The Distant Heart: Mediating Long-Distance Relationships through Connected Computational Jewelry
May 03, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yulia Silina, Hamed Haddadi
arXiv ID
1505.00489
Category
cs.HC: Human-Computer Interaction
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In the world where increasingly mobility and long-distance relationships with family, friends and loved-ones became commonplace, there exists a gap in intimate interpersonal communication mediated by technology. Considering the advances in the field of mediation of relationships through technology, as well as prevalence of use of jewelry as love-tokens for expressing a wish to be remembered and to evoke the presence of the loved-one, developments in the new field of computational jewelry offer some truly exciting possibilities. In this paper we investigate the role that the jewelry-like form factor of prototypes can play in the context of studying effects of computational jewelry in mediating long-distance relationships.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted