Abstract

Abstract

Abstract
The main goal of the ANTAREX project is to express by a Domain Specific Language (DSL) the application self-adaptivity and to runtime manage and autotune applications for green and heterogeneous High Performance Computing (HPC) systems up to the Exascale level. Key innovations of the project include the introduction of a separation of concerns between self-adaptivity strategies and application functionalities. The DSL approach will allow the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management.

Abstract
With the rising research in emotionally believable agents, several advances in agent technology have been made, ranging from interactive virtual agents to emotional mechanism simulations and emotional agent architectures. However, creating an emotionally believable agent capable of emotional thought is still largely out of reach. It has been proposed that being able to accurately model human emotion would allow agents to mimic human behaviour while these models are studied to create more accurate theoretical models. In light of these challenges, we present a general method for human emotional state modelling in interactive environments. The proposed method employs a three-layered classification process to model the arousal and valence (i.e., hedonic) emotional components, based on four selected psychophysiological metrics. Additionally, we also developed a simplified version of our system for use in real-time systems and low-fidelity applications. The modelled emotional states by both approaches compared favourably with a manual approach following the current best practices reported in the literature while also improving on its predictive ability. The obtained results indicate we are able to accurately predict human emotional states, both in offline and online scenarios with varying levels of granularity; thus, providing a transversal method for modelling and reproducing human emotional profiles.

Abstract
This paper presents an approaches. that assists in producing highly compacted Nesting layouts with irregular pieces using free rotations. This approach consists in the selection and compaction of big pieces in a first phase, while in a second phase, places the remaining small pieces between the big pieces, compacting all of them. The effect of several parameters are analyzed, such as minimum length to be achieved in the first phase, attraction of the pieces to the edges of the container, attraction between each pair of pieces, among others. This approach can provide good compaction results, while improving computational cost in some cases, which cart allow to tackle real world problems more effectively mkt efficiently.

Abstract
In this paper, we address the irregular strip packing problem (or nesting problem) where irregular shapes have to be placed on strips representing a piece of material whose width is constant and length is virtually unlimited. We explore a constructive heuristic that relies on the use of graphical processing units to accelerate the computation of different geometrical operations. The heuristic relies on static selection processes, which assume that a sequence of pieces to be placed is defined a priori. Here, the emphasis is put on the analysis of the impact of these sequences on the global performance of the solution algorithm. Computational results on benchmark datasets are provided to support this analysis, and guide the selection of the most promising methods to generate these sequences.