• Journal of radiological science and technology
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• v.44 no.6
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• pp.635-643
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• 2021

The results of empirical researches on the diagnosis of lung cancer are insufficient, so it is limited to objectively judge the clinical possibility and utilization according to the accuracy of diagnosis. Thus, this study retrospectively analyzed the lung cancer diagnostic performance of PET-MRI (Positron Emission Tomography-Magnetic Resonance Imaging) by using the decision matrix. This study selected and experimented total 165 patients who received both hematological CEA (Carcinoembryonic Antigen) test and hybrid PET-MRI (¹⁸F-FDG, 5.18 MBq/kg / Body TIM coil. VIVE-Dixon). After setting up the result of CEA (positive:>4 ㎍/ℓ. negative:<2.5㎍/ℓ) as golden data, the lung cancer was found in the image of PET-MRI, and then the SUV_max (positive:>4, negative:<1.5) was measured, and then evaluated the correlation and significance of results of relative diagnostic performance of PET-MRI compared to CEA through the statistical verification (t-test, P>0.05). Through this, the PET-MRI was analyzed as 96.29% of sensitivity, 95.23% of specificity, 3.70% of false negative rate, 4.76% of false positive rate, and 95.75% of accuracy. The false negative rate was 1.06% lower than the false positive rate. The PET-MRI that significant accuracy of diagnosis through high sensitivity and specificity, and low false negative rate and false positive rate of lung cancer, could acquire the fusion image of specialized soft tissue by combining the radio-pharmaceuticals with various sequences, so its clinical value and usefulness are regarded as latently sufficient.

• Journal of Technologic Dentistry
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• v.43 no.4
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• pp.186-193
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• 2021

Purpose: The purpose of the study was to determine the general characteristics of students in dental technology departments; the correlations among their immersion in learning, class satisfaction, and academic achievement; factors influencing online learning experience; ways to improve students' class satisfaction; and basic data for designing effective online courses. Methods: A total of 300 questionnaires were produced and distributed to dental technology students from September 29 through October 8, 2020. The outcome was analyzed using IBM SPSS Statistics ver. 25.0. A significance level of α=0.05 was used for reliable verification. Results: Immersion in learning, class satisfaction, and academic achievement were relatively high among students who studied on a regular basis, and class satisfaction and academic achievement were relatively high among students who studied with almost no interruption. Concerning the correlations between academic achievement, immersion in learning, and class satisfaction in online learning, the correlation between academic achievement and class satisfaction was the highest at r=0.862. Class satisfaction was the largest factor that influenced academic achievement, and the higher students' immersion in learning and class satisfaction were, the higher their academic achievement was. Conclusion: The research is a case study that investigated the general characteristics of dental technology department students and the correlations among their immersion in learning, class satisfaction, and academic achievement. The study outcome could be used in determining factors that influence online learning and designing effective online courses that improve learner satisfaction.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.3
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• pp.285-292
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• 2022

The objective of this study is to investigate whether CGS generated in IGCC satisfies the fine aggregate quality items specified in KS F 2527(Concrete Aggregate) through the pretreatment process system and the quality improvement the system. The statistical significance of the pretreatment process was analyzed through Repeated Measurements ANOVA as measured values according to individually pretreatment process system. As a result of the analysis, In the case of CGS fine aggregate quality before and after the pretreatment process system, the density increased 5.2 %, the absorption rate decreased by 1.86 %, the 0.08 mm passing ratio decreased by 2.25 %, and Fineness Modulus and Particle-size Distribution were also found to be adjustable. It was found that the pretreatment process system was significant in improving the quality of CGS.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.10-17
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• 2022

Currently, in Korea, lower and upper tier qualifying quantities of the 97 substances requiring preparation for accidents have been designated. The information on the submission of chemical accident prevention management plan varies depending on whether the handling volume is above or below the lower or upper qualifying quantity. Because the criteria of the lower and upper qualifying quantities of substance requiring preparation for accidents are not stipulated in the Chemical Substances Control Act, this study attempted to establish a criterion through significance verification. In addition, the study investigated whether these qualifying quantities are related to the Globally Harmonized System of Classification and Labelling of Chemicals (GHS), toxic concentration endpoint, and National Fire Protection Association (NFPA). Finally, by comparing the risk categorization of the GHS, endpoint, and NFPA, it was evaluated whether the circulation-volume-based risk categorization of the substance requiring preparation for accidents that are in the top 13 is appropriate. The qualifying quantities of benzene, toluene, and sulfuric acid needed to be adjusted upward, while those of methyl alcohol and ammonia were adjusted downward from the current qualifying quantities. It is required to establish a quantified criterion that fully reflects the domestic situations in Korea and various indicators such as toxicity, physicochemical properties, and circulation volume for the qualified criterion of hazardous chemical substances. The study is expected to be helpful in establishing an efficient system by systematizing the criterion for qualifying quantity.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.543-551
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• 2022

The purpose of this study was to investigate the mediating effect of academic self-efficacy in the process that nursing students' task value affects class participation. The subjects of this study were 161 second-year students of the Department of Nursing at K University located in G city, and the data collection period was from October 5 to October 14, 2020. The mediating effect of academic self-efficacy in the relationship between task value and class participation was analyzed using Baron and Kenny's 3-step mediating effect verification procedure using simple and multiple regression analysis and the statistical significance of mediating effects was verified by the Sobel test. As a result of this study, task value and academic self-efficacy were major factors influencing class participation, and academic self-efficacy was found to be a significant partial mediating variable in the relationship between task value and class participation. These factors explained 55% of class participation. In order to increase learners' class participation, an integrated approach that can improve task value and academic self-efficacy is needed.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.66-83
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• 2022

Artificial Intelligence (AI) is to assumed to be one of next generation technology which determine technological competitiveness and strategic advantage of a certain country. By using the patent data, this study aims to have a comparative analysis of the technological competitiveness of evolving artificial intelligence at different stages of development among the five largest intellectual property offices in the world (IP5). For the analysis data, all AI technology patent data from 1956 to 2019 were utilized according to the classification system presented in the "WIPO 2019 Technology Trend: Artificial Intelligence" report published by the World Intellectual Property Organization (WIPO) in 2019. The results shows that China has already surpassed the United States in terms of the number of patent applications in the field of artificial intelligence technology. However, in the domains of the United States, Europe, Japan, and Korea, the technology competitiveness of the United States is far ahead of China. Interestingly, the rate of increase of Korea's technology competitiveness is also very fast, and it has been shown that the technology strength is ahead of China in non-Chinese domains. The significance of this study can be found in the fact that the temporal and spatial change process of technological competitiveness of significant countries in the field of artificial intelligence technology artificial intelligence was viewed as a macro-framework using the technology index (TS) the differences were compared.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.1
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• pp.5-16
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• 2023

Purpose: This methodological study developed a scale that reflects the social support characteristics of nursing students who have experienced clinical practice and verified their reliability and validity. Methods: The 37 initial items of the scale were derived based on the results of a previous study that analyzed the concept of nursing students' social support. The initial items were revised through content validity verification, and 29 preliminary items were finally selected. Data were collected from 220 students enrolled in a nursing department in Jeollabuk-do, who had clinical practice experience, and 205 surveys were used for the final analysis. The data collection period was from March 11 to April 26, 2022. An exploratory factor analysis was performed using maximum likelihood factor extraction and varimax rotation. Results: The social support scale for nursing students who have experienced clinical practice consisted of a total of three sub-factors and 17 items. The three sub-factors were 'support from family and friends' (eight items), 'support from school, professors, and clinical instructors' (seven items) and 'support from department seniors' (two items). The reliability of the developed scale was found to be high, with a Cronbach's alpha of .93. As a result of verifying the criterion validity of the developed scale, the correlation between the criterion tool and the scale developed in this study was statistically significant. Conclusion: The significance of this study is that it developed a scale to measure social support for the first time among nursing students in Korea.

• Journal of ILASS-Korea
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• v.28 no.1
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• pp.1-9
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• 2023

In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R² and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.891-897
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• 2021

There is a need for a technology that can quickly and accurately analyze soil carbon contents. Existing soil carbon analysis methods are cumbersome in terms of professional manpower requirements, time, and cost. It is against this background that the present study leverages the soil physical properties of color and water content levels to develop a model capable of predicting the carbon content of soil sample. To predict the total carbon content of soil, the RGB values, water content of the soil, and lux levels were analyzed and used as statistical data. However, when R, G, and B with high correlations were all included in a multiple regression analysis as independent variables, a high level of multicollinearity was noted and G was thus excluded from the model. The estimates showed that the estimation coefficients for all independent variables were statistically significant at a significance level of 1%. The elastic values of R and B for the soil carbon content, which are of major interest in this study, were -2.90 and 1.47, respectively, showing that a 1% increase in the R value was correlated with a 2.90% decrease in the carbon content, whereas a 1% increase in the B value tallied with a 1.47% increase in the carbon content. Coefficient of determination (R²), root mean square error (RMSE), and mean absolute percentage error (MAPE) methods were used for regression verification, and calibration samples showed higher accuracy than the validation samples in terms of R² and MAPE.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.6
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• pp.317-325
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• 2015

The aim of this research was to investigate the relationship among team learning behavior, individual creativity, team shared mental model(TSMM), mutual performance monitoring on team creativity and then providing the fundamental data on the education. Also it intended to acknowledge relative predictive power on team creativity of independent variables. The total of 257 college students participated the team learning for 6 weeks in a semester. Pearson's product moment correlation and regression analysis were used for data analysis and testing of significance of verification, The main research results are summarized as follows; team learning behavior, TSMM, mutual performance monitoring had no significant effects on three subfactors of team creativity such as novelty, resolution, elaboration & synthesis. Therefore followed researches are needed about inter and intra processing of team creativity.