Abstract
The failure to meet production requirements, e.g., due to condition dynamic environment condition changes, operational performance deviations or missing opportunities to adapt, leads to a decrease of competitiveness. Technological advances are then required to promote flexible and adaptive systems with the ability to reconfigure their offered services in a cost effective manner. In spite of the current research efforts, there is still a lack of automated tools to support the service reconfiguration capability at run-time, being the understanding of when and how to reconfigure crucial to support an efficient reconfiguration process. This paper focuses on the problematic of when to reconfigure a system, with the proposed service-based multi-agent system performing the dynamic service reconfiguration based on triggering strategies. This allows to discover reconfiguration opportunities to maintain the system stable and competitive, but also to explore and promote new system configurations when needed. The envisaged triggering strategies, implemented through the intelligence mechanisms embedded in the agents' behaviors, consist in the event, periodic and trend approaches following the reactive, predictive and preventive behaviors. The preliminary experimental results validate the feasibility of such triggering strategies for service reconfiguration leading to more efficient and agile systems.

Abstract

Abstract
Previous studies demonstrated the capability of mixed culture DC1 to mineralize the thiocarbamate herbicide molinate through the activity of molinate hydrolase (MolA). Because liquid suspensions are not compatible with long-term storage and are not easy to handle when bioremediation strategies are envisaged, in this study spray drying was evaluated as a cost-effective method to store and transport these molinate biocatalysts. Microparticles of mixed culture DC1 (DC1) and of cell free crude extracts containing MolA (MA) were obtained without any carrier polymer, and with calcium alginate (CA) or modified chitosan (MCt) as immobilizing agents. All the DC1 microparticles showed high molinate degrading activity upon storage for 6 months, or after 9 additions of similar to 0.4 mM molinate over 1 month. The DC1-MCt microparticles were those with the highest survival rate and lowest heterogeneity. For MA microparticles, only MA-MCt degraded molinate. However, its V-max was only 1.4% of that of the fresh cell free extract (non spray dried). The feasibility of using the DC1-MCt and MA-MCt microparticles in bioaugmentation processes was assessed in river water microcosms, using mass (g):volume (L) ratios of 1:13 and 1:0.25, respectively. Both type of microparticles removed 65-75% of the initial 1.5 mg L-1 molinate, after 7 days of incubation. However, only DC1-MCt microparticles were able to degrade this environmental concentration of molinate without disturbing the native bacterial community. These results suggest that spray drying can be successfully used to produce DC1-MCt microparticles to remediate molinate polluted sites through a bioaugmentation strategy.

Abstract

Abstract
In order to overcome a number of difficulties detected on the Brazilian electricity market this paper proposes and tests a bid based short-term market. To simulate the behavior of the hydros in this new market, it was implemented an Agent-Based Model - ABM using the reinforcement QLearning algorithm, Simulated Annealing, and linear programming. In the simulations we used real data from the Brazilian power system encompassing more than 98% of the total hydro installed capacity and three years of market data. The results indicate that the management of (virtual) reservoirs can be under the responsibility of each hydro, which could save water according to their own risk perception, while it is maintained the current efficiency and security levels. Results also suggest that the final monthly short-term market prices can substantially decrease in comparison with the current prices.

Abstract
This contribution presents a new system for fast and intuitive industrial robot reprogramming. It is based on a luminous marker built with high-intensity LEDs, which are captured by a set of industrial cameras. Using stereoscopy, the marker supplies 6-DoF human wrist tracking with both position and orientation data. This marker can be efficiently attached to any working tool which then provides a way to capture human skills without further intrusion in the tasks. The acquisition technique makes the tracking very robust against lighting conditions so no environment preparation is needed. The robot is automatically programmed from the demonstrated task which delivers complete abstraction of programming concepts. The system is able to perform in real time, and is low-cost starting with a single pair of industrial cameras though more can be used for improved effectiveness and accuracy. The real-time feature means that the robot is ready to perform as soon as the demonstration is over which carries no overhead of reprogramming times. Also, there is no interference with the task itself since the marker is attached to the work tool and the tracking is contactless; the human operator can then perform naturally. The test bed is a real industrial environment: a spray painting application. A prototype has been developed and installed, and is currently in operation. The tests show that the proposed system enables transferring to the machine the human ability of manipulating a spray gun.