• Journal of the Semiconductor & Display Technology
• /
• v.20 no.3
• /
• pp.120-124
• /
• 2021

Recently, human attribute recognition (HAR) attracts a lot of attention due to its wide application in video surveillance systems. Recent deep-learning-based solutions for HAR require time-consuming training processes. In this paper, we propose a post-processing technique that utilizes the historical video frames to improve prediction results without invoking re-training or modifying existing deep-learning-based classifiers. Experiment results on a large-scale benchmark dataset show the effectiveness of our proposed method.

• KEPCO Journal on Electric Power and Energy
• /
• v.8 no.2
• /
• pp.137-141
• /
• 2022

To inspect the power facility faults using artificial intelligence, it need that improve the accuracy of the diagnostic model are required. Data augmentation skill using generative adversarial network (GAN) is one of the best ways to improve deep learning performance. GAN model can create realistic-looking fake images using two competitive learning networks such as discriminator and generator. In this study, we intend to verify the effectiveness of virtual data generation technology by including the fake image of power facility generated through GAN in the deep learning training set. The GAN-based fake image was created for damage of LP insulator, and ResNet based normal and defect classification model was developed to verify the effect. Through this, we analyzed the model accuracy according to the ratio of normal and defective training data.

• Journal of The Korean Association of Information Education
• /
• v.8 no.2
• /
• pp.141-153
• /
• 2004

Pupils with learning impediments in elementary schools have difficulties in learning numerical calculations. Numerical concepts, the basis of numerical calculations, require repetitious exercises, and it has been widely reported that computer-mediated learning motivates the learners to concentrate on their learning for longer hours. The aim of the research is to develop and apply a Web-based courseware to experimental groups to improve learning numerical concepts of the learners with learning difficulties in elementary school and to discuss the effects of the results. The courseware is designed to improve the numerical concepts of the learners through many thought activities. The experiment shows effectiveness of the learning activities to improve learning numerical concepts for students with learning difficulties, categorized into two groups - an experimental group and a control group, and also it shows positive responses on improvement of their calculation ability.

• Journal of Korean Library and Information Science Society
• /
• v.41 no.2
• /
• pp.81-106
• /
• 2010

The purpose of this study is to evaluate the effectiveness and problems of an independent research program. The researcher has collected and analysed data from 99 teachers and 825 students who participated in the 'Book Writing' program of Daegu Metropolitan City Board of Education. As an way to improve teaching and learning methods of schools, the 'Book Writing' program is evaluated to be effective and relevant. In conclusion, the researcher suggested several ways to improve the program.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.24 no.3
• /
• pp.181-188
• /
• 2017

Purpose: Competency in physical assessment is an important component of nursing practice. However, some physical assessment skills are not being utilized within the current teacher-centered, content-heavy curriculum. This study was conducted to identify the effects of student-centered, self-directed learning in the physical assessment class. Methods: An experimental study with a post-test only control group design was used to compare an intervention group that was provided self-directed learning classes and a control group that was provided traditional lecture and practice classes. Competency in physical assessment, academic self-confidence, and learning satisfaction were evaluated. Collected data were analyzed using $x^2$-test (Fisher's exact test) and independent t-test. Results: Competency in physical assessment was significantly higher in the experimental group. However, academic self-confidence and learning satisfaction were not significantly different between the groups. Conclusion: The findings in this study indicate that self-directed learning can improve nursing students competency in physical assessment and that self-directed learning is a good education method to improve nursing students' competency in physical assessment during clinical practice and perform quality patient care by making active use of physical assessment skills.

• The Journal of the Korea Contents Association
• /
• v.18 no.3
• /
• pp.215-227
• /
• 2018

Research on ways to improve e-learning effectiveness has been actively conducted due to the increased numbers of web-based e-learning learners. Of many variables related to e-learning effectiveness, self-regulated learning strategy and presence have been reported as major factors that influences academic achievement in e-learning settings. The purpose of this study was to investigate the effect of self-regulated learning strategy and presence on academic achievement in web-based e-learning. In addition, this study tried to provide useful basic data for successful support and design of e-learning by verifying the mediating effect of these variables. As a result, it was verified that teaching presence and social presence have mediating effects in the relationship between self-regulated learning strategy and perceived achievement in web-based e-learning. Moreover, subjective perception of student's academic achievement played a mediating role between learners' perceived presence and academic achievement. Through this study, it is verified that it is necessary to search for ways to improve the level of learners' teaching presence and social presence in web-based e-learning design in order to eventually improve academic achievement.

• 대한공업교육학회지
• /
• v.33 no.1
• /
• pp.213-232
• /
• 2008

The purpose of this study is that after developing and applying multimedia rich project-based learning methods in a Korean Special high school(Industrial and Technical Area), to provide how the learners recognize the effectiveness for it and to obtain the implication from effectiveness which they recognized. This study was conducted as action research based on a high school situation. The study included 100 participants in two classes purposively selected from 9 classes at 450 student high school. Data were collected through observations, surveys and interview. Results indicated the multimedia rich project-based learning allowed students to understand the contents of major subject overall, improve the handling skill for computer multimedia and be better at investigating and organizing skill for subject content. Also, it allowed them to improve interaction among students and participation, motivation, satisfaction, interest and confidence for learning. And there was close cooperation with and among group members to create better products.. Finally, the flexibility in the project-based learning environment allowed the participants to make decisions about their abilities, resources, and plans. Recommendations and implications for teacher educators as well as inservice and preservice teachers are also presented.

• Journal of Information Science Theory and Practice
• /
• v.7 no.3
• /
• pp.6-20
• /
• 2019

Learning analytics, or educational data mining, is an emerging field that applies data mining methods and tools for the exploitation of data coming from educational environments. Learning management systems, like Moodle, offer large amounts of data concerning students' activity, performance, behavior, and interaction with their peers and their tutors. The analysis of these data can be elaborated to make decisions that will assist stakeholders (students, faculty, and administration) to elevate the learning process in higher education. In this work, the power of Excel is exploited to analyze data in Moodle, utilizing an e-learning course developed for enhancing the information computer technology skills of school teachers in primary and secondary education in Greece. Moodle log files are appropriately manipulated in order to trace daily and weekly activity of the learners concerning distribution of access to resources, forum participation, and quizzes and assignments submission. Learners' activity was visualized for every hour of the day and for every day of the week. The visualization of access to every activity or resource during the course is also obtained. In this fashion teachers can schedule online synchronous lectures or discussions more effectively in order to maximize the learners' participation. Results depict the interest of learners for each structural component, their dedication to the course, their participation in the fora, and how it affects the submission of quizzes and assignments. Instructional designers may take advice and redesign the course according to the popularity of the educational material and learners' dedication. Moreover, the final grade of the learners is predicted according to their previous grades using multiple linear regression and sensitivity analysis. These outcomes can be suitably exploited in order for instructors to improve the design of their courses, faculty to alter their educational methodology, and administration to make decisions that will improve the educational services provided.

• Communications for Statistical Applications and Methods
• /
• v.29 no.2
• /
• pp.177-191
• /
• 2022

This paper addresses the use of machine learning methods for causal estimation of treatment effects from observational data. Even though conducting randomized experimental trials is a gold standard to reveal potential causal relationships, observational study is another rich source for investigation of exposure effects, for example, in the research of comparative effectiveness and safety of treatments, where the causal effect can be identified if covariates contain all confounding variables. In this context, statistical regression models for the expected outcome and the probability of treatment are often imposed, which can be combined in a clever way to yield more efficient and robust causal estimators. Recently, targeted maximum likelihood estimation and causal random forest is proposed and extensively studied for the use of data-adaptive regression in estimation of causal inference parameters. Machine learning methods are a natural choice in these settings to improve the quality of the final estimate of the treatment effect. We explore how we can adapt the design and training of several machine learning algorithms for causal inference and study their finite-sample performance through simulation experiments under various scenarios. Application to the percutaneous coronary intervention (PCI) data shows that these adaptations can improve simple linear regression-based methods.

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.2
• /
• pp.443-450
• /
• 2008

Peer assessment is the process of assessment of students by other students and one form of innovative assessment. It actively involves students in the assessment process and is generally agreed that such involvement enhances the quality and effectiveness of the learning process, since assessing something and benchmarking process is a powerful aid to mastering it themselves. It is more effective on the hard courses for them to understand. In this article we present a peer assessment technique which was applied to students enrolled in a mathematical statistics course and a historical course. In order to measure the effectiveness of the technique, students had to evaluate their colleagues based on predefined criteria and a comparison is presented between the instructor assessments and the peer assessment.