• The KIPS Transactions:PartB
• /
• v.10B no.2
• /
• pp.143-150
• /
• 2003

Error concealment plays an important role in combating transmission errors. Methods of error concealment which produce better quality are generally of higher complexity, thus making some of the more sophisticated algorithms is not suitable for real-time applications. In this paper, we develop temporal and spatial error resilient video encoding and data hiding approach to facilitate the error concealment at the decoder. Block interleaving scheme is introduced to isolate erroneous blocks caused by packet losses for spatial area of error resilience. For temporal area of error resilience, data hiding is applied to the transmission of parity bits to protect motion vectors. To do error concealment quickly, a set of edge features extracted from a block is embedded imperceptibly using data hiding into the host media and transmitted to decoder. If some part of the media data is damaged during transmission, the embedded features are used for concealment of lost data at decoder. This method decreases a complexity of error concealment by reducing the estimation process of lost data from neighbor blocks. The proposed data hiding method of parity bits and block features is not influence much to the complexity of standard encoder. Experimental results show that proposed method conceals properly and effectively burst errors occurred on transmission channel like Internet.

• Journal of Korea Water Resources Association
• /
• v.55 no.spc1
• /
• pp.1295-1303
• /
• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• The Journal of the Acoustical Society of Korea
• /
• v.35 no.4
• /
• pp.295-302
• /
• 2016

Underwater acoustic communication channel is often defined as a multipath fading channel since the multipath arrivals from various paths interfere with each other and cause frequency dependent constructive or destructive interference in received signals. Therefore signal-to-noise ratio (SNR) of received signal fluctuates as a function of frequency. In addition, sea surface fluctuation induces frequency dependent time variant signal fading due to coherent component variation of surface bounce path. The frequency shift keying (FSK) system is known to be less sensitive and more robust under these interference and fading, and M-ary frequency shift keying (MFSK) system is adopted to increase a data rate. In this study, a bit error rate (BER) of 4 channels 4FSK system are examined in shallow sea multipath channel. Experimental results show that RS code reduces efficiently the BER of 4FSK system since frequency dependent time-varying fading is characterized to give burst errors. The BER of a different data rate or different source-to-receiver range depends on not only the channel coherent bandwidth but also frequency dependent multipath fading.