Abstract
This paper presents CoopREP, a system that provides support for fault replication of concurrent programs, based on cooperative recording and partial log combination. CoopREP employs partial recording to reduce the amount of information that a given program instance is required to store in order to support deterministic replay. This allows to substantially reduce the overhead imposed by the instrumentation of the code, but raises the problem of finding the combination of logs capable of replaying the fault. CoopREP tackles this issue by introducing several innovative statistical analysis techniques aimed at guiding the search of partial logs to be combined and used during the replay phase. CoopREP has been evaluated using both standard benchmarks for multi-threaded applications and a real-world application. The results highlight that CoopREP can successfully replay concurrency bugs involving tens of thousands of memory accesses, reducing logging overhead with respect to state of the art non-cooperative logging schemes by up to 50 times in computationally intensive applications.

Abstract
Researching into the incomplete information games (IIG) field requires the development of strategies which focus on optimizing the decision making process, as there is no unequivocal best choice for a particular play. As such, this paper describes the development process and testing of an agent able to compete against human players on Poker - one of the most popular IIG. The used methodology combines pre-defined opponent models with a reinforcement learning approach. The decision-making algorithm creates a different strategy against each type of opponent by identifying the opponent's type and adjusting the rewards of the actions of the corresponding strategy. The opponent models are simple classifications used by Poker experts. Thus, each strategy is constantly adapted throughout the games, continuously improving the agent's performance. In light of this, two agents with the same structure but different rewarding conditions were developed and tested against other agents and each other. The test results indicated that after a training phase the developed strategy is capable of outperforming basic/intermediate playing strategies thus validating this approach. © 2012 Springer-Verlag.

Abstract
Interactive visualization systems are powerful tools in the task of exploring and understanding data. We describe two implementations of this approach, where a multidimensional network of news clips is depicted by taking advantage of its community structure. The first implementation is a multiresolution map of news clips that uses topic detection both at the clip level and at the community level, in order to assign labels to the nodes in each resolution. The second implementation is a traditional force-directed network visualization with several additional interactive aspects that provide a rich user experience for knowledge discovery. We describe a common use case for the visualization systems as a journalistic research and knowledge discovery tool. Both systems illustrate the links between news clips, induced by the co-occurrence of named entities, as well as several metadata fields based on the information contained within each node. Copyright © 2012 SciTePress - Science and Technology Publications.

Abstract
In this paper it is proposed a technique to identify the relevant neighbouring electric power systems using the Horizontal Network scheme. The developed methodology was applied to study the IEEE 118 test power network and the Iberian systems. All simulations were performed using the computational software package PSS®E developed by the Siemens/PTI. From the simulation results, some conclusions that provide a valuable contribution to the understanding of the impact of the cross-border interconnections between the countries will be pointed out.

Abstract
Cellular Genetic Algorithms (cGAs) exhibit a natural parallelism that makes them interesting candidates for hardware implementation, as several processing elements can operate simultaneously on subpopulations shared among them. This paper presents a scalable architecture for a cGA, suitable for FPGA implementation. A regular array of custom designed processing elements (PEs) works on a population of solutions that is spread into dual-port memory blocks locally shared by adjacent PEs. A travelling salesman problem with 150 cities was used to verify the implementation of the proposed cGA on a Virtex-6 FPGA, using a population of 128 solutions with different levels of parallelism (1, 4, 16 and 64 PEs). Results have shown that an increase of the number of PEs does not degrade the quality of the convergence of the iterative process, and that the throughput increases almost linearly with the number of PEs. Comparing with a software implementation running in a PC, the cGA with 64 PEs has shown a 45x speedup.

Abstract
This paper proposes a methodology to analyze complex manufacturing systems, based on discrete-event simulation models. The methodology was validated by performing different simulation experiments and will be applied to a multistage multiproduct production line, based on a real case, with a closed-loop network configuration of machines and intermediate buffers consisting of conveyors, which is very common in the automobile sector. A simulation model in an Arena environment was developed, which allowed for an analysis of the important aspects not yet studied in specialized literature, namely the assessment of the impact of the production sequence on the automobile assembly line. Various sequence rules were analyzed and the performance of each of the corresponding simulation models was registered.