• Journal of Science Education
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• v.44 no.2
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• pp.214-224
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• 2020

Physics image and interest are factors that influence physics learning. Freshmen enter an engineering college under various learning conditions when they were in high school. Understanding physics image and interest according to characteristics of freshmen will help college physics education. The purpose of this study is to investigate the physics image and interest of freshmen in an engineering college according to their gender and physics course completion in high school and discuss the educational implications of college students on physics learning. The subjects of the study are 664 first grade students in engineering college. We analyzed physics image and interest of students according to gender and physics course completion in high school. Physics image is analyzed using semantic analysis. As a result of the analysis, the physics image is different according to the physics course completion. Interest in Physics depends on gender and physics course completion. Finally, we discuss the educational implications of college physics learning for engineering students.

• Progress in Medical Physics
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• v.31 no.3
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• pp.81-98
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• 2020

This review aims to provide a brief, comprehensive overview of advanced technologies of nuclear medicine physics, with a focus on recent developments from both hardware and software perspectives. Developments in image acquisition/reconstruction, especially the time-of-flight and point spread function, have potential advantages in the image signal-to-noise ratio and spatial resolution. Modern detector materials and devices (including lutetium oxyorthosilicate, cadmium zinc tellurium, and silicon photomultiplier) as well as modern nuclear medicine imaging systems (including positron emission tomography [PET]/computerized tomography [CT], whole-body PET, PET/magnetic resonance [MR], and digital PET) enable not only high-quality digital image acquisition, but also subsequent image processing, including image reconstruction and post-reconstruction methods. Moreover, theranostics in nuclear medicine extend the usefulness of nuclear medicine physics far more than quantitative image-based diagnosis, playing a key role in personalized/precision medicine by raising the importance of internal radiation dosimetry in nuclear medicine. Now that deep-learning-based image processing can be incorporated in nuclear medicine image acquisition/processing, the aforementioned fields of nuclear medicine physics face the new era of Industry 4.0. Ongoing technological developments in nuclear medicine physics are leading to enhanced image quality and decreased radiation exposure as well as quantitative and personalized healthcare.

• Journal of The Korean Association For Science Education
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• v.37 no.6
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• pp.1051-1061
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• 2017

An image is a comprehensive result that you have experienced about an object and means the image that you have on the surface of your consciousness. The image of the subject has an important influence on learning the subject. The image analysis of the subjects that the learners have will be good data to decide the direction of teaching and learning. The purpose of this study is to develop and apply measurement tools for physics image and discuss its educational implications. The research method is to develop the measurement tools for the physics image by semantic analysis method and apply it to the secondary pre-service physics teacher. The subjects of the study were 39 first graders, 31 second graders, 37 third graders, and 38 fourth graders at the University of Education, a total of 145 students, 82 of whom were male and 63 were female. The study results show that the image measurement tools for physics consisted of 25 items from five elements: 'interest,' 'feeling,' 'scope,' 'evaluation,' and 'viewpoint.' There were statistically significant differences between the male and female students in applying the measurement tools developed for the physics image of secondary pre-service physics teachers. Male students showed significantly higher statistical significance than female students in the 'interest' and 'feeling' elements of measurement tools for the physics image. In the 'scope' element of measurement tools for the physics image the second grade was statistically higher than the fourth grade. Finally, we discussed educational implications for image analysis of physics and the usefulness of using measurement tools in physics image.

• Progress in Superconductivity
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• v.11 no.2
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• pp.128-134
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• 2010

The magnetic flux profiles in SmBCO and YBCO coated conductors(CC) in the presence of the external field were comparatively investigated by magneto-optic image and scanning hall probe measurements. The current distributions calculated by using the inversion method from measured field profiles show that the decrease of current densities near the edges of SmBCO CC is more significant than those of YBCO CC. Through the comparison of the numerical analysis based on Kim's critical state model and the Brandt and Indenbom's solution, we found that this feature is related to their different field dependant properties of the critical current densities.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1160-1163
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• 2009

Many researches showed that perceived image contrast increases as the relative surround luminance increases. However, most experiments were conducted under limited surround conditions. In this research, a psychophysical experiment was conducted to investigate the change in perceived image contrast under wide range of surround luminance up to 1820 cd/$m^2$. A large area illuminator was used as a backlight. It consists of 23 dimmable fluorescent lamps and a sheet of diffuser. The luminance could be adjusted to 7 different surround ratios: 0, 0.3, 0.56, 0.96, 2.24, 5.81, and 9.99. Results showed that perceived image contrast changes as a typical band-pass shape and the maximum contrast is found near $S_R$=1.

• Smart Structures and Systems
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• v.30 no.3
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• pp.287-301
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• 2022

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.

• Journal of Korea Game Society
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• v.9 no.5
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• pp.43-52
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• 2009

This paper analyzes the four game physics engines in terms of real time techniques. Real time physics is the technology that simplifies the physics-based simulation to apply for the real time applications such as game. Our study includes two commercial physics engines, Havok's Physics SDK and NVIDIA's PhysX SDK, and two open source projects, Open Dynamics Engine and Bullet physics engine. As a result, most of them covers rigid body dynamics and some include either deformable body simulation or fluids simulation, or both. For real time simulation, they adopt the simplified numerical methods, the effective in collision detection/response, and also use the parallel processing hardwares, i.e., multi core CPU, Physics processing unit(PPU), or graphics processing unit(GPU).

• Korean Journal of Optics and Photonics
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• v.30 no.3
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• pp.106-113
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• 2019

When elemental images are remapped to solve the depth conversion in integral imaging, the integrated image is inevitably accompanied by discontinuity. This paper analyzes the discontinuity factor caused by elemental-image remapping, to validate the reduction of the discontinuity through converging pick-up and reconstruction of the three-dimensional image in real and virtual modes simultaneously. The validity of the proposed method is quantitatively verified when compared with the conventional parallel pick-up.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.119-126
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• 2023

Acquiring experimental data for PIV verification or machine learning training data is resource-demanding, leading to an increasing interest in synthetic particle images as simulation data. Conventional synthetic particle image generation algorithms do not follow physical laws, and the use of CFD is time-consuming and requires computing resources. In this study, we propose a new method for synthetic particle image generation, based on a Physics-Informed Neural Networks(PINN). The PINN is utilized to infer the flow fields, enabling the generation of synthetic particle images that follow physical laws with reduced computation time and have no constraints on spatial resolution compared to CFD. The proposed method is expected to contribute to the verification of PIV algorithms.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.341-344
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• 2014

This study proposes a modified sub-aperture stitching algorithm, which uses an image sharpening algorithm and particle swarm optimization to improve the stitching accuracy. In sub-aperture stitching interferometers with high positional accuracy, the high-frequency components of measurements are more important than the low-frequency components when compensating for position errors using a sub-aperture stitching algorithm. Thus we use image sharpening algorithms to strengthen the high-frequency components of measurements. When using image sharpening algorithms, sub-aperture stitching algorithms based on the least-squares method easily become trapped at locally optimal solutions. However, particle swarm optimization is less likely to become trapped at a locally optimal solution, thus we utilized this method to develop a more robust algorithm. The results of simulations showed that our algorithm compensated for position errors more effectively than the existing algorithm. An experimental comparison with full aperture-testing results demonstrated the validity of the new algorithm.