• Journal of Microbiology and Biotechnology
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• v.32 no.8
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• pp.1026-1033
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• 2022

This study presents a novel DNA part characterization technique that increases throughput by combinatorial DNA part assembly, solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. We confirmed that the fluorescence intensities of colonies on plates were comparable to fluorescence at the single-cell level from a high-end, flow-cytometry device and developed a high-throughput image analysis pipeline. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA parts and their combinations with a single sequencing experiment. Using our techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h without any automated equipment. We anticipate that this high-throughput and easy-to-use part characterization technique will contribute to increasing part diversity and be useful for building genetic circuits and metabolic pathways in synthetic biology.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.133-141
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• 2023

Accurate measurement of seafloor topography plays a crucial role in developing marine industries such as maritime safety, resource exploration, environmental protection, and coastal management. The seafloor topography is constructed using side scan sonar (SSS) and single beam echosounder (SBES) or multibeam echosounder (MBES), which transmit and receive ultrasound waves through a device attached to a marine survey vessel. However, the use of a sonar system is affected by noise pollution areas, and the single beam has a limited scope of application. At the same time, the multibeam is mainly applicable for depth observation. For these reasons, it is difficult to determine the boundaries and areas of seafloor topography. Therefore, this study proposes a method to improve the backscatter data of multibeam echosounder, which has a relationship with the seafloor quality, by using digital image processing to classify the shape of the underwater surface.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.291-298
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• 2012

In automatic target recognition(ATR) systems, target extraction techniques are very important because ATR performance depends on segmentation result. So, this paper proposes a multi-sensor image fusion method based on adaptive weights. To incorporate the FLIR image and CCD image, we used information such as the bi-modality, distance and texture. A weight of the FLIR image is derived from the bi-modality and distance measure. For the weight of CCD image, the information that the target's texture is more uniform than the background region is used. The proposed algorithm is applied to many images and its performance is compared with the segmentation result using the single image. Experimental results show that the proposed method has the accurate extraction performance.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.695-708
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• 2011

Image fusion is the process of combining multiple images of the same scene into a single fused image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and military affairs. The widely used image fusion rules that use wavelet transform have been based on a simple comparison with the activity measures of local windows such as mean and standard deviation. In this case, information features from the original images are excluded in the fusion image and distorted fusion images are obtained for noisy images. In this paper, we propose the use of a nonparametric squared ranks test on the quality of variance for two samples in order to overcome the influence of the noise and guarantee the homogeneity of the fused image. We evaluate the method both quantitatively and qualitatively for image fusion as well as compare it to some existing fusion methods. Experimental results indicate that the proposed method is effective and provides satisfactory fusion results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.117-124
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• 2008

The approaches to overcome the limited spatial resolution and the limited dynamic range of image sensors have been studied independently. A high resolution image is reconstructed from multiple low resolution observations and a wide dynamic range image is reconstructed from differently exposed multiple low dynamic range in es based on signal processing approach. In practical situations, it is reasonable to address them in a unified context because the recorded image suffers from limitations of both spatial resolution and dynamic range. In this paper, the image acquisition process including limited spatial resolution and limited dynamic range is modelled. With the image acquisition model, the response function of the imaging system is estimated and the single image of which spatial resolution and dynamic range are simultaneously enhanced is obtained. Experimental results indicate that the proposed algorithm outperforms the conventional approaches that perform the high resolution and wide dynamic range reconstruction sequentially with respect to both objective and subjective criteria.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.110-116
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• 2008

This paper presents a new postprocessing method to eliminate the false minutiae, that caused by the skelectonization of fingerprint image, and an image compression method using Isometric Self Organizing Map(ISOSOM). Since the SOM has simple structure, fast encoding time, and relatively good classification characteristics, many image processing areas adopt this such as image compression and pattern classification, etc. But, the SOM shows limited performances in pattern classification because of it's single layer structure. To maximize the performance of the pattern classification with small code book, we a lied the Isometric SOM with the isometry of the fractal theory. The proposed Isometric SOM postprocessing and compression algorithm of fingerprint image showed good performances in the elimination of false minutiae and the image compression simultaneously.

• Journal of Industrial Convergence
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• v.18 no.6
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• pp.33-39
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• 2020

The multi-screen image system could make the audiences appreciate contents without special devices by expansively composing the images played on a single screen to many facets suitable for the use, which could provide the great immersiveness to the audiences. Based on the recent interest in realistic images, it is produced as films through the multi-projection technology such as Screen X or Escape, and it is developed into the media that could deliver stories and information. Also, the size of display tends to gradually get larger while the image quality is improved to high definition. Thus, the development is accelerated in the form of Digital Signage that could play the high definition image contents by solidly composing many HD or UHD display screens. Moreover, through the convergence of digital technologies, it is developed into the higher value-added industry that could have two-way communication. This study aims to understand the developmental history of multi-screen image from 1950 to the present, technical analysis, and the production method, and then to research how to minimize the image degradation when playing the contents, in various platforms using the multi-screen image.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.260-286
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• 2024

This study investigates consumer experiences and word-of-mouth (WOM) intentions in luxury brand pop-up stores, including standalone and department store setups. Grounded in experience economy theory, this study examines the experiential elements based on the types of pop-up stores and the relationships among consumer experience, pop-up store image, and WOM intentions for each type. Data were collected from 300 visitors to luxury brand pop-up stores between January and July 2023 and analyzed using Smart PLS 4.0. The findings reveal several key insights. First, standalone pop-up stores offer educational and escapist experiences, while pop-ups within department stores have a single identified factor of consumer experience. Second, regardless of the store type, luxury pop-up store experiences significantly influence pop-up image perceptions. Third, luxury pop-up store image drives WOM intentions for both standalone and department store pop-ups. Notably, the unique image significantly impacts solely department store pop-ups and does not influence standalone pop-ups. Moreover, image perceptions in both pop-up store types do not significantly affect brand WOM intentions. Finally, WOM intentions for pop-up stores significantly influence WOM intentions for brands. This study contributes to the theoretical understanding of consumer experiences in luxury pop-up stores, providing practical insights for stakeholders in the luxury brand industry to enhance pop-up store image perceptions and WOM intentions.

• Journal of the Korea Computer Graphics Society
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• v.28 no.1
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• pp.1-9
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• 2022

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.