Abstract
Due to the complexity of underwater transients and background interference, model based approaches to transient detection/classification are often not practical. This has motivated an interest for data-driven, model-free methods. One such method was presented in [2] and modified in [1], where it was applied to the detection of underwater transients. In this article, we will extend that approach, to allow its use in the more demanding environment of a brown water environment, where background noise is constituted by a multitude of different interferences, non-white, and highly non-stationary. Also, the assumption of linear separability amongst the transients and the background noise in the time-frequency or related domains will be discarded, leading to the use of an additional classifier stage. A technique to minimize the number of prototypes on this classifier will be presented. The developed methods are used to detect and classify real underwater transients, recorded off the Portuguese coast. Estimation of the overall error rate of the method is obtained using cross-validation with the available data set, showing that these methods can effectively be used in real environment situations.

Abstract
In this paper, we present a low-cost versatile device developed to support the navigation of autonomous underwater vehicles. Unlike the usual transponders extensively used for LBL acoustic navigation of a single vehicle, this device allows the navigation of multiple vehicles and the remote tracking of their positions, without any extra acoustic signals being transmitted. The navigation beacon has a radio buoy connected to an underwater reconfigurable multi-frequency transponder. A remote tracking station receives data from the buoy and monitors the position of the vehicles in real time. We describe the mechanical, electronic and software modules involved, as well as the tracking algorithm, and we also present experimental data from an operational mission.

Abstract
The wastewater plumes show to be very difficult to observed in detail. The several studies already conducted exhibit very complex and patchy structures both in vertical and horizontal sections. It is not clear if this plume patchiness is due to physical processes or measurement limitations. Rapid tow-yo sampling is expected to reduce the time variability during and between transects. The AUVs may be a useful instrument to map and detect wastewater plumes. This paper presents several prediction studies using time series files of actual in-situ measurements integrated in a near field model. The model predictions of the plume characteristics at the end of near field support the definition of the best sampling strategy for an AUV monitoring mission in a Portuguese west coast outfall.

Abstract
An automated maneuver control framework for a Remotely Operate Vehicle (ROV) is presented. This framework entails a three-layered control architecture, a principled approach to design and implementation within the architecture, and hybrid systems design techniques. The control architecture is structured according to the principle of composition of vehicle motions from a minimal set of elemental maneuvers that are designed and verified independently. The principled approach is based on distributed hybrid systems techniques, and spans integrated design, simulation and implementation as the same model is used throughout. Hybrid systems control techniques are used to synthesize the elemental maneuvers and to design protocols, which coordinate the execution of elemental maneuvers within a complex maneuver. The architecture is fault-tolerant by design since it uses verified maneuvers. This work is part of the Inspection of Underwater Structures (IES) project whose main objective is the implementation of a ROV-based system for the Inspection of underwater structures.

Abstract
Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts. © Springer-Verlag Berlin Heidelberg 2001.

Abstract
The concepts of Instantaneous Frequency (IFt) and Instantaneous Bandwidth (IBt) have traditionally been considered as independent spectral features. Recent work has suggested, however, that the spectral dynamics of the signal (and, hence, its IFt) may have an impact on IBt and on the achievable spectral resolution. In this article, we consider model based AR spectral estimators. Simulations are done with several distinct time-frequency tools, to confirm the theoretical predictions.