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97,461
Robust real-time periodic motion detection, analysis, and applications
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2000
"... We describe new techniques to detect and analyze periodic motion as seen from both a static and a moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic and we apply Time-Fr ..."
Abstract
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Cited by 301 (14 self)
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We describe new techniques to detect and analyze periodic motion as seen from both a static and a moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic and we apply Time
Time Periods
"... Biologists have a long tradition of applying the theories of ecology, animal behavior, and ..."
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Biologists have a long tradition of applying the theories of ecology, animal behavior, and
Real-Time Dynamic Voltage Scaling for Low-Power Embedded Operating Systems
, 2001
"... In recent years, there has been a rapid and wide spread of nontraditional computing platforms, especially mobile and portable computing devices. As applications become increasingly sophisticated and processing power increases, the most serious limitation on these devices is the available battery lif ..."
Abstract
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Cited by 501 (4 self)
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importance, is largely overlooked/under-developed. To provide real-time guarantees, DVS must consider deadlines and periodicity of real-time tasks, requiring integration with the real-time scheduler. In this paper, we present a class of novel algorithms called real-time DVS (RT-DVS) that modify the OS
Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations
, 2005
"... How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include hea ..."
Abstract
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Cited by 541 (48 self)
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heavy tails for in- and out-degree distributions, communities, small-world phenomena, and others. However, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time. Here we study a wide range of real graphs
A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
, 1989
"... The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a precis ..."
Abstract
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Cited by 534 (4 self)
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the retention of information over time periods having either fixed or indefinite length. 1 Introduction A major problem in connectionist theory is to develop learning algorithms that can tap the full computational power of neural networks. Much progress has been made with feedforward networks, and attention
The flooding time synchronization protocol
, 2004
"... Wireless sensor network applications, similarly to other distributed systems, often require a scalable time synchronization service enabling data consistency and coordination. This paper introduces the robust Flooding Time Synchronization Protocol (FTSP), especially tailored for applications requir ..."
Abstract
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Cited by 469 (16 self)
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periodic radio broadcast of synchronization messages, and implicit dynamic topology update. The unique high precision performance is reached by utilizing MAC-layer time-stamping, comprehensive error compensation, including linear regression, which reduces time skew and keeps network traffic overhead low
Representing twentieth century space-time climate variability, part 1: development of a 1961-90 mean monthly terrestrial climatology
- Journal of Climate
, 1999
"... The construction of a 0.58 lat 3 0.58 long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor pressur ..."
Abstract
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Cited by 581 (13 self)
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The construction of a 0.58 lat 3 0.58 long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor
Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests, With an Application to the PPP Hypothesis; New Results. Working paper
, 1997
"... We examine properties of residual-based tests for the null of no cointegration for dynamic panels in which both the short-run dynamics and the long-run slope coefficients are permitted to be heterogeneous across individual members of the panel+ The tests also allow for individual heterogeneous fixed ..."
Abstract
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Cited by 529 (13 self)
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and power performance, and we illustrate their use in testing purchasing power parity for the post–Bretton Woods period+ 1.
End-to-End Routing Behavior in the Internet
, 1996
"... The large-scale behavior of routing in the Internet has gone virtually without any formal study, the exception being Chinoy's analysis of the dynamics of Internet routing information [Ch93]. We report on an analysis of 40,000 end-to-end route measurements conducted using repeated “traceroutes” ..."
Abstract
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Cited by 655 (13 self)
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, ” the likelihood that a route remains unchanged over a long period of time. We find that Internet paths are heavily dominated by a single prevalent route, but that the time periods over which routes persist show wide variation, ranging from seconds up to days. About 2/3's of the Internet paths had routes
Mining Sequential Patterns: Generalizations and Performance Improvements
- RESEARCH REPORT RJ 9994, IBM ALMADEN RESEARCH
, 1995
"... The problem of mining sequential patterns was recently introduced in [3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transaction-time, and each transaction is a set of items. The problem is to discover all sequential patterns with a user-specified ..."
Abstract
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Cited by 759 (5 self)
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generalize the problem as follows. First, we add time constraints that specify a minimum and/or maximum time period between adjacent elements in a pattern. Second, we relax the restriction that the items in an element of a sequential pattern must come from the same transaction, instead allowing the items
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