Principle of Locality:
Programs access a small proportion of their address space at any time.
Items accessed recently are likely to be accessed again soon,
e.g., instructions in a loop, induction variables.
Items near those accessed recently are likely to be accessed soon,
E.g., sequential instruction access, array data.
Satellite altimetry was developed in the 1960s soon after
the flight of artificial satellites became a reality. From the
vantage point in space, a radar altimeter is able to measure
the shape of the sea surface globally and frequently. Such
measurements have a wide range of applications to oceanography,
geodesy, and geophysics. The results are often revolutionary.
For example, in oceanography; it takes a ship weeks
or months to cross the ocean making measurements while
the ocean is constantly changing its circulation, temperature,
Most of the VOCs probably derived from indoor sources. However, the wall cavity was
an apparent source of acetaldehyde, toluene and xylenes and the belly space was a source of
2-butanone, lower volatility aldehydes and aromatic hydrocarbons. Indoor minus outdoor VOC
concentrations varied with time. Adjusted formaldehyde concentrations exhibited the most
temporal variability with concentrations ranging from 25 µg m-3
to 128 µg m-3
and the lowest
concentrations occurring in winter months when indoor RH was low.
Our main contribution is to study a variable, international soccer results, that has particu-
larly attractive properties as a measure of mood. While extensive psychological evidence, which
we review below, shows that sports in general have a signiﬁcant eﬀect on mood, TV viewing
ﬁgures, media coverage, and merchandise sales suggest that soccer in particular is of “national
interest” in many of the countries we study.
1 It is hard to imagine other regular events that
produce such substantial and correlated mood swings in a large proportion of a country’s pop-
Self-sustained oscillations are perhaps the most studied objects in science.
The accomplishment of such a task reliably and accurately requires the
presence of specific control mechanisms to face the presence of variable
and largely unpredictable environmental stimuli and noise.
U.S. Savings Bonds are issued by the U.S. Treasury Department. They are nonmarketable
securities. This means you may not sell savings bonds to or buy them from
anyone except an issuing and paying agent authorized by the Treasury Department.
Savings bonds are registered securities, meaning that they are owned exclusively by the
person or persons named on them.
I Bonds and Series EE Savings Bonds are accrual securities. They earn, that is, accrue
interest monthly at a variable rate and the interest is compounded semiannually.
The objective of this study was to evaluate the effect of agricultural pollution on periphyton in streams
and rivers of southern Que´bec. influence the strength of the temporal variation. Some data did not respect normality after be- ing transformed. However, as noted by Scheffe´ (1959) and Montgomery (2001), ANOVAs are relatively in- sensitive to moderate deviations from normality and
Land use analyses
Mean values for the physico-chemical variables at each site are shown in Table 2 and land use information
is shown in Table 3.
When earth material properties are constant in any of the cartesian variables then
it is useful to Fourier transform (FT) that variable.
In seismology, the earth does not change with time (the ocean does!) so for the earth, we
can generally gain by Fourier transforming the time axis thereby converting time-dependent
differential equations (hard) to algebraic equations (easier) in frequency (temporal frequency).
In seismology, the earth generally changes rather strongly with depth, so we cannot
usefully Fourier transform the depth axis and we are stuck with differential equations in
The main goal herein is to describe and analyze, in a unifying manner, the spatial and temporal IV-SSF approaches recently proposed for array signal processing in colored noise ﬁelds. (The acronym IV-SSF stands for “Instrumental Variable - Signal Subspace Fitting”). Despite the
In this paper, we focus our attention on providing a
formal framework for expressing data mining tasks in-
volving time granularities, and on proposing efficient algo-
rithms for performing such tasks. To this end, we introduce
the notion of an event structure. An event structure is essen-
tially a set of temporal constraints on a set of variables
representing events. Each constraint bounds the distance
between a pair of events in terms of a time granularity.
Furthermore, the particular bus in which the commuter
travelled during this week was not air conditioned so
ventilation was provided by open windows, allowing air to
flow freely in and out of the bus. This is an interesting result
as it demonstrates that due to the high temporal and spatial
variability in CO concentrations, other variables (such as
ventilation rate and proximity to emissions) may be more
important in determining exposure than choice of transport
To effectively perform data mining, however, we cannot
naively consider all candidate instantiations, since the
number of such instantiations is exponential in the number
of variables. We provide algorithms and heuristics that ex-
ploit the granularity system and the given constraints to
reduce the hypothesis space for the pattern matching task.
The global approach offers an effective procedure to dis-
cover patterns of events that occur frequently in a sequence
satisfying specific temporal relationships.
Clinical Manifestations The clinical syndrome of infective endocarditis is highly variable and spans a continuum between acute and subacute presentations. Native valve endocarditis (whether acquired in the community or in association with health care), prosthetic valve endocarditis, and endocarditis due to injection drug use share clinical and laboratory manifestations (Table 118-2).
The causative microorganism is primarily responsible for the temporal course of endocarditis. β-Hemolytic streptococci, S. aureus, and pneumococci typically result in an acute course, although S.
Our framework assumes that funds' sensitivities to passive assets are constant over time.
One way of relaxing this assumption is to model these coe±cients as linear functions of
state variables, as for example in Ferson and Schadt (1996) and Shanken (1990). In such
a modi¯cation, passive asset returns scaled by the state variables can be viewed as returns
on additional passive assets (dynamic passive strategies), and the approach developed here
could be extended to such a setting. Another approach to dealing with temporal variation
in parameters could employ data on fund holdings.
The remainder of the paper is organized as follows. Section 2 provides an overview of the
history of the Eritrea-Ethiopia conflict and sketches the spatial and temporal event data for the
most recent war. Section 3 describes the survey data used in the analysis and explains the key
variables. Section 4 describes the empirical identification strategy and Section 5 presents the
main results as well as robustness tests. Section 6 concludes.