PPT-Tracking Fine-grain Vehicular Speed Variations by Warping Mobile Phone Signal Strengths

Presented by Tam Vu Gayathri Chandrasekaran Tam Vu Alexander Varshavsky Marco Gruteser Richard P Martin Jie Yang Yingying Chen WINLAB. Smartphones have more features and applications that can utilize external accessories and the number of different external accessories will continue to grow in the future The challenge in designing new phones is how to connect to all these new acces Dongliang. . Zhang, . Xin. Wang, . Yunsong. Huang, Gerard Schuster. KAUST. Outline. . Conclusions. Motivation. Flatten the common image gathers. Numerical Example. Test . on . Marmousi. model and GOM data. : Brain-Mobile Phone Interface. . using a Wireless EEG Headset. Source: . MobiHeld. 2010. Presented By: Corey Campbell. INTRODUCTION. A new way to use the mobile phone. Design and Evaluation of . NeuroPhone. O2. and . Vodafone. In Life- Support. BASIC CHECKS FOR PHONE/NETWORK ISSUES. Has the customer got a signal? Ask the customer to check signal on their handset.. Complete a manual roam on the . handset.. Presented by Tam Vu. Gayathri. . Chandrasekaran. *, . Tam Vu*, Alexander . Varshavsky. †. , . Marco . Gruteser. *. , Richard . P. . Martin. *. , . Jie. . Yang. ‡. , . Yingying. . Chen. ‡. *WINLAB. Emmanuel Baccelli, Philippe Jacquet, Bernard Mans, and Georgios Rodolakis. Presented by: Mayank Shekhar. Contents. Information Propagation Speed. Significance. Dependency. Mathematical Model for Delay Tolerant Networks. Introduction. The main scope . is . to detect the lost . mobiles. For the detection of lost mobile SNIFFER plays a vital . role. The sniffer device has to be designed precisely and size should be reduced for easy mobility for the purpose of detection . MQPs for 2011-2012. Hugh C. . Lauer. http://www.wpi.edu/~lauer/MQP. MQPs for 2010-2011. Fine-Grain Parallelism. 1. Fine-Grain Parallelism. Concurrent execution in multi-core environment at level of . PHONES. By Addagudi Sandeep. Introduction. The main scope . is . to detect the lost . mobiles. For the detection of lost mobile SNIFFER plays a vital . role. The sniffer device has to be designed precisely and size should be reduced for easy mobility for the purpose of detection . Presented by Tam Vu. Gayathri. . Chandrasekaran. *, . Tam Vu*, Alexander . Varshavsky. †. , . Marco . Gruteser. *. , Richard . P. . Martin. *. , . Jie. . Yang. ‡. , . Yingying. . Chen. ‡. *WINLAB. Marco Pedersoli Andrea Vedaldi Jordi Gonzàlez. [Fischler Elschlager 1973]. Object detection. 2. 2. Addressing the computational bottleneck. branch-and-bound . [Blaschko Lampert 08, Lehmann et al. 09]. , and Facial Recognition. Project Team. Privacy Educators Program. Intro Poll. I have a cell phone. . I understand how my phone knows where I am when I use it. . I have signed on to wireless Internet either at my home, another person’s home, or at . Andrew T. Campbell, . Tanzeem. . Choudhury. , . Shaohan. . Hu. , Hong Lu,. Matthew K. . Mukerjee. !, . Mashfiqui. Rabbi, and Rajeev D. S. . Raizada. Dartmouth College, Hanover, NH, USA. Motivation . Sandra L. C. éspedes. Broadband. . Communications. . Research. Group (BBCR). University. of Waterloo. MOBOPTS RG – 81. st. IETF meeting, . Qu. ébec. , . Canada. Outline. Introduction to Vehicular networking.