Abstract
The advances in wireless communications are still very limited when intended to be used on Underwater Communication Systems mainly due to the adverse proprieties of the submarine channel to the acoustic and radio frequency (RF) waves propagation. This work describes the development and characterization of a polyvinylidene difluoride ultrasound transducer to be used as an emitter in underwater wireless communications. The transducer has a beam up to 10 degrees x 70 degrees degrees and a usable frequency band up to 1 MHz. The transducer was designed using Finite Elements Methods and compared with real measurements. Pool trials show a transmitting voltage response (TVR) of approximately 150 dB re mu Pa/V@1 m from 750 kHz to 1 MHz. Sea trials were carried in Ria Formosa, Faro (Portugal) over a 15 m source-receiver communication link. All the signals were successfully detected by cross-correlation using 10 chirp signals between 10 to 900 kHz.

Abstract

Abstract
Pressurised networks are widely used to transport gas through extensive distances. To secure the gas transport at safety levels and also economic viability, the networks are thoroughly monitored. Paramount to network control and analysis is the modelling of the gas dynamics in the pipelines and its consequent simulation. In this work, the pipeline is represented by a quasi-hyperbolic PDE, whose exact solution is not easy to withdraw, and in alternative we opt for an approximation. The construction of the initial function, very important to obtain a good approximation, is done using a separation of variables. Special relevance is given to issues as consistency, stability and convergence in order to evaluate a class of FD methods for the solution of gas network models, in particular the quasi-hyperbolic equation. Horizontal pipelines are considered as well as some particular centred schema for an inclined pipeline.

Abstract
The genetic algorithm is a general purpose optimization metaheuristic for solving complex optimization problems. Because the algorithm usually requires a large number of iterations to evolve a population of solutions to good final solutions, it normally exhibits long execution times, especially if running on low-performance conventional processors. In this work, we present a scalable computing array to parallelize and accelerate the execution of cellular GAs (cGAs). This is a variant of genetic algorithms which can conveniently exploit the coarse-grain parallelism afforded by custom parallel processing. The proposed architecture targets Xilinx FPGAs and was implemented as an auxiliary processor of an embedded soft-core CPU (MicroBlaze). To facilitate the customization for different optimization problems, a high-level synthesis design flow is proposed where the problem-dependent operations are specified in C++ and synthesised to custom hardware, thus demanding of the programmer only minimal knowledge of low-level digital design for FPGAs. To demonstrate the efficiency of the array processor architecture and the effectiveness of the design methodology, the development of a hardware solver for the minimum energy broadcast problem in wireless ad hoc networks is employed as a use case. Implementation results for a Virtex-6 FPGA show significant speedups, especially when comparing to embedded processors used in current FPGA devices.

Abstract
In this work we present a reconfigurable and scalable custom processor array for solving optimization problems using cellular genetic algorithms (cGAs), based on a regular fabric of processing nodes and local memories. Cellular genetic algorithms are a variant of the well-known genetic algorithm that can conveniently exploit the coarse-grain parallelism afforded by this architecture. To ease the design of the proposed computing engine for solving different optimization problems, a high-level synthesis design flow is proposed, where the problem-dependent operations of the algorithm are specified in C++ and synthesized to custom hardware. A spectrum allocation problem was used as a case study and successfully implemented in a Virtex-6 FPGA device, showing relevant figures for the computing acceleration.

Abstract
Underwater sensing and mapping operations using autonomous vehicles are becoming widely used. This article describes an automated system to launch and recover an AUV. It can operate in any host platform and can transport any torpedo-shaped vehicle with 0.2 meters of diameter, length up to 3 meters and weight up to 1000 N. The system ensures a restrained transportation of the vehicle and guarantees that it performs a smooth entrance in the water. It was instrumented for continuous status remote monitoring, using linear and angular motion sensors, as well as enables to remotely take control over the operation. Experimental results carried out within the XPRIZE competition demonstration scope are presented.