0000
111.
Data-Driven Model to Improve Mechanical Harvesters for Nut Trees Proceedings Article
In: 0000.
@inproceedings{noauthor_data-driven_nodate,
title = {Data-Driven Model to Improve Mechanical Harvesters for Nut Trees},
url = {https://doi.org/10.13031/aim.202400858},
urldate = {2024-08-09},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
112.
Slicing-Aided Hyper Inference for Enhanced Fruit Bud Detection and Counting in Apple Orchards during Dormant Season Proceedings Article
In: 0000.
@inproceedings{noauthor_slicing-aided_nodate,
title = {Slicing-Aided Hyper Inference for Enhanced Fruit Bud Detection and Counting in Apple Orchards during Dormant Season},
url = {https://doi.org/10.13031/aim.202401055},
urldate = {2024-08-09},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
113.
Abrar Fallatah; Md Montaser Hamid; Fatima A. Moussaoui; Chimdi Chikezie; Martin Erwig; Christopher Bogart; Anita Sarma; Margaret Burnett
Intersectional HCI on a Budget: An Analytical Approach Powered by Types Journal Article
In: International Journal of Human–Computer Interaction, vol. 0, no. 0, pp. 1–24, 0000, ISSN: 1044-7318, (Publisher: Taylor & Francis _eprint: https://doi.org/10.1080/10447318.2025.2474494).
Abstract | Links | BibTeX | Tags: AI, Humans
@article{fallatah_intersectional_nodate,
title = {Intersectional HCI on a Budget: An Analytical Approach Powered by Types},
author = {Abrar Fallatah and Md Montaser Hamid and Fatima A. Moussaoui and Chimdi Chikezie and Martin Erwig and Christopher Bogart and Anita Sarma and Margaret Burnett},
url = {https://doi.org/10.1080/10447318.2025.2474494},
doi = {10.1080/10447318.2025.2474494},
issn = {1044-7318},
journal = {International Journal of Human\textendashComputer Interaction},
volume = {0},
number = {0},
pages = {1\textendash24},
abstract = {Intersectional HCI recognizes that humans' interconnected social identities shape their experiences with technology. However, intersectional HCI requires extensive resources, such as access to intersectional populations, which many HCI practitioners may lack. For these practitioners, we present an analytical approach to bring intersectional lenses to HCI practices. The approach uses types\textemdashnot at the level of identities, but at the level of personal traits drawn from foundational research. We first formally prove that certain analytical methods for detecting inclusivity issues can be meaningfully composed to provide equitable consideration of typically overlooked populations; then present four design use-cases to illustrate what the approach brings to HCI practices; and then empirically investigated one of the four use-cases with 24 HCI participants. Results show that practitioners using the compositional approach detected even more intersectional inclusivity problems than those using a complementary intersectional approach.},
note = {Publisher: Taylor \& Francis
_eprint: https://doi.org/10.1080/10447318.2025.2474494},
keywords = {AI, Humans},
pubstate = {published},
tppubtype = {article}
}
Intersectional HCI recognizes that humans' interconnected social identities shape their experiences with technology. However, intersectional HCI requires extensive resources, such as access to intersectional populations, which many HCI practitioners may lack. For these practitioners, we present an analytical approach to bring intersectional lenses to HCI practices. The approach uses types—not at the level of identities, but at the level of personal traits drawn from foundational research. We first formally prove that certain analytical methods for detecting inclusivity issues can be meaningfully composed to provide equitable consideration of typically overlooked populations; then present four design use-cases to illustrate what the approach brings to HCI practices; and then empirically investigated one of the four use-cases with 24 HCI participants. Results show that practitioners using the compositional approach detected even more intersectional inclusivity problems than those using a complementary intersectional approach.
114.
Abrar Fallatah; Md Montaser Hamid; Fatima A. Moussaoui; Chimdi Chikezie; Martin Erwig; Christopher Bogart; Anita Sarma; Margaret Burnett
Intersectional HCI on a Budget: An Analytical Approach Powered by Types Journal Article
In: International Journal of Human–Computer Interaction, vol. 0, no. 0, pp. 1–24, 0000, ISSN: 1044-7318, (Publisher: Taylor & Francis _eprint: https://doi.org/10.1080/10447318.2025.2474494).
Abstract | Links | BibTeX | Tags: AI, Humans
@article{fallatah_intersectional_nodateb,
title = {Intersectional HCI on a Budget: An Analytical Approach Powered by Types},
author = {Abrar Fallatah and Md Montaser Hamid and Fatima A. Moussaoui and Chimdi Chikezie and Martin Erwig and Christopher Bogart and Anita Sarma and Margaret Burnett},
url = {https://doi.org/10.1080/10447318.2025.2474494},
doi = {10.1080/10447318.2025.2474494},
issn = {1044-7318},
urldate = {2025-08-06},
journal = {International Journal of Human\textendashComputer Interaction},
volume = {0},
number = {0},
pages = {1\textendash24},
abstract = {Intersectional HCI recognizes that humans' interconnected social identities shape their experiences with technology. However, intersectional HCI requires extensive resources, such as access to intersectional populations, which many HCI practitioners may lack. For these practitioners, we present an analytical approach to bring intersectional lenses to HCI practices. The approach uses types\textemdashnot at the level of identities, but at the level of personal traits drawn from foundational research. We first formally prove that certain analytical methods for detecting inclusivity issues can be meaningfully composed to provide equitable consideration of typically overlooked populations; then present four design use-cases to illustrate what the approach brings to HCI practices; and then empirically investigated one of the four use-cases with 24 HCI participants. Results show that practitioners using the compositional approach detected even more intersectional inclusivity problems than those using a complementary intersectional approach.},
note = {Publisher: Taylor \& Francis
_eprint: https://doi.org/10.1080/10447318.2025.2474494},
keywords = {AI, Humans},
pubstate = {published},
tppubtype = {article}
}
Intersectional HCI recognizes that humans' interconnected social identities shape their experiences with technology. However, intersectional HCI requires extensive resources, such as access to intersectional populations, which many HCI practitioners may lack. For these practitioners, we present an analytical approach to bring intersectional lenses to HCI practices. The approach uses types—not at the level of identities, but at the level of personal traits drawn from foundational research. We first formally prove that certain analytical methods for detecting inclusivity issues can be meaningfully composed to provide equitable consideration of typically overlooked populations; then present four design use-cases to illustrate what the approach brings to HCI practices; and then empirically investigated one of the four use-cases with 24 HCI participants. Results show that practitioners using the compositional approach detected even more intersectional inclusivity problems than those using a complementary intersectional approach.
115.
Soumiki Chattopadhyay
Systematizing inclusive design in MOSIP : an experience report Miscellaneous
0000, (Publisher: Oregon State University).
@misc{chattopadhyay_systematizing_nodate,
title = {Systematizing inclusive design in MOSIP : an experience report},
author = {Soumiki Chattopadhyay},
note = {Publisher: Oregon State University},
keywords = {AI, Humans},
pubstate = {published},
tppubtype = {misc}
}
