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» Learning from sensor network data
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CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 7 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
HPDC
2010
IEEE
15 years 3 months ago
Lessons learned from moving earth system grid data sets over a 20 Gbps wide-area network
In preparation for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, the climate community will run the Coupled Model Intercomparison Project phase 5 (...
Rajkumar Kettimuthu, Alex Sim, Dan Gunter, Bill Al...
AINA
2006
IEEE
15 years 8 months ago
Simulation Architecture for Data Processing Algorithms in Wireless Sensor Networks
Abstract— Wireless sensor networks, by providing an unprecedented way of interacting with the physical environment, have become a hot topic for research over the last few years. ...
Yann-Aël Le Borgne, Mehdi Moussaid, Gianluca ...
GI
2004
Springer
15 years 7 months ago
Who's onCampus: A Campus-Wide Location System
: Wireless Local Area Networks (WLAN) do not only provide a means for wireless communication, they can also supply terminal positions to location-aware services and applications. T...
Michael Wallbaum, Andreas Dieckmann, Peter Russell...
TSP
2008
103views more  TSP 2008»
15 years 1 months ago
Distributed Adaptive Quantization for Wireless Sensor Networks: From Delta Modulation to Maximum Likelihood
Abstract-- We consider distributed parameter estimation using quantized observations in wireless sensor networks where due to bandwidth constraint, each sensor quantizes its local ...
Jun Fang, Hongbin Li