• Bulletin of the Korean Chemical Society
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• v.28 no.11
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• pp.1910-1916
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• 2007

Analyzed are recent advances in design of novel boronared conjugates of synthetic and natural porphyrins and chlorins. These compounds showed high efficacy as cytotoxic agents for tumor cells in culture and as phototoxins in photodynamic therapy of tumor xenografts. Thus, boronated porphyrins and chlorins emerge as promising class of anticancer agents with potentially multiple advantages: the chemotherapeutic drugs alone and photo- and radiosensitizers in binary treatments.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.242-245
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• 2006

This paper addresses an image fingerprinting scheme for the print-to-capture model performed by a photo printer and digital camera. When capturing an image by a digital camera, various kinds of distortions such as noise, geometrical distortions, and lens distortions are applied slightly and simultaneously. In this paper, we consider several steps to extract fingerprints from the distorted image in print-and capture scenario. To embed ID into an image as a fingerprint, multi-bits embedding is applied. We embed 64 bits ID information as a fingerprint into spatial domain of color images. In order to restore a captured image from distortions a noise reduction filter is performed and a rectilinear tiling pattern is used as a template. To make the template a multi-bits fingerprint is embedded repeatedly like a tiling pattern into the spatial domain of the image. We show that the extracting is successful from the image captured by a digital camera through the experiment.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.385-389
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• 2019

Knowledge of abundance, or population size, is fundamental in wildlife conservation and management. Camera-trapping, in combination with capture-recapture methods, has been extensively applied to estimate abundance and density of individually identifiable animals due to the advantages of being non-invasive, effective to survey wide-ranging, elusive, or nocturnal species, operating in inhospitable environment, and taking low labor. We assessed the possibility of using coat patterns from images to identify an individual leopard cat (Prionailurus bengalensis), a Class II endangered species in South Korea. We analyzed leopard cat images taken from Digital Single-Lense Relfex camera (high resolution, 18Mpxl) and camera traps (low resolution, 3.1Mpxl) using HotSpotter, an image matching algorithm. HotSpotter accurately top-ranked an image of the same individual leopard cat with the reference leopard cat image 100% by matching facial and ventral parts. This confirms that facial and ventral fur patterns of the Amur leopard cat are good matching points to be used reliably to identify an individual. We anticipate that the study results will be useful to researchers interested in studying behavior or population parameter estimates of Amur leopard cats based on capture-recapture models.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.383-392
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• 2006

In this paper, we propose a new relevance feedback algorithm using Probabilistic Neural Networks(PNN) while supporting multi-class learning. Then, to validate the effectiveness of our feedback approach, we incorporate the proposed algorithm into our region-based image retrieval tool, FRIP(Finding Regions In the Pictures). In our feedback approach, there is no need to assume that feature vectors are independent, and as well as it allows the system to insert additional classes for detail classification. In addition, it does not have a long computation time for training because it only has four layers. In the PNN classification process, we store the user's entire past feedback actions as a history in order to improve performance for future iterations. By using a history, our approach can capture the user's subjective intension more precisely and prevent retrieval performance errors which originate from fluctuating or degrading in the next iteration. The efficacy of our method is validated using a set of 3000 images derived from a Corel-photo CD.

• Smart Media Journal
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• v.1 no.1
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• pp.10-16
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• 2012

Stereo and multi-view cameras have been used to capture the three-dimensional (3D) scene for 3D contents generation. Besides, depth sensors are frequently used to obtain 3D information of the captured scene in real time. In order to generate 3D contents from captured images, we need several preprocessing operations to reduce noises and distortions in the images. 3D contents are considered as the basic media for realistic broadcasting that provides photo-realistic and immersive feeling to users. In this paper, we show technical trends of 3D image capturing and contents generation, and explain some core techniques for 3D image processing for realistic 3DTV broadcasting.

• The Journal of Advanced Prosthodontics
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• v.9 no.6
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• pp.409-415
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• 2017

PURPOSE. Accurate information is essential in dentistry. The image information of missing teeth is used in optically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardized model was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a model that combines the variables with reference to ISO 12836:2015 was designed. MATERIALS AND METHODS. The basic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) and the bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture. The scans were performed several times according to the prescribed sequence to distinguish the model from the one that did not form, and the results confirmed it to be the best. RESULTS. In the case of the initial basic model, a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognition rate of the image was improved with every variable factor, and the difference depends on the tooth profile and the pattern of the floor surface. CONCLUSION. Based on the recognition error of the LDA, the recognition rate decreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of each class needs to be provided when developing a standardized model.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.72.2-72.2
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• 2010

The extremely metal-poor halo planetary nebula BoBn 1 has been investigated based on IUE archive data, Subaru/HDS spectra, VLT/UVES archive data, and Spitzer/IRS spectra. We have measured a heliocentric radial velocity of $+191.6\pm1.3\;kms^{-1}$ and expansion velocity 2Vexp of $40.5\pm3.3\;kms^{-1}$ from an average over 300 lines. The estimations of C, N, O, and Ne abundances from the optical recombination lines (ORLs) and Kr, Xe, and Ba from the collisional excitation lines (CELs) are also done. We have detected 5 fluorine and several slow neutron capture elements (the s-process). The amounts of [F/H], [Kr/H], and [Xe/H] suggest that BoBn 1 is the most F-rich among F detected PNe and is a heavy s-process element rich PN. The photo-ionization models built with non-LTE theoretical stellar atmospheres indicate that the progenitor was a 1-1.5 $M_\bigstar$ that would evolve into a white dwarf with an $0.62M_{\odot}$ core mass and $0.09M_{\odot}$ ionized nebula. Careful examination implies that BoBn 1 has evolved from a binary and experienced coalescence during the evolution to become a visible PN. The elemental abundances except N could be explained by a binary model composed of $0.75M_{\odot}+1.5M_{\odot}$ stars.

• Journal of Radiation Industry
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• v.6 no.3
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• pp.205-209
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• 2012

The decomposition of 50 pesticides present in an aqueous solution using ${\gamma}-irradiation$ from a $^{60}Co$ gamma-ray source was investigated using laboratory-scale experiment. The rates of decomposition were determined using a gas chromatography-electron capture detector (GC-ECD), high-performance liquid chromatography-photo diode array detector (HPLC-PDA), and HPLC-fluorescence detector (FLD). When the initial concentration of pesticides was 10 ppm, and the radiation dose was 2, 5, 10, 20, and 30 kGy, respectively, 14 pesticide samples showed high removal rates (>50%) at absorbed doses of more than 10 kGy. With the exception of procymidone, they were all completely removed at a 30 kGy irradiation dose. These results provide fundamental data on the reactivity between gamma-irradiation and pesticides in an aqueous solution. Further, an evaluation of the toxicity of radiolytic intermediate products is required.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.64-79
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• 2022

The concept of Virtual Character has been developed for a long time with people's demand for cultural and entertainment products such as games, animations, and movies. In recent years, with the rapid development of concepts and industries such as social media, self-media, web3.0, artificial intelligence, virtual reality, and Metaverse, Virtual Character has also expanded new derivative concepts such as Virtual Idol, Virtual YouTuber, and Virtual Digital Human. With the development of technology, people's life is gradually moving towards digitalization and virtualization. At the same time, under the global environment of the new crown epidemic, human social activities are rapidly developing in the direction of network society and online society. From the perspective of digital media content, this paper studies the production technology of Virtual Character related products in the Chinese market, and analyzes the future development direction and possibility of the Virtual Character industry in combination with new media development directions and technical production methods. Consider and provide reference for the development of combined applications of digital media content industry, Virtual Character and Metaverse industry.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.11-14
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• 2020

The importance of data in the development of deep learning is very high. Data with high morphological features are usually utilized in the domains where careful lens calibrations are needed by a human to capture those data. Synthesis of high morphological data for that domain can be a great asset to improve the classification accuracy of systems in the field. Unsupervised learning can be employed for this task. Generating photo-realistic objects of interest has been massively studied after Generative Adversarial Network (GAN) was introduced. In this paper, we propose Morpho-GAN, a method that unifies several GAN techniques to generate quality data of high morphology. Our method introduces a new suitable training objective in the discriminator of GAN to synthesize images that follow the distribution of the original dataset. The results demonstrate that the proposed method can generate plausible data as good as other modern baseline models while taking a less complex during training.