Abstract
In this paper, islanding in a distributed generation (DG) based hybrid system is presented based on extracted features of wavelet transform (WT), S-transform (ST), Hyperbolic S-transform (HST) and TT-Transform. The hybrid system comprises of DG resources like photovoltaic (PV), fuel cell (FC) and wind energy systems (WES) connected to the grid. The negative sequence component of the voltage signal extracted at the point of common coupling (PCC) is considered for detection of islanding of these resources from the grid. The study for different scenarios of DG system is presented in the form of time-frequency analysis. The energy content and standard deviation (STD) of HST contour is also reported in order to validate the graphical results. The results demonstrate the advantages of HS-transform, TT-Transform over wavelet transform and S-transform in detection of islanding events under noise-free as well as noisy scenarios.

Abstract
Kolmogorov Complexity measures the amount of information in a string by the size of the smallest program that generates that string. Antunes, Fortnow, van Melkebeek, and Vinodchandran captured the notion of useful information by computational depth, the difference between the polynomial-time-bounded Kolmogorov complexity and traditional Kolmogorov complexity. We show unconditionally how to probabilistically find satisfying assignments for formulas that have at least one assignment of logarithmic depth. The converse holds under a standard hardness assumption though fails if BPP = FewP = EXP. We also prove that assuming the existence of good pseudorandom generators one cannot increase the depth of a string efficiently.

Abstract
This paper proposes a new integrated architecture for advanced manufacturing management with a Ubiquitous Management System (UMS) and a collection of adequate features to sustain it, where pragmatics on collaboration mechanisms prevails. The Market-of-Resources repository and its advanced brokering process will enable reliable interoperability, services dynamic packages and reconfiguration, as well as the (co-) management of production process, regardless information systems and using real-time collaboration mechanisms. This article contributes for building a logical model for UMS as well as an UML formalization for its supporting architecture

Abstract
Many Unionoida are considered to be extinct, endangered, or of special concern. These bivalves have complex life cycle stages that limit successful culture. In nature, the larvae (glochidia) of these bivalves must successfully parasitize a host (mainly fish) in order to metamorphose into juveniles. The two artificial methods used to obtain juvenile freshwater mussels in laboratory are either by induced attachment to host fish or by in vitro culture of glochidia. This article is focused on the in vitro method that represents a novel and alternative process to fish infestation, offering the ability to obtain larger numbers of juveniles without the need for host fishes and reducing the overall costs of propagation. In vitro culture requires a medium which fulfills the nutritional needs of each glochidia species and avoids microbial contamination. Recently, this methodology has presented excellent results with survival and transformation rates up to 94% using host fish plasma. High efficiencies on growth, and survival rates (84%) of juvenile freshwater bivalve Hyriopsis myersiana (Lea, 1856) up to 120 days were obtained when reared in adequate recirculating aquacultural systems using a very specific diet. More research is still needed to demonstrate successful propagation, mainly concerning the media nutritional composition to increase glochidia transformation and juvenile quality.

Abstract
This paper tackles the problem of localization of an acoustic pinger by a team of cooperative marine robots. A pinger, whose location is unknown, intermittently emits an acoustic ping which is sensed by hydrophones mounted on marine robots. In addition to position, the instant of emission is unknown. A team of robots carrying a total of four hydrophones is therefore (theoretically) required to estimate the position without ambiguity. The precision of the estimate and the uncertainty critically depend on the position of the hydrophones. In order to obtain the best possible estimation, we explore the possibility of using a cooperative method that leads the robots to points where the overall observability is improved.

Abstract
A typical classification problem involves building a model to correctly segregate instances of two or more classes. Such a model exhibits differential prediction with respect to given data subsets when its performance is significantly different over these subsets. Driven by a mammography application, we aim at learning rules that predict breast cancer stage while maximizing differential prediction over age-stratified data. In this work, we present the first multi-relational differential prediction (aka uplift modeling) system, and propose three different approaches to learn differential predictive rules within the Inductive Logic Programming framework. We first test and validate our methods on synthetic data, then apply them on a mammography dataset for breast cancer stage differential prediction rule discovery. We mine a novel rule linking calcification to in situ breast cancer in older women. © 2012 Springer-Verlag.