• PNF and Movement
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• v.14 no.1
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• pp.41-47
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• 2016

Purpose: In general, confabulation is defined as confusion of reality with past events without apparent prompting, in association with disruption of the capacity for retrieval and encoding of memory. We report on a patient who showed spontaneous confabulation associated with injury of the Papez circuit following middle cerebral artery (MCA) infarction. Methods: A 67-year-old female patient suffered cerebral infarct resulting from spontaneous MCA territory. After onset of the MCA infarct, she showed severe memory impairment and provoked confabulation. The Papez circuit was reconstructed for evaluation of part of it using diffusion tensor tractography (DTT). Fractional anisotropy (FA), mean diffusivity (MD), and tract volume were measured. Results: The right thalamocingulate tract showed a significant decrement of FA value and tract volume, and an increment of MD value by more than two standard deviations of that of normal control subjects. The tract volume in the left fornix and mammillothalamic tract decreased by more than two standard deviations of that of normal control subjects. Conclusion: Injuries of the Papez circuit were demonstrated in a patient who showed severe memory impairment and provoked confabulation following MCA infarct. We believe that analysis of the Papez circuit tract using DTT is useful in elucidating the cause of provoked confabulation in patients with MCA infarct.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.176-185
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• 2019

Diffusion tensor images were obtained for middle-aged men according to the AUDIT-K scale. As a result of the fractional anisotropy (FA) value of the gyrus nerve fibers in the brain region measured and analyzed by the Tract-Based Spatial Statics, FA values of general drinkers were measured lower than those of estimated alcohol use disabled people. This was statistically significant. In other words, the use of alcohol significantly affects the anatomic microstructural changes measured in the Gyrus of the brain region, and it may damage the nerve fiber tract and affect the functional abnormalities associated with it.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.177.2-177.2
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• 2005

• Honam Mathematical Journal
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• v.46 no.1
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• pp.70-81
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• 2024

We consider the *-general critical equation on LP Sasakian manifolds, and show that such a manifold is generalized η-Einstein. After then, we consider LP Sasakian manifolds with *-conformally semisymmetric condition, and show that such manifolds are *-Einstein. Moreover, we show that the *-conformally semisymmetric LP Sasakian manifold is locally isometric to Eⁿ⁺¹(0) × Sⁿ(4).

• Journal of Digital Convergence
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• v.16 no.5
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• pp.221-229
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• 2018

Machine learning and artificial intelligence are core technologies for the 4th industrial revolution. However, it is difficult for the general public to get familiar with those technologies because most people lack programming ability. Thus, we developed a Graphic User Interface(GUI) to overcome this obstacle. We adopted TensorFlow and used .Net of Microsoft for the develop. With this new GUI, users can manage data, apply algorithms, and run machine learning without coding ability. We hope that this development will be used as a basis for developing artificial intelligence in various fields.

• Journal of the Korean Magnetic Resonance Society
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• v.7 no.1
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• pp.16-24
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• 2003

Nuclei with the spin quantum number not smaller than unity have not only the nuclear magnetic moment but also the electric quadrupole moment. The quadrupole moment couples with the electric field gradient (EFG) to produce the nuclear quadrupole interaction. It is well known that two independent parameters, i.e. the quadrupole coupling constant (QCC) and the asymmetry parameter ($\eta$) together with the principal axis directions can fully describe the interaction and are very sensitive to the local symmetry and structure of the solid. In order to obtain quantitative estimates of the EFG tensor for various simple ionic configurations surrounding the nucleus under consideration, we employ the simple point charge approximation and apply the calculated results to some real crystals. General agreement is rather satisfactory.

• Structural Engineering and Mechanics
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• v.77 no.6
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• pp.765-777
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• 2021

Recently, the plate bending analysis has been interpreted in terms of the tensor's components of curvatures and bending moments by presenting the conceptual perspectives of the Hydrostatic Method of Analysis (HM) and theoretical formulations that combine the continuum mechanics with the graphical statics analysis, the theory of thin orthotropic and isotropic plates, and the elasticity theory. In pursuance of uncovering a genuine formulation of the plate's flexural differential equations, that possess the general-covariance and coordinates-independency. This study had then, tackled various natural and structural problems in both solid and fluid branches of the continuum mechanics in a description of such theoretical and conceptual attainment in uncovering the dimensional independent diffeomorphism covariant partial differential laws.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.467-474
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• 2019

In this paper, we propose a novel method to improve FPS while maintaining the accuracy of YOLO v2 model in NVIDIA Jetson TX1. In general, in order to reduce the amount of computation, a conversion to an integer operation or reducing the depth of a network have been used. However, the accuracy of recognition can be deteriorated. So, we use methods to reduce computation and memory consumption through adjustment of the filter size and integrated computation of the network The first method is to replace the $3{\times}3$ filter with a $1{\times}1$ filter, which reduces the number of parameters to one-ninth. The second method is to reduce the amount of computation through CBR (Convolution-Add Bias-Relu) among the inference acceleration functions of TensorRT, and the last method is to reduce memory consumption by integrating repeated layers using TensorRT. For the simulation results, although the accuracy is decreased by 1% compared to the existing YOLO v2 model, the FPS has been improved from the existing 3.9 FPS to 11 FPS.

• Publications of The Korean Astronomical Society
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• v.19 no.1
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• pp.1-10
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• 2004

On the framework of a linearly perturbed Friedmann-Robertson-Walker spacetime, we derive an expression for the cosmological angular diameter distance affected by scalar and tensor perturbations. Our expression is applicable in linear order to distances in general FRW models. We study the effect of a stocastic gravitaional wave background on the two-point correlation function of the angular diameter distance fluctuations and, on the basis of this we also derive an expression for the power spectrum of the angular diameter distance fluctuations.

• Database Research
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• v.34 no.3
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• pp.3-13
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• 2018

Text classification is one of the text mining technologies that classifies a given textual document into its appropriate categories and is used in various fields such as spam email detection, news classification, question answering, emotional analysis, and chat bot. In general, the text classification system utilizes machine learning algorithms, and among a number of algorithms, naïve Bayes and support vector machine, which are suitable for text data, are known to have reasonable performance. Recently, with the development of deep learning technology, several researches on applying deep neural networks such as recurrent neural networks (RNN) and convolutional neural networks (CNN) have been introduced to improve the performance of text classification system. However, the current text classification techniques have not yet reached the perfect level of text classification. This paper focuses on the fact that the text data is expressed as a vector only with the word dimensions, which impairs the semantic information inherent in the text, and proposes a neural network architecture based upon the semantic tensor space model.