Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Senaka Buthpitiya"'
Publikováno v:
Proceedings of the 30th International Conference on Advances in Geographic Information Systems.
Publikováno v:
KDD
We present BusTr, a machine-learned model for translating road traffic forecasts into predictions of bus delays, used by Google Maps to serve the majority of the world's public transit systems where no official real-time bus tracking is provided. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65991e543da170f1c840d8d90fa308fe
Autor:
Feng-Tso Sun, Kuo, Cynthia, Heng-Tze Cheng, Senaka Buthpitiya, Collins, Patricia, Griss, Martin L
"Continuous stress monitoring may help users better understand their stress patterns and provide physicians with more reliable data for interventions. Previously, studies on mental stress detection were limited to a laboratory environment where parti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::976d24c2786a16c1e2aa781a365648dc
Autor:
Senaka Buthpitiya, Patrick Tague, Feng-Tso Sun, Anind K. Dey, Martin L. Griss, Heng-Tze Cheng
Sharing sensitive context information among multiple distributed components in mobile environments introduces major security concerns. The distributed sensing, processing and actuating components of these applications can be compromised and modified
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ccb084ccbf1e65367bf183afcf01eed0
Publikováno v:
IUI
In this paper we develop a model capable of classifying drivers from their driving behaviors sensed by only low level sensors. The sensing platform consists of data available from the diagnostic outlet (OBD) of the car and smartphone sensors. We deve
Publikováno v:
CHI
Recent mobile phones integrate fingerprint scanners to authenticate users biometrically and replace passwords, making authentication more convenient for users. However, due to their cost, capacitive fingerprint scanners have been limited to top-of-th
Publikováno v:
PerCom
As mobile context-aware services gain mainstream popularity, there is increased interest in developing techniques that can detect anomalous activities for applications such as user authentication, adaptive assist technologies and remote elder-care mo
Publikováno v:
2014 International Conference on Computational Science and Computational Intelligence.
Combining information from a variety of sources greatly improves the classification accuracy compared with a single source. When the information sources are asynchronous (i.e., the combined feature set has missing values) and training data is limited
Autor:
Senaka Buthpitiya
As ubiquitous computing (ubicomp) technologies reach maturity, smart phones and context-based services are gaining mainstream popularity. A smart phone accompanies its user throughout (nearly) all aspects of his life, becoming an indispensable assist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38e88da85127abcfba4f3ce4bd2ab817
Publikováno v:
2012 Innovative Parallel Computing (InPar).
Robust and accurate speech recognition systems can only be realized with adequately trained acoustic models. For common languages, state-of-the-art systems are trained on many thousands of hours of speech data and even with large clusters of machines