21,704 research outputs found
Sensing and visualizing spatial relations of mobile devices
Location information can be used to enhance interaction with mobile devices. While many location systems require instrumentation of the environment, we present a system that allows devices to measure their spatial relations in a true peer-to-peer fashion. The system is based on custom sensor hardware implemented as USB dongle, and computes spatial relations in real-time. In extension of this system we propose a set of spatialized widgets for incorporation of spatial relations in the user interface. The use of these widgets is illustrated in a number of applications, showing how spatial relations can be employed to support and streamline interaction with mobile devices
Peak to average power ratio based spatial spectrum sensing for cognitive radio systems
The recent convergence of wireless standards for incorporation of spatial dimension in wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. This added dimension is principally exploited for stream multiplexing, user multiplexing and spatial diversity. Considering such a wireless environment for primary users, we propose an algorithm for spectrum sensing by secondary users which are also equipped with multiple antennas. The proposed spatial spectrum sensing algorithm is based on the PAPR of the spatially received signals. Simulation results show the improved performance once the information regarding spatial diversity of the primary users is incorporated in the proposed algorithm. Moreover, through simulations a better performance is achieved by using different diversity schemes and different parameters like sensing time and scanning interval
Anomalous versus slowed-down Brownian diffusion in the ligand-binding equilibrium
Measurements of protein motion in living cells and membranes consistently
report transient anomalous diffusion (subdiffusion) which converges back to a
Brownian motion with reduced diffusion coefficient at long times, after the
anomalous diffusion regime. Therefore, slowed-down Brownian motion could be
considered the macroscopic limit of transient anomalous diffusion. On the other
hand, membranes are also heterogeneous media in which Brownian motion may be
locally slowed-down due to variations in lipid composition. Here, we
investigate whether both situations lead to a similar behavior for the
reversible ligand-binding reaction in 2d. We compare the (long-time)
equilibrium properties obtained with transient anomalous diffusion due to
obstacle hindrance or power-law distributed residence times (continuous-time
random walks) to those obtained with space-dependent slowed-down Brownian
motion. Using theoretical arguments and Monte-Carlo simulations, we show that
those three scenarios have distinctive effects on the apparent affinity of the
reaction. While continuous-time random walks decrease the apparent affinity of
the reaction, locally slowed-down Brownian motion and local hinderance by
obstacles both improve it. However, only in the case of slowed-down Brownian
motion, the affinity is maximal when the slowdown is restricted to a subregion
of the available space. Hence, even at long times (equilibrium), these
processes are different and exhibit irreconcilable behaviors when the area
fraction of reduced mobility changes.Comment: Biophysical Journal (2013
A Simple Flood Forecasting Scheme Using Wireless Sensor Networks
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
Creation and characterization of vector vortex modes for classical and quantum communication
Vector vortex beams are structured states of light that are non-separable in
their polarisation and spatial mode, they are eigenmodes of free-space and many
fibre systems, and have the capacity to be used as a modal basis for both
classical and quantum communication. Here we outline recent progress in our
understanding of these modes, from their creation to their characterization and
detection. We then use these tools to study the propagation behaviour of such
modes in free-space and optical fibre and show that modal cross-talk results in
a decay of vector states into separable scalar modes, with a concomitant loss
of information. We present a comparison between probabilistic and deterministic
detection schemes showing that the former, while ubiquitous, negates the very
benefit of increased dimensionality in quantum communication while reducing
signal in classical communication links. This work provides a useful
introduction to the field as well as presenting new findings and perspectives
to advance it further
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