• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3199-3209
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• 2024

During the decommissioning of nuclear and particle accelerator facilities, a considerable amount of large-scale radioactive waste may be generated. Accurately defining the activation level of the waste is crucial for proper disposal. However, directly measuring the internal radioactivity distribution poses challenges. This study introduced a novel technology employing machine learning to assess the internal radioactivity distribution based on external measurements. Random radioactivity distribution within a structure were established, and the photon spectrum measured by detectors from outside the structure was simulated using the FLUKA Monte-Carlo code. Through training with spectrum data corresponding to various radioactivity distributions, an evaluation model for radioactivity using simulated data was developed by above Monte-Carlo simulation. Convolutional Neural Network and Transformer methods were utilized to establish the evaluation model. The machine learning construction involves 5425 simulation datasets, and 603 datasets, which were used to obtain the evaluated results. Preprocessing was applied to the datasets, but the evaluation model using raw spectrum data showed the best evaluation results. The estimation of the intensity and shape of the radioactivity distribution inside the structure was achieved with a relative error of 10%. Additionally, the evaluation based on the constructed model takes only a few seconds to complete the process.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.95-100
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• 2018

In this paper, we propose a binarized multi-scale module to accelerate the speed of the pose estimating deep neural network. Recently, deep learning is also used for fine-tuned tasks such as pose estimation. One of the best performing pose estimation methods is based on the usage of two neural networks where one computes the heat maps of the body parts and the other computes the part affinity fields between the body parts. However, the convolution filtering with a large kernel filter takes much time in this model. To accelerate the speed in this model, we propose to change the large kernel filters with binarized multi-scale modules. The large receptive field is captured by the multi-scale structure which also prevents the dropdown of the accuracy in the binarized module. The computation cost and number of parameters becomes small which results in increased speed performance.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.54-59
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• 2002

In general, the aluminum extrusions are used to the light construction of the high speed rail vehicle structures. However, the research works ok the crashworthy design of the high speed rail vehicle structures are not published sufficiently because the crash test of high speed rail vehicle structures costs high and is complicated. So, a method that can predict crash characteristics of a large size structure like a high speed tail vehicle should be suggested. In this study, the scale model studies are performed to predict the impact energy absorption characteristics of full scale model. In the first place, we verified the theory of scale law using FE-simulation from the crashworthiness point of view. Secondly, we performed the crush test using scale model, made of aluminum sub structure. As a result, we could predict the crash characteristics using scale model by 10∼20% error.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.211-216
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• 2021

This study intended to test the structure of the latent factor of a subjective happiness scale and the stability of invariance across groups of students' classifications (gender and students' status). In the large, non-clinical sample (619), students completed the subjective happiness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students classifications. The findings of the CFA indicated support for the original one-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of students' statuses. The scale exists in both groups to assess the same concepts of (single and married), excluding Items 3 and 4. Given that this study is the first investigation for the structure of the subjective happiness scale.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.149-156
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• 2021

This study intended to test the structure of the latent factor of an effectiveness scale and the stability of invariance across groups of students' classifications (gender and levels of education). In the large, non-clinical sample (850), students completed the effectiveness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students' classifications. The findings of the CFA indicated support for the original four-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of levels of education. The scale exists in groups of levels of education assess the same concepts of, excluding Items 15 and 10. Given that this study is the first investigation for the structure of the effectiveness scale.

• Journal of the Korean Institute of Educational Facilities
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• v.26 no.5
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• pp.25-36
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• 2019

School gymnasium is a multi-purpose large space building for various events and physical education activities, and is a facility that requires an approach to the desirable structural design, besides mechanical problems of structure against loads. For the integrated structure design concerning the architectural features, the major considerations of gymnasium planning that are the internal and external shape of the gymnasium, the space scale with structure members, the structural efficiency by members weight reduction and openness of the gymnasium space will have to take into account in the structural planning. From this point of view, the several cases of the school gymnasium were investigated and the parametric analyses were performed to the models using the various structural system. The parameters were the composition elements of structure system that are profile of structure, rigidity of member, connection and anchorage and stability. At the result, It was presented that the profile of structure member was the most influential factor to structural efficiency and the effect of the form and space of gymnasium. Also the design informations of structure design having the various feature of form and space were presented for the initial gymnasium planning.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.626-633
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• 2009

A large scale resonant column testing equipment is under development. The would-be equipment is aiming to test 150mm-diameter specimens, which can contain as large a grain size as 25mm. Such a large specimen is hardly excitated with the existing fixed-free end condition because the torsional force cannot be effectively coupled to the specimen. The specimen will be rather resonated with free-free condition and the scheme is implemented with a rotational bearing installed between coil-magnet exciter and base pedestal. Presently the equipment was assembled and is under calibration with a cylindrical brass specimen.

• Journal of Korean Association for Spatial Structures
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• v.15 no.4
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• pp.107-114
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• 2015

Large spatial structures can not easily predict the dynamic behavior due to the lack of construction and design practices. The spatial structures are generally analyzed through the numerical simulation and experimental test in order to investigate the seismic response of large spatial structures. In the case of analysis for seismic response of large spatial structure, the many studies by the numerical analysis was carried out, researches by the shaking table test are very rare. In this study, a shaking table test of a small-scale arch structure was conducted and the dynamic characteristics of arch structure are analyzed. And the dynamic characteristics of arch structures are investigated according to the various column cross-section and length. It is found that the natural vibration periods of the small-scaled arch structure that have large column stiffness are very similar to the natural vibration period of the non-column arch structure. And in case of arch structure with large column stiffness, primary natural frequency period by numerical analysis is very similar to the primary natural frequency period of by shaking table test. These are because the dynamic characteristics of the roof structure are affected by the column stiffness of the spatial structure.

• Journal of Korean Association for Spatial Structures
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• v.18 no.1
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• pp.22-29
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• 2018

• Bulletin of the Korean Chemical Society
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• v.35 no.9
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• pp.2726-2732
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• 2014

The promoting effect of rhodium on the structure and activity of the supported Cu-Co based catalysts for CO hydrogenation was investigated in detail. The samples were characterized by DRIFTS, $N_2$-adsorption, XRD, $H_2$-TPR, $H_2$-TPD and XPS. The results indicated that the introduction of rhodium to Cu-Co catalysts resulted in modification of metal dispersion, reducibility and crystal structure. DRIFTS results of CO hydrogenation at reaction condition (P=2 MPa, $T=260^{\circ}C$) indicated the addition of 1 wt % rhodium improved hydrogenation ability of Cu-Co catalysts. The ethanol selectivity and CO conversion were both improved by 1 wt % Rh promoted Cu-Co based catalysts. The alcohol distribution over un-promoted and rhodium promoted Cu-Co based catalysts obeys A-S-F rule and higher chain growth probability was got on rhodium promoted catalyst.