• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.343-355
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• 2003

Fair bandwidth allocations at routers protect adaptive flows from non-adaptive ones and may simplify end-to end congestion control. However, traditional fair bandwidth allocation mechanisms, like Weighted Fair Queueing and Flow Random Early Drop, maintain state, manage buffera and perform packet scheduling on a per-flow basis. These mechanisms are more complex and less scalable than simple FIFO queueing when they are used in the interi or of a high-speed network. Recently, to overcome the implementation complexity problem and address the scalability and robustness, several fair bandwidth allocation mechanisms without per-flow state in the interior routers are proposed. Core-Stateless Fair Queueing and Rainbow Fair Queuing are approximates fair queueing in the core-stateless networks. In this paper, we proposed simple Layered Fair Queueing (SLFQ), another core-stateless mechanism to approximate fair bandwidth allocation without per-flow state. SLFQ use simple layered scheme for packet labeling and has simpler packet dropping algorithm than other core-stateless fair bandwidth allocation mechanisms. We presente simulations and evaluated the performance of SLFQ in comparison to other schemes. We also discussed other are as to which SLFQ is applicable.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.19-26
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• 2019

In this paper, the classification performance of learning algorithms is compared for TAB digit recognition. The TAB digits that are segmented from TAB musical notes contain TAB lines and musical symbols. The labeling method and non-linear filter are designed and applied to extract fret digits only. The shift operation of the 4 directions is applied to generate more data. The selected models are Bayesian classifier, support vector machine, prototype based learning, multi-layer perceptron, and convolutional neural network. The result shows that the mean accuracy of the Bayesian classifier is about 85.0% while that of the others reaches more than 99.0%. In addition, the convolutional neural network outperforms the others in terms of generalization and the step of the data preprocessing.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.439-445
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• 2021

Low-cost, ultra-high-speed cameras, made possible by the development of image sensors and small displays, can be very useful in image processing and pattern recognition. This paper introduces an algorithm that corrects irregular lighting from a high-speed image that is continuously input with a slight time interval, and which then obtains an exposed skin color region that is the area of interest in a person from the corrected image. In this study, the non-uniform lighting effect from a received high-speed image is first corrected using a frame blending technique. Then, the region of interest is robustly obtained from the input high-speed color image by applying an elliptical skin color distribution model generated from iterative learning in advance. Experimental results show that the approach presented in this paper corrects illumination in various types of color images, and then accurately acquires the region of interest. The algorithm proposed in this study is expected to be useful in various types of practical applications related to image recognition, such as face recognition and tracking, lighting correction, and video indexing and retrieval.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.1-9
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• 2022

Ship detection in synthetic aperture radar (SAR) images is an important application in marine monitoring for the military and civilian domains. Over the past decade, object detection has achieved significant progress with the development of convolutional neural networks (CNNs) and lot of labeled databases. However, due to difficulty in collecting and labeling SAR images, it is still a challenging task to solve SAR ship detection CNNs. To overcome the problem, some methods have employed conventional data augmentation techniques such as flipping, cropping, and affine transformation, but it is insufficient to achieve robust performance to handle a wide variety of types of ships. In this paper, we present a novel and effective approach for deep SAR ship detection, that exploits label-rich Electro-Optical (EO) images. The proposed method consists of two components: a data augmentation network and a ship detection network. First, we train the data augmentation network based on conditional generative adversarial network (cGAN), which aims to generate additional SAR images from EO images. Since it is trained using unpaired EO and SAR images, we impose the cycle-consistency loss to preserve the structural information while translating the characteristics of the images. After training the data augmentation network, we leverage the augmented dataset constituted with real and translated SAR images to train the ship detection network. The experimental results include qualitative evaluation of the translated SAR images and the comparison of detection performance of the networks, trained with non-augmented and augmented dataset, which demonstrates the effectiveness of the proposed framework.

• BMB Reports
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• v.55 no.6
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• pp.267-274
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• 2022

Molecular imaging is used to improve the disease diagnosis, prognosis, monitoring of treatment in living subjects. Numerous molecular targets have been developed for various cellular and molecular processes in genetic, metabolic, proteomic, and cellular biologic level. Molecular imaging modalities such as Optical Imaging, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and Computed Tomography (CT) can be used to visualize anatomic, genetic, biochemical, and physiologic changes in vivo. For in vivo cell imaging, certain cells such as cancer cells, immune cells, stem cells could be labeled by direct and indirect labeling methods to monitor cell migration, cell activity, and cell effects in cell-based therapy. In case of cancer, it could be used to investigate biological processes such as cancer metastasis and to analyze the drug treatment process. In addition, transplanted stem cells and immune cells in cell-based therapy could be visualized and tracked to confirm the fate, activity, and function of cells. In conventional molecular imaging, cells can be monitored in vivo in bulk non-invasively with optical imaging, MRI, PET, and SPECT imaging. However, single cell imaging in vivo has been a great challenge due to an extremely high sensitive detection of single cell. Recently, there has been great attention for in vivo single cell imaging due to the development of single cell study. In vivo single imaging could analyze the survival or death, movement direction, and characteristics of a single cell in live subjects. In this article, we reviewed basic principle of in vivo molecular imaging and introduced recent studies for in vivo single cell imaging based on the concept of in vivo molecular imaging.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.3
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• pp.113-125
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• 2023

The COVID-19 pandemic has led to the normalization of mask-wearing worldwide, and young children are particularly vulnerable to respiratory diseases. Children's masks come in various sizes and shapes, causing confusion among consumers who struggle to find products that can accommodate their child's unique physical conditions. This research aims to analyze the shape and dimensions of health masks designed for young children. A total of 67 mask varieties were collected, and 58 were subjected to analysis. The masks were found to have two primary shapes: foldable and beak-like, with sizes categorized as small and extra-small. The majority of masks were manufactured in Korea, and the size labeling systems varied among manufacturers. The mask materials were non-woven fabric or polypropylene, and there was diversity in terms of the adjustable earbands and the use of additional accessories. The dimensions of the masks varied depending on their shape, with significant differences in the weight and the length of the wire holes. Subsequent research should focus on conducting wearability evaluations to verify the dimensional suitability of commercially available children's health masks based on shape and size. Additionally, this study aims to provide foundational data that can assist in the development of children's masks with size ranges that differentiate them from adult masks and cater to specific age groups.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.589-601
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• 2023

Purpose: Baicalein, a natural flavone found in herbs, exhibits diverse biological activities. Nonalcoholic steatohepatitis (NASH) is an irreversible condition often associated with a poor prognosis. This study aimed to evaluate the effects of baicalein on the development of NASH in mice. Methods: Male C57BL/6J mice were randomly divided into four groups. Three groups were fed a methionine-choline-deficient (MCD) diet to induce NASH and were simultaneously treated with baicalein (at doses of 50 and 100 mg/kg) or vehicle only (sodium carboxymethylcellulose) through oral gavage for 4 weeks. The control group was fed a methionine-choline-sufficient (MCS) diet without the administration of baicalein. Results: The baicalein treatment significantly reduced serum levels of alanine aminotransferase and aspartate aminotransferase, suggestive of reduced liver damage. Histological analysis revealed a marked decrease in nonalcoholic fatty liver activity scores induced by the MCD diet in the mice. Similarly, baicalein treatment at both doses significantly attenuated the degree of hepatic fibrosis, as examined by Sirius red staining, and hepatocellular death, as examined by the terminal deoxynucleotidyl transferase dUTP nick end labeling assay. Baicalein treatment attenuated MCD-diet-induced lipid peroxidation, as evidenced by lower levels of hepatic malondialdehyde and 4-hydroxynonenal, demonstrating a reduction in oxidative stress resulting from lipid peroxidation. Moreover, baicalein treatment suppressed hepatic protein levels of 12-lipoxygenase (12-Lox) induced by the MCD diet. In contrast, baicalein enhanced the activities of antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase. Additionally, baicalein treatment significantly reduced hepatic non-heme iron concentrations and hepatic ferritin protein levels in mice fed an MCD diet. Conclusion: To summarize, baicalein treatment suppresses hepatic lipid peroxidation, 12-Lox expression, and iron accumulation, all of which are associated with the attenuation of NASH progression.

• Korean Circulation Journal
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• v.54 no.5
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• pp.233-252
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• 2024

Background and Objectives: Myocardial ischemia-reperfusion injury (MIRI) refers to the damage of cardiac function caused by restoration of blood flow perfusion in ischemic myocardium. However, long non-coding RNA prostate androgen regulated transcript 1 (PART1)'s role in MIRI remain unclear. Methods: Immunofluorescence detected LC3 expression. Intermolecular relationships were verified by dual luciferase reporter assay. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, flow cytometry and transferase-mediated dUTP nick-end labeling (TUNEL) assays analyzed cell viability and apoptosis. The release of lactate dehydrogenase was tested via enzyme-linked immunosorbent assay (ELISA). Left anterior descending coronary artery surgery induced a MIRI mouse model. Infarct area was detected by 2,3,5-triphenyltetrazolium chloride staining. Hematoxylin and eosin staining examined myocardial injury. ELISA evaluated myocardial marker (creatine kinase MB) level. Results: PART1 was decreased in hypoxia/reoxygenation (H/R) induced AC16 cells and MIRI mice. PART1 upregulation attenuated the increased levels of Bax, beclin-1 and the ratio of LC3II/I, and enhanced the decrease of Bcl-2 and p62 expression in H/R-treated cells. PART1 upregulation alleviated H/R-triggered autophagy and apoptosis via miR-302a-3p. Mechanically, PART1 targeted miR-302a-3p to upregulate transcription factor activating enhancer-binding protein 2C (TFAP2C). TFAP2C silencing reversed the protected effects of miR-302a-3p inhibitor on H/R treated AC16 cells. We further established TFAP2C combined to dual-specificity phosphatase 5 (DUSP5) promoter and activated DUSP5. TFAP2C upregulation suppressed H/R-stimulated autophagy and apoptosis through upregulating DUSP5. Overexpressed PART1 reduced myocardial infarction area and attenuated MIRI in mice. Conclusion: PART1 improved the autophagy and apoptosis in H/R-exposed AC16 cells through miR-302a-3p/TFAP2C/DUSP5 axis, which might provide novel targets for MIRI treatment.

• Toxicological Research
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• v.33 no.1
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• pp.43-48
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• 2017

With ultraviolet and visible light exposure, some pharmaceutical substances applied systemically or topically may cause phototoxic skin irritation. The major factor in phototoxicity is the generation of reactive oxygen species (ROS) such as singlet oxygen and superoxide anion that cause oxidative damage to DNA, lipids and proteins. Thus, measuring the generation of ROS can predict the phototoxic potential of a given substance indirectly. For this reason, a standard ROS assay (ROS assay) was developed and validated and provides an alternative method for phototoxicity evaluation. However, negative substances are over-predicted by the assay. Except for ultraviolet A (UVA), other UV ranges are not a major factor in causing phototoxicity and may lead to incorrect labeling of some non-phototoxic substances as being phototoxic in the ROS assay when using a solar simulator. A UVA stimulator is also widely used to evaluate phototoxicity in various test substances. Consequently, we identified the applicability of a UVA simulator to the ROS assay for photoreactivity. In this study, we tested 60 pharmaceutical substances including 50 phototoxins and 10 non-phototoxins to predict their phototoxic potential via the ROS assay with a UVA simulator. Following the ROS protocol, all test substances were dissolved in dimethyl sulfoxide or sodium phosphate buffer. The final concentration of the test solutions in the reaction mixture was 20 to $200{\mu}M$. The exposure was with $2.0{\sim}2.2mW/cm^2$ irradiance and optimization for a relevant dose of UVA was performed. The generation of ROS was compared before and after UVA exposure and was measured by a microplate spectrophotometer. Sensitivity and specificity values were 85.7% and 100.0% respectively, and the accuracy was 88.1%. From this analysis, the ROS assay with a UVA simulator is suitable for testing the photoreactivity and estimating the phototoxic potential of various test pharmaceutical substances.