• Journal of Distribution Science
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• v.20 no.9
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• pp.47-59
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• 2022

Purpose: This study aims to analyze a triangulation model: 1) the effect of entrepreneurship education (EE) on entrepreneurship knowledge (EK) and entrepreneurship mindset (EM) and 2) the effect of EK on EM. Entrepreneurship education is a medium and pedagogical tool to cultivate EK and EM with the purpose enhancing of students who will be interested in entrepreneurial activities. Knowledge of adequate entrepreneurship is a stimulus strategic tool to develop the entrepreneurial mindset of students. Research design, data, and methodology: There were 278 respondents from Business and Non-Business both Indonesian and Malaysian students. The research design was quantitative and evaluated three hypotheses by PLS-SEM using WarpPLS v.7 software. Statistic descriptive for respondent used SPSS IBM v.26. Results: The results showed that the three hypotheses had supported with a significant level of p-value < 0.001. It's meant EE enhanced both EK and EM. Furthermore, increasing EM was not only by EE, but also EM could be increased through EK. Conclusions: The novelty of this research contributes to filling the knowledge gap in the development of pedagogy in the pursuit of entrepreneurship using a triangulation model of the relationship among EE, EK, and EM.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.501-509
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• 2019

In this paper a body-centered cubic(BCC) crystal plasticity model based on microscopic dislocation mechanism is introduced and numerically implemented. The model is coupled with irradiation effect via tracking dislocation loop evolution on each slip system. On the basis of the model, uniaxial tensile tests of unirradiated and irradiated RPV steel(take Chinese A508-3 as an example) at different temperatures are simulated, and the simulation results agree well with the experimental results. Furthermore, crystal plasticity damage is introduced into the model. Then the damage behavior before and after irradiation is studied using the model. The results indicate that the model is an effective tool to study the effect of irradiation and temperature on the mechanical properties and damage behavior.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.346-350
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• 2023

Trajectory prediction is an essential element for driving autonomous vehicles, and various trajectory prediction models have emerged with the development of deep learning technology. Convolutional neural network (CNN) is the most commonly used neural network architecture for extracting the features of visual images, and the latest models exhibit high performances. This study was conducted to identify an efficient CNN backbone model among the components of deep learning models for trajectory prediction. We changed the existing CNN backbone network of multiple-trajectory prediction models used as feature extractors to various state-of-the-art CNN models. The experiment was conducted using nuScenes, which is a dataset used for the development of autonomous vehicles. The results of each model were compared using frequently used evaluation metrics for trajectory prediction. Analyzing the impact of the backbone can improve the performance of the trajectory prediction task. Investigating the influence of the backbone on multiple deep learning models can be a future challenge.

• Structural Engineering and Mechanics
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• v.71 no.6
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• pp.683-697
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• 2019

The reinforced concrete (RC) structures usually suffer large residual displacements under strong motions. The large residual displacements may substantially reduce the anti-seismic capacity of structures during the aftershock and increase the difficulty and cost of structural repair after an earthquake. To reduce the adverse residual displacement, several self-centering energy dissipation braces (SCEBs) have been proposed to be installed to the RC structures. To investigate the seismic responses of the RC structures with SCEBs under the earthquake excitation, an extended Bouc-Wen model with degradation and self-centering effects is developed in this study. The extended model realized by MATLAB/Simulink program is able to capture the hysteretic characteristics of the RC structures with SCEBs, such as the energy dissipation and the degradation, especially the self-centering effect. The predicted hysteretic behavior of the RC structures with SCEBs based on the extended model, which used the unscented Kalman filter (UKF) for parameter identification, is compared with the experimental results. Comparison results show that the predicted hysteretic curves can be in good agreement with the experimental results. The nonlinear dynamic analyses using the extended model are then carried out to explore the seismic performance of the RC structures with SCEBs. The analysis results demonstrate that the SCEB can effectively reduce the residual displacements of the RC structures, but slightly increase the acceleration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.771-788
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• 2020

Detection of abandoned objects for smart video surveillance should be robust and accurate in various situations with low computational costs. This paper presents a new algorithm for abandoned object detection based on the dual background model. Through the template registration of a candidate stationary object and presence authentication methods presented in this paper, we can handle some complex cases such as occlusions, illumination changes, long-term abandonment, and owner's re-attendance as well as general detection of abandoned objects. The proposed algorithm also analyzes video frames at specific intervals rather than consecutive video frames to reduce the computational overhead. For performance evaluation, we experimented with the algorithm using the well-known PETS2006, ABODA datasets, and our video dataset in a live streaming environment, which shows that the proposed algorithm works well in various situations.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.141-156
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• 2014

This study intended to evaluate the viability of cyber education in terms of learning satisfaction and learning achievement. The study integrated two research streams such as social presence model and learning environment model. Where the learning environment model emphasizes the components of learning aids, social presence model considers more deeply the relationships among peers and with instructors. These two research streams have been considered relatively independently. The study integrated these ideas and measured their reliabilities and validities. The results demonstrate that the two constructs are relevantly independent and both of these constructs are very important considerations for the success of cyber education. The study concludes that cyber education 2.0 requires more social presence factors than the learning environment factors such as technological development or new equipments.

• Educational Technology International
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• v.12 no.2
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• pp.135-151
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• 2011

Recently, a wide variety of studies on future learning have appeared owing to rapid advances in information and communication technology (ICT) and increased discussion about core competencies in twenty-first-century learning. These studies, though insufficient in number, cover various fields such as architecture (design of the learning space), education (learning model), and technology (adaptation of mobile devices). However, these studies focus on mainstream students and do not discuss the future situation of inclusive education with regard to both mainstream and students with physical disabilities. Hence, in order to fill this gap, the present study explores the perceptions and ideas held by special education preservice teachers on the future learning space with regard to school design and peer-to-peer feedback. For this purpose, these preservice teachers' design proposals about future school were collected and analyzed. In conclusion, special education preservice teachers perceive the future learning space as an inclusive environment in which smart technology is incorporated. Future learning environment were categorized in terms of flexible, ubiquitous technology, physical and mental health, safety, and spaces with facilities for students with physical disabilities.

• Journal of Korea Technology Innovation Society
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• v.10 no.3
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• pp.531-554
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• 2007

This paper suggests a new model connecting various knowledge activities through classification systems such as classifications of research, technology, industry, major and job. Although research activities are linked to technology and industry areas or to education and job areas, there is no effort to link these kinds of activities. There are a few studies to link research and technology or research and education respectively. But, there have been no studies to connect technology-industry linkage and education-job linkage. This paper suggests that research area can be a basis of link between technology-industry linkage and education-job linkage. The methods building the links are not simple, but easy; 1) setting up new science/research classification system having two dimensions of research and application, 2) building electronic systems and databases allowing fields for several classification systems, and 3) making rules using multi-dimensional classification systems following the purpose of the programs. The model is designed to meet the needs of nationwide R&D and human resources policies, and for the preparation of knowledge society to grasp the relationship between sequential activities using knowledge. If we know the interactive relationships between various areas, we can trace related phenomena in different activities with restricted information.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.1-11
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• 2018

The purpose of this study is to develop and analyze the meaning and contents of the "H-STEAM teaching & learning model" which combines Science, Technology, Engineering, Arts & Mathematics (STEAM) with the elements of Humanities. We developed this model based on the key competencies linked with career path for middle school students in Korea, with the recognition of two issues. First, the existing Korean STEAM education lacks the elements of humanities, thus failing to achieve an authentic convergence education. Second, it is necessary to develop a program that might correspond to the Free Semester Program that was first introduced in 2013, and implemented at full scale in 2016 for middle school students in Korea. The advantages of H-STEAM are as follows: First, H-STEAM enables students to flexibly think while traversing the physical world and the symbolic world in the process of dealing with the daily problems. Second, it combines advanced technology with human sensibility and imagination, and enables students to derive creative outcomes that stimulate their minds. Third, it makes students feel and realize a point of contact between the subject that students learn, and jobs of the real world.

• Earthquakes and Structures
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• v.9 no.5
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• pp.1029-1044
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• 2015

To investigate the seismic pounding response of long-span bridges with high-piers under strong ground motions, shaking table tests were performed on a 1/10-scaled bridge model consisting of three continuous spans with rigid frames and one simply-supported span. The seismic pounding responses of this bridge model under different earthquake excitations including the uniform excitation and the traveling wave excitations were experimentally studied. The influence of dampers to the seismic pounding effects at the expansion joints was analyzed through nonlinear dynamic analyses in this research. The seismic pounding effects obtained from numerical analyses of the bridge model are in favorable agreement with the experimental results. Seismic pounding effect of bridge superstructures is dependent on the structural dynamic properties of the adjacent spans and characteristics of ground motions. Moreover, supplemental damping can effectively mitigate pounding effects of the bridge superstructures, and reduce the base shear forces of the bridge piers.