• Journal of Microbiology and Biotechnology
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• v.27 no.4
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• pp.718-724
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• 2017

The combination of rabies immunoglobulin (RIG) with a vaccine is currently effective against rabies infections, but improvements are needed. Genetic engineering antibody technology is an attractive approach for developing novel antibodies to replace RIG. In our previous study, a single-chain variable fragment, scFv57R, against rabies virus glycoprotein was constructed. However, its inherent weak stability and short half-life compared with the parent RIG may limit its diagnostic and therapeutic application. Therefore, an acidic tail of synuclein (ATS) derived from the C-terminal acidic tail of human alpha-synuclein protein was fused to the C-terminus of scFv57R in order to help it resist adverse stress and improve the stability and half-life. The tail showed no apparent effect on the preparation procedure and affinity of the protein, nor did it change the neutralizing potency in vitro. In the ELISA test of molecular stability, the ATS fusion form of the protein, scFv57R-ATS, showed an increase in thermal stability and longer half-life in serum than scFv57R. The protection against fatal rabies virus challenge improved after fusing the tail to the scFv, which may be attributed to the improved stability. Thus, the ATS fusion approach presented here is easily implemented and can be used as a new strategy to improve the stability and half-life of engineered antibody proteins for practical applications.

• Journal of Microbiology and Biotechnology
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• v.18 no.8
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• pp.1475-1481
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• 2008

B3 antibody specifically binds the $Lewis^Y$-related carbohydrate antigen of many carcinomas, and it is used as a model antibody in this study. In a previous study, the Fab fragment of the antibody was fused to a 38 kDa truncated form of Pseudomonas exotoxin A, PE38, to make Fab-PE38, where PE38 is fused to the Fd fragment of the Fab domain. This parent monomer molecule, Fab-PE38, had no cysteine in the hinge region, and it could not make a disulfide bond to form a disulfide bond bridged homodimer. In this study, we constructed three different kinds of divalent Fab-toxin fusion homodimers where the toxin is fused to the light chain of Fab, $(Fab-PE38fl)_2$. In addition to the PE38 toxin fused to the light chain, these three molecules have different hinge sequences hi, h2, and h3 making Fabh1-, Fabh2-, and Fabh3-PE38fl monomers, respectively. These hinges contain only one cysteine on different positions of the hinge sequence. The disulfide bond between the hinge region of two monomers forms homodimers $(Fabh1-PE38fl)_2$, $(Fabh2-PE38fl)_2$, and $(Fabh3-PE38fl)_2$. The refolding yields of these dimers were 5-16-fold higher than a previously constructed dimer where the PE38 was fused to the Fd fragment $(Fabh2-PE38)_2$ [8]. Our data suggest that the steric repulsion between the two PE38s in $(Fabh1-PE38)_2$ during disulfide bridge formation is relieved by fusing it at the end of the light chain. The best cytotoxicity value of these dimers showed about 2.5-fold higher on an MCF7 cell line than that of the monovalent reference molecule in ng/ml scale, which is 15-fold higher in pM scale.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.8
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• pp.758-765
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• 2016

This paper proposes a novel method for the recognition of the inverse synthetic aperture radar(ISAR) image of multiple targets flying in formation. Rather than separating the ISAR image of each target, the proposed method combines an ISAR image obtained by fusing the ISAR images in the training database. Fusion is conducted by optimizing the non-linear problem whose parameters are the aspect angle and the target location. Assuming that the aspect angle is properly estimated, the proposed method estimates the number of the targets and their locations by optimizing the template matching using PSO. In simulations using the F-16 scale model, the efficiency of the proposed method was demonstrated by yielding the ISAR image identical to that of targets in formation.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.29-34
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• 2014

Data fusion techniques combine data from multiple radars and related information to achieve more accurate estimations than could be achieved by a single, independent radar. In this paper, we analyze delay and loss of packets to be processed by multiple radar and minimize data processing interval from centralized data processing operation as fusing multiple radar data. Therefore, we model radar network about central data fusion, and analyze delay and loss of packets inside queues on assuming queues respectively as the M/M/1/K using NS-2. We confirmed average delay time, processing fused multiple radar data, through the analysis data. And then, this delay time can be used as a reference time for radar data latency in fusion center.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4060-4079
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• 2020

Blur is an important type of image distortion. How to evaluate the quality of blurred image accurately and efficiently is a research hotspot in the field of image processing in recent years. Inspired by the multi-scale perceptual characteristics of the human visual system (HVS), this paper presents a no-reference image blur/sharpness assessment method based on multi-scale local features in the spatial domain. First, considering various content has different sensitivity to blur distortion, the image is divided into smooth, edge, and texture regions in blocks. Then, the Gaussian scale space of the image is constructed, and the categorized contrast features between the original image and the Gaussian scale space images are calculated to express the blur degree of different image contents. To simulate the impact of viewing distance on blur distortion, the distribution characteristics of local maximum gradient of multi-resolution images were also calculated in the spatial domain. Finally, the image blur assessment model is obtained by fusing all features and learning the mapping from features to quality scores by support vector regression (SVR). Performance of the proposed method is evaluated on four synthetically blurred databases and one real blurred database. The experimental results demonstrate that our method can produce quality scores more consistent with subjective evaluations than other methods, especially for real burred images.

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.58-65
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• 2002

The most widespread techniques for DEM generation are stereoscopy for optical sensor images and interfereometry for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. In this paper, different strategies for fusing SAR and optical data are combined to derive high quality DEM products. The multiresolution wavelet transform, which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. By taking advantage of the fact that errors of the DEMs are of different nature using the multiresolution wavelet transform, affected part are filtered and replaced by those of the counterpart and is tested with two sets of SPOT and ERS DEM, resulting in a remarkable improvement in DEM. For the analysis of results, the reference DEM is generated from digital base map(1:5000).

• Journal of the Korean Chemical Society
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• v.34 no.1
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• pp.63-68
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• 1990

The chemical ingredients such as $SiO_2,\;Al_2O_3,\;MgO,\;Fe_2O_3,\;CaO$ and $TiO_2$in silica minerals were determined by X-ray fluorescence spectrometry using a matrix correction method. The synthesized standards mixed with reagent grade oxides and the sample were diluted by fusing with 16 times $Li_2B_4O_7$. The matrix effects correlated among the ingredients were corrected by the empirical coefficient method based on the Lucas-Tooth and Pyne model. The analytical results showed relatively good agreement between the different sets of coefficients but were improved with increasing the number of standard. The accuracy of this method was also examined with the standard reference material of NIST.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.27-35
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• 2010

Extracting skin color is significant in adult image detection. However, conventional methods still have essential problems in extracting skin color. That is, colors of human skins are basically not the same because of individual skin difference or difference races. Moreover, skin regions of images may not have identical color due to makeup, different cameras used, etc. Therefore, most of the existing methods use predefined skin color models. To resolve these problems, in this paper, we propose a new adult image detection method that robustly segments skin areas with an input image-adapted skin color distribution model, and verifies if the segmented skin regions contain naked bodies by fusing several representative features through a neural network scheme. Experimental results show that our method outperforms others through various experiments. We expect that the suggested method will be useful in many applications such as face detection and objectionable image filtering.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.510-512
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• 2019

Recently, there have been growing requirements in the public safety sector to ensure safety through detection of hazardous situations or preemptive predictions. It is noteworthy that various sensor data can be analyzed and utilized as a result of mobile device's dissemination, and many advantages can be used in terms of safety and security. An effective modeling technique is needed to combine sensor data generated by smart-phones and wearable devices to analyze users' moving patterns and behavioral patterns, and to ensure public safety by fusing location-based crime risk data provided.