A combined queueing network and stochastic Petri-net approach for evaluating the performability of fault-tolerant computer systems

In this paper the performability analysis of fault-tolerant computer systems using a hierarchical decomposition technique is presented. A special class of queueing network (QN) models, the so-called BCMP [4], and generalized stochastic Petri nets (GSPN) [1] which are often used to separately model performance and reliability respectively, have been combined in order to preserve the best modelling features of both.

A conceptual model is decomposed into GSPN and BCMP submodels, which are solved in isolation. Then, the remaining GSPN portion of the model is aggregated with flow-equivalents of BCMP models, in order to compute performability measures. The substitutes of BCMP models are presented by means of simple GSPN constructs, thereby preserving the 1st and 2nd moments of the throughput. A simple example of a data communication system where failed transmissions are corrected, is presented.     

Effect of catalysts in the quality of syngas and by-products obtained by co-gasification of coal and wastes. 1. Tars and nitrogen compounds abatement

The aim of this work is to analyse the possibility of using co-gasification technology to process coal mixed with wastes to take profit of its energy content and at the same time to minimize the environmental impact associated with the use of wastes and to diminish the costs of flue gas treatment. The addition to coal of different types of materials, like: pine based waste, petcoke and polyethylene (PE), was not found to give rise to any operational problems, regarding both the feeding system and gasification process and led to higher energy conversions, however, the gas presented higher tars and hydrocarbons content. Several catalysts were tested, such as, dolomite, olivine, nickel and magnesium oxides, zinc oxides and cobalt and molybdenum oxides. Catalyst action was analysed in tars release and also in ammonia compounds reduction. The presence of catalysts allowed increasing hydrogen release, whilst there was a decrease in hydrocarbons and tars contents. A nickel-magnesium oxide was the catalyst that led to the highest reduction in hydrocarbons and tars. This catalyst also led to the lowest NH₃ content in the fuel gas produced, due to the catalyst efficiency in NH₃ destruction.     

Interactional Order and Constructed Ways of Seeing with Touchless Imaging Systems in Surgery

While surgical practices are increasingly reliant on a range of digital imaging technologies, the ability for clinicians to interact and manipulate these digital representations in the operating theatre using traditional touch based interaction devices is constrained by the need to maintain sterility. To overcome these concerns with sterility, a number of researchers are have been developing ways of enabling interaction in the operating theatre using touchless interaction techniques such as gesture and voice to allow clinicians control of the systems. While there have been important technical strides in the area, there has been little in the way of understanding the use of these touchless systems in practice. With this in mind we present a touchless system developed for use during vascular surgery. We deployed the system in the endovascular suite of a large hospital for use in the context of real procedures. We present findings from a study of the system in use focusing on how, with touchless interaction, the visual resources were embedded and made meaningful in the collaborative practices of surgery. In particular we discuss the importance of direct and dynamic control of the images by the clinicians in the context of talk and in the context of other artefact use as well as the work performed by members of the clinical team to make themselves sensable by the system. We discuss the broader implications of these findings for how we think about the design, evaluation and use of these systems.     

Sense representations for Portuguese: experiments with sense embeddings and deep neural language models

Sense representations have gone beyond word representations like Word2Vec, GloVe and FastText and achieved innovative performance on a wide range of natural language processing tasks. Although very useful in many applications, the traditional approaches for generating word embeddings have a strict drawback: they produce a single vector representation for a given word ignoring the fact that ambiguous words can assume different meanings. In this paper, we explore unsupervised sense representations which, different from traditional word embeddings, are able to induce different senses of a word by analyzing its contextual semantics in a text. The unsupervised sense representations investigated in this paper are: sense embeddings and deep neural language models. We present the first experiments carried out for generating sense embeddings for Portuguese. Our experiments show that the sense embedding model (Sense2vec) outperformed traditional word embeddings in syntactic and semantic analogies task, proving that the language resource generated here can improve the performance of NLP tasks in Portuguese. We also evaluated the performance of pre-trained deep neural language models (ELMo and BERT) in two transfer learning approaches: feature based and fine-tuning, in the semantic textual similarity task. Our experiments indicate that the fine tuned Multilingual and Portuguese BERT language models were able to achieve better accuracy than the ELMo model and baselines.

     

Disquiet in the plasma

The metaphor of plasma is taken up to present and discuss movement and engagement by participants in mixed reality installation arts. Two works involving full body video portraits exhibited through large plasma screens in a variety of public settings are covered. Machinic mediations of video realism are considered in terms of embodied interaction in which viewer-participants contribute to the ‘disquiet’ of gendered figuring. Processural, proximal and personal aspects of responsive engagement are discussed. This is extended to performativity that may lead us to critical reflection of our own actions and responses in mixed reality arts.     

Influence of green creativity on organizations: A case study from the perspectives of leaders and subordinates

The sustainability framework has a strong influence on the policies, practices and procedures of companies. Green creativity plays a pivotal role in the development of initiatives and innovations for the environmental pillar of sustainability. Based on a survey applied to a Portuguese company with an accredited environmental management system (N = 146), the findings reveal that green creativity is influenced in different ways when analysed from distinct perspectives. The leader's green creativity is positively influenced by the subordinate's green self-efficacy and personal identification with the leader, whereas the subordinate's green creativity is positively influenced by their green passion and green self-efficacy, and the leaders' green creativity. This study shows that green creativity develops differentially according to distinct job positions and expectations that in practice must be complementary and synergistic for its effective development.     

A semi-automatic strategy for achieving learning content and practice repurposing

The development of instructional content using Information Technologies is an expensive, time-consuming and complex process that requires new methodologies. It was in this context that the concept of Learning Objects (LOs) was proposed in order to promote reuse. However, this goal is not yet fully attained and new contributions to increase reuse are still welcome. Besides, if content is conveyed in LOs that are easier to reuse, they must be combined and sequenced in order to build more elaborated and complex content. This paper presents a strategy to deal with these problems based on the definition of small LOs here called Component Objects (COs). These COs are structured and combined according to a conceptual metamodel, which is the basis for the definition of conceptual schemas representing the existing material, including not only content but also practice. This strategy for searching, extracting, and sequencing COs, supports a teacher to better control the implementation of complex content, reducing errors in the authoring process. This approach includes a specification language and an algorithm for semi-automatic sequencing learning content and practice. Finally, a case study that shows the proposed approach and some results of using the algorithm are presented.     

When brands come to life: experimental research on the vividness effect of Virtual Reality in transformational marketing communications

Mobile Virtual Reality provides a gateway for marketers to innovatively reach consumers. This study examines the impact of Virtual Reality in the context of transformational brand experience appeals, focussing specifically on the determining role of vividness. A three-dimensional conceptual framework is presented, offering a systematic review of the literature on vividness effects in marketing communications, revealing the major gap that most available studies only focus on informational messages. We conducted an experiment to address this gap and demonstrate in the context of a transformational ad that Virtual Reality generates higher perceptions of vividness and presence than a regular two-dimensional video, with vividness positively affecting attitude toward the ad, both directly and indirectly via presence. Our study also reveals that vividness in turn elicits a positive effect on brand attitudes which stimulates consumers’ purchase intentions. As such, the strategic potential of Virtual Reality for marketing communications is highlighted.