• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.9
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• pp.663-669
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• 2004

The mobile tole-cardiology system is the new research area that support an ubiquitous health care based on mobile telecommunication networks. Although there are many researches presenting the modeling concepts of a GSM-based mobile telemedical system, practical application needs to be considered both compression performance and error corruption in the mobile environment. This paper evaluates three wavelet ECG compression algorithms over CDMA networks. The three selected methods are Rajoub using EPE thresholding, Embedded Zerotree Wavelet(EZW) and Wavelet transform Higher Order Statistics Coding(WHOSC) with linear prediction. All methodologies protected more significant information using Forward Error Correction coding and measured not only compression performance in noise-free but also error robustness and delay profile in CDMA environment. In addition, from the field test we analyzed the PRD for movement speed and the features of CDMA 1X. The test results show that Rajoub has low robustness over high error attack and EZW contributes to more efficient exploitation in variable bandwidth and high error. WHOSC has high robustness in overall BER but loses performance about particular abnormal ECG.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.141-145
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• 2009

In this paper, we propose an efficient lossless compression algorithm using spatial and temporal information. The proposed method obtains higher lossless compression of images than other lossless compression techniques. It is divided into two parts, a motion adaptation based predictor part and a residual error coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors. The predictor decides the proper selection of the spatial and temporal prediction values according to each past prediction error. The reduced error is coded by existing context coding method. Experimental results show that the proposed algorithm has better performance than those of existing context modeling methods.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.360-374
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• 2016

Since WSNs (Wireless Sensor Networks) applied to their application areas such as smart home, smart factory, environment monitoring, etc., depend on sensor data, the sensor data is the most important among WSN components. The resources of each node consisting of WSN are extremely limited in energy, hardware and so on. Due to these limitation, communication failure probabilities become much higher and the communication failure causes data loss to occur. For this reason, this paper proposes 2MC (Maximum/Minimum Compression) that is a method to compress sensor data by selecting circular queue-based maximum/minimum sensor data values. Our proposed method reduces sensor data losses and value errors when they are recovered. Experimental results of 2MC method show the maximum/minimum 35% reduction efficiency in average sensor data accumulation error rate after the 3 times compression, comparing with CQP (Circular Queue Compression based on Period) after the compressed data recovering.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.587-599
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• 1996

In general fractal imge compression, each range block is approximated by a contractive transform of the matching domain block under the mean squared error criterion. In this paper, a distortion measure reflecting the properties of human visual system is defined and applied to a fractal image compression. the perceptual distortion measure is obtained by multiplying the mean square error and the noise sensitivity modeled by using the background brightness and spatial masking. In order to compare the performance of the mean squared error and perceptual distortion measure, a simulation is carried out by using the 512*512 Lena and papper gray image. Compared to the results, 6%-10% compression ratio improvements under improvements under the same image quality are achieved in the perceptual distortion measure.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.407-411
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• 2010

During the cardiopulmonary resuscitation (CPR), the correct chest compression depth and period are very important to increase the resuscitation possibility. For the feedback of chest compression depth, the depth monitoring device based on the accelerometer is developed and widely used. But this method tends to overestimate the compression depth on the bed. To overcome this limitation, the chest compression depth estimation method using two accelerometers is suggested With the additional accelerometer between the patient and mattress on the bed, the compression of the mattress is also measured and it is used to compensate the overestimation error. The experimental results show that the single accelerometer estimates as 61.4mm for the actual compression depth of 43.6mm on the mattress. The depth estimation with the dual accelerometer was 44.6mm which is close to the actual depth. With the automatic zeroing in every single compression, the integration error for the depth can be reduced. The dual accelerometer method is effective to increase the accuracy of the chest compression depth estimation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.8
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• pp.99-104
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• 2004

This paper proposes a new error pattern ROM (EP-ROM) compression method for continuousdata. The EP-ROM reduces the ROM size by dividing the continuous data into coarse values and their errors and by storing the indices of error patterns instead of the non. This method significantly reduces the ROM size by exploiting the characteristic that the errors for continuous data possess the same patterns. The experiment results show that the EP-ROM achieves 60∼77% ROM size reductions for various continuous data.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.533-545
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• 2017

Massive volumes of GPS trajectory data bring challenges to storage and processing. These issues can be addressed by compression algorithm which can reduce the size of the trajectory data. A key requirement for GPS trajectory compression algorithm is to reduce the size of the trajectory data while minimizing the loss of information. Synchronized Euclidean distance (SED) as an important error measure is adopted by most of the existing algorithms. In order to further reduce the SED error, an improved algorithm for open window time ratio (OPW-TR) called local optimum open window time ratio (LO-OPW-TR) is proposed. In order to make SED error smaller, the anchor points are selected by calculating point's accumulated synchronized Euclidean distance (ASED). A variety of error metrics are used for the algorithm evaluation. The experimental results show that the errors of our algorithm are smaller than the existing algorithms in terms of SED and speed errors under the same compression ratio.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.4
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• pp.27-33
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• 2001

In this study, it is observed that the distribution of combustion chamber volume affects the volumetric efficiency. The distribution ratio was adjusted by controlling combustion chamber volume of head and piston bowl one. Four cases were investigated, which are the combination of different distribution ratios and different compression ratios (9.8-10.0). A commercial SOHC 3-valve engine was modified by cutting the bottom face of the head and/or replacing the piston by the one that has different volume. The result shows that the less the head side volume, the more volumetric efficiency is achieved under the same compression ratio. It is also observed that increasing volumetric efficiency results in early knock occurrence due to increased "real" compression ratio. To consider reliability in estimating the volumetric efficiency, we examined the sensitivity of the AFR equation to possible errors in emission measurements. It is shown that the volumetric efficiency, which is calculated by measuring AFR and fuel consumption, can be controlled in 1% error. 1% error.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.169-172
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• 2005

Genetic algorithm based predictor for lossless image compression is propsed. We describe a genetic algorithm to learn predictive model for lossless image compression. The error image can be further compressed using entropy coding such as Huffman coding or arithmetic coding. We show that the proposed algorithm can be feasible to lossless image compression algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.915-927
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• 1997

In this paper, we propose an error concealment technique using directional interpolation in block-based image compression. In the proposed method the edge direction is determined by finding the maximum correlation coefficients of boundary pixels of blocks neighboring the errored block in spatial domain. Then the errored block is interpolated linearly or bilinearly along the determined edge direction. The proposed method can conceal the block error, the macro block error, and the slice error adaptively. Also, the parameters for the directional interpolation are represented by closed forms. When applied to compressed images, the proposed method shows superior subjective and objective quality to conventional error concealment methods.