• Journal of KIISE:Information Networking
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• v.30 no.6
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• pp.755-763
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• 2003

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.2
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• pp.211-218
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• 1998

In this paper, we analyze various errors in prediction results of ray tracing propagation model for microcellular environments. It is shown that improper electrical parameters of building materials and limitations of diffraction orders can cause high errors in prediction results. Especially, the effect of errors in building database on prediction results is considered in detail. It is also shown that the prediction error increases as the resolution of building map data is getting worse, and the error is analyzed depending on LOS and NLOS domains. Based on the results obtained by the analysis developed in this paper, 5 m resolution is suitable for the building map data if the maximum prediction error is required to be below 6 dB.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.2
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• pp.45-57
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• 2003

An artificial neural network model was developed to analyze and forecast Short-term river runoff from the Naju watershed, in Korea. Error back propagation neural networks (EBPN) of hourly rainfall and runoff data were found to have a high performance In forecasting runoff. The number of hidden nodes were optimized using total error and Bayesian information criterion. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$is greater than 0.99) for calibration and verification data sets. Increasing the time horizon for application data sets, thus mating the model suitable for flood forecasting. decreases the accuracy of the model. The resulting optimal EBPN models for forecasting hourly runoff consists of ten rainfall and four runoff data(ANN0410 model) and ten rainfall and ten runoff data(ANN1010 model). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$is greater than 0.92).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.2
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• pp.35-43
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• 1990

In this paper a two dimensional network adjustment theory is developed to analyze the plane trilateration network of single triangle network, of quadrilateral network, of polygon trilateration network and of combined network. The characteristics of error were analysed by developing an error propagation equation for each form of plane trilateration network. In case of combined network, the result of error analysis was represented by error ellipses and gross error detection was carried out by data snooping method.

• Journal of IKEEE
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• v.23 no.2
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• pp.479-486
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• 2019

CCN utilizes MHT-based content authentication scheme. Some schemes propose improved MHT scheme to solve the inefficiency of the MHT-based content authentication scheme which is caused by repetitive hash value computation and witness transmission. For using MHT, it is essentially needed to minimize the possibility of error-occurrence as well as to improve the efficiency of the authentication scheme. This paper describes the improved MHT scheme is error-prone. Also, it analyzes the effect of a segment authentication error, especially, the degree of error propagation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.303-310
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• 2007

Compressed video bitstreams are intended for real-time transmission over communication networks. Because video compression algorithms eliminate the temporal, spatial, and statistical redundancies, the coded video bitstreams are very sensitive to transmission errors. We propose an error resilient video coding technique to limit the effect of error propagation in low bit-rate video coding. The success of error resilient coding techniques relies on how accurately the transmission errors can be detected. To detect the transmission error, we propose a very simple error detection technique based on data hiding Next, we conceal the corrupted MB data using intra MB refresh and motion compensation with the estimated motion vector and compare the simulation results. This method will be useful in video communication in error Prone environment such as WCDMA networks.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.2
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• pp.167-172
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• 2015

In this paper, we have compared some radio propagation models in order to verify the performance of W.C.Y LEE propagation model in mountain area. The four propagation models, which are Okumura-Hata, ITU-R P.525, Egli and W.C.Y. LEE, are analyzed by comparing the differences between measured values and propagation loss estimation values. And a correction method for W.C.Y LEE model is suggested to improve the performance of W.C.Y. LEE model with measured data in mountain area. Simulation results show that the estimation error using W.C.Y LEE model is the lowest among four propagation models. Also, the results show that the corrected W.C.Y LEE model with suggested method improves the performance of propagation loss estimation.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.3
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• pp.413-420
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• 2010

An Estimation of VHF data link range for EW(Electronic Warfare) equipment in the sea environment was studied to predict the data link range between transmitting and receiving station. The theoretical estimation predicts within 3% error with actual measurement of VHF data link range at sea. Data link range factors including refraction and reflection are added in the basic wave propagation equation. The effect of refraction and reflection to the range is analysed with quantity level.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.984-990
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• 2002

We propose a new type of nonlinear fixed interval smoother to which an existing nonlinear smoother is modified. The nonlinear smoother is derived from two-filter formulas. For the backward filter. the propagation and the update equation of error states are derived. In particular, the modified update equation of the backward filter uses the estimated error terms from the forward filter. Data fusion algorithm, which combines the forward filter result and the backward filter result, is altered into the compatible form with the new type of the backward filter. The proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing algorithm to off-line navigation system and show the proposed algorithm estimates position, and altitude fairly well through the computer simulation.