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RISS 인기검색어
- 검색키워드
- 저자 : Fan Runze (검색결과 3 건)
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Influence on the Use Intention of User’s Traits in China Market
이종호,Runze Wu,Linlin Fan 한국유통과학회 2017 Asian Journal of Business Environment (AJBE) Vol.7 No.2
Purpose - Because of the development of smartphone and communication technology, Smart TV programs are filled with various contents and applications. This study included additional individual variables like innovativeness and self-efficacy, and characteristics of smart TV are both user-interface and function as exogenous factors based on TAM model. So, this study focuses on identifying the influencing factors of continuous use intention of smart TV traits and user ones and analyzing how they make influences on them in China market. Research design, data, and methodology - Totally 182 samples were adopted as appropriate ones for analysis in this study. They were collected from 20 February 2016 to 10 March 2016. Results - The results are as follows. First, function has positive influence on perceived usefulness. Second, innovation and user-interface make affirmative influences on perceived easiness. Third, perceived easiness has affirmative influence on perceived usefulness. Fourth, the perceived easiness and perceived usefulness make positive ones on continuous use intention. Fifth, perceived ease of use affects significantly on perceived usefulness. Conclusions - According to the findings, they (smart TV traits and user traits), influencing on continuous use intention, are possible to give significant implications on persistent development in China smart TV market.
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Dynamic behavior of an ellipsoidal bubble contaminated by surfactant near a vertical wall
Enbo Ju,Runze Cai,Haopeng Sun,Ying Fan,Wenyi Chen,Jiao Sun 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.5
Adding a small amount of surfactant to gas-liquid two-phase flow can markedly change bubble behavior,which has crucial application value in nuclear energy, petrochemical, chemical, and environmental engineering. In thispaper, the dynamic behavior of a single ellipsoidal bubble (Re~800) contaminated by surfactant rising near a verticalwall in stagnant liquid is studied using the shadow method. The effects of different concentrations of sodium dodecylsulfate solution (100 ppm, 400 ppm, 800 ppm) and initial dimensionless distances on bubble dynamics were compared. The dynamic parameters, shape oscillation, force, and energy of the bubble were analyzed. The results show that thecritical initial dimensionless distance at which the collision occurs is decreased due to a dimensionless distance changefrom 3.3 to 0.23, accelerating the transition from zigzag to spiral movement. Transverse movement of the contaminatedbubble is restrained. Because of the Marangoni effect caused by the surfactant, the boundary condition changesfrom zero shear to non-zero shear, resulting in a decrease in velocity and an increase in the drag coefficient. As the surfactantconcentration increases, the lift coefficient does not significantly change with concentration variations. Theinfluences of the wall effect on velocity and drag gradually weaken. Comparing free-rising and collision conditions, theaspect ratio of the contaminated bubble is distinct from the regularity of a clean bubble. The surfactant also changes thewall-normal velocity frequency and symmetrical shape frequency and inhibits energy conversion during collision.
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Self-supervised feature matched virtual try-on
Jiang Shiyi,Xu Yang,Li Danyang,Fan Runze 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.5
Virtual try-on is a technology that enables users to preview the effect of wearing a target garment without wearing the actual garment. However, existing image-based virtual try-on methods often require additional human parsing or segmentation operations to generate intermediate representations required for garment deformation and texture fusion. These operations not only increase the computational complexity and memory consumption, but also limit the real-time and portability of virtual try-on. Additionally, inaccurate parsing results can lead to misleading final generated images. To overcome these challenges, we propose a self-supervised feature matched virtual try-on network, which can directly generate high-quality try-on results from human body images and target clothing images without any additional input. Specifically, we design an optical flow warp module, which focuses on the optical flow changes between the person image and the clothing image to achieve accurate clothing alignment and deformation. Furthermore, a feature refine warp module is designed to enhance the features of the extracted optical flow information and the original character segmentation and analysis operations, reducing the influence of background clutter features on the content, and ensuring that the wrinkles and deformation of the replacement clothes are close to the original clothes. The feature match module is developed to calculate the feature matching loss of the converted clothing and the generated results of the teacher network and the student network, and the corresponding knowledge is distilled and passed to the student network to assist in self-supervised training. We conduct experiments on the VITON dataset and show that our model can generate high quality and high resolution, and our proposed method outperforms the state-of-the-art virtual try-on methods both qualitatively and quantitatively.
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