• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.578-589
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• 2014

In this paper, we introduce the concept of cyber-physical intersection systems (CPIS) which interconnects roadside units (RSU) located at the intersection, on-board units (OBU) of moving vehicles, and the smartphone apps, named the Smartphone Agent (SA). At the pedestrian mode of the SA, the connectivity management schemes, such as a location update and a handover control algorithm, are proposed to better support the CPIS services while minimizing the power consumption of the pedestrian's smartphone. We develop a real prototype of the CPIS, including RSU, OBU, and the SA. Based on the numerical results collected from a pedestrian moving around the Pusan National University campus, we validate that the proposed connectivity management schemes can improve not only the power efficiency of the pedestrian's smartphone, but also the quality of the CPIS services.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2783-2797
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• 1997

This paper proposes a new motion estimation algorithm that employs matching in a variable search area. Instead of uisg a fixed search range for coarse motion estimation, we examine a varying search range, which is determined adaptively by the peak signal to noise ratio (PSNR) of the frame difference. The hexagonal matching method is one of the refined methods in image warping. It produces improved image quality, but it requires a large amount of computataions. The proposed adaptive partial matching method reduces computational complexity below about 50% of the hexagonal matching method, while maintaining the image quality comparable. The performance of two motion compensation methods, which combine the affine or bilinear transformation with the proposed motion estimation algorithm, is evaluated based on the following criteria:computtational complexity, number of coding bits, and reconstructed image quality. The quality of reconstructed images by the proposed method is substantially improved relative to the conventional BMA method, and is comparable to the full hexagonal matching method;in addition, computational complexity and the number of coding bits are reduced significantly.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.305-322
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• 2005

Watermarking is a widely employed method tn protecting copyright of a digital image, the owner's unique image is embedded into the original image. Strengthened level of watermark insertion would help enhance its resilience in the process of extraction even from various distortions of transformation on the image size or resolution. However, its level, at the same time, should be moderated enough not to reach human visibility. Finding a balance between these two is crucial in watermarking. For the algorithm for watermarking, the predefined strength of a watermark, computed from the physical difference between the original and embedded images, is applied to all images uniformal. The mean brightness or contrast of the surrounding images, other than the absolute brightness of an object, could affect human sensitivity for object detection. In the present study, we examined whether the detectability for watermark noise might be attired by image statistics: mean brightness and contrast of the image. As the first step to examine their effect, we made rune fundamental images with varied brightness and control of the original image. For each fundamental image, detectability for watermark noise was measured. The results showed that the strength ot watermark node for detection increased as tile brightness and contrast of the fundamental image were increased. We have fitted the data to a regression line which can be used to estimate the strength of watermark of a given image with a certain brightness and contrast. Although we need to take other required factors into consideration in directly applying this formula to actual watermarking algorithm, an adaptive watermarking algorithm could be built on this formula with image statistics, such as brightness and contrast.

• Economic and Environmental Geology
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• v.43 no.3
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• pp.259-267
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• 2010

Resistivity logging instruments were designed to measure electrical resistivity of formation, which can be directly interpreted to provide water-saturation profile. Short and long normal logging measurements are made under groundwater level. In some investigation sites, groundwater level reaches to a depth of a few meters. It has come to attention that the proximity of groundwater level might distort short and long normal logging readings, when the measurements are made near groundwater level, owing to the proximity of an insulating air. This study investigates the effects of the proximity of groundwater level (and also the proximity of earth surface) on the normal by simulating normal logging measurements near groundwater level. In the simulation, we consider all the details of real logging situation, i.e., the presence of wellbore, the tool mandrel with current and potential electrodes, and currentreturn and reference-potential electrodes. We also model the air to include the earth’'s surface in the simulation rather than the customary choice of imposing a boundary condition. To obtain apparent resistivity, we compute the voltage, i.e., potential difference between monitoring and reference electrodes. For the simulation, we use a twodimensional, goal-oriented and high-order self-adaptive hp finite element refinement strategy (h denotes the element size and p the polynomial order of approximation within each element) to obtain accurate simulation results. Numerical results indicate that distortion on the normal logging is greater when the reference potential electrode is closer to the borehole and distortions on long normal logging are larger than those on short normal logging.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.137-142
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• 2010

Although multi-model speech recognizer has been shown to be quite successful in noisy speech recognition, the results were based on general speech front-ends which do not take into account noise adaptation techniques. In this paper, for the accurate evaluation of the multi-model based speech recognizer, we adopted a quite noise-robust speech front-end, AFE, which was proposed by the ETSI for the noisy DSR environment. For the performance comparison, the MTR which is known to give good results in the DSR environment has been used. Also, we modified the structure of the multi-model based speech recognizer to improve the recognition performance. N reference HMMs which are most similar to the input noisy speech are used as the acoustic models for recognition to cope with the errors in the selection of the reference HMMs and the noise signal variability. In addition, multiple SNR levels are used to train each of the reference HMMs to improve the robustness of the acoustic models. From the experimental results on the Aurora 2 databases, we could see better recognition rates using the modified multi-model based speech recognizer compared with the previous method.