402 research outputs found
Knowledge Refinement via Rule Selection
In several different applications, including data transformation and entity
resolution, rules are used to capture aspects of knowledge about the
application at hand. Often, a large set of such rules is generated
automatically or semi-automatically, and the challenge is to refine the
encapsulated knowledge by selecting a subset of rules based on the expected
operational behavior of the rules on available data. In this paper, we carry
out a systematic complexity-theoretic investigation of the following rule
selection problem: given a set of rules specified by Horn formulas, and a pair
of an input database and an output database, find a subset of the rules that
minimizes the total error, that is, the number of false positive and false
negative errors arising from the selected rules. We first establish
computational hardness results for the decision problems underlying this
minimization problem, as well as upper and lower bounds for its
approximability. We then investigate a bi-objective optimization version of the
rule selection problem in which both the total error and the size of the
selected rules are taken into account. We show that testing for membership in
the Pareto front of this bi-objective optimization problem is DP-complete.
Finally, we show that a similar DP-completeness result holds for a bi-level
optimization version of the rule selection problem, where one minimizes first
the total error and then the size
On exponential stability for linear discrete-time systems in Banach spaces
In this paper we investigate four concepts of exponential stability for
difference equations in Banach spaces. Characterizations of these concepts are
given. They can be considered as variants for the discrete-time case of the
classical results due to E.A. Barbashin [2] and R. Datko [5]. An illustrative
example clarifies the relations between these concepts.Comment: Computers & Mathematics with Applications, accepted for publicatio
A PC Chase
PC stands for path-conjunctive, the name of a class of queries and dependencies that we define over complex values with dictionaries. This class includes the relational conjunctive queries and embedded dependencies, as well as many interesting examples of complex value and oodb queries and integrity constraints. We show that some important classical results on containment, dependency implication, and chasing extend and generalize to this class
Energy storage systems and power conversion electronics for e-transportation and smart grid
The special issue “Energy Storage Systems and Power Conversion Electronics for E-Transportation and Smart Grid” on MDPI Energies presents 20 accepted papers, with authors from North and South America, Asia, Europe and Africa, related to the emerging trends in energy storage and power conversion electronic circuits and systems, with a specific focus on transportation electrification and on the evolution of the electric grid to a smart grid. An extensive exploitation of renewable energy sources is foreseen for smart grid as well as a close integration with the energy storage and recharging systems of the electrified transportation era. Innovations at both algorithmic and hardware (i.e., power converters, electric drives, electronic control units (ECU), energy storage modules and charging stations) levels are proposed
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