• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.396-400
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• 2009

During periods of large data transmission, routing selection methods are used to efficiently manage data traffic and improve the speed of transmission. One approach in routing selection is AntNet that applies the Ant algorithm in transmissions with uniform probability. However, this approach uses random selection, which can cause excessive data transmission rates and fail to optimize data This paper presents the use of the Genetic Algorithm (GA) to efficiently route and disperse data transmissions, during periods with "unnecessary weight increases for random selection". This new algorithm for improved performance provides highly accurate estimates of the transmission time and the transmission error rate.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.483-492
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• 2004

This paper presents an efficient algorithm for the estimation of damage location and severity in bridge structures using Probabilistic Neural Network (PNN). Generally, the Back Propagation Neural Network (BPNN)-based damage detection methods need a lot of training patterns for neural network learning process and the optimum architecture of a BPNN is selected by trial and error. In this paper, the PNN instead of the conventional BPNN is used as a pattern classifier. The modal properties of damaged structure are somewhat different from those of undamaged one. The basic idea of proposed algorithm is that the PNN classifies a test pattern which consists of the modal characteristics from damaged structure, how close it is to each training pattern which is composed of the modal characteristics from various structural damage cases. In this algorithm, two PNNs are sequentially used. The first PNN estimates the damage location using mode shape and the results of the first PNN are put into the second PNN for the damage severity estimation using natural frequency. The proposed damage assessment algorithm using the PNN is applied to a cable-stayed bridge to verify its applicability.

• The Journal of the Acoustical Society of Korea
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• v.9 no.3
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• pp.48-55
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• 1990

We analyze the effect of second-order sampling on estimating the mean frequency of the Doppler signal. In order to reduce the sampling frequency of analogue-to-digital converter, it is possible to obtain the Doppler signal by sampling the radio frequency echo signal with the low frequence of $4f_0$/5 or $4f_0$/9 instead of $4f_0$, where $f_0$ is the center frequency of the transmitted signal. The computer simulation and experiments show that if the narrowband signal is transmitted as is usual in the Doppler system, the error of the mean frequency estimates due to the low sampling frequency is negligible.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.479-485
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• 2009

When a part of data is unobserved the marginal likelihood of parameters given the observed data often involves analytically intractable high dimensional integral and hence it is hard to find the maximum likelihood estimate of the parameters. Simulated maximum likelihood(SML) method which estimates the marginal likelihood via Monte Carlo importance sampling and optimize the estimated marginal likelihood has been used in many applications. A key issue in SML is to find a good proposal density from which Monte Carlo samples are generated. The optimal proposal density is the conditional density of the unobserved data given the parameters and the observed data, and attempts have been given to find a good approximation to the optimal proposal density. Algorithms which adaptively improve the proposal density have been widely used due to its simplicity and efficiency. In this paper, we describe a fully adaptive algorithm which has been used by some practitioners but has not been well recognized in statistical literature, and evaluate its estimation performance and robustness via a simulation study. The simulation study shows a great improvement in the order of magnitudes in the mean squared error, compared to non-adaptive or partially adaptive SML methods. Also, it is shown that the fully adaptive SML is robust in a sense that it is insensitive to the starting points in the optimization routine.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.209-216
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• 2005

In wireless sensor networks, an estimation method is proposed for distances between nodes within two hops. The method uses only proximity information of nodes without physiccal distance measurements. It drastically improves the performance of localization algorithms based on Proximity information. In addition, it is the first method that estimates distances between nodes exactly in two hops. The distances are estimated from the number of common neighbors under an assumption that the number of common neighbors is proportional to the intersection of two unit disks centered at the two nodes. Simulation analysis shows that the estimation error is roughly from 10 to 20 percent of real distances. Meanwhile, the number of messages required by a distributed algorithm realizing this method is only two times the number of nodes.

• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.106-113
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• 2008

This paper presents an underwater navigation system based on range measurements from a known reference station fixed on the sea bottom or floated at surface with a buoy, for which the system is extended to 3-dimensional coordinates. We formulated a state equation in polar coordinates and constituted an extended Kalman filter for discrete-time implementation of the navigation algorithm. The autonomous underwater vehicle, lSiMl, cruising with a constant speed can estimate its trajectory using just range measurements and additional depth, heading and pitch sensors. Simulation studies were performed to evaluate the underwater navigation of the maneuvering AUV with range measurements. We modulated the sample rate of range measurements to evaluate the effect of the update rate, and changed the initial position error of the AUV to check the robustness to estimation errors. Simulation results illustrates that the extended navigation system provides convergence of the state estimates. The navigation system was conditionally stable when it had initial position errors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1A
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• pp.18-30
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• 2004

In this paper, the calibration problem of an asynchronous CDMA-based antenna array is studied. A new iterative calibration algorithm for antenna array in the presence of frequency offset error is presented. The algorithm is applicable to a non-linear array and does not require a prior knowledge of the (direction of arrivals) DOAs of the signals of any user, and it only requires the code sequence of a reference user. The algorithm is based on the two step procedures, one for estimating both channel and frequency offset and the other for estimating the unknown array gain and phase. Consequently, estimates of the DOAs, the multi-path impulse response of the reference signal sources, and the carrier frequency offset as well as the calibration of antenna array are provided. The performance of the proposed algorithm is investigated by means of computer simulations and is verified by using field data measured through a custom-built W-CDMA test-bed.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.396-409
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• 2012

With the proliferation of diverse wireless devices, there is an increasing concern about the security of location information which can be spoofed or disrupted by adversaries. This paper investigates the characterization and detection of location spoofing attacks, specifically those which are attempting to falsify (degrade) the position estimate through signal strength based attacks. Since the physical-layer approach identifies and assesses the security risk of position information based solely on using received signal strength (RSS), it is applicable to nearly any practical wireless network. In this paper, we characterize the impact of signal strength and beamforming attacks on range estimates and the resulting position estimate. It is shown that such attacks can be characterized by a scaling factor that biases the individual range estimators either uniformly or selectively. We then identify the more severe types of attacks, and develop an attack detection approach which does not rely on a priori knowledge (either statistical or environmental). The resulting approach, which exploits the dissimilar behavior of two RSS-based estimators when under attack, is shown to be effective at detecting both types of attacks with the detection rate increasing with the severity of the induced location error.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.822-826
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• 2013

In this paper, we propose an AFDO (Adaptive Fault Diagnosis Observer) and a fault tolerant controller for a class of nonlinear continuous-time system under the nonlinear abrupt actuator faults. Together with its estimation laws, the AFDO which estimates that the actuator faults is designed by using the Lyapunov analysis. Then, based on the designed AFDO, an adaptive sliding mode controller is proposed as the fault tolerant controller. Using Lyapunov stability analysis, we also prove the uniform boundedness of the state, the output and the fault estimation errors, and the asymptotic stability of the tracking error under the nonlinear time-varying faults. Finally, we illustrate the effectiveness of the proposed diagnosis method and the control scheme thorough computer simulations.

• 한국해양학회지
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• v.12 no.1
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• pp.7-12
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• 1977

Vertical mixing in the ocean affects the formation of water masses as well as the vertical distribution of nutrients and dissolved substances. this study is to investigate the effect of stability on the intensity of vertical transfer in the case of shallow and straitfied channel. It is found that the relation of the stability and vertical turbulent diffusion is given by K$\sub$z/ = -${\beta}$-(c+${\beta}$) / ${\alpha}$(E-1/${\alpha}$) where K$\sub$z/ and E denotes the vertical turbulent diffusion coefficient and stability, respectively. The empirical coefficients ${\alpha}$, ${\beta}$ and c depend on the magnitude of vertical components and stability, i.e., through thermocline intensity. The study indicates that the diffusivity of the surface mixed layer is (K$\sub$z/)=300∼1,200$\textrm{cm}^2$/sec, the thermocline layer is (K$\sub$z/)= 50∼200$\textrm{cm}^2$/sec and the cold layer is (K$\sub$z/)=200∼600$\textrm{cm}^2$/sec based on near- minimum least-squares error estimates from the regression analysis. An important result of our study comes out that the model is in accordance with the general trends of the effect of stability on the vertical turbulent diffusion coefficients in the case of shallow and strongly stratified channel.