• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.237-245
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• 2022

The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.455-462
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• 2022

This study is a descriptive research study to confirm the effect of learning flow and self-efficacy on self-leadership of nursing students who experienced non-face-to-face learning in the context of COVID-19. Data were collected from November 19 to December 31, 2021 for 237 nursing students, and t-test, ANOVA, correlation analysis, and regression analysis were performed for data analysis. As a result of analyzing the correlation between the subject's learning flow, self-efficacy and self-leadership. Self-leadership was showed a significant positive correlation between learning flow(r=.512, 𝜌<.001) and self-efficacy(r=.664, 𝜌<.001). On a result of regression analysis, significant variables were 24 years of age or older(𝛽=0.16, 𝜌=.001), learning flow(𝛽=0.19, 𝜌=<.001), and self-efficacy(𝛽=0.39, 𝜌=<.001). and explanatory power was 49.8%(F=40.01, 𝜌<.001). According to this study, it is necessary to develop and apply various programs that can enhance learning flow and self-efficacy in order to improve self-leadership.

• Journal of the Korean Society of Earth Science Education
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• v.3 no.1
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• pp.47-54
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• 2010

The purpose of this study is finding examine the Thinking Maps and how to use Thinking Maps effectively in Science Education. The result of this study were as follows: First, There are 8 type Maps, Circle Map, Tree Maps, Bubble Map, Double Bubble Map, Flow Map, Multi Flow Map, Brace Map, Bridge Map. Each Maps are useful in the following activities ; Circle Map-Express their thoughts. Tree Map-Activities as like determine the structure, classification, information organization. Bubble Maps-Construction. Double Bubble Map-Comparison of similarities and differences. Flow Map-Set goals, determine the result of changes in time or place. Multi Flow Map-Analysis cause and effect, expectation and reasoning. Brace Map-Analysis whole and part. Bridge Map-Activities need analogies. Second, each element of inquiry has 1~2 appropriate type of Thinking Maps. So student can choose the desired map. Third, the result of analysing of Science Curriculum Subjects, depending on the subject variety maps can be used. Therefore the Thinking Maps can be used for a variety on activities and subject. And student can be selected according to their learning style. So Thinking Maps are effective to improve student's Self-Directed Learning.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.617-626
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• 2021

This study was conducted to explore self-directed learning, learning flow, academic self-efficacy and academic achievement on nursing students and to investigate the major factors that influence academic achievement. Data were collected from October 15 to 19, 2021, data were analyzed utilizing the SPSS WIN 21.0 program. Participants in this study were 145 students of the college in J city. As a result of the study, self-directed learning was 3.67±0.65 points out of 5, learning flow was 3.35±0.76 points out of 5, academic self-efficacy was 3.43±0.94 points out of 5, and academic achievement was 3.85±1.13 points out of 5. The relationships between self-directed learning, learning flow, academic self-efficacy and academic achievement showed significant positive correlations. As a result of multiple regression analysis, factors influencing the academic achievements of nursing students were found to be learning flow and academic self-efficacy. Therefore, in order to increase academic achievement in nursing college students, it is necessary to develop educational programs to increase the academic self-efficacy, and to continuously check the effect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1557-1565
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• 2014

The purpose of this study was to identify the factors influencing learning flow of nursing student. Design of this study was a descriptive research. The participants for this study were 283 nursing college students with four-years curriculum in D city from June 14th to June 24th, 2013. Data were analyzed using descriptive statistics, t-test, one way ANOVA, Pearson's correlation and multiple regression with SPSS 18.0 Program. There were significant correlations among self-leadership, academic self-efficacy, major satisfaction, and the learning flow. As a multiple regression analysis, factors that have an effect on learning flow were self-leadership, and academic self-efficacy. These factors explain 58.2% of the variance in learning flow. Self-leadership, academic self-efficacy, and learning flow relationship were positive relevant. To enhance learning flow ability for nursing students, it is necessary to develop training program and academic environment for increasing self-leadership and academic self-efficacy.

• Journal of Convergence for Information Technology
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• v.10 no.11
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• pp.107-116
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• 2020

The purpose of this study was to identify the degree of self-leadership, academic self-efficacy, and learning flow of nursing college students to took both online and offline lectures, and to identify the factors that influence learning flow. Data were collected by using questionnaires from 152 students who were in 2nd year of the nursing college in G city, from September 7 to September 29, 2020. Data were analyzed by t-test, ANOVA, Pearson's correlation, and stepwise multiple regression using SPSS WIN 25.0 program. As a result of the study, Learning flow according to general characteristics showed significant differences in perceived health status, interpersonal relationship, major satisfaction, and grades. Statistically, learning flow showed a significantly positive correlation with self-leadership and academic self-efficacy. Influencing factors on learning flow were academic self-efficacy(β=.44, p<.001), self-leadership(β=.35, p<.001), and major satisfaction(β=-.14, p=.031) accounting for 57% of the total change. Based on this study, strategies to enhance academic self-efficacy and self-leadership are required to improve the learning flow of nursing students.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.80-89
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• 2014

A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit relaxation approach narrows the solution space by introducing regulatory factors, according to the relationship between the constraint equations and the optimization variables. The regulatory factors are designed by ILC method to ensure the optimality of final solution under a predefined confidence level. The optimization algorithm for S-OPF is completed based on the combination of limit relaxation and ILC and tested on the IEEE 14-bus system.

• Journal of Korean Library and Information Science Society
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• v.46 no.3
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• pp.119-140
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• 2015

The domestic and foreign standards of school libraries suggest that school library should be run to give useful and pleasant experiences to students. This study applies Csikszentmihalyi's 'flow theory' to analyze the relationships between students' flow experience and their satisfaction about school libraries use. The variables selected in this study are students' satisfaction, flow experience, library skill, challenge of library use, types of library use and students' learning styles. The research model is designed by using these 6 variables in this study. The data are collected from 293 students and analyzed by structural equation modeling. The results of this study are as follows: The entire casual relationships show that library skills influence in types of library use, types of library use affect students' learning styles and students' learning styles influence in satisfaction through flow. To improve students' satisfaction about school library use, this study proposes effective ways related to teacher librarians' role performances to expand students' flow experience and increase their library skills.

• Korean Management Science Review
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• v.31 no.3
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• pp.77-94
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• 2014

This study empirically investigated the relationships among inter-organizational cost management (IOCM), cooperation with suppliers, information exchange between partners, inter-organizational learning, control integration, and the supply-chain performance of a firm. The results showed that the adoption of IOCM positively affects the collaboration between buyers and suppliers, which also leads to the increased information flow between them. According to the results of this study, it was found that inter-organizational information flow causes inter-organizational learning, and this learning contributes to the improved supply-chain performance. In this study, the positive effects of the cooperation with suppliers through IOCM on the control integration in supply-chains were not empirically confirmed. However, the impact of IOCM on control integration was significant and positive. Finally, the fact that the enhanced control integration can improve the supply-chain performance of a firm was empirically demonstrated.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.597-604
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• 2020

This is a narrative research study conducted on the subject in order to understand the relationship between the meta-cognition, learning flow, and problem solving ability of nursing students in online class, and to find out the factors that influence problem solving ability, 88 students enrolled in 2nd and 3rd grade students who participated in online classes at G city universities. The analysis method was analyzed by means, standard deviation, t-test, one-way ANOVA, Pearson correlation, and stepwise multiple regression using SPSS version WIN 23.0. As a result of the study, the difference between learning flow and problem-solving ability according to general characteristics was significantly different depending on the perception of nurses after learning and the motivation for admission to the department of nursing, and the problem-solving ability was positively correlated with metacognition and learning flow. There was a relationship, and metacognition and learning flow were significant variables that influenced problem solving ability. The conclusion of the study is considered to be the basic data for the development of a systematic program that can increase the learning flow and meta-cognition to increase problem solving ability amid the change from nursing education to online classes, and to change the teaching method.