• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.5
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• pp.54-61
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• 2024

This study conducted accelerated carbonation experiments on cement pastes using OPC and FA. It derived the correlation of pH prediction methods through component analysis of the carbonated pastes. Analysis of weight change due to thermal decomposition was performed using TG-DTA, and component analysis was conducted using XRF. A comparative review of each experimental result and pH measurement result was carried out. The study proposed a correlation analysis method between the component ratio of CO₂ and CaO, the component ratio of calcium carbonate and calcium hydroxide, and pH. By analyzing the relationship between the CO₂ components measured by XRF and pH, the correlation coefficients of all mixtures were 0.84 or higher, indicating a strong correlation.The correlation analysis of calcium carbonate and calcium hydroxide with pH using TG-DTA showed that the correlation coefficient for calcium carbonate was more than 0.86 for all formulations. However, the correlation coefficient between calcium hydroxide and pH was low, so a study was conducted to analyze the correlation with pH using the ratio of the results of the two components.

• 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.

• Explosives and Blasting
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• v.31 no.1
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• pp.11-22
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• 2013

This study compared and analysed ground vibration, size of underwater background noise in fish farms and underwater object noise of blasting and obtained ground vibration prediction equation through a regression analysis and correlation equation between underwater object noises in order to predict degrees of underwater noise in blasting and organize underwater noise control regulations. Before the study, when background noise of fish and shellfish farms with different conditions was measured, levels of background noise were different according to environmental characteristics of each farm. Ground vibration which causes underwater noise was measured to obtain a correlation equation between ground vibration and underwater object noise. Therefore, if underwater noise is predicted for each construction with a use of a correlation and permissible standards appropriate for each condition are applied for design and construction, financial loss from damages to fish and shellfish caused by development of insufficient technological and engineering logic can be prevented and successful construction with safety of underwater creatures guaranteed can be achieved.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.476-483
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• 2016

Epicardial adipose tissue(EAT) is metabolically active endocrine organ that secretes several hormones in fat thickness is a risk factor for cardiovascular disease and metabolic disorders. This study was to measure and then using ultrasound epicardial adipose tissue thickness, abdominal subcutaneous fat thickness in the target group correlates and general blood properties and characteristics, and presents a local thickness for prediction of metabolic disorders. Results epicardal adipose tissue of the average thickness measured in each of the subjects was 8.890mm, 4.783mm, 4.777, 6.147mm in each section. Showed the epicardial adipose tissue in correlation with the average thickness of the risk factors age, BMI, SBP, LDH, LDL, TC is a positive correlation relationship(p<0.05) in each section. In particular, the thickness of the metabolic disorders epicardial adipose tissue thickness, abdominal subcutaneous compared to subjects that do not have the risk subjects with a risk factor for fat significantly higher(p<0.05). It showed the most reliable that can be cut-off value of 8.950mm obtained with 66.7 % sensitivity and 80 % specificity for predicting the risk of metabolic disorders.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.540-548
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• 2017

This study analyzed the relationship between the achievement motivation and social intelligence in pre-service early childhood teachers and their achievement motivation and social intelligence. The achievement motivation Inventory for pre-service early childhood teachers (Song, 2004), the social intelligence questionnaire (Han, 2011) and the Children's social problem solving ability scale (Huh, 1999) were administered to 193 pre-service early childhood teachers. The data underwent Pearson correlation analysis using the SPSS 21.0 program. The results of this study were as follows. First, there were significant positive relationships among the achievement motivation, social intelligence, and social problem solving ability. Second, the achievement motivation and social intelligence was an important factor for predicting the social problem solving ability of pre-service early childhood teachers.

• Journal of the Korea Institute of Building Construction
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• v.14 no.2
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• pp.118-126
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• 2014

The establishment of the technology for evaluating friction resistance and pipe pressure and the relation of the fluid characteristics and pumpability of concrete is essential for concrete pumping performance for the rapid construction of super-tall buildings. In this study, a quantitative evaluation of concrete fluid characteristics and surface friction resistance was performed, applying different concrete mix proportions and pumping conditions. To achieve this, we developed a temporary horizontal pumping evaluation system to measure pipe pressure and surface friction characteristics, and performed an experiment to investigate the relations between concrete rheology characteristics and friction resistance in pipe. The experiment found that in terms of the rheology characteristics, plastic viscosity was reduced remarkably after pumping. As well, high regression between the surface friction and pressure gradient was confirmed. This means that it is possible to evaluate the friction resistance between concrete and pipe by means of a pumping system that includes a frictional resistance testing pipe. In addition, high regression between the plastic viscosity of concrete after pumping and friction resistance coefficient was confirmed. Finally, it is considered that pumping pressure can be predicted using the friction resistance coefficient derived in this study, and it has high regression.

• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.393-417
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• 2022

The current study analyzes the usage of social network services(SNS) according to one's collectivistic and individualistic tendency and the relationship with addiction. Additionally, the study attempted to controll intrapersonal variables such as gender, personalitly, and age, which affect SNS the usage. Also, Collectivistic-individualistic tendency in SNS and offline environment may not correspond to one another. Therefore, the study measured the collectivistic-individualistic tendency regarding of the two environment separately. For this purpose, we designed a new measurement scale to measure collectivistic-individualistic tendencies in for the SNS by involving a kin vs nonkin context. The sample consisted of 253 adolescents ranging from 13 to 15 years old and 246 adults ranging from 18 to 25 years old, which sums up to 499 samples in total. Results indicated that individualistic tendency within SNS showed a positive relationship with the amount of SNS usage and SNS addiction. Furthermore, female users spent more time on SNS and showed a higher level addiction than males. While adults had longer experience with SNS and spent more time on it daily than adolescents, they did not show a significant difference in regards to SNS addiction. The correlation analysis indicated that collectivistic-individualistic tendencies in SNS were weakly correlated to that of offline environments. The kin individualistic tendency in SNS significantly predicted SNS addiction after controlling for the effect of age, personality, gender, and offline collectivistic-individualistic tendency. Taken together, these findings indicate the need for an appropriate collectivistic-individualist tendency scale that correspond to the SNS context. The results also suggest that kin individualistic tendency in the SNS environment can be the main factor for SNS addiction.

• The Journal of the Acoustical Society of Korea
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• v.24 no.2
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• pp.103-110
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• 2005

Providing adequate amount of spatial impression for spaciousness) has been known to be one of the most important design considerations for the good acoustics of rooms for music. and the measurement, of room acoustics using parameters. such as LEF and IACC, forms an essential part of such evaluation. However. it is unavoidable to use different transducers (figure of eight microphones. head and torso) for the measurement of each parameter and it tends to make the measurement procedure complicated. The Present work tried to provide a simpler way to measure these binaural room acoustic parameters including monaural ones with a single measurement system using both spatial information collected through a 5-channel microphone and a trained neural network. A computer simulation program, CATT-Acoustic V7.2. which allowed us to obtain exactly the same spatial information as a 5-channel microphone was used. since it requires quite a large amount of data for practical training of a neural network. Since each reflection has different energy. delay and direction, energy should be integrated properly. the concept of ray tracing method was applied inversely in this work. Also applying weightings according to the delay times was considered in this work. Finally, predicted results were compared with the measured data md their correlations were analyzed and discussed.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.393-400
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• 2016

Recently, there have been various researches on efficient and automatic analysis on urban environment methods that utilize the computer vision and machine learning technology. Among many new analyses, urban safety analysis has received a major attention. In order to predict more accurately on safety score and reflect the human visual perception, it is necessary to consider the generic and local information that are most important to human perception. In this paper, we use Double-column Convolutional Neural network consisting of generic and local columns for the prediction of urban safety. The input of generic and local column used re-sized and random cropped images from original images, respectively. In addition, a new learning method is proposed to solve the problem of over-fitting in a particular column in the learning process. For the performance comparison of our Double-column Convolutional Neural Network, we compare two Support Vector Regression and three Convolutional Neural Network models using Root Mean Square Error and correlation analysis. Our experimental results demonstrate that our Double-column Convolutional Neural Network model show the best performance with Root Mean Square Error of 0.7432 and Pearson/Spearman correlation coefficient of 0.853/0.840.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.83-94
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• 2011

Main researching issue in affective computing is to give a machine the ability to recognize the emotion of a person and to react it properly. Efforts in that direction have mainly focused on facial and oral cues to get emotions. Postures have been recently considered as well. This paper aims to discriminate emotions posture by identifying and measuring the saliency of posture features that play a role in affective expression. To do so, affective postures from human subjects are first collected using a motion capture system, then emotional features in posture are described with spatial ones. Through standard statistical techniques, we verified that there is a statistically significant correlation between the emotion intended by the acting subjects, and the emotion perceived by the observers. Discriminant Analysis are used to build affective posture predictive models and to measure the saliency of the proposed set of posture features in discriminating between 6 basic emotional states. The evaluation of proposed features and models are performed using a correlation between actor-observer's postures set. Quantitative experimental results show that proposed set of features discriminates well between emotions, and also that built predictive models perform well.