Abstract
VLIW architectures are seeing increased deployment in a number of hostile environments. In addition, softcore VLIW architectures, which allow for run-time customization of the VLIW datapath, are becoming viable for a number of safety-critical applications. As error and failure rates rise, these applications elicit a need for automated and resilient architecture configuration tools. To mitigate these issues, this paper presents a Resiliency-aware Scheduling approach to the configuration of a custom VLIW architecture, providing computational resilience via software duplication. The automated RaS tool determines the optimal set of resources needed to provide a given level of resilience for a reconfigurable softcore VLIW architecture. For a sample case study, based on a common physics code kernel, the RaS approach is compared to traditional hardware (TMR) and software (source-level code replication) approaches. Results show a Resiliency-aware Scheduling-generated architecture configuration can potentially require up to 50% fewer functional units when compared to a TMR-hardened machine of similar performance, and can potentially improve performance by up to 40% over source-level software approaches. © 2012 IEEE.

Abstract
In game development there is often the need to generate realistic urban environments, i.e. 3D virtual environments that replicate existing urban areas. However, modeling such spaces using traditional techniques is both too slow and too expensive. A good solution is the use of procedural modeling techniques to automate the process. However these techniques require large amounts of geospatial data, which are usually stored in Geographic Information Systems (GIS). This paper presents a pipeline for the integration of both geometric and semantic data from GIS data sources into procedural modeling techniques used for the generation of 3D virtual urban environments. GIS data can already be used in procedural modeling tools but these do not provide an easy and uniform way to incorporate semantic information from different data sources. To solve this problem, the proposed pipeline is capable of transforming semantic and geometric information from different sources into 3D environments that replicate specific urban areas.

Abstract
Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents' behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Abstract
The number of configurable systems deployed in hostile environments continues to rise. This, along with decreasing geometries and lower operating voltages leads to an expected increase in transient errors. This paper presents Resiliency-aware Scheduling, a novel approach to resource allocation for hardening computations on configurable systems. Using modular and replicated functional units called hybrid TMR that exploit a computation's Intrinsic Resiliency, our results show that for designs with similar performance, RaS exhibits a 60% area savings over a traditional TMR configuration with the same operation coverage. © 2012 IEEE.

Abstract
Given the large amount of data mining algorithms, their combinations (e.g. ensembles) and possible parameter settings, finding the most adequate method to analyze a new dataset becomes an ever more challenging task. This is because in many cases testing all possibly useful alternatives quickly becomes prohibitively expensive. In this paper we propose a novel technique, called active testing, that intelligently selects the most useful cross-validation tests. It proceeds in a tournament-style fashion, in each round selecting and testing the algorithm that is most likely to outperform the best algorithm of the previous round on the new dataset. This 'most promising' competitor is chosen based on a history of prior duels between both algorithms on similar datasets. Each new cross-validation test will contribute information to a better estimate of dataset similarity, and thus better predict which algorithms are most promising on the new dataset. We also follow a different path to estimate dataset similarity based on data characteristics. We have evaluated this approach using a set of 292 algorithm-parameter combinations on 76 UCI datasets for classification. The results show that active testing will quickly yield an algorithm whose performance is very close to the optimum, after relatively few tests. It also provides a better solution than previously proposed methods. The variants of our method that rely on crossvalidation tests to estimate dataset similarity provides better solutions than those that rely on data characteristics.

Abstract
Even though we now witness a popular use of location-based mobile games, the player experience in these applications is always limited by the errors of common location technologies, especially in indoor scenarios. This paper describes the way we minimize this problem in our game development platform, by levering the potential behind smartphone sensors to estimate players' trajectories. Our approach is based on a Pedestrian Dead Reckoning (PDR) algorithm that combines methods to determine orientation, detect steps and estimate their length. Other typical multiplayer mobile games problems, like network latency, are also briefly addressed. © 2012 Springer-Verlag Berlin Heidelberg.