• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.389-390
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• 2019

Tensor decomposition, proven to be an efficient data processing method, can be used to provide data-driven services. we propose a novel datadriven mutation strategy for parent individuals selection, namely tensor-based DE with parapatric and cross-generation(TPCDE).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.422-424
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• 2022

We propose a novel data-driven mutation strategy for parent individuals selection, namely tensor-based DE with parapatric and cross-generation (TPCDE).

• Advances in aircraft and spacecraft science
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• v.2 no.3
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• pp.249-261
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• 2015

The mechanical characterization of composite materials is nowadays a major interest due to their increasing use in the aeronautic industry. The design of most of these materials is based on their stiffness, which is mainly obtained by means of tensile tests with strain gauge measurement. For thin laminated composites, this classical method requires adequate samples with specific orientation and does not provide all the independent elastic constants. Regarding ultrasonic characterization, especially immersion technique, only one specimen is needed and the entire determination of the stiffness tensor is possible. This paper presents a study of different methods to determine the mechanical properties of transversely isotropic carbon fibre composite materials (gauge and correlation strain measurement during tensile tests, ultrasonic immersion technique). Results are compared to ISO standards and manufacturer data to evaluate the accuracy of these techniques.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.53-58
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• 1998

In this paper, we study the response of several anisotropic systems to buried transient line loads. The problem is mathematically formulated based on the equations of motion in the constitutive relations. The load is in form of a normal stress acting with arbitrary axis on the plane of monoclinic symmetry. Plane wave equation is coupled with vertical shear wave, longitudinal wave and horizontal shear wave. We first considered the equation of motion in reference coordinate system, where the line load is coincident with symmetry axis of the orthotrioic material. Then the equation of motion is transformed with respect to general coordiante system with azimuthal angle by using transformation tensor. The load is first described as a body force in the equations of the motion for the infinite media and then it is mathematically characterized. Subsequently the results for semi-infinite spaces is also obtained by using superposition of the infinite medium solution together with a scattered solution from the free surface. Consequently explicit solutions for the displacements are obtained by using Cargniard-DeHoop contour. Numerical results which are drawn from concrete examples of orthotropic material belonging to monoclinic symmetry are demonstrated.

• Smart Structures and Systems
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• v.13 no.2
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.47-56
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• 2021

This paper deals with damage detection using a Gapped Smoothing Method (GSM) combined with deep learning. Convolutional Neural Network (CNN) is a model of deep learning. CNN has an input layer, an output layer, and a number of hidden layers that consist of convolutional layers. The input layer is a tensor with shape (number of images) × (image width) × (image height) × (image depth). An activation function is applied each time to this tensor passing through a hidden layer and the last layer is the fully connected layer. After the fully connected layer, the output layer, which is the final layer, is predicted by CNN. In this paper, a complete machine learning system is introduced. The training data was taken from a Finite Element (FE) model. The input images are the contour plots of curvature gapped smooth damage index. A free-free beam is used as a case study. In the first step, the FE model of the beam was used to generate data. The collected data were then divided into two parts, i.e. 70% for training and 30% for validation. In the second step, the proposed CNN was trained using training data and then validated using available data. Furthermore, a vibration experiment on steel damaged beam in free-free support condition was carried out in the laboratory to test the method. A total number of 15 accelerometers were set up to measure the mode shapes and calculate the curvature gapped smooth of the damaged beam. Two scenarios were introduced with different severities of the damage. The results showed that the trained CNN was successful in detecting the location as well as the severity of the damage in the experimental damaged beam.

• The Journal of Korean Physical Therapy
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• v.34 no.1
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• pp.38-44
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• 2022

Purpose: The purpose of this study was to investigate the effects of complex training on injury, flexibility, and muscle stiffness in high school male football players. Methods: A total of 60 football players were included in the study and were divided into three groups viz. the complex training group (CTG), 11+ training group (11+TG), and traditional training group (TTG). Injuries were recorded based on the prospective investigation method after starting the study, and the flexibility and muscle stiffness of the subjects were evaluated. Results: The research results showed that the injury rate per match was significantly lower in the CTG and 11+TG than the TTG. In the CTG, the flexibility of the hamstrings significantly increased and the stiffness of the rectus femoris (RF), biceps femoris (BF), and tensor fascia latae (TFL) muscles significantly decreased (p<0.05). In the 11+TG, the stiffness of the RF significantly decreased (p<0.05). In the TTG, the flexibility of the hamstrings significantly increased (p<0.05). Hamstring flexibility showed a significantly higher increase in the CTG and TTG compared to the 11+TG (p<0.05). Also, the stiffness of the RF and TFL muscles showed a significantly higher decrease in the CTG compared to the 11+TG and TTG (p<0.05). The stiffness of the BF muscles too showed a more significant decrease in the CTG compared to the TTG (p<0.05). Conclusion: The complex training method of the Fédération International de Football Association (FIFA) 11+ and self-myofascial release (SMFR) as a warm-up program, prevent injuries, enhance flexibility, and lower muscle stiffness of football players in high school. Thus, it is necessary to ensure the widespread use of the complex training program by instructors and players under the supervision of the Korea Football Association (KFA), given its reliability in preventing injuries and improving the performance of football players.