• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1450-1463
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• 2019

The problem towards crowd behavior recognition in a serious clustered scene is extremely challenged on account of variable scales with non-uniformity. This paper aims to propose a crowed behavior classification framework based on a transferring hybrid network blending 3D res-net with inception-v3. First, the 3D res-inception network is presented so as to learn the augmented visual feature of UCF 101. Then the target dataset is applied to fine-tune the network parameters in an attempt to classify the behavior of densely crowded scenes. Finally, a transferred entropy function is used to calculate the probability of multiple labels in accordance with these features. Experimental results show that the proposed method could greatly improve the accuracy of crowd behavior recognition and enhance the accuracy of multiple label classification.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.312-319
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• 2023

This study aims to enhance the engineering education for non-majors by incorporating the concept of Global Citizenship Education and addressing the need for education that responds to climate and ecological changes. The study uses robot programming as a tool to foster the development of global citizens. Non-majors often struggle with producing more than just motionless forms or solid productions, due to a lack of understanding of mechanisms and coding. The study proposes the use of the Convergence D-SteamRobot (DSR) to address this issue by blending humanities and engineering. This is achieved by presenting problems through books to increase empathy, integrating simple machine mechanisms, and creating prototypes to solve self-defined problems. Through this process, learners determine the SDGs topic they want to solve and learn about the simple mechanical mechanism involved in producing the prototype. The educational model provides a constructivist learning environment that emphasizes empathy and exploration, encourages peer-learning, and improves divergent thinking and problem-solving skills.

• International Journal of Contents
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• v.18 no.2
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• pp.47-57
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• 2022

e-Learning content can be defined as digital content to achieve educational goals. Since it is an educational material that can be distributed in offline, online, and mobile environments, it is important to create content that meets the learner's education environment and educational goals. In particular, if the learner is a public official, the vision, philosophy, and characteristics of each local government must reflect. As non-face-to-face online education expands further due to the COVID-19 pandemic, local governments that have relied on onsite education in the past urgently require developing strong basic competency education and special task competency content that reflect regional characteristics. Such e-learning content, however, hardly exists and the ability to independently develop them is also insufficient. In this circumstance, this case study describes the process of self-production of e-learning content suitable for Busan's characteristics by the Human Resource Development (HRD) Institute of Busan City, a local government. The field of instructional design and instructional technology is always evolving and growing by blending technological innovation into instructional platform design and adapting to the changes in society. Busan HRD Institute (BHI), therefore, tried to implement blended learning by developing content that reflected the recent trend of micro-learning in e-learning through a detailed analysis. For this, an e-learning content developer with certain requirements was selected and contracted, and the process of developing content through a collaboration between the client and developer was described in this study according to the ADDIE model of Instructional Systems Development (ISD).

• Hwankyungkyoyuk
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• v.19 no.3
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• pp.20-39
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• 2006

The purpose of the study is to develop e-Learning contents of environmental education for middle school students. The contents were developed based on literature review, the analysis of domestic and foreign programs and e-Learning contents on environmental education and expert advice. There are five main characteristics. First, this program has 12 sessions and is divided into six parts: introduction, air, water, animals and plants, soil, and resources and energy. Second, the contents were developed with consideration of middle school students' consist of optimized for learners by analyzing the needs of middle school students. Third, each part consists of five steps: "open", "unfold", "foster", "strengthen & refine", and "addition." Fourth, the contents have been developed in line with SCORM, an international standard for distnt education, to ensure reusability, accessibility, interoperability, and durability. Fifth, the contents are developed for blending online and off-line education. Developed program evaluated by 8 environmental education experts according to 10 evaluation item of total contents and contents development structure. In result, it evaluated comparatively high score.

• Current Optics and Photonics
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• v.8 no.3
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• pp.246-258
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• 2024

In aerospace and energy engineering, the reconstruction of three-dimensional (3D) temperature distributions is crucial. Traditional methods like algebraic iterative reconstruction and filtered back-projection depend on voxel division for resolution. Our algorithm, blending deep learning with computer graphics rendering, converts 2D projections into light rays for uniform sampling, using a fully connected neural network to depict the 3D temperature field. Although effective in capturing internal details, it demands multiple cameras for varied angle projections, increasing cost and computational needs. We assess the impact of camera number on reconstruction accuracy and efficiency, conducting butane-flame simulations with different camera setups (6 to 18 cameras). The results show improved accuracy with more cameras, with 12 cameras achieving optimal computational efficiency (1.263) and low error rates. Verification experiments with 9, 12, and 15 cameras, using thermocouples, confirm that the 12-camera setup as the best, balancing efficiency and accuracy. This offers a feasible, cost-effective solution for real-world applications like engine testing and environmental monitoring, improving accuracy and resource management in temperature measurement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.187-196
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• 2017

In using lecture evaluation methods to improve the quality of education, most universities need to reflect the changes in the educational environment. The transformation of university education into a mixed learning environment blending face-to-face education and online education necessitates the development of appropriate lecture evaluation items. For this purpose, we analyzed the items and the factor analysis for the students of C university in Daejeon. The primary data were carried out with 47 measurement items in 10 domains, such as planning and preparation of lectures, which were found through previous research analysis. Secondary data were validated by using the items confirmed through analysis of preliminary test data. The study results showed that 20 items including six domains such as planning and preparation of lectures, learning materials, learning tasks, instruction media, online course test and grades were derived. These study results suggest that universities lectures should be evaluated to ensure improvement.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.105-113
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• 2021

Due to the recent coronavirus outbreak, many universities in Korea have started to implement remote education. Accordingly, the Ministry of Education has stated its plans to continuously encourage and maintain remote learning as the future innovation model for education and suggested the need for a diverse range of remote learning models. However, studies on the development of practical learning models have not been carried out actively until now. Particularly, there are not many case studies in the field of design, especially regarding mobile website development. As means to improve the newly designed practice environment, this study therefore proposes the "modoo" project that offers domain creation and online marketing services. As a result of this study, the researcher suggests the use of a mixed(blending) teaching method and realized that the effectiveness of education multiplies when project-based learning and flipped learning is combined appropriately. The research methodology was divided into two big sections, education content and operations, and the effect was evaluated using the course evaluations. The study results confirmed that the applicability will increase given that learning satisfaction levels increased by more than 5% compared to face-to-face learning.

• Korean Journal of Radiology
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• v.23 no.7
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• pp.752-762
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• 2022

Objective: To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Materials and Methods: Post-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods. Results: The NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR (p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V (p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP (p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V (p < 0.001). Conclusion: For pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.27 no.2
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• pp.109-118
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• 2016

Objectives: The aim of this study was to develop the computerized Comprehensive Learning Test-Reading (CLT-R) to evaluate the cognitive processes and achievements related to their basic reading ability and identify dyslexia in children and adolescents in South Korea. We also obtained the normative data and evaluated the reliability and validity of the test. Methods: We developed the CLT-R, including the word attack/nonword decoding, paragraph reading, sound blending, nonword repetition, rapid automatized naming, letter-sound matching, visual attention, orthography awareness, and digit span tests, for the purpose of diagnosing dyslexia. We investigated the reliability and validity of the tests and gathered the normative data from 399 subjects (male 48.9%), aged 5-14 years, from the last grade in kindergarten to middle school, dwelling in Seoul and Gyeonggi Province, South Korea. Results: No statistical differences were observed between the means of the tests and retests of the CAT. The mean of the correlation coefficient of the test-retest scores was 0.85. According to the construct validity test calculated by principal constant analysis using the oblique rotation method, 4 factors explained 70.0% of the cumulative variances. In addition, the normative data were obtained for all of the CLT-R subtests. Conclusion: The computerized CLT-R can be used as a reliable and valid tool to evaluate the reading achievement and reading related cognitive process in Korean children and adolescents in schools, clinics, and research institutes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.4
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• pp.347-353
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• 2008

Reflected light can be decomposed into specular and diffuse components according to the light reflectance theory and experiments. The specular component appears in smooth surfaces mainly, while the diffuse one is visible in rough surfaces mostly. Therefore, each component can be used in forming their correlations to a surface roughness. However, they cannot represent the whole surface roughness seamlessly, because each formulation is merely validated in their available surface roughness regions. To solve this problem, new approaches to properly blend two light components in all regions are proposed in this paper. First is the weighting function method that a blending zone and rate can be flexibly adjusted, and second is the neural network method based on the learning from the measurement data. Simulations based on the light reflectance theory were conducted to examine its performance, and then experiments conducted to prove the enhancement of the measurement accuracy and reliability through the whole surface roughness regions.