2 research outputs found

    A Simple Flood Forecasting Scheme Using Wireless Sensor Networks

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    This paper presents a forecasting model designed using WSNs (Wireless Sensor Networks) to predict flood in rivers using simple and fast calculations to provide real-time results and save the lives of people who may be affected by the flood. Our prediction model uses multiple variable robust linear regression which is easy to understand and simple and cost effective in implementation, is speed efficient, but has low resource utilization and yet provides real time predictions with reliable accuracy, thus having features which are desirable in any real world algorithm. Our prediction model is independent of the number of parameters, i.e. any number of parameters may be added or removed based on the on-site requirements. When the water level rises, we represent it using a polynomial whose nature is used to determine if the water level may exceed the flood line in the near future. We compare our work with a contemporary algorithm to demonstrate our improvements over it. Then we present our simulation results for the predicted water level compared to the actual water level.Comment: 16 pages, 4 figures, published in International Journal Of Ad-Hoc, Sensor And Ubiquitous Computing, February 2012; V. seal et al, 'A Simple Flood Forecasting Scheme Using Wireless Sensor Networks', IJASUC, Feb.201

    Measurement of charged particle spectra in minimum-bias events from proton-proton collisions at root s =13 TeV

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    Pseudorapidity, transverse momentum, and multiplicity distributions are measured in the pseudorapidity range vertical bar eta vertical bar 0.5 GeV in proton-proton collisions at a center-of-mass energy of root s = 13 TeV. Measurements are presented in three different event categories. The most inclusive of the categories corresponds to an inelastic pp data set, while the other two categories are exclusive subsets of the inelastic sample that are either enhanced or depleted in single diffractive dissociation events. The measurements are compared to predictions from Monte Carlo event generators used to describe high-energy hadronic interactions in collider and cosmic-ray physics.Peer reviewe
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