Abstract
The convergence of the voice and data worlds is introducing exciting opportunities to companies. As a consequence, Voice over IP (VoIP) technology is attracting increasing attention and interest in the industry. Flexibility and cost efficiency are the key factors luring enterprises to transition to VoIP. However, voice services also introduce a new level of vulnerability to the network. This chapter categorizes and analyzes the most common security threats of a VoIP solution in a corporate environment. Besides that, the authors discuss the most relevant security policies that could have been adopted to mitigate the security vulnerabilities introduced by VoIP. These new policies and practices can have a positive impact on the security of the whole network, not just voice communications.

Abstract
The actual electric grid was developed to offer electricity to the clients from centralized generation, so with large-scale distributed renewable generation there is an urgent need for a more flexible, reliable and smarter grid. The wireless technologies are becoming an important asset in the smart grid, particularly the ZigBee devices. These smart devices are gaining increased acceptance, not only for building and home automation, but also for energy management, efficiency optimization and metering services, being able to operate for long periods of time without maintenance needs. In this context, this paper provides new comprehensive field tests using open source tools with ZigBee technologies for monitoring photovoltaic and wind energy systems, and also for building and home energy management. Our experimental results demonstrate the proficiency of ZigBee devices applied in distributed renewable generation and smart metering systems.

Abstract
Adverse drug events are a leading cause of danger and cost in health care. We could reduce both the danger and the cost if we had accurate models to predict, at prescription time for each drug, which patients are most at risk for known adverse reactions to that drug, such as myocardial infarction (MI, or "heart attack") if given a Cox2 inhibitor, angioedema if given an ACE inhibitor, or bleeding if given an anticoagulant such as Warfarin. We address this task for the specific case of Cox2 inhibitors, a type of non-steroidal anti-inflammatory drug (NSAID) or pain reliever that is easier on the gastrointestinal system than most NSAIDS. Because of the MI adverse drug reaction, some but not all very effective Cox2 inhibitors were removed from the market. Specifically, we use machine learning to predict which patients on a Cox2 inhibitor would suffer an MI. An important issue for machine learning is that we do not know which of these patients might have suffered an MI even without the drug. To begin to make some headway on this important problem, we compare our predictive model for MI for patients on Cox2 inhibitors against a more general model for predicting MI among a broader population not on Cox2 inhibitors. Copyright

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Abstract
The resources systems selection is still a difficult matter to solve in the Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. Globally, we can say that the resources selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project). We intend in this paper to show: a formulation of a kind of resources selection problem; the performance (computation processing time) of an exact solution algorithm proposed to solve it, according to the number of processing tasks and the number of pre-selected resources per processing tasks; and, as a consequence of the domain of applicability of that algorithm, to propose the formulation an approximate solution algorithm, namely genetic algorithm (GA) based. The final goal it is to improve the knowledge about the algorithms domain for the broker tool, in order to select the most adequate algorithm to perform the resources system selection.