Abstract
This article studies the optimal solution of an irrigation problem. It consists in optimizing the planning of water used so by the water amount in the soil (trajectory) fulfils the cultivation water requirements. We characterize the optimal solution by applying the necessary conditions of optimality in the form of the Maximum Principle. We also compare the results obtained analytically and numerically. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Peer-review under responsibility of ISEL Instituto Superior de Engenharia de Lisboa, Lisbon, PORTUGAL.

Abstract
Currently, software tends to assume increasingly critical roles in our society so assuring its quality becomes ever more crucial. There are several tools and processes of software testing to help increase quality in virtually any type of software. One example is the so called Model-Based Testing (MBT) tools, that generate test cases from models. However, most of these tools have a configuration phase, where test input data is provided manually by the tester, which influences the quality of the test suite generated. By adding coverage analysis to MBT tools it is possible to give feedback and help the tester to define the configuration data needed to achieve the most valuable test suite as possible. This paper presents a tool, PARADIGM-COV, that produces coverage information both over the PARADIGM model elements (to assess if input data is adequate to cover the test goals and assess if preconditions are achievable), and during test case execution (to identify the parts of the model/code that were actually exercised).

Abstract

Abstract
This paper deals with a control strategy of multilevel converter topologies for integration of distributed generation (DG) resources into the power grid. The proposed control plan is based on the direct Lyapunov control (DLC) technique, which is an appropriate tool for the analysis and definition of a stable operating condition for DG link in the power grid. The compensation of instantaneous variations in the reference current components in ac side and dc voltage variations of cascaded capacitors in dc side of the interfacing system is considered properly, which is the main contribution and novelty of this paper in comparison with other control methods. By utilization of the proposed control technique, DG can provide continuous injection of active power in fundamental frequency from the dispersed energy sources to the grid. In addition, reactive power and harmonic current components of nonlinear loads can be provided with fast dynamic response, by setting a multiobjective reference current component in the current loop of DLC-based model. Therefore, achieving sinusoidal grid currents in phase with load voltages are possible, while the required power from the load side is more than the maximum capacity of interfaced multilevel converter. Simulation results confirm the effectiveness of the proposed control strategy in DG technology during dynamic and steady-state operating conditions.

Abstract
The society is changing towards a new paradigm in which an increasing number of old adults live alone. In parallel, the incidence of conditions that affect mobility and independence is also rising as a consequence of a longer life expectancy. In this paper, the specific problem of falls of old adults is addressed by devising a technological solution for monitoring these users. Video cameras, accelerometers and GPS sensors are combined in a multi-modal approach to monitor humans inside and outside the domestic environment. Machine learning techniques are used to detect falls and classify activities from accelerometer data. Video feeds and GPS are used to provide location inside and outside the domestic environment. It results in a monitoring solution that does not imply the confinement of the users to a closed environment.

Abstract
Since the concerns for energy conservation and environment are growing, renewable energy resources are rapidly increasing, which lead to additional variability and uncertainty for the power system operators. The uncertainty imposes considerable technical and economic challenges to ISOs. According to recent advances in smart grid technologies, Demand Response Programs (DRPs) are expected to facilitate the integration of intermittent renewable energy resources into the grid. In this paper, DRPs are considered as an option to reduce and manage renewable energy resources uncertainty. On this basis, this paper proposes a flexible load approach with the application to wind power grid integration. In this context, and in order to model the reality of the power market, a network constrained unit commitment problem associated with DRPs is presented to clear the market transactions. Simulation results show that utilizing DRPs can improve grid integration of wind power, while making significant economic and technical benefits for the system.