Abstract
In recent years, our biologic understanding was increased with the comprehension of the multitude of regulatory mechanisms that are fundamental in both processes of inheritance and of development, and some researchers advocate the need to explore computationally this new understanding. One of the outcomes was the Artificial Gene Regulatory (ARN) model, first proposed by Wolfgang Banzhaf. In this paper, we use this model as representation for a computational device and introduce new variation operators, showing experimentally that it is effective in solving a set of benchmark problems.

Abstract
This paper presents a multistage transmission expansion planning (TEP) which alleviates the level of transmission congestion during the planning horizon. Due to the combinatorial nature of the proposed TEP model, a Benders decomposition approach intertwined with a manipulated disjunctive model is applied to decompose the original TEP problem into a master problem and two sub-problems standing for system security and optimal operation. The security sub-problem applying the N-1 contingency criterion to assess the transmission system security. Besides, the optimal operation sub-problem makes it possible for the proposed TEP model to fulfill the optimal operation as well as to calculate the difference between system lacational marginal prices (LMPs) for all buses. Also, this model appends a specific term into the TEP objective function as the congestion level (CL) reflecting the degree of market competitiveness. Therefore, the proposed TEP model minimizes the total costs comprising the investment cost of candidate transmission lines as well as the level of transmission congestion. The proposed approach is applied to the northeastern area of the Iranian power grid. © 2011 IEEE.

Abstract

Abstract
Wildfires can importantly affect the ecology and economy of large regions of the world. Effective prevention techniques are fundamental to mitigate their consequences. The design of such preemptive methods requires a deep understanding of the factors that increase the risk of fire, particularly when we can intervene on these factors. This is the case for the maintenance of ecological balances in the landscape that minimize the occurrence of wildfires. We use an inductive logic programming approach over detailed spatial datasets: one describing the landscape mosaic and characterizing it in terms of its use; and another describing polygonal areas where wildfires took place over several years. Our inductive process operates over a logic term representation of vectorial geographic data and uses spatial predicates to explore the search space, leveraging the framework of Spatial-Yap, its multi-dimensional indexing and tabling extensions. We show that the coupling of a logic-based spatial database with an inductive logic programming engine provides an elegant and powerful approach to spatial data mining.

Abstract
In this paper, we demonstrate the interrogation of fiber optic intensity sensors by using the combination of the frequency-modulated continuous wave concept with the spectral selective reflectivity of fiber Bragg gratings. Thus, we multiplex these kinds of sensors with this technique having simultaneously a referenced system. The basis of this dual functionality is described and results are presented for the case of interrogation of two multiplexed intensity sensors. Their evaluation permits to establish the conditions to address a sensor network of this type. Also, it is proposed a strategy to implement this sensing approach without the requirement of using optical fiber delay lines in the sensor heads.

Abstract
DAPHNE (Developing Aircraft PHotonic NEtworks) is a 3-year European FP7 project (started September 2009). The aim of DAPHNE is to exploit terrestrial optical networking technology (with associated performance advantages) in future aircraft and systems. The consortium comprises fifteen partners (from seven nations) ranging from major air framers (both fixed and rotary wing) through component and equipment manufacturers and leading European universities. The project is coordinated by Airbus. © 2011 IEEE.