92,193 research outputs found
IMPACT: Investigation of Mobile-user Patterns Across University Campuses using WLAN Trace Analysis
We conduct the most comprehensive study of WLAN traces to date. Measurements
collected from four major university campuses are analyzed with the aim of
developing fundamental understanding of realistic user behavior in wireless
networks. Both individual user and inter-node (group) behaviors are
investigated and two classes of metrics are devised to capture the underlying
structure of such behaviors.
For individual user behavior we observe distinct patterns in which most users
are 'on' for a small fraction of the time, the number of access points visited
is very small and the overall on-line user mobility is quite low. We clearly
identify categories of heavy and light users. In general, users exhibit high
degree of similarity over days and weeks.
For group behavior, we define metrics for encounter patterns and friendship.
Surprisingly, we find that a user, on average, encounters less than 6% of the
network user population within a month, and that encounter and friendship
relations are highly asymmetric. We establish that number of encounters follows
a biPareto distribution, while friendship indexes follow an exponential
distribution. We capture the encounter graph using a small world model, the
characteristics of which reach steady state after only one day.
We hope for our study to have a great impact on realistic modeling of network
usage and mobility patterns in wireless networks.Comment: 16 pages, 31 figure
Revisiting Interval Graphs for Network Science
The vertices of an interval graph represent intervals over a real line where
overlapping intervals denote that their corresponding vertices are adjacent.
This implies that the vertices are measurable by a metric and there exists a
linear structure in the system. The generalization is an embedding of a graph
onto a multi-dimensional Euclidean space and it was used by scientists to study
the multi-relational complexity of ecology. However the research went out of
fashion in the 1980s and was not revisited when Network Science recently
expressed interests with multi-relational networks known as multiplexes. This
paper studies interval graphs from the perspective of Network Science
The Network Picture of Labor Flow
We construct a data-driven model of flows in graphs that captures the
essential elements of the movement of workers between jobs in the companies
(firms) of entire economic systems such as countries. The model is based on the
observation that certain job transitions between firms are often repeated over
time, showing persistent behavior, and suggesting the construction of static
graphs to act as the scaffolding for job mobility. Individuals in the job
market (the workforce) are modelled by a discrete-time random walk on graphs,
where each individual at a node can possess two states: employed or unemployed,
and the rates of becoming unemployed and of finding a new job are node
dependent parameters. We calculate the steady state solution of the model and
compare it to extensive micro-datasets for Mexico and Finland, comprised of
hundreds of thousands of firms and individuals. We find that our model
possesses the correct behavior for the numbers of employed and unemployed
individuals in these countries down to the level of individual firms. Our
framework opens the door to a new approach to the analysis of labor mobility at
high resolution, with the tantalizing potential for the development of full
forecasting methods in the future.Comment: 27 pages, 6 figure
Fast and simple connectivity in graph timelines
In this paper we study the problem of answering connectivity queries about a
\emph{graph timeline}. A graph timeline is a sequence of undirected graphs
on a common set of vertices of size such that each graph
is obtained from the previous one by an addition or a deletion of a single
edge. We present data structures, which preprocess the timeline and can answer
the following queries:
- forall -- does the path exist in each of
?
- exists -- does the path exist in any of
?
- forall2 -- do there exist two edge-disjoint paths connecting
and in each of
We show data structures that can answer forall and forall2 queries in time after preprocessing in time. Here by we denote the
number of edges that remain unchanged in each graph of the timeline. For the
case of exists queries, we show how to extend an existing data structure to
obtain a preprocessing/query trade-off of and show a matching conditional lower bound.Comment: 21 pages, extended abstract to appear in WADS'1
Reevaluating evaluative conditioning: A nonassociative explanation of conditioning effects in the visual evaluative conditioning paradigm
In 2 studies, the authors investigated whether evaluative conditioning (EC) is an associative phenomenon. Experiment 1 compared a standard EC paradigm with nonpaired and no-treatment control conditions. EC effects were obtained only when the conditioned stimulus (CS) and unconditioned stimulus (UCS) were rated as perceptually similar. However, similar EC effects were obtained in both control groups. An earlier failure to obtain EC effects was reanalyzed in Experiment 2. Conditioning-like effects were found when comparing a CS with the most perceptually similar UCSs used in the procedure but not when analyzing a CS rating with respect to the UCS with which it was paired during conditioning. The implications are that EC effects found in many studies are not due to associative learning and that the special characteristics of EC (conditioning without awareness and resistance to extinction) are probably nonassociative artifacts of the EC paradigm
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