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あぁかがさざただなはばぱまやゃらわゎんいぃきぎしじちぢにひびぴみりうぅくぐすずつづっぬふぶぷむゆゅるえぇけげせぜてでねへべぺめれおぉこごそぞとどのほぼぽもよょろを

アァカサザタダナハバパマヤャラワヮンイィキギシジチヂニヒビピミリウゥクグスズツヅッヌフブプムユュルエェケゲセゼテデヘベペメレオォコゴソゾトドノホボポモヨョロヲ ―

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中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
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Α Β Γ Δ Ε Ζ Η Θ Ι Κ Λ Μ Ν Ξ Ο Π Ρ Σ Τ Υ Φ Χ Ψ Ω α β γ δ ε ζ η θ ι κ λ μ ν ξ ο π ρ σ τ υ φ χ ψ ω

á à Á À é è É È ç Ç ê

Ä Ö Ü ä ö ü ß

ְ ֳ ֲ ֱ ָ ַ ֵ ֶ ִ ֹ ּ ֻ ׂ ׁ ּ פ ם ן ו ט א ר ק ף ך ל ח י ע כ ג ד ש ץ ת צ מ נ ה ב

‘ ’ “ ” 〔〕〈〉「」『』【】＂（）［］｛｝

± × ÷ ≠ ≤ ≥ ∞ ∴ ♂ ♀ ∠ ⊥ ⌒ ∂ ∇ ≡ ≒ ≪ ≫ √ ∽ ∝ ∵ ∫ ∬ ∈ ∋ ⊆ ⊇ ⊂ ⊃ ∪ ∩ ∧ ∨ ￢ ⇒ ⇔ ∀ ∃ ∮ ∑ ∏ ＋－＜＝＞

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ⅰ ⅱ ⅲ ⅳ ⅴ ⅵ ⅶ ⅷ ⅸ ⅹ Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ Ⅵ Ⅶ Ⅷ Ⅸ Ⅹ

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10개씩 출력

1
ENHANCING CUSTOMER EXPERIENCES IN THE AUGMENTED REALITY ERA

Anqi Hu,Ruizhi Yuan,Martin J. Liu,Ruolan Chen 글로벌지식마케팅경영학회 2023 Global Marketing Conference Vol.2023 No.07
- 원문보기
In recent years E-commerce platforms recommend some products for consumers based on their shopping history and user persona. However, sometimes, unfamiliar products or styles would be recommended to consumers unintentionally or intentionally. Curiosity drives consumers to try but this idea would be declined with the consideration of product fit uncertainty. Augmented Reality (AR) is the integration of digital information with the user‘s environment in real-time (Hilken et al. 2018), it can deal with issues related to physical apprehension that hinder consumers’ online shopping (i.e, clothes, cosmetics), especially for the unfamiliar style. This study aims to investigate whether AR technology could improve consumers' purchase likelihood. Augmented Reality (AR) can enhance customer experiences in a multichannel environment (Hilken et al. 2017). AR Integrates online experiences into the offline experience (Hilken et al. 2018), such as virtual try-on or magic mirrors. Customers often find it difficult to imagine how firms’ products and services fit them personally or fit with their environment (Hilken et al. 2018). Drawn on AR, consumers can easily evaluate the fitness between themselves and the selected products. Prior studies have explored the different underlying processes of why AR technology could improve consumer purchase intention and customer experience. For instance, according to the situated cognition theory, AR creates a feeling of spatial presence (Hilken et al. 2017). The usage of AR benefits mental imagery, improving decision comfort (Heller et al. 2019). AR can compensate for consumers’ need for touch and offer hedonic and/or utilitarian benefits (Gatter et al. 2022). Based on media richness theory, AR offers more information for customers (Hoffmann et al. 2022), which represents a fitting concept for customers to evaluate the product (Javornik 2016).
2
Analyzing green view index and green view index best path using Google street view and deep learning

Zhang Jiahao,Hu Anqi 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5
As an important part of urban landscape research, analyzing and studying street-level greenery can increase the understanding of a city’s greenery, contributing to better urban living environment planning and design. Planning the best path of urban greenery is a means to effectively maximize the use of urban greenery, which plays a positive role in the physical and mental health of urban residents and the path planning of visitors. In this paper, we used Google street view to obtain street view images of Osaka City. The semantic segmentation model is adopted to segment the street view images and analyze the green view index (GVI) of Osaka City. Based on the GVI, we take advantage of the adjacency matrix and Floyd–Warshall algorithm to calculate GVI best path, solving the limitations of ArcGIS software. Our analysis not only allows the calculation of specific routes for the GVI best paths but also realizes the visualization and integration of neighborhood urban greenery. By summarizing all the data, we can conduct an intuitive feeling and objective analysis of the street-level greenery in the research area. Based on this, such as urban residents and visitors can maximize the available natural resources for a better life. The dataset and code are available at https://github.com/Jackieam/GVI-Best-Path.
3
Finite element analysis of high-density polyethylene pipe in pipe gallery of nuclear power plants

Shi, Jianfeng,Hu, Anqi,Yu, Fa,Cui, Ying,Yang, Ruobing,Zheng, Jinyang Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.3
- 원문보기 2
  ScienceON
  
  KCI
High density polyethylene (HDPE) pipe has many advantages over metallic pipe, and has been used in non-safety related application for years in some nuclear power plants (NPPs). Recently, HDPE pipe was introduced into safety related applications. The main difference between safety-related and non-safety-related pipes in NPPs is the design method of extra loadings such as gravity, temperature, and earthquake. In this paper, the mechanical behavior of HDPE pipe under various loads in pipe gallery was studied by finite element analysis (FEA). Stress concentrations were found at the fusion regions on inner surface of mitered elbows of HDPE pipe system. The effects of various factors were analyzed, and the influence of various loads on the damage of HDPE pipe system were evaluated. The results of this paper provide a reference for the design of nuclear safety-related Class 3 HDPE pipe. In addition, as the HDPE pipes analyzed in this paper were suspended in pipe gallery, it can also serve as a supplementary reference for current ASME standard on Class 3 HDPE pipe, which only covers the application for buried pipe application.