• International Journal of Oral Biology
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• v.31 no.4
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• pp.119-125
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• 2006

The importance of phytoestrogens to human health is currently being actively investigated. Hesperidin, abundantly found in citrus fruits, is known to possess antioxidant, anticancer, and anti-inflammatory effects. Recently, it has been reported that hesperidin inhibits bone loss and decreases serum and hepatic lipids in ovariectomized mice. In our study, to determine the possible role of hesperidin in the regulation of bone metabolism, we observed the effects of hesperidin on the proliferation and activity of osteoblasts, as well as the effects of hesperidin on osteoclast generation and activity. We observed that, when treated with hesperidin, the number and viability of osteoblastic cells increased, alkaline phosphatase (ALP) activity of osteoblastic cells increased, and osteoprotegerin (OPG) secretion from MG63 cells decreased. Hesperidin treatment had no effect on the osteoclast generation and activity in the bone marrow cell culture, but decreased the number and resorptive activity of osteoclasts generated from RAW/264.7 cells. Taken together, these results indicate that hesperidin increases the proliferation and activity of osteoblasts, while inhibiting generation and activity of osteoclasts. Although the precise role of hesperidin remains to be elucidated, our study suggests that it is one of the important modulators of bone metabolism.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.2
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• pp.123-129
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• 2009

Aprotinin is used clinically in cardiopulmonary bypass surgery to reduce transfusion requirements and the inflammatory response. The mechanism of action for the anti-inflammatory effects of aprotinin is still unclear. We examined our hypothesis whether inhibitory effects of aprotinin on cytokine-induced inducible nitric oxide synthase (iNOS) expression (IL-$l\beta$ plus TNF-$\alpha$), reactive oxygen species (ROS) generation, and vascular smooth muscle cell (VSMC) proliferation were due to HO-l induction in rat VSMCs. Aprotinin induced HO-l protein expression in a dose-dependent manner, which was potentiated during inflammatory condition. Aprotinin reduced cytokine mixture (CM)-induced iNOS expression in a dose dependent manner. Furthermore, aprotinin reduced CM-induced ROS generation, cell proliferation, and phosphorylation of JNK but not of P38 and ERK1/2 kinases. Aprotinin effects were reversed by pre-treatment with the HO-l inhibitor, tin protoporphyrin IX (SnPPIX). HO-l is therefore closely involved in inflammatory-stimulated VSMC proliferation through the regulation of ROS generation and JNK phosphorylation. Our results suggest a new molecular basis for aprotinin anti-inflammatory properties.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.268-276
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• 2002

In this paper we suggest a method to produce automatically teat data using UML development diagrams, and analytically describe the application of a tool, Automatic UML-based Test Data Generation (AUTEG) developed using XML technology, to the examples of insurance system. Our AUTEG automatically generates test diagrams that enable to detect errors existing at the interface area between modules composing the whole system, along with test data by applying the existing white-box test technique to the test diagram. Our AUTEG can be applied to the integration test as well as the system test and using the tool, users may make the unit modules of the integration test into several groups.

• Molecules and Cells
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• v.37 no.1
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• pp.36-42
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• 2014

The tomato (Solanum lycopersicum L.) is a model plant for genome research in Solanaceae, as well as for studying crop breeding. Genome-wide single nucleotide polymorphisms (SNPs) are a valuable resource in genetic research and breeding. However, to do discovery of genome-wide SNPs, most methods require expensive high-depth sequencing. Here, we describe a method for SNP calling using a modified version of SAMtools that improved its sensitivity. We analyzed 90 Gb of raw sequence data from next-generation sequencing of two resequencing and seven transcriptome data sets from several tomato accessions. Our study identified 4,812,432 non-redundant SNPs. Moreover, the workflow of SNP calling was improved by aligning the reference genome with its own raw data. Using this approach, 131,785 SNPs were discovered from transcriptome data of seven accessions. In addition, 4,680,647 SNPs were identified from the genome of S. pimpinellifolium, which are 60 times more than 71,637 of the PI212816 transcriptome. SNP distribution was compared between the whole genome and transcriptome of S. pimpinellifolium. Moreover, we surveyed the location of SNPs within genic and intergenic regions. Our results indicated that the sufficient genome-wide SNP markers and very sensitive SNP calling method allow for application of marker assisted breeding and genome-wide association studies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.381-390
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• 2022

Many attempts have been made to apply image recognition based on machine learning which has recently advanced dramatically to malware detection. They convert executable files to images and train deep learning networks like CNN to recognize or categorize dangerous executable files, which shows promising results. In this study, we are looking for an effective image generation method that may be used to identify malware using machine learning. To that end, we experiment and assess the effectiveness of various image generation methods in relation to malware detection. Then, we suggest a linear image creation method which represents control flow more clearly and our experiment shows our method can result in better precision in malware detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1794-1806
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• 2023

This study presents a method for capturing photographs of users as input and converting them into 2D character animation sprites using a generative adversarial network-based artificial intelligence network. Traditionally, 2D character animations have been created by manually creating an entire sequence of sprite images, which incurs high development costs. To address this issue, this study proposes a technique that combines motion videos and sample 2D images. In the 2D sprite generation process that uses the proposed technique, a sequence of images is extracted from real-life images captured by the user, and these are combined with character images from within the game. Our research aims to leverage cutting-edge deep learning-based image manipulation techniques, such as the GAN-based motion transfer network (impersonator) and background noise removal (U² -Net), to generate a sequence of animation sprites from a single image. The proposed technique enables the creation of diverse animations and motions just one image. By utilizing these advancements, we focus on enhancing productivity in the game and animation industry through improved efficiency and streamlined production processes. By employing state-of-the-art techniques, our research enables the generation of 2D sprite images with various motions, offering significant potential for boosting productivity and creativity in the industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.891-894
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• 2024

The quest for reliability in Artificial Intelligence (AI) is progressively urgent, especially in the field of next generation wireless networks. Future Beyond 5G (B5G)/6G networks will connect a huge number of devices and will offer innovative services invested with AI and Machine Learning tools. Wireless communications, in general, and medium access control (MAC) techniques were among the fields that were heavily affected by this improvement. This study presents the applications and services of future communication networks. This study details the Medium Access Control (MAC) scheduler of Beyond-5G/6G from 3^rd Generation Partnership (3GPP) and highlights the current open research issues which are yet to be optimized. This study provides an overview of how AI plays an important role in improving next generation communication by solving MAC-layer issues such as resource scheduling and queueing. We will select C-V2X as our use case to implement our proposed MAC scheduling model.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.33-46
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• 2011

This research focus on the economic activity as consumer and producer traits of future customers in the convergence age. We assess level of convergence for digital devices and services respectively by questionnaire survey and interview for 14 professions. And then, for evaluating convergence level and usage of digital services of each respondents, we conducted the questionnaire survey for 343 samples. Findings of our research hold that the group who showed higher level of convergence tends to use the socialized digital services more. Convergence generation were heavy users in appstore on smart-phone and wireless game and more participating. In digital service area, facebook/cyworld, twitter, UCC, portal, internet community in digital service. Convergence generation are global network communication, buying decision making activity, actively opinion expression, prosumer attitude, dependency on digital device, experience based purchase behavior, enthusiastic information sharing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1266-1269
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• 2004

With increasingly wide needs for a new energy source, many operation types of a wave-forced generation have been studied. To obtain an economically avaliable energy, it is imperative that the speed of the in put wave should be increased by a proper mechanism. In this study, we propose a new speed-increaser mechanism for the wave-force generation using a well-known Stephenson mechanism. In this paper, we have analysed kinematically the proposed speed-increasing mechanism. then a computer program based on the C++ language is developed to prove the validity of our mechanism and to simulate a wave-forced generation.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.725-734
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• 2005

Syntactic morpheme is proposed for reducing morpheme units generated by korean morpheme analyzer. It is proved that syntactic morpheme remarkably diminished the overhead of syntactic analyzer. However, the syntactic morpheme generation is so separated from the morpheme analyze phase in the existing system that it needs an extra execution time. Moreover, the method do not consider spacing-free statements. In this paper, we propose a syntactic morpheme generation using morpheme dictionary in order to resolve the problems. Experiments show that our proposed method reduce generation time more than one hundred times as compared with the existing one.