Zobrazeno 1 - 10
of 807
pro vyhledávání: '"Kay, Matthew"'
Visualizations play a critical role in validating and improving statistical models. However, the design space of model check visualizations is not well understood, making it difficult for authors to explore and specify effective graphical model check
Externí odkaz:
http://arxiv.org/abs/2408.16702
Generative AI has the potential to create a new form of interactive media: AI-bridged creative language arts (CLA), which bridge the author and audience by personalizing the author's vision to the audience's context and taste at scale. However, it is
Externí odkaz:
http://arxiv.org/abs/2403.00439
People with dementia (PwD) often present verbal agitation such as cursing, screaming, and persistently complaining. Verbal agitation can impose mental distress on informal caregivers (e.g., family, friends), which may cause severe mental illnesses, s
Externí odkaz:
http://arxiv.org/abs/2311.10912
Visualization literacy is an essential skill for accurately interpreting data to inform critical decisions. Consequently, it is vital to understand the evolution of this ability and devise targeted interventions to enhance it, requiring concise and r
Externí odkaz:
http://arxiv.org/abs/2308.14147
Autor:
Davis, Russell, Pu, Xiaoying, Ding, Yiren, Hall, Brian D., Bonilla, Karen, Feng, Mi, Kay, Matthew, Harrison, Lane
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics 2022
Graphical perception studies typically measure visualization encoding effectiveness using the error of an "average observer", leading to canonical rankings of encodings for numerical attributes: e.g., position > area > angle > volume. Yet different p
Externí odkaz:
http://arxiv.org/abs/2212.10533
Autor:
Ahopelto, Kaisa, Aoki, Yoshitaka, Beilmann-Lehtonen, Ines, Blanker, Marco H., Craigie, Samantha, Elberkennou, Jaana, Garcia-Perdomo, Herney A., Gomaa, Huda A., Gross, BCPS; Peter, Hajebrahimi, Sakineh, Huang, Linglong, Karanicolas, Paul J., Kilpeläinen, Tuomas P., Kivelä, Antti J., Korhonen, Tapio, Lampela, Hanna, Lee, Yung, Mattila, Anne K., Najafabadi, Borna Tadayon, Nykänen, Taina P., Nystén, Carolina, Pandanaboyana, Sanjay, Ratnayake, Chathura B.B., Raudasoja, Aleksi R., Sallinen, Ville J., Violette, Philippe D., Xiao, Yingqi, Yao, Liang, Lavikainen, Lauri I., Guyatt, Gordon H., Kalliala, Ilkka E.J., Cartwright, Rufus, Luomaranta, Anna L., Vernooij, Robin W.M., Tähtinen, Riikka M., Tadayon Najafabadi, Borna, Singh, Tino, Pourjamal, Negar, Oksjoki, Sanna M., Khamani, Nadina, Karjalainen, Päivi K., Joronen, Kirsi M., Izett-Kay, Matthew L., Haukka, Jari, Halme, Alex L.E., Ge, Fang Zhou, Galambosi, Päivi J., Devereaux, P.J., Cárdenas, Jovita L., Couban, Rachel J., Aro, Karoliina M., Aaltonen, Riikka L., Tikkinen, Kari A.O.
Publikováno v:
In American Journal of Obstetrics and Gynecology April 2024 230(4):390-402
Autor:
Ahopelto, Kaisa, Aoki, Yoshitaka, Beilmann-Lehtonen, Ines, Blanker, Marco H., Craigie, Samantha, Elberkennou, Jaana, Garcia-Perdomo, Herney A., Gomaa, Huda A., Gross, Peter, Hajebrahimi, Sakineh, Karanicolas, Paul J., Kilpeläinen, Tuomas P., Kivelä, Antti J., Korhonen, Tapio, Lampela, Hanna, Lee, Yung, Mattila, Anne K., Najafabadi, Borna Tadayon, Nykänen, Taina P., Nystén, Carolina, Pandanaboyana, Sanjay, Ratnayake, Chathura B.B., Raudasoja, Aleksi R., Sallinen, Ville J., Violette, Philippe D., Xiao, Yingqi, Yao, Liang, Lavikainen, Lauri I., Guyatt, Gordon H., Luomaranta, Anna L., Cartwright, Rufus, Kalliala, Ilkka E.J., Couban, Rachel J., Aaltonen, Riikka L., Aro, Karoliina M., Cárdenas, Jovita L., Devereaux, P.J., Galambosi, Päivi J., Ge, Fang Zhou, Halme, Alex L.E., Haukka, Jari, Izett-Kay, Matthew L., Joronen, Kirsi M., Karjalainen, Päivi K., Khamani, Nadina, Oksjoki, Sanna M., Pourjamal, Negar, Singh, Tino, Tähtinen, Riikka M., Vernooij, Robin W.M., Tikkinen, Kari A.O.
Publikováno v:
In American Journal of Obstetrics and Gynecology April 2024 230(4):403-416
Publikováno v:
In Food Chemistry: X 30 March 2024 21
Data from multifactor HCI experiments often violates the normality assumption of parametric tests (i.e., nonconforming data). The Aligned Rank Transform (ART) is a popular nonparametric analysis technique that can find main and interaction effects in
Externí odkaz:
http://arxiv.org/abs/2102.11824