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MOBISYS
2010
ACM
15 years 9 months ago
Darwin phones: the evolution of sensing and inference on mobile phones
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on ...
Emiliano Miluzzo, Cory Cornelius, Ashwin Ramaswamy...
SSR
2001
104views more  SSR 2001»
15 years 8 months ago
Secure and efficient mobile agent application reuse using patterns
As wide-area open networks like the Internet and intranets grow larger, mobile agent technology is attracting more attention. Mobile agents are units of software that can deal wit...
Yasuyuki Tahara, Nobukazu Toshiba, Akihiko Ohsuga,...
CE
2008
122views more  CE 2008»
15 years 6 months ago
Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques
The portability and immediate communication properties of mobile devices influence the learning processes in interacting with peers, accessing resources and transferring data. For...
G. D. Chen, C. K. Chang, C. Y. Wang
181
Voted
CN
2007
117views more  CN 2007»
15 years 6 months ago
Cellular universal IP for nested network mobility
In recent years, network mobility (NEMO) has been studied extensively due to its potential applications in military and public transportation. NEMO basic support protocol (NBSP), ...
Patrick P. Lam, Soung C. Liew, Jack Y. B. Lee
ICRA
2005
IEEE
122views Robotics» more  ICRA 2005»
16 years 11 days ago
Supervised Learning of Places from Range Data using AdaBoost
— This paper addresses the problem of classifying places in the environment of a mobile robot into semantic categories. We believe that semantic information about the type of pla...
Óscar Martínez Mozos, Cyrill Stachni...