Abstract

Abstract
Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant's manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97+/-0.01, 2.24+/-0.85 pixels and 11.12+/-6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

Abstract
The Web is rapidly becoming the prime medium for human socialization. The resources that enable that process (social web sites, blogs, media objects, etc.) present growing complexity and, collectively, weave an ever more intricate web of relationships. Current technology for declaring those relationships is predominantly implicit, ambiguous and semantically poor. As a consequence, their automatic assessment is complex and error prone, preventing the satisfaction of users' needs such as effective semantic searches. To address these limitations, whilst enabling the explicit declaration of semantically unambiguous relationships between digital resources, a solution employing structured semantic descriptors and ontologies was conceived, based on MPEG-21. This paper explains the functioning of the devised mechanism, and goes beyond that, into the definition of two novel employment venues for it, at the service of two real-world usage scenarios. These demonstrate the mechanism's added value as a powerful alternative for the semantically aware interconnection of web resources, and highlight the increased QoE that said mechanism enables.

Abstract
The energy sector restructuring process in industrialized countries had the aim of reducing electricity prices by increasing competitiveness, and facilitate the integration of distributed energy resources. However, the complexity in market players' interactions has increased, and new problems have emerged. Decision support tools that facilitate the study and comprehension of these markets became extremely useful, providing players with competitive advantage. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) arises in this context, modeling and simulating real electricity markets. It is crucial to MASCEM to have the ability to simulate as many market models and player types as possible, thus enhancing the ability to recreate the electricity markets reality in its maximum possible extent. This paper presents the EPEX Spot Day-Ahead market integration in MASCEM. EPEX Spot SE's mission is to lead European markets coupling in a single unified market, thus being crucial for the study of competitive electricity markets. © 2015 IEEE.

Abstract
In the growing field of Robotics, one of the many possible paths to explore is the social aspect that it can influence upon the present society. The combination of the goal-oriented development of robots with the interactivity used in games while employing mixed reality is a promising route to take in regard to designing user-friendly robots and improving problem solving featured in artificial intelligence software. In this paper, we present a competitive team-based game using Pololu's 3Pi robots moving in a projected map, capable of human interaction via game controllers. The game engine was developed utilizing the framework Qt Creator with C++ and OpenCV for the image processing tasks. The technical framework uses the ROS framework for communications that may be, in the future, used to connect different modules. Various parameters of the implementation are tested, such as position tracking errors.

Abstract
Aerial Robots has become very popular in robotics groups. This ongoing interest is driven by a significant number of potential end-user applications where it is necessary to reduce human intervention. The validation of control/cooperation algorithms not always is an easy task and requires a large number of humans to keep tests safety. Is present in this paper the simulation of a quadrotor model in SimTwo simulation environment and evaluated the flight dynamic of the robot. To do that was developed a control layer responsible to the hovering maneuver and “go to” position function. The results prove that the objectives were achieved successfully and the simulation was validated. The navigation simulation is left as future work.