This research proposes an AI platform for data sharing across multiple domains. Since the data in the smart city concept are domain-specific processed, the existing smart city architecture is suffered from cross-domain data interpretation. To go beyond the digital transformation efforts in smart city development, the AI city is created on the architecture of cross-domain data connectivity and transform learning in the machine learning paradigm. In this research, the health and human behavioral data are targeted on human traceability and contactless technologies. To measure the inhabitants quality of life (QoL), the primary emotion expression study is conducted to interpret the emotional states and the mental health of people in the urbanized city. The results of information augmentation draw attention to the immersive visualization of the Thammasat model.
This paper examines signs mediating tourist experience in temples and heritage sites in Thailand, paying particular attention to how language is used on signs, the semiotic make-up of the signs, and the economy of discourses embedded within those signs. Utilizing a geosemiotic approach (Scollon and Scollon 2003), we show that the signs populating tourist spaces in Thailand not only address rather different audiences, but also index distinct orders of discourse (religious, commercial, informational, regulatory). We propose that signs mediate differently the landscape of Thai Buddhist temples for the local Thai audience and for non-Thai Western others, implying for each group not only different kinds of behaviours but also contrasted positions and identities. In that sense, we view signs in this tourist context observed as cultural tools for boundary production between Easterner and Westerner.
In this paper, we proposed a two-phase project on emotion corpus creation based on multi-knowledge of cognitive semantics, discourse analysis, paralinguistics, and computer science. Data were gathered from Thai lexicon of five main Thai dictionaries and thesaurus, in addition to written and spoken texts of people with depression in Thai and facial expression with speech situation. We found that semantic primes and features of each emotion were needed to serve as a guideline of emotion categorization in Thai context. We introduced the step-by-step methods of the first phase to create Thai emotion corpus entailing both verbal and nonverbal corpora. The way to classify emotion corpus by focusing on the specific text of depression as well as to find the guidelines of labelling facial expression in the situation of specific emotions was explored. Lastly, the step of creating emotion corpus in the second phase was introduced with some suggestions and discussion.
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