protein sequence alignments is most critical to perform more accurate fold-recognition in comparative modeling, even more critical is the sequence alignment quality. Contrast to a lot of attention to developing a method for choosing the best template, prediction of alignment accuracy has not gained much interest. Here, we develop a method for prediction of the shift score, a recently proposed measure for alignment quality. We apply support vector regression (SVR) to predict shift score. The alignment between a query protein and a template protein of length n in our own library is transformed into an input vector of length n +2. Structural alignments are assumed to be the best alignment, and SVR is trained to predict the shift score between structural alignment and profile-profile alignment of a query protein to a template protein. The performance is assessed by Pearson correlation coefficient. The trained SVR predicts shift score with the correlation between observed and predicted shift score of 0.80.

• Computers and Concrete
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• v.20 no.3
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• pp.275-282
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• 2017

Grouting is an operation often carried out to consolidate and seal the rock mass in dam sites and tunnels. One of the important parameters in this operation is grouting pressure. In this paper, analytical models used to estimate pressure are investigated. To validate these models, grouting data obtained from Seymareh and Aghbolagh dams were used. Calculations showed that P-3 model from Groundy and P-25 model obtained from the results of grouting in Iran yield the most accurate predictions of the pressure and measurement errors compared to the real values in P-25 model in this dams are 12 and 14.33 Percent and in p-3 model are 12.25 and 16.66 respectively. Also, SPSS software was applied to define the optimum relation for pressure estimation. The results showed a high correlation between the pressure with the depth of the section, the amount of water take, rock quality degree and grout volume, so that the square of the multiple correlation coefficient among the parameters in this dams were 0.932 and 0.864, respectively. This indicates that regression results can be used to predict the amount of pressure. Eventually, the relationship between the parameters was obtained with the correlation coefficient equal to 0.916 based on the data from both dams generally and shows that there is a desirable correlation between the parameters. The outputs of the program led to the multiple linear regression equation of P=0.403 Depth+0.013 RQD+0.011 LU-0.109 V+0.31 that can be used in estimating the pressure.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1546-1551
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• 2004

This paper presents a mathematical model to predict the frost properties and heal and mass transfer within the frost layer formed on a cold plate. The laminar flow equations for the air-side are analyzed. and the empirical correlations of local frost properties are employed in order to predict the frost layer growth. The correlations of local frost density and effective thermal conductivity of frost layer, obtained from various experimental conditions, are derived as functions of various frosting parameters (Reynolds number, frost surface temperature, absolute humidity and temperature of moist air, cooling plate temperature, and frost density). The numerical results are compared with experimental data and the results of various models to validate the present model, and agree well with experimental data within a maximum error of 10%. The heat and mass transfer coefficients obtained from the numerical analyses are presented, as the results, it is found that the model for frost growth using the correlation of heat transfer coefficient without solving air flow have a limitation in its application.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1495-1507
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• 2022

The improvement of thermal-hydraulic analysis techniques is essential to ensure the safety and reliability of nuclear power plants. The one-dimensional two-fluid model has been adopted in state-of-the-art thermal-hydraulic system codes. Current constitutive equations used in the system codes reach a mature level. Some exceptions are the partition method of wall friction in the momentum equation of the two-fluid model and the interfacial drag force model for a horizontal two-phase flow. This study is focused on deriving the partition method of wall friction in the momentum equation of the two-fluid model and modeling the interfacial drag force model for a horizontal bubbly flow. The one-dimensional momentum equation in the two-fluid model is derived from the local momentum equation. The derived one-dimensional momentum equation demonstrates that total wall friction should be apportioned to gas and liquid phases based on the phasic volume fraction, which is the same as that used in the SPACE code. The constitutive equations for the interfacial drag force are also identified. Based on the assessments, the Rassame-Hibiki correlation, Hibiki-Ishii correlation, Ishii-Zuber correlation, and Rassame-Hibiki correlation are recommended for computing the distribution parameter, interfacial area concentration, drag coefficient, and relative velocity covariance of a horizontal bubbly flow, respectively.