• IMMUNE NETWORK
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• v.15 no.2
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• pp.73-82
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• 2015

Respiratory syncytial virus (RSV) infection is recognized by the innate immune system through Toll like receptors (TLRs) and retinoic acid inducible gene I. These pathways lead to the activation of type I interferons and resistance to infection. In contrast to TLRs, very few studies have examined the role of NOD-like receptors in viral recognition and induction of adaptive immune responses to RSV. Caspase-1 plays an essential role in the immune response via the maturation of the proinflammatory cytokines IL-$1{\beta}$ and IL-18. However, the role of caspase-1 in RSV infection in vivo is unknown. We demonstrate that RSV infection induces IL-$1{\beta}$ secretion and that caspase-1 deficiency in bone marrow derived dendritic cells leads to defective IL-$1{\beta}$ production, while normal RSV viral clearance and T cell responses are observed in caspase-1 deficient mice following respiratory infection with RSV. The frequencies of IFN-${\gamma}$ producing or RSV specific T cells in lungs from caspase-1 deficient mice are not impaired. In addition, we demonstrate that caspase-1 deficient neonatal or young mice also exhibit normal immune responses. Furthermore, we find that IL-1R deficient mice infected with RSV exhibit normal Th1 and cytotoxic T lymphocytes (CTL) immune responses. Collectively, these results demonstrate that in contrast to TLR pathways, caspase-1 might not play a central role in the induction of Th1 and CTL immune responses to RSV.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1978-1984
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• 2016

This paper proposes a robust vehicle detecting method by using Adaboost and CLAHE(Contrast-Limit Adaptive Histogram Equalization). We propose two method to detect vehicle effectively. First, we are able to judge rainy and night by converting RGB value to brightness. Second, we can detect a taillight, designate a ROI(Region Of Interest) by using CLAHE. And then, we choose an Adaboost algorithm by comparing traditional vehicle detecting method such as GMM(Gaussian Mixture Model), Optical flow and Adaboost. In this paper, we use proposed method and get better performance of detecting vehicle. The precision and recall score of proposed method are 0.85 and 0.87. That scores are better than GMM and optical flow.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.152-165
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• 1998

The contour coding usually occupies the biggest part in the encoded bitstream, which causes the bottleneck problem of a region-based coding scheme. In this paper, new adaptive contour coding technique is proposed for the segmentation-based image coding. By adaptive contour coding considering contrast of neighbor regions in the proposed method, the overall bitrate can be significantly reduced without loss of the subjective image quality. After segmentation using watershed algorithm to the image, the contour segments are classified according to the contrast of the adjacent regions. Then, the contour segments between classified low contrast regions are highly compressed using morphological low pass filtering. The needed bits for encoding the contour information is reduced without loss of subjective image quality in the experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1904-1926
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• 2016

Iris recognition for biometric personnel identification has gained much interest owing to the increasing concern with security today. The image quality plays a major role in the performance of iris recognition systems. When capturing an iris image under uncontrolled conditions and dealing with non-cooperative people, the chance of getting non-ideal images is very high owing to poor focus, off-angle, noise, motion blur, occlusion of eyelashes and eyelids, and wearing glasses. In order to improve the accuracy of iris recognition while dealing with non-ideal iris images, we propose a novel algorithm that improves the quality of degraded iris images. First, the iris image is localized properly to obtain accurate iris boundary detection, and then the iris image is normalized to obtain a fixed size. Second, the valid region (iris region) is extracted from the segmented iris image to obtain only the iris region. Third, to get a well-distributed texture image, bilinear interpolation is used on the segmented valid iris gray image. Using contrast-limited adaptive histogram equalization (CLAHE) enhances the low contrast of the resulting interpolated image. The results of CLAHE are further improved by stretching the maximum and minimum values to 0-255 by using histogram-stretching technique. The gray texture information is extracted by 1D Gabor filters while the Hamming distance technique is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. Results of the proposed method outperformed other methods in terms of equal error rate (EER).

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.108-117
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• 2015

If typical contrast enhancement algorithms for natural images are applied to X-ray images, they may cause artifacts such as overshooting or produce unnatural visual quality because they do not consider inherent characteristics of X-ray images. In order to overcome such problems, we propose a locally adaptive block-based contrast enhancement algorithm for X-ray images. After we derive a weighted cumulative distribution function for each block, we apply it to each block for contrast enhancement. Then, we obtain images that are removed from block effect by adopting block-based overlapping. In post-processing, we obtain the final image by emphasizing high frequency components. Experimental results show that the proposed block-based contrast enhancement algorithm provides at maximum 5-times higher visual quality than the exiting algorithm in terms of quantitative contrast metric.

• Journal of the Korean Society of Radiology
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• v.82 no.6
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• pp.1477-1492
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• 2021

Purpose Dedicated breast CT is an emerging volumetric X-ray imaging modality for diagnosis that does not require any painful breast compression. To improve the detection rate of weakly enhanced lesions, an adaptive image rescaling (AIR) technique was proposed. Materials and Methods Two disks containing five identical holes and five holes of different diameters were scanned using 60/100 kVp to obtain single-energy CT (SECT), dual-energy CT (DECT), and AIR images. A piece of pork was also scanned as a subclinical trial. The image quality was evaluated using image contrast and contrast-to-noise ratio (CNR). The difference of imaging performances was confirmed using student's t test. Results Total mean image contrast of AIR (0.70) reached 74.5% of that of DECT (0.94) and was higher than that of SECT (0.22) by 318.2%. Total mean CNR of AIR (5.08) was 35.5% of that of SECT (14.30) and was higher than that of DECT (2.28) by 222.8%. A similar trend was observed in the subclinical study. Conclusion The results demonstrated superior image contrast of AIR over SECT, and its higher overall image quality compared to DECT with half the exposure. Therefore, AIR seems to have the potential to improve the detectability of lesions with dedicated breast CT.

• Toxicological Research
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• v.33 no.4
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• pp.283-290
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• 2017

The host immune system is the first line of host defense, consisting mainly of innate and adaptive immunity. Immunity must be maintained, orchestrated, and harmonized, since overactivation of immune responses can lead to inflammation and autoimmune diseases, while immune deficiency can lead to infectious diseases. We investigated the regulation of innate and adaptive immune cell activation by Artemisia capillaris and its components (ursolic acid, hyperoside, scopoletin, and scopolin). Macrophage phagocytic activity was determined using fluorescently labeled Escherichia coli, as an indicator of innate immune activation. Concanavalin A (ConA)- and lipopolysaccharide (LPS)-induced splenocyte proliferation was analyzed as surrogate markers for cellular and humoral adaptive immunity, respectively. Neither A. capillaris water extract (WAC) nor ethanol extract (EAC) greatly inhibited macrophage phagocytic activity. In contrast, WAC suppressed ConA- and LPS-induced proliferation of primary mouse splenocytes in a dose-dependent manner. Similarly, EAC inhibited ConA- and LPS-induced splenocyte proliferation. Oral administration of WAC in mice decreased ConA- and LPS-induced splenocyte proliferation, while that of EAC suppressed LPS-induced splenocyte proliferation. Repeated administration of WAC in mice inhibited ConA- and LPS-induced splenocyte proliferation. Ursolic acid, scopoletin, and scopolin reduced ConA- and LPS-induced primary mouse splenocyte proliferation, while hyperoside did not show such activity. These results indicate that A. capillaris and its components, ursolic acid, scopoletin, and scopolin, suppress ConA- and LPS-induced adaptive immune cell activation. The results suggest that A. capillaris is useful as a regulator of adaptive immunity for diseases involving excessive immune response activation.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.238-247
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• 2015

We develop the signal processing method for adaptive implementing direction of signal and the frequency sensitivity of human visual system(HVS). Existing multibnad energy scaling method makes ringing artifact because it does not consider signal direction. To solve this problem, we use block gradient for signal direction in addition to existing method. And we use the fact that frequency component of signal is more sensitive than value of signal over human eyes. we enhance the signal according to contrast sensitivity function(CSF) which is the model of frequency sensitivity of human eye. Compared that the existing analysis models only improve the efficiencies in the existing systems, the developed method can process the image signals to be more desirable and suitable to HVS.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.617-621
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• 2012

This paper studies asymptotic consensus problem for linear multi-agent systems. We propose a distributed state feedback control algorithm for solving the problem under fixed and undirected network communication. In contrast with the conventional algorithms that use global information (e.g., graph connectivity), the proposed algorithm only uses local information from neighbors. The principle for achieving asymptotic consensus is that, for each agent, a distributed update law gradually increases the coupling gain of LQR-type feedback and thus, the overall stability of the multi-agent system is recovered by the gain margin of LQR.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.332-338
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• 2001

A visually adaptive quantization method of DCT-based images based on Human Visual System(HVS) is proposed. This approach uses the spatial masking in HVS characteristics to obtain higher compression ratio with relatively small degradation in the image quality. HVS is nonsensitive to an edge area, so a high complexity area is quantized coarsely in contrast to fine quantization of the low complexity area. The complexity of an area is estimated by the variance of DCT coefficients of the image. Experimental results demonstrate the performance of the proposed method and the resulting images show little difference from the original image in the subjective perception.