• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.599-607
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• 2018

This paper presents a ground-to-air bistatic radar system and its implementation algorithm, which resembles an SAR(synthetic aperture radar) reconstruction algorithm. Via cooperative working between a standoff transmitting radar and an array of ground based receiving radars, it detects and images moving targets under clutter in the air. In the proposed system, the whole receiving antenna aperture is synthesized by physical ground based radars, and thus, unlike conventional SAR, it does not require long illumination time of the target area. The reconstruction algorithm uses planewave approximation based polar format processing, which alleviates the requirement of positioning the receiving radars, which can cause grating lobes if not chosen properly. We derive a reconstruction algorithm including clutter suppression and discuss implementation issues, such as the resolution of a reconstructed image and the method of compensation for the irregularity of the receiving radars' positions. A simulation that validates the proposed algorithm is also shown.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.8
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• pp.118-128
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• 2004

Exhaust plume effects on longitudinal aerodynamics of missile were investigated by wind tunnel tests using a solid plume simulator and CFD analyses with both the solid plume and air jet plumes. Approximate plume boundary prediction technique was used to produce the outer shape of the solid plumer and chamber conditions and nozzle shapes of the air jet plumes were determined through plume modeling technique to compensate the difference in thermodynamic properties between air and real plume. From comparisons among turbulence models in case of external flow interaction with the air jet plume, Spalart-Allmaras model turned out to give accurate result and to be less grid-dependent. Effects induced by the plume were evaluated through the computations with Spalart-Allmaras turbulence model and the air jet plume to account for various ratios of chamber and ambient pressure and Reynolds number under the flight test condition.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.5
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• pp.438-447
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• 2008

This study is focused on reliability based design optimization (RBDO) using moving least squares. A response surface is used to derive a limit-state equation for reliability based design optimization. Response surface method (RSM) with least square method (LSM) or Kriging will be used as a response surface. RSM is fast to make the response surface. On the other hand, RSM has disadvantage to make the response surface of nonlinear equation. Kriging can make the response surface in nonlinear equation precisely but needs considerable amount of computations. The moving least square method (MLSM) is made of both methods (RSM with LSM+Kriging). Numerical results by MLSM are compared with those by LMS in Rosenbrock function and six-hump carmel back function. The RBDO of engine duct of smart UAV is pursued in this paper. It is proved that RBDO is useful tool for aerospace structural optimal design problems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.123-129
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• 2015

The Kalman filter has been widely used in the kinematic GPS positioning due to its flexibility and efficiency in computational points of view. At the same time, the relative positioning technique also provided the high precision positioning results by removing the systematic errors in the measurements significantly. However, the positioning quality may be degraded following to longer in baseline length. For this case, it is required that the remaining atmospheric effects, such as double-difference ionospheric delay and zenith wet delay, should be properly modeled by examining the characteristics of the stochastic processes. In general, atmospheric effects are estimated with the assumption of random walk, or the first-order Gauss-Markov stochastic process, which requires the precise modeling on the corresponding process noises. Therefore, we determined and provided the parameters for modelling the process noises for atmospheric effects. The auto-correlation functions are empirically determined at first, and then the parameters are extracted from the empirical auto-correlation function. In fact, the test results can be either applied directly, or used as guidance values for the modeling of process noises in the kinematic GPS positioning.

• Journal of Korean Society of Steel Construction
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• v.11 no.4 s.41
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• pp.329-338
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• 1999

A systematic procedure to evaluate fatigue damages and to predict remaining fatigue lives is introduced for a steel railway bridge. Fatigue damages are evaluated by using the currently available fatigue damage theory. Fatigue lives with the condition of fatigue crack initiation are estimated by the probabilistic approach based on the reliability theory as well as the simplified procedure. A equivalent deterministic procedure is also suggested to assess the remaining fatigue life under various traffic conditions. Numerical simulations are used to assess dynamic stress histories with correction factors. Loading models are obtained from the passenger volume data. Train coincidences are also considered. Based on the results, the fatigue life is found to be underestimated by without considering the coincidence of trains on the bridge. The simplified method proposed in this study are found to yield approximately the same results as the systematic procedure.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.661-672
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• 2005

For the efficient stochastic optimization of steel structures for which a large number of analyses is required, artificial neural networks,which have emerged as a powerful tool that could have been used to replace time-consuming procedures in many scientific or engineering applications, are applied. They are utilized for the solution of the equilibrium equations resulting from the application of the finite element method in connection with the reanalysis type of problem, for which a large number of finite element analyses are required in this study. As such, the use of artificial neural networks to predict finite element analysis outputs simplifies and facilitates the performance of the stochastic optimal design of structural systems where a trained neural network is used to replace the structural reanalysis phase. Moreover, to improve efficiency of used artificial neural networks, genetic algorithm is utilized. The stochastic optimizer used in this study is an algorithm based on the evolution theory. The efficiency of the proposed procedure is examined in problems with both volume (weight) functions and real-world cost functions

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.109-123
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• 2011

In this study, 2D finite volume model, which can apply to the mixed meshes that is effective to treat the complicated topography such as a natural river, is developed. To do so, an algorithm for finding the neighbouring cell of a computational cell is introduced, and fluxes are computed using the HLLC approximate Riemann solver at each interface between a computational cell and it's neighbouring cells. Moreover, in order to numerically treat the bed slope which has important effect on the balance between flux gradients and sourte terms, different formula to compute the bed slope for rectangular and triangular mesh are applied. The developed model is applied to analyze dam-break in an experimental channel with $90^{\circ}$ bend and Malpasset dam-break in France. The two cases consist of mixed meshes and the suggested method is validated for the experimental channel and natural channel by comparison with the experimental data, field data and computed results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.279-286
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• 2013

The recent power shortages due to surge in demand for electricity highlights the importance of smart grid technologies for efficient use of power. The experimental content for vulnerability against availability of smart meter, an essential component in smart grid networks, has been reported. Designing availability protection mechanism to boost the realization possibilities of the secure smart grid is essential. In this paper, we propose a mechanism to detect the availability infringement attack for smart meter and also to find anomaly nodes through analyzing smart grid structure and traffic patterns. The proposed detection mechanism uses approximate entropy technique to decrease the detection load and increase the detection rate with few samples and utilizes the signal information(CIR or RSSI, etc.) that the anomaly node can not be changed to find the anomaly nodes. Finally simulation results of proposed method show that the detection performance and the feasibility.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.1013-1019
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• 2016

This paper describes a novel Context-awareness Markov Chain Prediction (CMCP) algorithm based on movement prediction using Markov chain in Delay Tolerant Network (DTN). The existing prediction models require additional information such as a node's schedule and delivery predictability. However, network reliability is lowered when additional information is unknown. To solve this problem, we propose a CMCP model based on node behaviour movement that can predict the mobility without requiring additional information such as a node's schedule or connectivity between nodes in periodic interval node behavior. The main contribution of this paper is the definition of approximate speed and direction for prediction scheme. The prediction of node movement forwarding path is made by manipulating the transition probability matrix based on Markov chain models including buffer availability and given interval time. We present simulation results indicating that such a scheme can be beneficial effects that increased the delivery ratio and decreased the transmission delay time of predicting movement path of the node in DTN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.823-832
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• 2011

In this paper, an efficient blind carrier frequency offset (CFO) estimation method in orthogonal frequency division multiplexing (OFDM) systems is proposed. In the proposed method, we obtain two time different received OFDM symbols by using both the cyclic prefix and oversampling technique, and a cost function is defined by using the two OFDM symbols. We show that the cost function can be approximately expressed as a cosine function. Using a property of the cosine function, a formular for estimating the CFO is derived. The estimator of the CFO requires three independent cost function values calculated at three different points of frequency offset. The proposed method is very efficient in computational complexity since no searching operation for the minimum cost value is required. The proposed method reduces 97% of the amount of FFT computation, compared with the ML method. Unlike the conventional methods such as the ML method and the MUSIC] method, the accuracy of the proposed method is independent of the searching resolution since the closed form solution exists. The computer simulation shows that the performance of the proposed method is superior to those of the MUSIC and the ML method.