Abstract
This chapter presents the preliminary results of an IT organizational project management maturity research called OPM3® Portugal Project, which is currently underway. It was designed by Portuguese research and development organization Ambithus, based on PMI's (Project Management Institute) OPM3® (Organizational Project Management Maturity Model) standard. A descriptive analysis of IT organizations is made, the case studies selection criteria are explained, and a relevant literature revision of clustering models is made. Preliminary results from the IT organizations are presented and organized by Project Management and Portfolio Management processes, and Organizational Enablers. After the results analysis, it presents a list of processes and procedures that serves as the guidelines for what IT organizations need to improve to obtain a better level of maturity in Project Management. The overall results show that the IT Portuguese industry is strong on its processes and has a good level of maturity in project management.

Abstract
A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. This sensor can be used in mobile robots localization task. In this paper, a low cost laser scanner sensor is modelled so that it can be implemented in a simulation environment. The simulation reflects the laser model properties such as target colour dependences, noise, limits and time constraints. A correction of the laser scanner nonlinearities is proposed. The noise spectrum is also addressed.

Abstract
In this article, the problem of deriving a physical model of a mechanical structure from an arbitrary state-space realization is addressed. As an alternative to finite element formulations, the physical parameters of a model may be directly obtained from identified parametric models. However, these methods are limited by the number of available sensors and often lead to poor predictive models. Additionally, the most efficient identification algorithms retrieve models where the physical parameters are hidden. This last difficulty is known in the literature as the inverse vibration problem. In this work, an approach to the inverse vibration problem is proposed. It is based on a similarity transformation and the requirement that every degree of freedom should contain a sensor and an actuator (full instrumented system) is relaxed to a sensor or an actuator per degree of freedom, with at least one co-located pair (partially instrumented system). The physical parameters are extracted from a state-space realization of the former system. It is shown that this system has a symmetric transfer function and this symmetry is exploited to derive a state-space realization from an identified model of the partially instrumented system. A subspace continuous-time system identification algorithm previously proposed by the authors in [1] is used to estimate this model from the IO data.

Abstract
Diplomacy is a multi-player strategic and zero-sum board game, free of random factors, and allowing negotiation among players. The majority of existing artificial players (bots) for Diplomacy do not exploit the strategic opportunities enabled by negotiation, instead trying to decide their moves through solution search and the use of complex heuristics. We present DipBlue, an approach to the development of an artificial player that uses negotiation in order to gain advantage over its opponents, through the use of peace treaties, formation of alliances and suggestion of actions to allies. A simple trust assessment approach is used as a means to detect and react to potential betrayals by allied players. DipBlue was built to work with DipGame, a multi-agent systems testbed for Diplomacy, and has been tested with other players of the same platform and variations of itself. Experimental results show that the use of negotiation increases the performance of bots involved in alliances, when full trust is assumed. In the presence of betrayals, being able to perform trust reasoning is an effective approach to reduce their impact. Copyright

Abstract
The IEC 61499 standard provides an executable model for distributed control systems in terms of interacting function blocks. However, the current IEC 61499 standard lacks appropriate timing semantics for the specification of timing requirements, reasoning on timing properties at the model level, and for the timing verification of a specific deployment. In this paper we address this fundamental shortcoming by proposing Real-Time-4-FUN, a real-time semantics for IEC 61499. The key property is the preservation of non-determinism, allowing us to reason on (and verify) timing properties at the model level without assuming any specific scheduling policy or stipulating specific order of execution for the deployment. This provides for a clear separation of concerns, where the designer can focus on properties of the application prior to, and separately from, deployment verification. The proposed timing semantics is backwards compatible to the current standard, thus allow for reuse of existing designs. The transitional property allows timing requirements to propagate to downstream sub-systems, and can be utilized for scheduling both at device and network level. Based on a translation to RTFM-tasks and resources, IEC 61499 models can be analyzed, compiled and executed. As a proof of concept the timing semantics has been experimentally implemented in the RTFM-core language and the accompanying (thread based) RTFM-RT run-time system.

Abstract
New generations of turbines have lower repair and maintenance costs than the previous generation. This is justified by the development of new components and materials. As the power of newer turbines is usually substantially larger, it is possible to get an economy of scale and lower maintenance costs per kW of rated power. This is simply because it is not needed to service a large turbine more often than a small one. New methods of earlier detection of faults are needed. The use of all information from SCADA (Supervisory Control and Data Acquisition) system can be useful, but it is necessary to develop tools to deal with bigger amount of information. Neural networks can help and turn possible new maintenance and operation schemes.