• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.624-624
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• 2006

• Journal of the Korean Society for Precision Engineering
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• v.17 no.6
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• pp.135-142
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• 2000

In this paper, 3-dimensional numerical model of an escalator is developed to study the vibration characteristics. This proposed model is able to consider the elastic deformation of the frame during transient dynamic analysis. Deformation modes which are used to calculate the elastic deformation are selected from the FE model analysis. Because low frequency vibration is very important to the ride quality of fore/aft direction, low frequency deformation modes of the frame below 20Hz are considered. To show validity of this dynamics model, longitudinal acceleration of a step is compared with test data in frequency domain. Then robust design technique is applied to determine important design factors and improve ride quality with small number of experiments.

• Earthquakes and Structures
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• v.21 no.6
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• pp.601-612
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• 2021

The paper concerns the selection of a design accelerograms used for the slope stability assessment under earthquake excitation. The aim is to experimentally verify the Arias Intensity as an indicator of the excitation threat to the slope stability. A simple dynamic system consisting of a rigid block on a rigid inclined plane subjected to horizontal excitation is adopted as a slope model. Strong ground motions recorded during earthquakes are reproduced on a shaking table. The permanent displacement of the block serves as a slope stability indicator. Original research stand allows us to analyse not only the relative displacement but also the acceleration time history of the block. The experiments demonstrate that the Arias Intensity of the accelerogram is a good indicator of excitation threat to the stability of the slope. The numerical analyses conducted using the experimentally verified extended Newmark's method indicate that both the Arias Intensity and the peak velocity of the excitation are good indicators of the impact of dynamic excitation on the dam's stability. The selection can be refined using complementary information, which is the dominant frequency and duration of the strong motion phase of the excitation, respectively.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.148-156
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• 2009

The fixed spectrum assignment policy in today's wireless networks leads to inefficient spectrum usage. Cognitive radio network is a new communication paradigm that enables the unlicensed users to opportunistically use the spatio-temporally unoccupied portions of the spectrum, and hence realizing a dynamic spectrum access (DSA) methodology. Interference temperature model proposed by Federal Communications Commission (FCC) permits the unlicensed users to utilize the licensed frequencies simultaneously with the primary users provided that they adhere to the interference temperature constraints. In this paper, we formulate two NP-hard optimal scheduling methods that meet the interference temperature constraints for cognitive radio networks. The first one maximizes the network throughput, whereas the second one minimizes the scheduling delay. Furthermore, we also propose suboptimal schedulers with linear complexity, referred to as maximum frequency selection (MFS) and probabilistic frequency selection (PFS). We simulate the throughput and delay performance of the optimal as well as the suboptimal schedulers for varying number of cognitive nodes, number of primary neighbors for each cognitive node, and interference temperature limits for the frequencies. We also evaluate the performance of our proposed schedulers under both additive white gaussian noise (AWGN) channels and Gilbert-Elliot fading channels.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.58-71
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• 2019

This paper proposes architecture of a cognitive radio engine platform and the allowable frequency channel reasoning method that enables acquisition of the allowable channels for the military tactical network environment. The current military tactical wireless communication system is increasing need to secure a supplementary radio frequency to ensure that multiple wireless networks for different military wireless devices coexist, so that tactical wireless communication between the same or different systems can be operated effectively. This paper presents the allowable frequency channel reasoning method based on cognitive radio engine for realizing DSA(Dynamic Spectrum Access) as an optimal available frequency channel. To this end, a case-based allowable frequency channel reasoning method for cognitive radio devices is proposed through modeling of primary user's traffic status and calculation of channel occupancy probability. Also through the simulation of the performance analysis, changing rate of collision probability between the primary users' occupancy channel and the available channel acquisition information that can be used by the cognitive radio device was analysed.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.103-123
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• 1999

Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.205-213
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• 2012

In this paper, we propose a new channel hopping scheme based on IEEE 802.11h as a good countermeasure against jamming attacks in IEEE 802.11 wireless networks. 802.11h Dynamic Frequency Selection (DFS) is a mechanism which enables hopping to a best channel with full channel measurement, not a randomly chosen channel, when the current link quality degradation occurs due to interferers such as military radars. However, under jammer attacks, this needs a time for full channel measurement before a new channel hopping and due to link disconnection during the time network performance degradation is inevitable. In contrast, our proposed schemes make an immediate response right after a jammer detection since every device is aware of next hopping channel in advance. To do this, a next hopping channel is announced by Beacon frames and the channel is selected by full channel measurement within Beacon intervals. Simulation results show that proposed scheme minimizes throughput degradation and keeps the advantages of DFS.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.375-382
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• 2016

The mechanical property of a carbon-fiber-reinforced plastic (CFRP) is subjected to two elements, carbon fiber and polymer resin, in a first step and the selection of multi-layered structure is second one. Many combination of fabric layers, i.e. plainweave, twillweave, can be derived for candidates of test specimen used for a basic mechanical components so that a reliable identification of dynamic nature of possible multi-layered structures are essential during the development of CFRP based component system. In this paper, three kinds of multi-layered structure specimens were prepared and the dynamic characteristics of service specimens were conducted through classical modal test process with impact hammer. In addition, the design sensitivity analysis based on transmissibility function was applied for the measured response data so that the response sensitivity for each resonance frequency were compared for three CFRP test specimens. Finally, the evaluation of CFRP specimen over different multi-layered fabric structures are commented from the experimental consequences.

• Structural Monitoring and Maintenance
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• v.2 no.4
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• pp.399-418
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• 2015

Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in-service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions-based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)-Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a "blind" scenario, without any previous information about type and location of damage.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.214-220
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• 2009

The spindle is the main component in machine tools. The static and dynamic stiffness of the spindle directly affect the machining productivity and surface integrity of the workpiece. The static and dynamic stiffness of the spindle depend on the shaft size, bearing arrangement, bearing span length, and so on. Therefore, the selection of shaft size and bearing span length are important to improve the spindle stiffness. This paper presents the determination of shaft size and bearing span length in spindle design step. In order to select the optimal bearing and built-in motor locations with constraint conditions, the extreme vertices design was applied. The results show that extreme vertices design is usable for spindle design with design constraints.