4,875 research outputs found
The Ascending Double-Cone: A Closer Look at a Familiar Demonstration
The double-cone ascending an inclined V-rail is a common exhibit used for
demonstrating concepts related to center-of-mass in introductory physics
courses. While the conceptual explanation is well-known--the widening of the
ramp allows the center of mass of the cone to drop, overbalancing the increase
in altitude due to the inclination of the ramp--there remains rich physical
content waiting to be extracted through deeper exploration. Such an
investigations seems to be absent from the literature. This article seeks to
remedy the omission.Comment: LaTeX, 16 pages, 18 eps figure
The Internet's unexploited path diversity
The connectivity of the Internet at the Autonomous System level is influenced
by the network operator policies implemented. These in turn impose a direction
to the announcement of address advertisements and, consequently, to the paths
that can be used to reach back such destinations. We propose to use directed
graphs to properly represent how destinations propagate through the Internet
and the number of arc-disjoint paths to quantify this network's path diversity.
Moreover, in order to understand the effects that policies have on the
connectivity of the Internet, numerical analyses of the resulting directed
graphs were conducted. Results demonstrate that, even after policies have been
applied, there is still path diversity which the Border Gateway Protocol cannot
currently exploit.Comment: Submitted to IEEE Communications Letter
PresenceSense: Zero-training Algorithm for Individual Presence Detection based on Power Monitoring
Non-intrusive presence detection of individuals in commercial buildings is
much easier to implement than intrusive methods such as passive infrared,
acoustic sensors, and camera. Individual power consumption, while providing
useful feedback and motivation for energy saving, can be used as a valuable
source for presence detection. We conduct pilot experiments in an office
setting to collect individual presence data by ultrasonic sensors, acceleration
sensors, and WiFi access points, in addition to the individual power monitoring
data. PresenceSense (PS), a semi-supervised learning algorithm based on power
measurement that trains itself with only unlabeled data, is proposed, analyzed
and evaluated in the study. Without any labeling efforts, which are usually
tedious and time consuming, PresenceSense outperforms popular models whose
parameters are optimized over a large training set. The results are interpreted
and potential applications of PresenceSense on other data sources are
discussed. The significance of this study attaches to space security, occupancy
behavior modeling, and energy saving of plug loads.Comment: BuildSys 201
Three dimensional four-fermion models - A Monte Carlo study
We present results from numerical simulations of three different 3d
four-fermion models that exhibit Z_2, U(1), and SU(2) x SU(2) chiral
symmetries, respectively. We performed the simulations by using the hybrid
Monte Carlo algorithm. We employed finite size scaling methods on lattices
ranging from 8^3 to 40^3 to study the properties of the second order chiral
phase transition in each model. The corresponding critical coupling defines an
ultraviolet fixed point of the renormalization group. In our high precision
simulations, we detected next-to-leading order corrections for various critical
exponents and we found them to be in good agreement with existing analytical
large-N_f calculations.Comment: 15 pages, 7 figures, and 2 table
Social Game for Building Energy Efficiency: Utility Learning, Simulation, and Analysis
We describe a social game that we designed for encouraging energy efficient
behavior amongst building occupants with the aim of reducing overall energy
consumption in the building. Occupants vote for their desired lighting level
and win points which are used in a lottery based on how far their vote is from
the maximum setting. We assume that the occupants are utility maximizers and
that their utility functions capture the tradeoff between winning points and
their comfort level. We model the occupants as non-cooperative agents in a
continuous game and we characterize their play using the Nash equilibrium
concept. Using occupant voting data, we parameterize their utility functions
and use a convex optimization problem to estimate the parameters. We simulate
the game defined by the estimated utility functions and show that the estimated
model for occupant behavior is a good predictor of their actual behavior. In
addition, we show that due to the social game, there is a significant reduction
in energy consumption
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