Abstract
This paper proposes new clustering criteria for distinguishing Saccharomyces cerevisiae (yeast) strains using their spectrometric signature. These criteria are introduced in an agglomerative hierarchical clustering context, and consist of: (a) minimizing the total volume of clusters, as given by their respective convex hulls; and, (b) minimizing the global variance in cluster directionality. The method is deterministic and produces dendrograms, which are important features for microbiologists. A set of experiments, performed on yeast spectrometric data and on synthetic data, show the new approach outperforms several well-known clustering algorithms, including techniques commonly used for microorganism differentiation.

Abstract
The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization (PSO) using natural selection, or survival-of-the-fittest, to enhance the ability to escape from local optima. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots. Therefore, the RDPSO decreases the amount of required information exchange among robots, and is scalable to large populations of robots. This paper presents a stability analysis of the RDPSO to better understand the relationship between the algorithm parameters and the robot's convergence. Moreover, the analysis of the RDPSO is further extended for real robot constraints (e.g., robot dynamics, obstacles and communication constraints) and experimental assessment with physical robots. The optimal parameters are evaluated in groups of physical robots and a larger population of simulated mobile robots for different target distributions within larger scenarios. Experimental results show that robots are able to converge regardless of the RDPSO parameters within the defined attraction domain. However, a more conservative parametrization presents a significant influence on the convergence time. To further evaluate the herein proposed approach, the RDPSO is further compared with four state-of-the-art swarm robotic alternatives under simulation. It is observed that the RDPSO algorithm provably converges to the optimal solution faster and more accurately than the other approaches.

Abstract
In the end of a requirements elicitation phase, it is expectable that all information can be properly perceived by the implementation teams. In our work, we faced the problem of dealing with a large set of requirements that need to be implemented by different teams, to ensure on-time delivery. The teams are physically separated and with different working cultures and skills. The system requirements were (semi-) automatically derived from user requirements, are framed within a logical architecture (of the intended system) and the desired high-level execution scenarios are defined and included in the requirements description. Due to the large size of the architecture and to the nature of the working environment, the architecture must be divided before being delivered. In this paper, we present our approach for dividing the logical architecture of the intended system into modules to be delivered for implementation. The division in constructed upon requirement views that provide information about the modules, their interfaces, the intended execution scenarios, and the interfaces with other modules or systems. The approach is evaluated using the ISOFIN project.

Abstract
Mobile Ad hoc Networks have attracted much attention in the last years, since they allow the coordination and cooperation between agents belonging to a multi-robot system. However, initially deploying autonomously a wireless sensor robot network in a real environment has not taken the proper attention. Moreover, maintaining the connectivity between agents in real and complex environments is an arduous task since the strength of the connection between two nodes (i.e., robots) can change rapidly in time or even disappear. This paper compares two autonomous and realistic marsupial strategies for initial deployment in unknown scenarios, in the context of swarm exploration: Random and Extended Spiral of Theodorus. These are based on a hierarchical approach, in which exploring agents, named scouts, are autonomously deployed through explicit cooperation with supporting agents, denoted as rangers. Experimental results with a team of heterogeneous robots are conducted using both real and virtual robots. Results show the effectiveness of the methods, using a performance metric based on dispersion. Conclusions drawn in this work pave the way for a whole series of possible new approaches.

Abstract
This study presents an experimental research design of a PhD work, studying the effectsof the variability in the performance of the Golf putting. The instruments used to analyze the putting were two digital cameras to detect the relevant dynamic objects (i.e., ball and putter) and a biaxial accelerometer to confirm the exactmoment at which the putter hits the ball. To synchronize the instruments, it was used a trigger. The ball’s trajectory and the putting movement were automatically analyzed based on visual detection and parameter estimation. The kinematic analysis of the putting was performed using the Matlab software, to determine the amplitude, velocity and acceleration of the players’gestures. We concluded that the Golf putting action parameters are divided into different stages(i.e., backswing, downswing and follow-through) and that those can be useful to investigate the effects of variability in this movement. © Springer Science+Business Media Dordrecht 2014.

Abstract
This book presents a careful selection of the contributions presented at the Mathematical Methods in Engineering (MME10) International Symposium, held at the Polytechnic Institute of Coimbra- Engineering Institute of Coimbra (IPC/ISEC), Portugal, October 21-24, 2010. The volume discusses recent developments about theoretical and applied mathematics toward the solution of engineering problems, thus covering a wide range of topics, such as: Automatic Control, Autonomous Systems, Computer Science, Dynamical Systems and Control, Electronics, Finance and Economics, Fluid Mechanics and Heat Transfer, Fractional Mathematics, Fractional Transforms and Their Applications, Fuzzy Sets and Systems, Image and Signal Analysis, Image Processing, Mechanics, Mechatronics, Motor Control and Human Movement Analysis, Nonlinear Dynamics, Partial Differential Equations, Robotics, Acoustics, Vibration and Control, and Wavelets. © Springer Science+Business Media Dordrecht 2014.