Proceedings of the Korea Information Processing Society Conference
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2022.11a
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pp.594-596
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2022
Over the last decades, deep neural networks have demonstrated significant success in various tasks. To address the special vision task, choosing a hot network as backbone to extract feature is a common way in both research and industry project. However, the choice of backbone usually requires the expert experience and affects the performance of the classification task. In this work, we propose a novel idea to support backbone decision-making by exploring the feature attribution and weights distribution of hidden layers from various backbones. We first analyze the visualization of feature maps on different size object and different depth layers to observe learning ability. Then, we compared the variance of weights and feature in last three layers. Based on analysis of the feature and wights, we summarize the traits and commonalities of existing networks.
International conference on construction engineering and project management
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2011.02a
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pp.38-45
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2011
Studies have shown that infrastructure projects have continued to experience significant delays and cost overrun over an extended period of time and no evidence of learning ever have happened [1] [2]. Various causes contribute to the bias towards overrun [3]. This study contributes to literature by developing and subsequently validating a set of hypothesized relationships between project complexity and project performance. The results show that project complexity is associated with both the magnitude and variance of overrun. Further, the extent and magnitude of the positive bias towards overrun are moderated by project complexity.
Journal of Korean Society of Disaster and Security
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v.15
no.2
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pp.45-56
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2022
The countermeasure for the shortage of water during dry season and drought period has not been considered with return flowrate in detail. In this study, the outflow of STP was predicted through a data-based machine learning model, LSTM. As the first step, outflow, inflow, precipitation and water elevation were utilized as input data, and the distribution of variance was additionally considered to improve the accuracy of the prediction. When considering the variability of the outflow data, the residual between the observed value and the distribution was assumed to be in the form of a complex trigonometric function and presented in the form of the optimal distribution of the outflow along with the theoretical probability distribution. It was apparently found that the degree of error was reduced when compared to the case not considering where the variance distribution. Therefore, it is expected that the outflow prediction model constructed in this study can be used as basic data for establishing an efficient river management system as more accurate prediction is possible.
Background: As the medical knowledge base grows at an accelerating rate, evidence-based clinical performance becomes increasingly important for providing quality care. Previous studies have highlighted the need to promote job crafting to actualize evidence-based practical skills in the medical field. This study aimed to investigate the degree of evidence-based practice among dental hygienists and assess the impact of job crafting on the evidence-based practical skills of dental hygienists. Methods: Dental hygienists working at dental hospitals and clinics in Seoul and Gyeonggi Province were surveyed between February 28 and April 6, 2023. The sample was comprised of 267 participants. The hypotheses were tested independent t-tests, one-way analysis of variance, Pearson's correlation coefficients, and multiple regression analyses using SPSS 29.0. Results: The degree of job crafting by dental hygienists demonstrated significant differences based on educational attainment, workplace size, and workplace type. Evidence-based practical skills exhibited significant variations based on educational attainment and job position. All job crafting subfactors demonstrated positive correlations with evidence-based practical skills. The job crafting subfactors affecting the evidence-based practical skills of dental hygienists were 'increasing structural job resources' and 'increasing challenging job demands,' which together explained 38.7% of the variance in evidence-based practical skills. Conclusion: This study demonstrates that job crafting was positively and significantly correlated with evidence-based practical skills. To strengthen the job crafting ability of dental hygienists, improving environmental conditions and fostering an organizational culture that motivates continued participation in education is necessary. The development and promotion of programs that enable learning of the latest evidence should be actively pursued. Additionally, regular attendance at workshops and participation in organizational evidence-based practice education programs are necessary.
This study is a descriptive study designed to identify the relationships among positive psychological capital, physical health status, depression, interpersonal relationship and learning flow. The subjects were 181 nursing students and the data collection was from May 8 to June 20, 2019. Data analysis methods were descriptive statistics, t-tests, ANOVA, Pearson's correlation coefficients, and stepwise multiple regression, using the SPSS 22.0 program. Positive psychological capital showed statistical differences according to age, grade, motive for major choice, major satisfaction and subjective health status. Positive psychological capital was correlated with depression(r=-.454, p<.001), interpersonal relationship(r=.611, p<.001) and learning flow(r=.452, p<.001). The factors affecting learning flow were positive psychological capital(β=.414, p<.001), major satisfaction(β=.177, p=.014), and grade(β=-.150, p=.026), which explained 24.4% of the variance. Therefore, it is necessary to develop and apply educational programs that can promote positive psychological capital in nursing students.
A fault is a geological structure that can be a migration path or a cap rock of hydrocarbon such as oil and gas, formed from source rock. The fault is one of the main targets of seismic exploration to find reservoirs in which hydrocarbon have accumulated. However, conventional fault detection methods using lateral discontinuity in seismic data such as semblance, coherence, variance, gradient magnitude and fault likelihood, have problem that professional interpreters have to invest lots of time and computational costs. Therefore, many researchers are conducting various studies to save computational costs and time for fault interpretation, and machine learning technologies attracted attention recently. Among various machine learning technologies, many researchers are conducting fault interpretation studies using the support vector machine, multi-layer perceptron, deep neural networks and convolutional neural networks algorithms. Especially, researchers use not only their own convolution networks but also proven networks in image processing to predict fault locations and fault information such as strike and dip. In this paper, by investigating and analyzing these studies, we found that the convolutional neural networks based on the U-Net from image processing is the most effective one for fault detection and interpretation. Further studies can expect better results from fault detection and interpretation using the convolutional neural networks along with transfer learning and data augmentation.
Journal of the Korean Applied Science and Technology
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v.39
no.4
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pp.542-551
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2022
The purpose of this study is a descriptive survey research in order to grasp the relationship between learning satisfaction, self-efficacy and critical thinking of nursing students and the influence factors of critical thinking who have experienced non-face-to-face online lectures. Participants were 191 nursing students in G city. Data collection was conducted from May 2 to 30, 2022. Data were collected with structured questionnaires and analyzed using t-test, ANOVA, Pearson's correlation analysis, and multiple regression analysis. As a result of there were positive correlations between the learning satisfaction (r=.20, p=.005) and self-efficacy (r=.61, p<.001) that critical thinking. Factors affecting critical thinking of nursing college students were self-efficacy (𝛽=.66, p<.001), major of interest-very interesting (𝛽=.41, p<.001), learning satisfaction (𝛽=-.31, p<.001), Grade-third (𝛽=.26, p<.001), major of interest-interesting (𝛽=.21, p=.029), Grade-second (𝛽=.16, p<.001) and which explained 60.1% of the variance. Based on the results of this study, in order to promote critical thinking among nursing college students, it is necessary to by grade and the interest of major individual counseling and guidance. Also develop and implement various programs that can improve self-efficacy and class satisfaction.
The purpose of this study was to investigate knowledge, attitudes and practices of women toward breast self-examination and to identify factors that may influence compliance with breast examination. The subjects for this study were 282 women in three hospitals located in In-Chun. Data were collected during the period from October 15 to 30, 1993 by means of a structured questionnaire. The data were analyzed using the SAS program and include descriptive statistics, 1-test, ANOVA, Pearson correlation coefficient and stepwise multiple regression. The results of study are as follows : 1. The mean knowledge score for the total sample was 13.58. Factors affecting the women's knowledge of breast cancer and BSE were : age, level of education, experience with breast cancer patients, experience in learning BSE, information about BSE, self-practice of BSE, level of intention to perform BSE, and participation in a BSE class. 2. Elements related to attitude included : (a) perceived feeling of susceptibility to breast cancer, and (b) belief about the effectiveness of BSE. The mean perceived susceptibility score was 1.62 and the mean effectiveness score was 4.22. Factors affecting the women's perceived susceptibility to breast cancer were exercise for health, level of intention to perform BSE , intention to recommend to others and self-practice of BSE. The relation between the womens' belief about effectiveness of BSE and level of intention to perform BSE and intention to recommend to others were statistically significant. 3. The mean self-practice score for the total sample was 4.01. Factors affecting the women's practice were experience with breast cancer patients, information about BSE, experience in learning BSE, enlisting the help of significant peers, and level of intention to perform BSE. Results indicated 35.8% of the total sample practiced BSE. The most frequent reason women gave for not performing BSE was “Didn’t knew about BSE technique”, “Didn’t think do it”. 4. No relation was found between knowledge and attitudes and practices. 5. When all the variables were examined for their contribution to the variance in the practice of BSE, it was found that confidence in ability to detect a mass by BSE, knowledge about breast cancer and BSE, and experience with breast cancer patients were significant variables and explained 35.8% of the variance. From the results of this study it can be said that women need to be taught proper BSE technique so they can become more proficient in detecting breast abnormalities.
Park, Seung-Min;Park, Jun-Heong;Lee, Young-Hwan;Ko, Kwang-Eun;Sim, Kwee-Bo
Journal of the Korean Institute of Intelligent Systems
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v.20
no.6
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pp.884-889
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2010
Recently, a music genre classification has been studied. However, experts use different criteria to classify each of these classifications is difficult to derive accurate results. In addition, when the emergence of a new genre of music genre is a newly re-defined. Music as a genre rather than to separate search should be classified as emotional words. In this paper, the feelings of people on the basis of brightness and darkness tries to categorize music. The proposed classification system by applying VCM(Variance Considered Machines) is the contrast of the music. In this paper, we are using three kinds of musical characteristics. Based on surveys made throughout the learning, based on musical attributes(beat, timbre, note) was used to study in the VCM. VCM is classified by the trained compared with the results of the survey were analyzed. Note extraction using the MATLAB, sampled at regular intervals to share music via the FFT frequency analysis by the sector average is defined as representing the element extracted note by quantifying the height of the entire distribution was identified. Cumulative frequency distribution in the entire frequency rage, using the difference in Timbre and were quantified. VCM applied to these three characteristics with the experimental results by comparing the survey results to see the contrast of the music with a probability of 95.4% confirmed that the two separate.
The purpose of this thesis was to improve the plans and methods of teaching and learning activities and contribute to developing teachers` quality and reeducating them by investigating teachers' attitudes toward teaching and learning have a significant effect on the students' attitudes toward mathematics and the students' ability development at mathematics. The inventory was composed of 56 items : three main areas and eight sub-areas. Added seven background factors were sex, by whom was established (is it a public or nongovernmental \ulcorner), teaching career, age, what kind of school (is it general or vacational high school or middle school\ulcorner), region, college. For this analysis of materials used SAS program. And analysis of variance was applied on the seven background factors. All subjects in this study were 341 secondary school mathematics teachers in pusan city and Kyungsangnam-do were surveyed by the questionnaire of Likert type to which the respondents' seven background elements were added. Main results this study were as follows : 1. The overall attitude of the measured secondary school mathematics teachers tends to be positive but a little indifferent. Also attitude toward the students was a little more positive than the other attitudes. 2. There were significant differences (1%) among the sub-level areas except three of them. (r = 0.17~0.60) 3. There were significant differences (5%) by the result of Multiple comparison test among the schools in learning and teaching. So the teachers working at middle schools and general high schools were more positive than those working at vocational high schools. 4. The result of comparison among region was that teachers working in towns and cities were more positive than those working in the country. But there was no significant difference between the teachers working in large cities and those working in other region. 5. There was no significant difference in the overall attitudes toward teaching and learnig among the sex, by whom was established(is it public or nongovernmental\ulcorner), teaching career, age, college. The study left much deficiency to be desired and has to be followed by a continuing study to make it better. For the following study, it is necessary to examine the validity and reliability of the measuring tools more thoroughly and investigate the attitudes with sufficient samples all over the country.
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