Demo Data from EDBT 2026 / reviewers in the wild / expert
William Headley
dblp:327/5148
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 100% | |
| Computer networks
1 paper |
Wireless sensing and localization · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization › navigation
dead reckoning |
0.1 | 1 | 2014 | Design, Realization, and Evaluation of uDirect-An Approach for Pervasive Observation of User Facing Direction on Mobile Phones · IEEE Trans. Mob. Comput. 2014 |
Methods — techniques the papers use, named apart from their topics
trigonometric interpolation · 0.4PCA · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Design, Realization, and Evaluation of uDirect-An Approach for Pervasive Observation of User Facing Direction on Mobile PhonesabstractA novel method for a mobile phone centric observation of a user's facing direction is presented. To estimate this direction, our proposed technique exploits the acceleration pattern that can be measured by a smartphone as the user is walking. For an accurate analysis of the acceleration pattern, the proposed approach benefits from a new trigonometric interpolation scheme. Our algorithm is independent of the initial orientation of the device and is adaptable to various wearing positions on a user's body, which gives the user a larger degree of freedom. A detailed description of the algorithm, which has been customized for a trouser pocket is presented. In addition, complementary hints for adaptation of the algorithm to other wearing positions along with an example of chest pocket position are provided. We have evaluated a prototype implementation of our algorithm on a smartphone, through several field experiments. It has been observed that our algorithm outperforms the conventional GPS and PCA-based techniques in terms of accuracy, reliability and energy consumption. The results also show that our approach has been able to handle the sudden variations of the user's direction. We have further incorporated our algorithm into a dead-reckoning application as an example of its real-world utility. Seyed Amir Hoseinitabatabaei, Alexander Gluhak, Rahim Tafazolli, William Headley |
IEEE Trans. Mob. Comput. | 4 |