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A quasi-current representation for information needs inspired by Two-State Vector Formalism
Recently, a number of quantum theory (QT)-based information retrieval (IR) models have been proposed for modeling session search task that users issue queries continuously in order to describe their evolving information needs (IN). However, the standard formalism of QT cannot provide a complete description for usersâ current IN in a sense that it does not take the âfutureâ information into consideration. Therefore, to seek a more proper and complete representation for usersâ IN, we construct a representation of quasi-current IN inspired by an emerging Two-State Vector Formalism (TSVF). With the enlightenment of the completeness of TSVF, a âtwo-state vectorâ derived from the âfutureâ (the current query) and the âhistoryâ (the previous query) is employed to describe usersâ quasi-current IN in a more complete way. Extensive experiments are conducted on the session tracks of TREC 2013 & 2014, and show that our model outperforms a series of compared IR models
Full Counting Statistics of Interacting Electrons
In order to fully characterize the noise associated with electron transport,
with its severe consequences for solid-state quantum information systems, the
theory of full counting statistics has been developed. It accounts for
correlation effects associated with the statistics and effects of entanglement,
but it remains a non-trivial task to account for interaction effects. In this
article we present two examples: we describe electron transport through quantum
dots with strong charging effects beyond perturbation theory in the tunneling,
and we analyze current fluctuations in a diffusive interacting conductor.Comment: To be published in special issue of "Fortschritte der Physik" (ed. by
Wolfgang Schleich
On packet marking and Markov modeling for IP Traceback: A deep probabilistic and stochastic analysis
From many years, the methods to defend against Denial of Service attacks have been very attractive from different point of views, although network security is a large and very complex topic. Different techniques have been proposed and so-called packet marking and IP tracing procedures have especially demonstrated a good capacity to face different malicious attacks. While host-based DoS attacks are more easily traced and managed, network-based DoS attacks are a more challenging threat. In this paper, we discuss a powerful aspect of the IP traceback method, which allows a router to mark and add information to attack packets on the basis of a fixed probability value. We propose a potential method for modeling the classic probabilistic packet marking algorithm as Markov chains, allowing a closed form to be obtained for evaluating the correct number of received marked packets in order to build a meaningful attack graph and analyze how marking routers must behave to minimize the overall overhead
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