• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.1-5
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• 2019

As the number of IOT devices is growing rapidly, various 'see-thru connection' techniques have been reported for efficient communication with them. In this paper, we propose a deep learning based IOT device recognition system for interaction with these devices. The overall system consists of a TensorFlow based deep learning server and two Android apps for data collection and recognition purposes. As the basic neural network model, we adopted Google's inception-v3, and modified the output stage to classify 20 types of IOT devices. After creating a data set consisting of 1000 images of 20 categories, we trained our deep learning network using a transfer learning technology. As a result of the experiment, we achieve 94.5% top-1 accuracy and 98.1% top-2 accuracy.

• ETRI Journal
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• v.41 no.5
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• Investigative Magnetic Resonance Imaging
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• v.17 no.2
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• pp.123-132
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• 2013

Purpose : We report the results of the various parameters of diffusion tensor imaging (DTI) and CSF flow study of the cervical spinal cord using magnetic resonance (MR) imaging techniques. Materials and Methods: Intramedullary FA and MD were measured in the gray matter and posterior cord of the white matter and both lateral cords of the white matter at the C2-3, C4-5, C5-6 spinal levels. For the CSF flow study, velocity encoding was obtained at the C2-3, C4-5, C5-6 spinal levels. Results: There was a significant difference of the FA and MD between the white matter and gray matter (p < 0.05). The FA of the gray matter was significantly different according to the cervical spinal cord levels (p < 0.05). Otherwise, the FA and MD parameters were not significantly different (p > 0.05). The mean peak systolic velocity and mean peak diastolic velocity were $5.18{\pm}2.00cm/sec$ and $-7.32{\pm}3.18cm/sec$, respectively from C2 to C6 spinal cords. There was no significant difference in these velocities among the cervical spinal cord (p > 0.05). Conclusion: This basic information about DTI and CSF dynamics of the cervical spinal cord may be useful for assessing cervical spinal cord abnormalities using MR imaging.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.43-47
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• 2004

Interests in human brain functionality and its connectivity have much frown up. DTI (Diffusion tensor imaging) has been known as a non-invasive MR) technique capable of providing information on water diffusion in tissues and the organization of white matter tract. Thus. It can provide us the information on the direction of brain fiber tract and the connectivity among many important cortical regions which can not be examined by other anatomical or functional MRI techniques. In this study. was used the 24 bit color coding scheme on the IDL platform in the windows environment to visualize the orientation of major fiber tracts of brain such as main association, projection, commissural fibers and corticospinal tracts. We additionally implemented a color coding scheme for each directional component and FA (fractional anisotropy), and used various color tables for them to be visualized more definitely. Consequently we implemented a fancy and basic technique to visualize the directional information of fiber tracts efficiently and we confirmed the feasibility of the 24 bit color coding scheme in DTI by visualizing main fiber tracts.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.26 no.1
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• pp.47-54
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• 2020

Background: This study examined the changes in the leg muscle activities of 30 healthy subjects according to different pressures caused by isometric hip adduction during squat exercise. Methods: With their knee flexed at 60°, the subjects performed isometric hip adduction with a pressure of 0, 20, 40, and 60mmHg. Surface electromyography was used to measure their muscle activities. Changes in the activities of the muscles, such as the gluteus maximus (GMAX), Gluteus medius (GM), vastus medialis oblique (VMO), vastus lateralis oblique (VLO), biceps femoris (BF), and Tensor fasciae latae (TFL) muscles, were analyzed. Results: The activities of the VMO, VLO, GM, BF, and GMAX muscles were significantly different after exercise compared to that before exercise (p<.05). The activities of all the leg muscles measured were highest at a pressure of 60mmHg during isometric hip joint adduction. Conclusion: The pressure produced by isometric hip joint adduction during squat exercise increased the leg muscle activities of the subjects. These results will provide basic data on effective squat exercise to alleviate knee joint diseases.

• Communications of the Korean Mathematical Society
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• v.32 no.3
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• pp.661-676
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• 2017

Let T be a bounded linear operator acting on a complex Hilbert space ${\mathfrak{H}}$. In this paper we introduce the class, denoted ${\mathcal{Q}}(A(k),m)$, of operators satisfying $T^{m{\ast}}(T^{\ast}{\mid}T{\mid}^{2k}T)^{1/(k+1)}T^m{\geq}T^{{\ast}m}{\mid}T{\mid}^2T^m$, where m is a positive integer and k is a positive real number and we prove basic structural properties of these operators. Using these results, we prove that if P is the Riesz idempotent for isolated point ${\lambda}$ of the spectrum of $T{\in}{\mathcal{Q}}(A(k),m)$, then P is self-adjoint, and we give a necessary and sufficient condition for $T{\otimes}S$ to be in ${\mathcal{Q}}(A(k),m)$ when T and S are both non-zero operators. Moreover, we characterize the quasinilpotent part $H_0(T-{\lambda})$ of class A(k) operator.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.628-633
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• 1994

A new Riemannian geometric model for the controlled plant is proposed by imbedding the control vector space in the state space, so as to reduce the dimension of the model. This geometric model is derived by replacing the orthogonal straight coordinate axes on the state space of a linear system with the curvilinear coordinate axes. Therefore the integral manifold of the geometric model becomes homeomorphic to that of fictitious linear system. For the lower dimensional Riemannian geometric model, a nonlinear optimal regulator with a quadratic form performance index which contains the Riemannian metric tensor is designed. Since the integral manifold of the nonlinear regulator is determined to be homeomorphic to that of the linear regulator, it is expected that the basic properties of the linear regulator such as feedback structure, stability and robustness are to be reflected in those of the nonlinear regulator. To apply the above regulator theory to a real nonlinear plant, it is discussed how to distort the curvilinear coordinate axes on which a nonlinear plant behaves as a linear system. Consequently, a partial differential equation with respect to the homeomorphism is derived. Finally, the computational algorithm for the nonlinear optimal regulator is discussed and a numerical example is shown.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.65-72
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• 2001

This paper demonstrates an explicit-implicit, finite element analysis for linear as well as nonlinear hygrothermal stress problems. Additional features, such as moisture diffusion equation, crack element and virtual crack extension(VCE) method for evaluating J-integral are implemented in this program. The Linear Elastic Fracture Mechanics(LEFM) Theory is employed to estimate the crack driving force under the transient condition for an existing crack. Pores in materials are assumed to be saturated with moisture in the liquid form at the room temperature, which may vaporize as the temperature increases. The vaporization effects on the crack driving force are also studied. The ideal gas equation is employed to estimate the thermodynamic pressure due to vaporization at each time step after solving basic nodal values. A set of field equations governing the time dependent response of porous media are derived from balance laws based on the mixture theory. Darcy's law is assumed for the fluid flow through the porous media. Perzyna's viscoplastic model incorporating the Von-Mises yield criterion are implemented. The Green-Naghdi stress rate is used for the invariant of stress tensor under superposed rigid body motion. Isotropic elements are used for the spatial discretization and an iterative scheme based on the full Newton-Raphson method is used for solving the nonlinear governing equations.

• Structural Engineering and Mechanics
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• v.13 no.2
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• pp.135-154
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• 2002

This paper presents the convected material frame approach to study the nonlinear behavior of inelastic frame structures. The convected material frame approach is a modification of the co-rotational approximation by incorporating an adaptive convected material frame in the basic definition of the displacement vector and strain tensor. In the formulation, each discrete element is associated with a local coordinate system that rotates and translates with the element. For each load increment, the corresponding strain-displacement and nodal force-stress relationships are defined in the updated local coordinates, and based on the updated element geometry. The rigid body motion and deformation displacements are decoupled for each increment. This modified approach incorporates the geometrical nonlinearities through the continuous updating of the material frame geometry. A generalized nonlinear function is used to derive the inelastic constitutive relation and the kinematic hardening is considered. The equation of motion is integrated by an explicit procedure and it involves only vector assemblage and vector storage in the analysis by assuming a lumped mass matrix of diagonal form. Several numerical examples are demonstrated in close agreement with the solutions obtained by the ANSYS code. Numerical studies show that the proposed approach is capable of investigating large deflection of inelastic planar structures and providing an excellent numerical performance.

• Investigative Magnetic Resonance Imaging
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• v.16 no.2
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• pp.115-123
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• 2012

Purpose : To evaluate white matter abnormalities on diffusion tensor imaging (DTI) in patients with mild Alzheimer disease (AD) and mild cognitive impairment (MCI), using tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM). Materials and Methods: DTI was performed in 21 patients with mild AD, in 13 with MCI and in 16 old healthy subjects. A fractional anisotropy (FA) map was generated for each participant and processed for voxel-based comparisons among the three groups using TBSS. For comparison, DTI data was processed using the VBM method, also. Results: TBSS showed that FA was significantly lower in the AD than in the old healthy group in the bilateral anterior and right posterior corona radiata, the posterior thalamic radiation, the right superior longitudinal fasciculus, the body of the corpus callosum, and the right precuneus gyrus. VBM identified additional areas of reduced FA, including both uncinates, the left parahippocampal white matter, and the right cingulum. There were no significant differences in FA between the AD and MCI groups, or between the MCI and old healthy groups. Conclusion: TBSS showed multifocal abnormalities in white matter integrity in patients with AD compared with old healthy group. VBM could detect more white matter lesions than TBSS, but with increased artifacts.