• Bulletin of the Korean Chemical Society
• /
• v.9 no.1
• /
• pp.36-40
• /
• 1988

The time correlation functions of concentration fluctuations due to the random forces near the steady state are evaluated for a general two-component nonlinear chemical system by solving the corresponding two dimensional Fokker-Planck equation. The approximate method of solving the Fokker-Planck equation is based on the eigenfunction expansion and the corresponding eigenvalues for both the linear and nonlinear Fokker-Planck operators are obtained near the steady state. The general results are applied to the Lotka model near the oscillatory marginal steady state and the comparison is made between linear and nonlinear cases.

• Structural Monitoring and Maintenance
• /
• v.9 no.2
• /
• pp.157-177
• /
• 2022

In this paper, an innovative finite element updating method is presented based on the variation wavelet transform coefficients of Auto/cross-correlations function (WTCF). The Quasi-linear sensitivity of the wavelet coefficients of the WTCF concerning the structural parameters is evaluated based on incomplete measured structural responses. The proposed algorithm is used to estimate the structural parameters of truss and plate models. By the solution of the sensitivity equation through the least-squares method, the finite element model of the structure is updated for estimation of the location and severity of structural damages simultaneously. Several damage scenarios have been considered for the studied structure. The parameter estimation results prove the high accuracy of the method considering measurement and mass modeling errors.

• Nuclear Engineering and Technology
• /
• v.53 no.12
• /
• pp.4189-4200
• /
• 2021

In this study, the relationship between the environmental radiation dose rate and meteorological variables was investigated with multiple regression analysis and big data of those variables. The environmental radiation dose rate and 36 different meteorological variables were measured on Ulleung Island, Republic of Korea, from 2011 to 2015. Not all meteorological variables were used in the regression analysis because the different meteorological variables significantly affect the environmental radiation dose rate during different periods, and the degree of influence changes with time. By applying the Pearson correlation analysis and stepwise selection methods to the big dataset, the major meteorological variables influencing the environmental radiation dose rate were identified, which were then used as the independent variables for the regression model. Subsequently, multiple regression models for the monthly datasets and dataset of the entire period were developed.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.4
• /
• pp.249-255
• /
• 2022

The COVID-19 virus appeared in 2019 and is extremely contagious. Because it is very infectious and has a huge impact on people's mobility. In this paper, multiple linear regression and random forest models are used to predict the number of COVID-19 cases using COVID-19 infection status data (open source data provided by the Ministry of health and welfare) and Google Mobility Data, which can check the liquidity of various categories. The data has been divided into two sets. The first dataset is COVID-19 infection status data and all six variables of Google Mobility Data. The second dataset is COVID-19 infection status data and only two variables of Google Mobility Data: (1) Retail stores and leisure facilities (2) Grocery stores and pharmacies. The models' performance has been compared using the mean absolute error indicator. We also a correlation analysis of the random forest model and the multiple linear regression model.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.5
• /
• pp.733-741
• /
• 2023

The purpose his study was a descriptive research study to identify the influencing factors of mentoring for nursing students, and was conducted with 120 nursing students. The collected data were subjected to real number and percentage, mean and standard deviation, t-test, ANOVA, Scheffe test, Pearson's correlation, and multiple regression analysis using SPSS/WIN 25.0. As a result of the study, mentoring was found to have a significant positive correlation with organizational socialization, core nursing competency, and clinical performance competency, and the explanatory power of the regression model was 64.1%. Since mentoring is an effective teaching method, based on this study, we propose a study to develop a structured mentoring program including organizational socialization, core nursing competency, and clinical performance competency to test the effectiveness. In addition, proposes a study to identify the relationship with various variables by dividing mentoring into sub-competencies of career development function, psychological stability function, and role model function.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.8 no.4
• /
• pp.42-50
• /
• 2000

Drop size distribution of an air-assisted fuel injector(AAFI) was investigated. Influence of parameters such as ambient air density supply pressure and air-liquid mass ratio(ALR) was examined through both measurement and analysis. The Sauter mean diameter$D_{32}$ varied from 9 to 25$\mu$m throughout all experimental conditions. An empirical correlation for droplet size was obtained. Analytical correlations for predicting $D_{32}$ with respect to operating conditions were also derived through energy consideration and introduction of a simplified model of the from the empirical fitting was adapted to the original equation the proposed correlation in this study matched more closely with measured results. The current correlation exhibited a favorable study matched more closely with measured results. The current correlation exhibited a favorable prediction for $D_{32}$ compared to that by the empirical correlation at selected experimental conditions so that it may be used to predict atomization performance of the AAFI at operating conditions which was not covered in the measurements. After validation the analytical equation was applied to survey the feasible operating conditions for gasoline direct injection application.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.415-418
• /
• 2002

As Remodeling is proceed in the limited condition that is utilization of existing resource, the selection of remodeling objects and scope are affected by the correlation of building systems. Unexpected problems have occurred in construction phase by lack of the consideration about correlation of building systems; increasing of cost, delaying of schedule etc. Therefore, this research suggests the Building System Correlation Diagram Model and the direction of cost estimation .for selecting alternative reasonably in remodeling design process.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.402-405
• /
• 2003

As Remodeling is proceed in the limited condition that is utilization of existing resource, the selection of remodeling objects and scope are affected by the correlation of building systems. Unexpected problems have occurred in construction phase by lack of the consideration about correlation of building systems; increasing of cost, delaying of schedule etc. Therefore, this research suggests the Building System Correlation Diagram Model and the method for selecting the alternative reasonably in remodeling project.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2488-2511
• /
• 2015

Data redundancy has high impact on Wireless Sensor Network's (WSN) performance and reliability. Spatial and temporal similarity is an inherent property of sensory data. By reducing this spatio-temporal data redundancy, substantial amount of nodal energy and bandwidth can be conserved. Most of the data gathering approaches use either temporal correlation or spatial correlation to minimize data redundancy. In Collective Prediction exploiting Spatio Temporal correlation (CoPeST), we exploit both the spatial and temporal correlation between sensory data. In the proposed work, the spatial redundancy of sensor data is reduced by similarity based sub clustering, where closely correlated sensor nodes are represented by a single representative node. The temporal redundancy is reduced by model based prediction approach, where only a subset of sensor data is transmitted and the rest is predicted. The proposed work reduces substantial amount of energy expensive communication, while maintaining the data within user define error threshold. Being a distributed approach, the proposed work is highly scalable. The work achieves up to 65% data reduction in a periodical data gathering system with an error tolerance of 0.6℃ on collected data.

• Journal of Korean Academy of Nursing Administration
• /
• v.11 no.3
• /
• pp.265-273
• /
• 2005

Purpose: This study was to investigate the degree and pattern of learning organization and MBTI personality type in clinical nurses. Methods: The participants were 685 nurses working in the 8 general hospitals located in Seoul and Incheon. The data were collected by self-reporting questionnaires from April 1 to August 30, 2004. The data were analyzed using SAS program for descriptive statistics and Pearson's correlation coefficient. Results: The most frequent identified personality type was ISTJ and the least identified personal types was ENFJ. In 4 preference patterns, Extroversion, Sensing, Thinking and Judgement were identified a dominant index in each categories. The mean score of learning organization was 3.47 and the mental model was got the highest score. The EI index had a significant positive correlation with personal mastery. However the TF index had a negative correlation with personal mastery, systems thinking, and mental models, and also the JP index had a negative correlation with 5 learning organization sub categories. Conclusion: With these results, it was identified that the preference patterns on MBTI had the significant correlation with learning organization. So these results will be used to develop the more effective strategies to increase learning organization based on nurse's personality types.