Abstract
In a previous study, the authors developed the planning of the water used in the irrigation systems of a given farmland in order to ensure that the field cultivation is in a good state of preservation. This planning was modelled and tackled as an optimal control problem: minimize the water flow (control) so that the extent water amount in the soil (trajectory) fulfils the cultivation water requirements. In this paper, we characterize the solution of our problem guaranteeing the existence of the solution and applying the necessary and sufficient conditions of optimality. We validate the numerical results obtained previously, comparing the analytical and numerical solutions.

Abstract
This paper proposes the impact assessment of the workers in the optimal time of operations in a Flexible Job Shop Scheduling Problem. In this work, a real enterprise was studied. The problem consists in finding the workers operations schedule, taking into account the precedence constraints. The main objective is to minimize the finish time of the last task completed in the schedule. The genetic algorithm was used to solve the optimization problem and some numerical results are presented.

Abstract
Cognitive robotics looks at human cognition as a source of inspiration for automatic perception capabilities that will allow robots to learn and reason out how to behave in response to complex goals. For instance, humans learn to recognize object categories ceaselessly over time. This ability to refine knowledge from the set of accumulated experiences facilitates the adaptation to new environments. Inspired by such abilities, this paper proposes an efficient approach towards 3D object category learning and recognition in an interactive and open-ended manner. To achieve this goal, this paper focuses on two state-of-the-art questions: (i) How to use unsupervised object exploration to construct a dictionary of visual words for representing objects in a highly compact and distinctive way. (ii) How to learn incrementally probabilistic models of object categories to achieve adaptability. To examine the performance of the proposed approach, a quantitative evaluation and a qualitative analysis are used. The experimental results showed the fulfilling performance of this approach types of objects. The proposed system is able to interact with human users and learn new object categories over time.

Abstract

Abstract
Mobile applications are a rapidly increasing part of our daily life, featuring more than one million applications and fifty billions downloads in the two major markets. Thus, it is important to ensure their functional correctness. The Pattern-Based GUI Testing (PBGT) project presented an approach for systematising and automating the GUI testing of web applications by modelling testing goals with User Interface Test Patterns(UITPs), i.e., test strategies for recurring behaviour of the UI. This paper extends the set of UITPs used by the PBGT project with three UITPs specific to the testing of mobile applications: Side Drawer, Orientation and Resources Dependency.

Abstract
The increasing penetration of plug-in electric vehicles (PEVs) has encouraged solutions for facilitating their utilization. In this regard, PEV parking lots (PLs) have proved to be essential for future systems with high amounts of PEVs. However, operating a PL in order to maximize its profit while enforcing its own constraints generates conflicts between the PL and the distribution system operator (DSO). As a result, this paper proposes a model to solve the PL equilibria behavior. A bi-level problem including the operation of DSO and PL is solved using mathematical programming with equilibrium constraints (MPEC). The PL's behavior is defined by its hourly energy and reserve interaction with the market through the DSO. As the total amount of PL's interaction with the grid will affect the DSO's operational decision making, the proposed model finds the equilibrium point to maximize the benefit for PL and DSO.