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Toan Khac Nguyen,Jaewoong Yu,Hyung-Won Choi,인병천,임진희 한국원예학회 2018 원예과학기술지 Vol.36 No.1
Chrysanthemum is one of the most popular ornamental flowers in Korea due to its great diversity ofcolors and forms. To understand this diversity and to efficiently breed chrysanthemum varieties, agenetic diversity assessment of Korean native chrysanthemum populations using molecularmarkers is required. Genotyping-by-sequencing (GBS) is a newly developed and widely used nextgeneration sequencing (NGS) method based on the single nucleotide polymorphism (SNP) markersystem. In this study, we tested three restriction enzyme combinations (ApeKI, ApeKI/MseI, andApeKI/MspI) for GBS library construction using eight Korean native Chrysanthemum spp. accessions. Three libraries were constructed and sequenced on the Illumina NextSeq 500 platformand results were analyzed in the Stacks de novo GBS pipeline. Overall, the ApeKI/MseIcombination showed the best library quality, highest number of tags, and SNP generation potential.
Tools for Cut Flower for Export: Is It a Genuine Challenge from Growers to Customers?
Toan Khac Nguyen,Youn Ok Jung,Jin Hee Lim 한국화훼학회 2020 화훼연구 Vol.28 No.4
Currently, the cut flower market seems to be an export revenue in the world trade of the flower industry. The amount of exported cut flowers is impressive with increased production in various countries, especially in Korea. In the Fourth Industrial Revolution, automatic technologies are continuing to develop agricultural effective tools in the challenge of digital innovation. Thus, the low production costs set up in the field, greenhouse, or smart farm set up, and the short time of harvest must be considered within a few months. The postharvest quality of cut flowers presents freshness and long vase life, and the tools for postharvest handling are expected to optimize these. This review highlights the most important factors improving postharvest quality of cut flowers, the potential standard applicable techniques for commercial handling outlines of cut flower vase life, and recommendations for improving postharvest handling in the flower industry.
Augmented Reality for architectural education and fire prevention of traditional Korean buildings
○Toan Phan Viet,Choo Seung Yeon 대한건축학회지회연합회 2008 대한건축학회지회연합회 학술발표대회논문집 Vol.2008 No.1
This article shows an application of Augmented Reality for Korean Cultural Traditional Building. In this case, the Namdaemun Gate; the "National Treasure No.1"of South Korea, was reviewed. We know that, on 10 February 2008, the Namdaemun Gate was burned down under thefire and collapsed although many fireman forces arrived on time. The main reason for the fail of the fire prevention is the difficulty of getting fire under control without knowledge about the basic structure of wooden frameworks. Therefore, along with great progress of digital technology, an applying science of virtual information to architectural heritage buildings is needed. The new technology, Augmented Reality (AR), comes out and brings with itself many advantages for digital architectural design and construction fields. The AR is being considered the new method of design to approach architecture. With the AR environment, the 3D graphic model of Namdaemun Gate can be integrated into real world, and users can interact to it, namely the firemen can gain knowledge of wooden frameworks structure and be trained for emergency case. The main focus of this research is to give educational information on the traditional wooden structure on- and off-site for architectural students, archaeological profession, etc., especially the fireman, using this new technology. In this article, some experiments are shown out to illustrate how the AR system can assist fireman to get knowledge for prevention of fire on wooden traditional buildings.
마스크된 복원에서 질병 진단까지: 안저 영상을 위한 비전 트랜스포머 접근법
( Toan Duc Nguyen ),변규린 ( Gyurin Byun ),추현승 ( Hyunseung Choo ) 한국정보처리학회 2023 한국정보처리학회 학술대회논문집 Vol.30 No.2
In this paper, we introduce a pre-training method leveraging the capabilities of the Vision Transformer (ViT) for disease diagnosis in conventional Fundus images. Recognizing the need for effective representation learning in medical images, our method combines the Vision Transformer with a Masked Autoencoder to generate meaningful and pertinent image augmentations. During pre-training, the Masked Autoencoder produces an altered version of the original image, which serves as a positive pair. The Vision Transformer then employs contrastive learning techniques with this image pair to refine its weight parameters. Our experiments demonstrate that this dual-model approach harnesses the strengths of both the ViT and the Masked Autoencoder, resulting in robust and clinically relevant feature embeddings. Preliminary results suggest significant improvements in diagnostic accuracy, underscoring the potential of our methodology in enhancing automated disease diagnosis in fundus imaging.
Efficient MPEG-4 to H.264/AVC Transcoding with Spatial Downscaling
Toan Dinh Nguyen,이귀상,June-Young Chang,Han-Jin Cho 한국전자통신연구원 2007 ETRI Journal Vol.29 No.6
Efficient downscaling in a transcoder is important when the output should be converted to a lower resolution video. In this letter, we suggest an efficient algorithm for transcoding from MPEG-4 SP (with simple profile) to H.264/AVC with spatial downscaling. First, target image blocks are classified into monotonous, complex, and very complex regions for fast mode decision. Second, adaptive search ranges are applied to these image classes for fast motion estimation in an H.264/AVC encoder with predicted motion vectors. Simulation results show that our transcoder considerably reduces transcoding time while video quality is kept almost optimal.
Using Tensor Voting for Detecting Noise Regions in Text Images
Toan Nguyen Dinh,Jonghyun Park,GueeSang Lee 한국멀티미디어학회 2009 한국멀티미디어학회 학술발표논문집 Vol.2009 No.1
Many kinds of noises may present in natural text images such as streaks, shadows, cracks and even small objects which produce occluded text. To achieve good binarized text results, we need to detect and remove noise regions. The 3D tensor voting framework generates the surface saliency map in which the pixel saliency value is directly proportional to the region area in which this pixel belongs to. Since the noise regions are usually smaller than background and text regions, we use 3D tensor voting to detect them. The experimental results show that we can successfully detect several kinds of noises in natural text images.