• Title/Summary/Keyword: FBX

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A Comparative Study on 3D Data Performance in Mobile Web Browsers in 4G and 5G Environments

  • Nam, Duckkyoun;Lee, Daehyeon;Lee, Seunghyun;Kwon, Soonchul
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.8-19
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    • 2019
  • Since their emergence in 2007, smart phones have advanced up to the point that 5G mobile communication in 2019 started to be commercialized. Accordingly, now it is possible to share 3D modeling files and collaborate by means of a mobile web. As the recently commercialized 5G mobile communication network is so useful in sharing 3D modeling files and collaborating that even large-size geometry files can be transmitted at ultra high speed with ultra low transfer delay. We examines characteristics of major 3D file formats such as STL, OBJ, FBX, and glTF and compares the existing 4G LTE (Long Term Evolution) network with the 5G NR (New Radio) mobile communication network. The loading time and packets of each format were measured depending on the mobile web browser environments. We shows that in comparison with 4G LTE, the loading time of STL and OBJ file formats were reduced as much as 6.55 sec and 9.41 sec, respectively in the 5G NR and Chrome browsers. The glTF file format showed the most efficient performance in all of the 4G/5G mobile communication networks, Chrome, and Edge browsers. In the case of STL and OBJ, the traffic was relatively excessive in 5G NR and Edge browsers. The findings of this study are expected to be utilized to develop a 3D file format that reduces the loading time in a mobile web environment.

Undaria pinnatifida Extracts and Alginic Acid Attenuated Muscle Atrophy in TNF-α Induced Myoblast Cells through MAFbx Signaling Cascade (미역 추출물과 알긴산의 근육손실 억제 효능)

  • Choi, Sang Yoon;Kim, Mina;Lee, Hyun Hee L.;Hur, Jinyoung
    • Journal of Life Science
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    • v.31 no.2
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    • pp.137-143
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    • 2021
  • Muscle atrophy refers to a decrease in muscle cells due to damage to muscle fibers. It is reported that muscle atrophy is caused by heart disease, diabetes, and other chronic diseases related to aging. The purpose of this study is to reveal the inhibitory effects of seaweed extracts, which are widely consumed in Korea, and alginic acid on muscle cell damage in muscle atrophy and regeneration models. We found that seaweed extracts (U) and alginic acid (A) attenuated TNF-α-induced muscle atrophy in differentiated C2C12 myoblast cells and inhibited muscle atrophy markers such as MuRF1 and MAFbx. In addition, U and A also regulated ubiquitination marker FoxO1 protein. To confirm the muscle regeneration effect in animal tissue, cardiotoxin (CTX) was used for the regeneration model. Six hours after CTX injection, gastrocnemius muscle volume was increased compared to control. Otherwise, the muscle volume of the U and A treatment groups was not changed. U and A also upregulated regeneration markers MyHC and PGC-1α in a CTX mouse model. These results indicate that seaweed extracts and alginic acid, a seaweed component, are applicable to senile sarcopenia by inhibiting muscle loss and promoting muscle regeneration.

Protective Effect of Enzymatically Modified Stevia on C2C12 Cell-based Model of Dexamethasone-induced Muscle Atrophy (덱사메타손으로 유도된 근위축 C2C12 모델에서 효소처리스테비아의 보호 효과)

  • Geon Oh;Sun-Il Choi;Xionggao Han;Xiao Men;Se-Jeong Lee;Ji-Hyun Im;Ho-Seong Lee;Hyeong-Dong Jung;Moon Jin La;Min Hee Kwon;Ok-Hwan Lee
    • Journal of Food Hygiene and Safety
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    • v.38 no.2
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    • pp.69-78
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    • 2023
  • This study aimed to investigate the protective effect of enzymatically modified stevia (EMS) on C2C12 cell-based model of dexamethasone (DEX)-induced muscle atrophy to provide baseline data for utilizing EMS in functional health products. C2C12 cells with DEX-induced muscle atrophy were treated with EMS (10, 50, and 100 ㎍/mL) for 24 h. C2C12 cells were treated with EMS and DEX to test their effects on cell viability and myotube formation (myotube diameter and fusion index), and analyze the expression of muscle strengthening or degrading protein markers. Schisandra chinensis Extract, a common functional ingredient, was used as a positive control. EMS did not show any cytotoxic effect at all treatment concentrations. Moreover, it exerted protective effects on C2C12 cell-based model of DEX-induced muscle atrophy at all concentrations. In addition, the positive effect of EMS on myotube formation was confirmed based on the measurement and comparison of the fusion index and myotube diameter when compared with myotubes treated with DEX alone. EMS treatment reduced the expression of muscle cell degradation-related proteins Fbx32 and MuRF1, and increased the expression of muscle strengthening and synthesis related proteins SIRT1 and pAkt/Akt. Thus, EMS is a potential ingredient for developing functional health foods and should be further evaluated in preclinical models.

Real-Time Joint Animation Production and Expression System using Deep Learning Model and Kinect Camera (딥러닝 모델과 Kinect 카메라를 이용한 실시간 관절 애니메이션 제작 및 표출 시스템 구축에 관한 연구)

  • Kim, Sang-Joon;Lee, Yu-Jin;Park, Goo-man
    • Journal of Broadcast Engineering
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    • v.26 no.3
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    • pp.269-282
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    • 2021
  • As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.