Abstract

Abstract
Falls of patients are an important issue in hospitals, it causes severe injuries to the patients, increases hospitalization time and treatment costs. The detection of a fall, in time, provides faster rescue to the patient, preventing more serious injuries, as well as saving nursing time. The MovinSense (R) is an electronic device designed for monitoring patients to prevent pressure sores, and the main goal of this work was to develop a new tool for this device, with the purpose of detecting if the patient has fallen from the hospital bed, without changing any of the device original features. Experiments for gathering data samples of inertial signals of falling from the bed were obtained using the device. For fall detection a sensitivity of 72% and specificity of 100% were reached. Another algorithm was developed to detect if the patient got out of his/her bed.

Abstract
This paper describes the implementation of a navigation algorithm for Autonomous Surface Vehicles (ASVs), that is composed by two stages: 1) spline curve follower and; 2) reactive collision avoidance, obeying to the International Regulations for Preventing Collisions at Sea (COLREGs). The spline curve follower determines path's parametric functions that the vehicle should follow, taking into account : 1) the initial and goal points on the fixed world frame and; 2) the final desired orientation for the ASV. The reactive collision avoidance substitutes the splines navigation in situations of potential collision with moving obstacles. To do this, the algorithm considers the relative velocity between the controlled ASV and the moving obstacle (other ASV). It also takes into account the escape trajectory that the controlled ASV is capable to perform at each instant. The algorithm was implemented under the Robotic Operating System (ROS) framework. An intuitive spline curve configuration tool, using the RVIZ's package. The paper presents results of the simulation of two ASVs, following predefined spline trajectories, and the reactive collision avoidance routine in a rendezvous situation. A reference for a video illustrating the navigation algorithm is also provided.

Abstract
Novel techniques and a toolset are presented for automatically testing the conformance of software implementations against partial behavioral models constituted by a set of parameterized UML sequence diagrams (SDs), describing both external and internal interactions. Test code is automatically generated from the SDs and executed on the Java implementation under test, and test results and coverage information are presented back visually in the model. A runtime test library handles internal interaction checking, test stubs, and user interaction testing. Incremental conformance checking is achieved by first translating SDs to non-deterministic acceptance automata with parallelism. © IFIP International Federation for Information Processing 2013.

Abstract
The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Abstract
Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players' actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.