by
Siqi Lin, Yu-Lin Hsu *
Abstract: This study explores the modernization of tea packaging, departing from traditional landscape-themed illustrations to resonate with younger consumers. With a focus on the Ancient Tea-Horse Road theme and Ya’an Tibetan tea, various methodologies are employed: Literature Review: Illustration styles are analyzed across historical periods to inform modern design choices. Case Analysis: Existing tea packaging designs, particularly those targeting young consumers, and integrating elements of the Ancient Tea-Horse Road, are examined. Field Research: The historical and cultural significance of the Ancient Tea-Horse Road are investigated. Design Implementation: Computer software blended hand-drawn images with modern images. By infusing the essence of the Ancient Tea-Horse Road into Ya’an Tibetan tea packaging through modern illustrations, this study aims to create a visually appealing product that bridges tradition with contemporary aesthetics. This approach revitalizes traditional themes, enhancing product distinctiveness and market competitiveness.
Yang Xu, Qingnan Li, Xianmeng Zhao, Dake Liu,
Nanqiao Shi *
by
Abstract: Purpose: To review and analyze the research status of the application of generative adversarial networks (GANs) in the field of architecture design. Methods: This study followed the latest PRISMA guidelines and systematically collected relevant research literature from domestic and international sources. In-depth analysis was conducted on 95 representative Chinese and English language articles. During the analysis process, three dimensions of intelligent architectural generation methods were comprehensively and deeply explored: the data application scale, algorithm type, and architectural design process. Results: (1) GANs have been applied to various processes in architectural design practice, from design generation, development, and evaluation to final solution expression; (2) GANs can be applied at different architectural scales, ranging from large-scale complex functional buildings to refined layout designs of residential units; (3) the appearance of GANs enables designers to quickly present design results at various stages, greatly improving work efficiency; and (4) at present, GANs also have many shortcomings, mainly reflected in the accuracy of the data and the usability of tools. Conclusion: Improvements in computer performance and the enrichment of data resources have promoted the widespread application of intelligent architectural generation methods. GANs have great potential in the field of architectural design and can provide a more efficient, flexible, and diverse design process. However, further research and development are needed to address the challenges and limitations of using GANs in this field.
by
Laura Niño Cáceres * ,
,
Daisy Yoo ,
Caroline Hummels
*Abstract: COVID-19 accelerated digital healthcare technology usage in many countries, such as Colombia, whose digital healthcare vision and projects are proof of this. However, with a significant cultural indigenous and Afro-Colombian heritage, only some parts of the country are willing to follow the proposed digital Western approach to health. Our paper presents the national healthcare system’s digital narrative, which we contrast with the micro-narrative of an Afro-Colombian ethnomedicine unit in Bogota called Kilombo Yumma. This ethnomedical unit is building its mobile app to safeguard and represent its ancestral medicine practices in local and national healthcare information systems. Kilombo Yumma is keen on promoting their beliefs and practices, which have been passed on through oral traditions and currently exist in the hands of a few elderly. We unraveled their ambition, core beliefs, and practices through asset-based design. These assets outlined pluriversal and decolonizing forms of digital healthcare to increase social justice and connect Western and ancestral medicine digital opportunities through HCI.
Lates articles
Abstract: Purpose: To review and analyze the research status of the application of generative adversarial networks (GANs) in the field of architecture design. Methods: This study followed the latest PRISMA guidelines and systematically collected relevant research literature from domestic and international sources. In-depth analysis was conducted on 95 representative Chinese and English language articles. During the analysis process, three dimensions of intelligent architectural generation methods were comprehensively and deeply explored: the data application scale, algorithm type, and architectural design process. Results: (1) GANs have been applied to various processes in architectural design practice, from design generation, development, and evaluation to final solution expression; (2) GANs can be applied at different architectural scales, ranging from large-scale complex functional buildings to refined layout designs of residential units; (3) the appearance of GANs enables designers to quickly present design results at various stages, greatly improving work efficiency; and (4) at present, GANs also have many shortcomings, mainly reflected in the accuracy of the data and the usability of tools. Conclusion: Improvements in computer performance and the enrichment of data resources have promoted the widespread application of intelligent architectural generation methods. GANs have great potential in the field of architectural design and can provide a more efficient, flexible, and diverse design process. However, further research and development are needed to address the challenges and limitations of using GANs in this field.
Abstract: Purpose: To review and analyze the research status of the application of generative adversarial networks (GANs) in the field of architecture design. Methods: This study followed the latest PRISMA guidelines and systematically collected relevant research literature from domestic and international sources. In-depth analysis was conducted on 95 representative Chinese and English language articles. During the analysis process, three dimensions of intelligent architectural generation methods were comprehensively and deeply explored: the data application scale, algorithm type, and architectural design process. Results: (1) GANs have been applied to various processes in architectural design practice, from design generation, development, and evaluation to final solution expression; (2) GANs can be applied at different architectural scales, ranging from large-scale complex functional buildings to refined layout designs of residential units; (3) the appearance of GANs enables designers to quickly present design results at various stages, greatly improving work efficiency; and (4) at present, GANs also have many shortcomings, mainly reflected in the accuracy of the data and the usability of tools. Conclusion: Improvements in computer performance and the enrichment of data resources have promoted the widespread application of intelligent architectural generation methods. GANs have great potential in the field of architectural design and can provide a more efficient, flexible, and diverse design process. However, further research and development are needed to address the challenges and limitations of using GANs in this field.
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