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Sökning: WFRF:(Huang H) > Humaniora

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1.
  • Delios, A., et al. (författare)
  • Examining the generalizability of research findings from archival data
  • 2022
  • Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:30
  • Tidskriftsartikel (refereegranskat)abstract
    • This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability-for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples. 
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2.
  • Zhu, H., et al. (författare)
  • Some effects of specific interest on the brain of children with autism spectrum disorder (ASD) : A functional near-infrared spectroscopy study
  • 2015
  • Konferensbidrag (refereegranskat)abstract
    • Autism spectrum disorder (ASD) is a neuro-developmental disorder, characterized by two major domains: impairments in the social cognition and communication as well as restricted, repetitive, stereotyped interests and behaviors. In this study, functional near-infrared spectroscopy (fNIRS) was applied to investigate the atypical activation pattern of language areas (bilateral inferior frontal gyrus and bilateral temporal cortex) and uncover the impact of a specific interest on the brain function of children with ASD. We employed a listening comprehension task to stimulate the language areas of 2 ASD boys (A1 and A2) who had strong interests in the experiment material ("Lightning McQueen") and another 2 ASD boys (A3 and A4) who were matched with A1 and A2 respectively by age, intelligence quotient, language ability and the severity of symptoms. Our results showed that, during the task, the picture of "Lightning McQueen", but not the words of "The little red car", elicited stronger activation in the bilateral inferior frontal gyrus and temporal cortex of A1 and A2 than A3 and A4. These results could facilitate our understanding of language development of ASD and reconsider the role of specific interests (especially visual stimuli) played in the brain functional development of ASD.
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3.
  • Sturm, Bob, 1975-, et al. (författare)
  • Editorial for TISMIR Special Collection : AI and Musical Creativity
  • 2022
  • Ingår i: Transactions of the International Society for Music Information Retrieval. - : Ubiquity Press, Ltd.. - 2514-3298. ; 5:1, s. 67-70
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • This special issue focuses on research developments and critical thought in the domain of artificial intelligence (AI) applied to modeling and creating music. It is motivated by the AI Song Contests of 2020 and 2021, in which the four guest editors adjudicated or participated among many teams from around the world. The 2020 edition had 13 submissions and the 2021 edition had 38. The 2022 edition is now being planned. These unique events provide exciting opportunities for AI music researchers to test the state of the art and push the boundaries of what is possible, within the context of music creation. They portend a future when humans and machines work together as partners in music creation. Maybe "portend" is not the right term, but we must not think that the future of AI and music is only warm and fuzzy. It is important and timely to consider how we, in local and global contexts, can effectively and ethically develop and apply AI in contexts of music creation.
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