• Smart Structures and Systems
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• v.14 no.2
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• pp.159-189
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• 2014

One of the most important requirements in the evaluation of existing structural systems and ensuring a safe performance during their service life is damage assessment. Damage can be defined as a weakening of the structure that adversely affects its current or future performance which may cause undesirable displacements, stresses or vibrations to the structure. The mass and stiffness of a structure will change due to the damage, which in turn changes the measured dynamic response of the system. Damage detection can increase safety, reduce maintenance costs and increase serviceability of the structures. Artificial Neural Networks (ANNs) are simplified models of the human brain and evolved as one of the most useful mathematical concepts used in almost all branches of science and engineering. ANNs have been applied increasingly due to its powerful computational and excellent pattern recognition ability for detecting damage in structural engineering. This paper presents and reviews the technical literature for past two decades on structural damage detection using ANNs with modal parameters such as natural frequencies and mode shapes as inputs.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.12
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• pp.164-175
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• 2008

Atmospheric effects on laser beam propagation can be broken down into two categories: attenuation of the laser power and fluctuation of laser power due to laser beam deformation. Attenuation consists of scattering of the laser light photons by the fog. Laser beam deformation occurs because of small-scale dynamic changes in the index of refraction of the atmosphere. This causes pointing error. In order to analyse these effect on optical wireless communication system, in this paper uses cassegrain optics as a transmitting and receiving telescope, AID as a detecting device and ill as a light source. The signal modulating and demodulating method is a IM/DD. I show the effects of fog and pointing error and calculate the possible communication distance for BER is $10^{-9}$.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• Journal of Communications and Networks
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• v.10 no.4
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• pp.422-429
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• 2008

Mobile peer-to-peer (P2P) systems have recently got in the limelight of the research community that is striving to build efficient and effective mobile content addressable networks. Along this line of research, we propose a new peer-to-peer file sharing protocol suited to mobile ad hoc networks (MANET). The main ingredients of our protocol are network coding and mobility assisted data propagation, i.e., single-hop communication. We argue that network coding in combination with single-hop communication allows P2P file sharing systems in MANET to operate in a more efficient manner and helps the systems to deal with typical MANET issues such as dynamic topology and intermittent connectivity as well as various other issues that have been disregarded in previous MANET P2P researches such as addressing, node/user density, non-cooperativeness, and unreliable channel. Via simulation, we show that our P2P protocol based on network coding and single-hop communication allows shorter file downloading delays compared to an existing MANET P2P protocol.

• Journal of Broadcast Engineering
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• v.8 no.2
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• pp.153-162
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• 2003

This paper describes a structure of adaptive equalizer to improve reception performance of ATSC digital television (DTV) for 8-VSB receivers. There are many strong and dynamic echoes affecting reliable reception of DTV signal. Conventional DFE based least mean square (LMS) algorithm is readily implemented and has good Performance. There are still problems to be solved, however, in handling strong echoes and indoor reception. In this paper, structure of adaptive equalizer to mitigate these Problems in strong multipath interference conditions and indoor reception environment is first presented. Methods to reduce error propagation effects on DFE and initialization scheme of filter coefficients for fast convergence are then introduced. Computer simulation results prove that an adaptive equalizer with proposed design methods can combat with Brazil Ensemble and the Threshold of Visibility(TOV) is improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.363-366
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• 2010

Currently social games with an emphasis on the relationship between the friends, especially women customers, have contributed to the expansion of game market attracting large audiences. Though recent interest in social games and the explosive propagation of social game into game industry, scholarly research for social game is insufficient. The objective of the study is to explore the success factors for successful social games. We suggest the guidelines for development of social game. Commercial success of social games and the number of users with the best game, farmville, were investigated for understanding key success factors in social game field. As a result, social interaction, simple interface, non-dynamic methods, instrumental rationality factors have been identified. This study will expect the guideline in order to develop a successful social games.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.612-621
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• 2008

For the purpose of improving accuracy in jet noise prediction and investigating its generation mechanism, high subsonic jets were computed by using compressible Large Eddy Simulation(LES), wherein the inflow forcing or disturbance added in the inflow shear layer was incorporated. The far-field Sound Pressure Levels(SPL) as well as the flow field resulted in good agreement with available experimental data by applying only the high azimuthal modes among the inflow forcing parameters. We found that this result was due to an important role of the inflow forcing upon breaking down the axiymmetric vortices that caused high amplitude velocity and pressure fluctuations. In order to examine generation mechanism of the dominant noise component, wavelet transformation was introduced to reveal the presence of a well-organized structure of pressure fluctuations that originated mainly from vortex motions near the end of the jet potential core. This structure took a train of alternately positive and negative wavelet-transformed pressure regions along the jet distance, spreading towards the downstream with advection and propagation. It was concluded that this structure and its dynamic motion are the reason why a high subsonic jet produces the dominant noise with a particular downstream directivity.

• Geomechanics and Engineering
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• v.13 no.3
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• pp.411-429
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• 2017

A Spectral Element Method for 3D seismic wave propagation simulation is derived based on the three-dimensional fluctuating elastic dynamic equation. Considering the 3D real terrain and the attenuation characteristics of the medium, the topographic effect of Wenchuan earthquake is simulated by using the Spectral Element Method (SEM) algorithm and the ASTER DEM model. Results show that the high PGA (peak ground acceleration) region was distributed along the peak and the slope side away from the epicenter in the epicenter area. The overall distribution direction of high PGA and high PGV (peak ground velocity) region is parallel to the direction of the seismogenic fault. In the epicenter of the earthquake, the ground motion is to some extent amplified under the influence of the terrain. The amplification effect of the terrain on PGA is complicated. It does not exactly lead to amplification of PGA at the ridge and the summit or attenuation of PGA in the valley.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.702-708
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• 2019

This paper deals with break size estimation of loss of coolant accidents (LOCA) using a nonlinear autoregressive with exogenous inputs (NARX) neural network. Previous studies used static approaches, requiring time-integrated parameters and independent firing algorithms. NARX neural network is able to directly deal with time-dependent signals for dynamic estimation of break sizes in real-time. The case studied is a LOCA in the primary system of Bushehr nuclear power plant (NPP). In this study, number of hidden layers, neurons, feedbacks, inputs, and training duration of transients are selected by performing parametric studies to determine the network architecture with minimum error. The developed NARX neural network is trained by error back propagation algorithm with different break sizes, covering 5% -100% of main coolant pipeline area. This database of LOCA scenarios is developed using RELAP5 thermal-hydraulic code. The results are satisfactory and indicate feasibility of implementing NARX neural network for break size estimation in NPPs. It is able to find a general solution for break size estimation problem in real-time, using a limited number of training data sets. This study has been performed in the framework of a research project, aiming to develop an appropriate accident management support tool for Bushehr NPP.