Abstract

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.

Abstract
Current affective user experience studies require both laborious and time-consuming data analysis, as well as dedicated affective classification algorithms. Moreover, the high technical complexity and lack of general guidelines for developing these affective classification algorithms further limits the comparability of the obtained results. In this paper we target this issue by presenting a tool capable of automatically annotating and triangulating players' physiologically interpreted emotional reactions to in-game events. This tool was initially motivated by an experimental psychology study regarding the emotional habituation effects of audio-visual stimuli in digital games and we expect it to contribute in future similar studies by providing both a deeper and more objective analysis on the affective aspects of user experience. We also hope it will contribute towards the rapid implementation and accessibility of this type of studies by open-sourcing it. Throughout this paper we describe the development and benefits presented by our tool, which include: enabling researchers to conduct objective a posteriori analyses without disturbing the gameplay experience, automating the annotation and emotional response identification process, and formatted data exporting for further analysis in third-party statistical software applications.

Abstract
Technology plays a key role in daily life of people with special needs, being a mean of integration or even communication with society. By built up experience, we find that support tools play a crucial part in empowerment of persons with special needs and small advances may represent shifts and opportunities. The diversity of solutions and the need for dedicated hardware to each feature represents a barrier to its use, compromising the success of the solutions against, among others, problems of usability and scale. This paper aims to explore the concept of inclusive collaboration to enhance the mutual interaction and assistance. The proposed approach combines and generalizes the usage of human computation in a collaborative environment with assistive technologies creating redundancy and complementarity in the solutions provided, contributing to enhance the quality of life of people with special needs and the elderly. The CanIHelp platform is an embodiment of the concept as a result from an orchestrated model using mechanisms of collective intelligence through social inclusion initiatives. The platform features up for integrating assistive technologies, collaborative tools and multiple multimedia communication channels, accessible through multimodal interfaces for universal access. A discussion of the impacts of fostering collaboration and broadening from the research concepts to the societal impacts is presented. As final remarks a set of future research challenges and guidelines are identified.