• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.1
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• pp.1-9
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• 2008

In seismic response analysis of building structures, the input ground accelerations have considerable effect on the nonlinear response characteristics of structures. The characteristics of soil and the locality of the site where those ground motions were recorded affect on the contents of earthquake waves. Therefore, it is difficult to select appropriate input ground motions for seismic response analysis. This study describes a generation of artificial earthquake wave compatible with seismic design spectrum, and also evaluates the seismic response values of multistory reinforced concrete structures by the simulated earthquake motions. The artificial earthquake wave are generated according to the previously recorded earthquake waves in past major earthquake events. The artificial wave have identical phase angles to the recorded earthquake wave, and their overall response spectra are compatible with seismic design spectrum with 5% critical viscous damping. The input ground motions applied to this study have identical elastic acceleration response spectra, but have different phase angles. The purpose of this study is to investigate their validity as input ground motion for nonlinear seismic response analysis. As expected, the response quantifies by simulated earthquake waves present better stable than those by real recording of ground motion. It was concluded that the artificial earthquake waves generated in this paper are applicable as input ground motions for a seismic response analysis of building structures. It was also found that strength of input ground motions for seismic analysis are suitable to be normalize as elastic acceleration spectra.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.240-245
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• 2005

In this paper, the current research for the biomechanics of artificial knee joints including experiments and stress analysis is surveyed and Introduced. The knee joint is the most large and the motion is very complicated, so the design of artificial joint is difficult and most research Is being done abroad. Up to date, most products are foreign products and Imported here and the gap between here and advanced countries of the technical and capability for the design and manufacturing is too deep to follow. So, the contents of papers in this area including the most excellent results are introduced. And the preliminary research on the contact stress analysis of the joints is present.

• Korean Journal of Computational Design and Engineering
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• v.13 no.1
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• pp.58-66
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• 2008

The artificial discs have recently used to preserve the motion of the treated segment in lumbar spine surgery. However, there have been lack of biomechanical information of the artificial discs to explain current clinical controversies such as long-term results of implant wear and excessive facet contact forces. In this study, we investigated the biomechanical effects of three artificial implants on the lumbar spinal segments by finite element analysis. The finite element model of intact lumbar spine(L1-S) was developed and the three implants were inserted in L4-L5 segment of the spine model. 5 Nm of flexion and extension moments were applied on the superior plate of L1 with 400 N of compressive load. Excessive motions and high facet contact forces at the surgical level were generated in the all three implanted models. In the flexion, the peak von-Mises stresses in the semi-constrained type implant was higher than those in the un-constrained type implant which would cause wear on the polyethylene core. The results of the study would provide a biomechanical guideline for selecting optimal surgical approach or evaluating the current design of the implants, or developing a new implant.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.4
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• pp.355-364
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• 2010

Filiform hairs that respond to movements of the surrounding medium are the mechanoreceptors commonly found in arthropods and vertebrates. In these creatures, the filiform hairs function as a sensory system for raider detection. Parametric analyses of the motion response of filiform hairs are conducted by using a mathematical model of an artificial flow sensor to understand the possible operating ranges of a microfabricated device. It is found that the length and diameter of the sensory hair are the major parameters that determine the mechanical sensitivities and responses in a mean flow with an oscillating component. By changing the hair length, the angular displacement, velocity, and acceleration could be detected in a wide range of frequencies. Although the torques due to drag and virtual mass are very small, they are also very influential factors on the hair motion. The resonance frequency of the hair decreases as the length and diameter of the hair increase.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.29-34
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• 2015

Brain-computer interface (BCI) is being studied for convenient life in various application fields. The purpose of this study is to investigate a changing electroencephalography (EEG) for precise motion of a robot or an artificial arm. Three subjects who participated in this experiment performed three-task: Grip, Move, Relax. Acquired EEG data was extracted feature data using two feature extraction algorithm (power spectrum analysis and multi-common spatial pattern). Support vector machine (SVM) were applied the extracted feature data for classification. The classification accuracy was the highest at Grip class of two subjects. The results of this research are expected to be useful for patients required prosthetic limb using EEG.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.205-208
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• 2022

Multi-exposure high dynamic range (HDR) image reconstruction, the task of reconstructing an HDR image from multiple low dynamic range (LDR) images in a dynamic scene, often produces ghosting artifacts caused by camera motion and moving objects and also cannot deal with washed-out regions due to over or under-exposures. While there has been many deep-learning-based methods with motion estimation to alleviate these problems, they still have limitations for severely moving scenes. They also require large parameter counts, especially in the case of state-of-the-art methods that employ attention modules. To address these issues, we propose a frequency domain approach based on the idea that the transform domain coefficients inherently involve the global information from whole image pixels to cope with large motions. Specifically we adopt Residual Fast Fourier Transform (RFFT) blocks, which allows for global interactions of pixels. Moreover, we also employ Depthwise Overparametrized convolution (DO-conv) blocks, a convolution in which each input channel is convolved with its own 2D kernel, for faster convergence and performance gains. We call this LFFNet (Lightweight Frequency Fusion Network), and experiments on the benchmarks show reduced ghosting artifacts and improved performance up to 0.6dB tonemapped PSNR compared to recent state-of-the-art methods. Our architecture also requires fewer parameters and converges faster in training.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.1-8
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• 2006

This paper describes the procedures developing the algorithm for analyzing signals acquired from the Bridge Weigh-in-Motion (BWIM) system installed in Seohae Bridge as a part of the bridge monitoring system. Through the analysis procedure, information about heavy traffics such as weight, speed, and number of axles are attempted to be extracted from time domain strain data of the BWIM system. One of numerous pattern recognition techniques, artificial neural network (ANN) is employed since it can effectively include dynamic effects, bridge-vehicle interaction, etc. A number of vehicle running experiments with sufficient load cases are executed to acquire training and/or test set of ANN. Extracted traffic information can be utilized for developing quantitative database of loading effect. Also, it can contribute to estimate fatigue lift or current health condition, and design truck can be revised based on the database reflecting recent trend of traffic.

• Journal of the Korean Society of Physical Medicine
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• v.14 no.1
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• pp.53-61
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• 2019

PURPOSE: This study examined the dynamic range of motion (ROM) of the hip, knee, and ankle joint when wearing different shoe sole lifts, as well as the limb asymmetry of the range according to the leg length discrepancy (LLD) during normal speed walking. METHODS: The participants were 40 healthy adults. A motion analysis system was used to collect kinematic ROM data. The participants had 40 markers attached to their lower extremities and were asked to walk on a 6 m walkway, under three different shoe lift conditions (without an insole, 1 cm insole, and 2 cm insole). Visual3D professional software was used to coordinate kinematic ROM data. RESULTS: Most of the ROM variables of the short limbs were similar under each insole lift condition (p>.05). In contrast, when wearing a shoe with a 2 cm insole lift, the long limbs showed significant increases in flexion and extension of the knee joint as well as; plantarflexion, dorsiflexion, pronation, eversion, and inversion of the ankle joint (p<.05). Of the shoes with the insole lifts, significant differences in all ROM variables were observed between the left and right knees, except for the knee internal rotation (p<.05). CONCLUSION: As the insole lift was increased, more ROM differences were observed between the left and right limbs, and the asymmetry of the bilateral lower limbs increased. Therefore, appropriate interventions for LLD are needed because an artificial mild LLD of less than 2.0 cm could lead to a range of musculoskeletal problems of the lower extremities, such as knee and ankle osteoarthritis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.239-246
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• 2021

In the field of computer graphics and HCI, there are many studies on systems that create characters and interact naturally. Such studies have focused on the user's response to the user's behavior, and the study of the character's behavior to elicit positive emotions from the user remains a difficult problem. In this paper, we develop a prototype of an interaction system to elicit positive emotions from users according to the movement of virtual characters using artificial intelligence technology. The proposed system is divided into face recognition and motion generation of a virtual character. A depth camera is used for face recognition, and the recognized data is transferred to motion generation. We use imitation learning as a learning model. In motion generation, random actions are performed according to the first user's facial expression data, and actions that the user can elicit positive emotions are learned through continuous imitation learning.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.801-807
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• 2024

Linear motion robots are devices that perform functions such as transferring parts or positioning devices, and require high precision. In companies that develop linear robot application systems, human workers are in charge of quality control and fault diagnosis of linear robots, and the result and accuracy of a fault diagnosis varies depending on the skill level of the person in charge. Recently, there have been many attempts to utilize artificial intelligence to diagnose faults in industrial devices. In this paper, we present a system that automatically diagnoses linear rail and ball screw misalignment of a linear robot using transfer learning. In industrial systems, it is difficult to obtain a lot of learning data, and this causes a data imbalance problem. In this case, a transfer learning model configured by retraining an established model is widely used. The information obtained by using an acceleration sensor and torque sensor was used, and its usefulness was evaluated for each case. After converting the signal obtained from the sensor into a spectrogram image, the type of abnormality was diagnosed using an image recognition artificial intelligence classifier. It is expected that the proposed method can be used not only for linear robots but also for diagnosing other industrial robots.