• Human Ecology Research
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• v.59 no.4
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• pp.557-567
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• 2021

This study examined the relationship between COVID-19 stress, self-regulation, and smartphone addiction among university students. It also assessed whether self-regulation mediates the relationship between COVID-19 stress and smartphone addiction. The participants comprised 346 students enrolled in G city university. Data were analyzed using SPSS and AMOS to generate descriptive statistics, perform a correlation analysis, and create a structural equation model. The main findings were as follows. First, COVID-19 stress had a negative correlation with self-regulation, but a positive correlation with smartphone addiction. A negative correlation was observed between self-regulation ability and smartphone addiction. Secondly, self-regulation partially mediated the relationship between COVID-19 stress and smartphone addiction. The results will inform educational and counseling interventions aimed at preventing smartphone addiction among university students living in the era of the COVID-19 pandemic.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.3 no.2
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• pp.81-89
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• 1999

This study estimates the correlation dimensions of the land-sea breeze phenomenon, that has a clear diurnal cycle, in order to gain a more detailed understanding of this phenomenon. The data adopted include north-south wind velocity component(v) and temperature(T) time series that were observed at Kimhae Airport and Inje University over a period of 5 days, from the 4th to the 8th of August, 1994. The embedding phase space of the time series were reconstructed from 2 to 14 dimensions, and the correlation dimensions of the attractors were then estimated. The results show that the land-sea breeze phenomenon exhibits a deterministic chaos with non-integer correlation dimension values between 2 and 3. Accordingly, 3 is the minimum number of independent variables required to model the dynamics of the landsea breeze phenomenon in the Kimhae area. Since the saturated embedding dimension, when the correlation dimension remains unchanged, is larger for the wind velocity v-component than for temperature, this indicates that wind velocity is susceptible to topology.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.2
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• pp.188-195
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• 2002

This paper statistically verifies two correlation algorithms by comparing the data of GTEM cell to those of semi-anechoic chamber (SAC). Correlation algorithms considered in this paper are 3 and 15 position methods, which simulate the EMI test for an equipment under test (EUT) over the ground plane by using the radiated power from EUT located within GTEM cell. Also, the results obtained by two algorithms are compared with the theoretical values calculated from an ideal dipole model. From the results, it was found that the data obtained by two correlation algorithms and SAC have a strong correlation. In addition, the EMI data by 3 position method showed higher than those by 15 position method and SAC measurements.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.157-164
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• 2018

The purpose of this study was to investigate the effect of empowerment in nurses through a systematic literature review and meta-analysis. 23 studies were collected through a systematic process of using several databases such as NDSL, DBPIA, and KISS. Keywords included 'nurse', 'empowerment', and 'correlation' and the reviewed articles were published from 2002 to 2017. In order to estimate the effect size of correlation between empowerment, 3 variables (job satisfaction, organizational commitment, and nursing performance) were considered. Using the R program, meta-analysis was calculated by using random effects model, and effect sizes on three types were estimated. As the result, it was found, first, the effect size of correlation between job satisfaction and empowerment is .50. Second, the effect size of correlation between organizational commitment and empowerment is .45. Third, for the nursing performance and empowerment relationship, the effect of correlation is 0.50. Also, Egger's regression test, fail-safe N, trim-and-fill test, and funnel plot were showed to evaluate the results. These results highlights the need for appropriate policies of the relationship between empowerment and job satisfaction, organizational commitment and nursing performance in nurses.

• Advances in concrete construction
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• v.16 no.6
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• pp.317-325
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• 2023

Strength prediction and correlation of concrete is done using experimental and analytical methods. Main objective is to correlate the experimental and simulated values of compressive strength of concrete mix using Fly Ash (FA) and Silica Fume (SF) by partial replacement of cement in concrete. Mix proportion was determined using IS method for M40grade concrete. Hundred and forty-seven cubes were cast and tested using Universal Testing Machine (UTM). Genetic Algorithm (GA) model was developed using C++ program to simulate the compressive strength of concrete for various proportions of FA and SF replacements individually at 3% increments. Experiments reveal that 12 percent silica fume replacement produced maximum compressive strength of 35.5 N/mm², 44.5 N/mm² and 54.8 N/mm² moreover 9 percent fly ash replacement produced a maximum strength of 31.9 N/mm², 37.6 N/mm² and 51.8 N/mm² during individual material replacement of concrete mix. Correlation coefficient for each curing period of fly ash and silica fume replaced mix were acquired using trend lines. The correlation coefficient is found to be approximately 0.9 in FA and SF replaced mix irrespective of the mix proportion and age of concrete. A higher and positive correlation was found between the experimental and simulated values irrespective of the curing period in all the replacements.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.4
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• pp.318-327
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• 2012

The operating sound radiated from a laser printer includes tonal noise components caused by the rotating mechanical parts such as gear, shaft, motor, fan, etc. The negative effects of the tonal noise components need to be considered in the process of developing a sound quality index for the quantitative evaluation of the emotional satisfaction in terms of psycho-acoustics. However, in a previous paper, it was confirmed that the Aures tonality did not have enough correlation with the results of jury evaluation. The sound quality index based on loudness, articulation index, fluctuation strength has a little problem in considering the effects of rotating mechanical parts on the sound quality. In this paper, to solve the tonality evaluation problem, the calculation algorithm of Aures tonality was investigated in detail to find the cause of decreasing the correlation. The new tonality evaluation model was proposed by modifying and optimizing the masking effect, loudness ratio, and shape of weighting curve based on the basic algorithm of Aures tonality, and applied to two kinds of operating sound groups in order to verify the usefulness of proposed model. As a result, it is confirmed that the proposed tonality evaluation model has enough correlation and usefulness for expressing the tonalness in the operating sounds of laser printers. In the following paper, this results will be used to model the sound quality index as the input data by using the classification algorithm.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.47-60
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• 1999

In this study, the dynamic route choice behavior of driver is assumed to be affected by the current conditions of traffic environments as well as the Past traffic environments and activities. The repeated survey of multi-timed to owner drove in Chon-ju city by the virtual traffic information system was performed by the stated preference method. And the LISREL(An analysis of linear structural relationship) model was used. As the results. the variable Parameter and t-value of travel time information on applied model was high and their results have an effect greatly to the route choice. After all, the route choice was negative from Kirin-ro, which Penetrates the downtown, and positive from Chunbyun-ro which was a roundabout way was confirmed. Estimated result of the reasonability, the highest suitable model was ode which applied the concept of serial correlation and stated dependence and was shown applying rightfulness to dynamic model. As the serial correlation and stated dependence parameter value, when time interval was large, parameter value was small and the serial correlation and stated dependence was in inverse proportion ratio to the time interval.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.511-520
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• 2020

Purpose: The purpose of this study was to devise an accurate machine learning model for predicting silica concentrations following the addition of impurities, through time series analysis of mining data. Methods: The mining data were preprocessed and subjected to time series analysis using the machine learning model. Through correlation analysis, valid variables were selected and meaningless variables were excluded. To reflect changes over time, dependent variables at baseline were treated as independent variables at later time points. The relationship between independent variables and the dependent variable after n point was subjected to Pearson correlation analysis. Results: The correlation (R2) was strongest after 3 hours, which was adopted as a dependent variable. According to root mean square error (RMSE) data, the proposed method was superior to the other machine learning methods. The XGboost algorithm showed the best predictive performance. Conclusion: This study is important given the current lack of machine learning studies pertaining to the domestic mining industry. In addition, using time series analysis in mining data will show further improvement. Before establishing a predictive model for the proposed method, predictions should be made using data with time series characteristics. After doing this work, it should also improve prediction accuracy in other domains.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.605-618
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• 2012

In this study, the possibility of decision error is investigated to identify and improve the reliability of participants in the process of conducting the sound quality analysis for laser printers. So far, there is not a way to identify and express the possibility of individual participant quantitatively. Thus, the decision error model is proposed which is based on the expectation value between the perceived sounds. Through the experimental verification on the laser printers, it was found that the possibility of decision error is affected according to the normalized difference. The possibility of decision error has inversely proportional to the normalized difference between the perceived sounds. When the normalized difference becomes small value, the uncertainly between decisions is inversely increase, and then it is difficult to obtain the proper result in the process of the jury evaluation for laser printers. For this reason, in this study, the proposed decision error model is added in the previous step of the correlation verification. Comparing to the conventional process only using the correlation based method, after the reliability of each participant is verified, the correlation with the mean response of participants is verified. It was found that the participants who were recognized as having unusual preferences are actually identified as having the reliability problem. Based on the results of this study, the proposed decision error model will be helpful to identify and improve the reliability of participants in the following study for the sound quality analysis.

• Journal of Educational Research in Mathematics
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• v.14 no.1
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• pp.71-88
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• 2004

The purpose of this study was to examine particular variables that play a significant role in the difficulty of math test items in College Scholastic Ability Test (CSAT). The study also aimed to develop a model of measuring the item difficulty. Variables correlated to item difficulty were drawn from the review of the related literature and the analysis of the content and difficulty of the past test items of CSAT. The first instrument was designed by using the correlated variables. According to the results of correlation analysis, the second instrument was made by deleting the variables which showed relatively low correlation with item difficulty and by refining some variables. Several models were proposed by using the revised instrument. The comparison of the R square and cross validity of each model reveals that integrated regression model was the most stable and accurate among the proposed models. The study also showed that statistically significant predictors were choice format, content domain, behavior domain, and the degree of item familiarity in the order of proportion of variance accounted by the predictors. Despite the limited scope of the present research, it can be suggested that its findings provide useful insights into predicting math test item difficulty.