Abstract
Wireless sensor networks may be deployed to retrieve visual information from the monitored field, enriching monitoring and control applications. Whenever a set of camera-enabled sensor nodes are deployed for time-critical monitoring, visual information as still images and video streams may need to reach the sink as soon as possible, requiring a differentiated treating of the network when compared with non-critical visual data. In such way, considering that source nodes may have different sensing relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view, we propose a delay-aware multihop routing mechanism where higher relevant visual data packets are routed through paths with lower end-to-end delay. As sensor nodes are expected to be energy-constrained, transmitting only high-relevant packets through shorter/faster paths may prolong their lifetime and assure longer time-critical delivering, with low impact to the overall monitoring quality.

Abstract
The explicit incorporation of uncertainty in transmission network design can help to improve the balance between different and important concerns such as network utilization, demand satisfaction, or dynamic sourcing from lower-cost generation options. The explicit study of mean-risk trade-offs in network design can also better support planners in risk-related decisions. With these motivations, we present in this paper a mean-risk mixed integer linear programming model for transmission network expansion planning. The model has the potential to be used in practical applications, but in the scope of the paper is used to search for network design insights, with a study of loss-averse design of three fundamental network building blocks-an independent design, a radial design, and a meshed design. The study illustrates how different network designs feature different trade-offs between mean cost minimization and risk mitigation, focusing on the impact of network structure, loss aversion, variability, and demand correlation.

Abstract
Proliferation of the Internet is enabling the use of sensors and actuators to capture data and control devices remotely in a multitude of domains. Still, there is a general lack of best practices while designing such large scale real-time systems. This paper describes a generic architecture used on the implementation of a framework for deploying such systems in the cloud, enabling run-time evolution of the system with new sensors, actuators or services possibly developed by third-parties being integrated dynamically. Such architecture orchestrates the flow of information in the ecosystem and scales transparently to external components when needed, requiring no change in them. Adoption in the Portuguese nation-wide AAL project AAL4ALL is then described. Copyright © 2013 by the Association for Computing Machinery, Inc. (ACM).

Abstract
In this paper we present a user-centered interface for a scheduling system. The purpose of this interface is to provide graphical and interactive ways of defining a scheduling problem. To create such user interface an evaluation-centered user interaction development method was adopted: the star life cycle. The created prototype comprises the Task Module and the Scheduling Problem Module. The first one allows users to define a sequence of operations, i.e., a task. The second one enables a scheduling problem definition, which consists in a set of tasks. Both modules are equipped with a set of real time validations to assure the correct definition of the necessary data input for the scheduling module of the system. The usability evaluation allowed us to measure the ease of interaction and observe the different forms of interaction provided by each participant, namely the reactions to the real time validation mechanism.

Abstract
Cooperation with humans is a requirement for the next generation of robots so it is necessary to model how robots can sense, know, share and acquire knowledge from human interaction. Instead of traditional SLAM (Simultaneous Localization and Mapping) methods, which do not interpret sensor information other than at the geometric level, these capabilities require an environment map representation similar to the human representation. Topological maps are one option to translate these geometric maps into a more abstract representation of the the world and to make the robot knowledge closer to the human perception. In this paper is presented a novel approach to translate 3D grid map into a topological map. This approach was optimized to obtain similar results to those obtained when the task is performed by a human. Also, a novel feature of this approach is the augmentation of topological map with features such as walls and doors.

Abstract
National governments sometimes introduce policies that modify energy markets to achieve other social and political goals. These policies, created with the best of intentions, often have unintended consequences. Here we present a case study of one such policy, the Royal Decree in Spain that mandates the use of the Spanish-Indigenous Coal (IC). © 2013 IEEE.