Abstract
Little is known about the impact of the addition of each stimulus in multisensory augmented reality experiences in cultural heritage contexts. This paper investigates the impact of different sensory conditions on a users sense of presence, enjoyment, knowledge about the cultural site, and value of the experience. Five different multisensory conditions, namely, Visual, Visual+ Audio, Visual +Smell, and Visual + Audio + Smell conditions, and regular visit referred to as None condition, were evaluated by a total of 60 random visitors distributed across the specified conditions. According to the results, the addition of particular types of stimuli created a different impact on the sense of presence subscale scores, namely, on spatial presence, involvement, and experienced realism, but did not influence the overall presence score. Overall, the results revealed that the addition of stimuli improved enjoyment and knowledge scores and did not affect the value of the experience scores. We concluded that each stimulus has a differential impact on the studied variables, demonstrating that its usage should depend on the goal of the experience: smell should be used to privilege realism and spatial presence, while audio should be adopted when the goal is to elicit involvement.

Abstract
Training firefighters using Virtual Reality (VR) technology brings several benefits over traditional training methods including the reduction of costs and risks. The ability of causing the same level of stress as a real situation so that firefighters can learn how to deal with stress was investigated. An experiment aiming to study the influence that additional stimuli (heat, weight, smell and using personal protective equipment-PPE) have on user's stress level while performing a Virtual Environment (VE) designed to train firefighters was developed. Participants' stress and Heart Rate Variability (HRV) were obtained from electrocardiograms recorded during the experiment. The results suggest that wearing the PPE has the largest impact on user's stress level. The results also showed that HRV was able to evidence differences between two phases of the experiment, which suggests that it can be used to monitor users' quantified reaction to VEs.

Abstract

Abstract
Internet-of-Things has reshaped the way people interact with their surroundings. In a smart home, controlling the lights is as simple as speaking to a conversational assistant since everything is now Internet-connected. But despite their pervasiveness, most of the existent IoT systems provide limited out-of-the-box customization capabilities. Several solutions try to attain this issue leveraging end-user programming features that allow users to define rules to their systems, at the cost of discarding the easiness of voice interaction. However, as the number of devices increases, along with the number of household members, the complexity of managing such systems becomes a problem, including finding out why something has happened. In this work we present Jarvis, a conversational interface to manage IoT systems that attempts to address these issues by allowing users to specify time-based rules, use contextual awareness for more natural interactions, provide event management and support causality queries. A proof-of-concept was used to carry out a quasi-experiment with non-technical participants that provides evidence that such approach is intuitive enough to be used by common end-users. © Springer Nature Switzerland AG 2020.

Abstract
A number of approaches have been proposed to identify service boundaries when decomposing a monolith to microservices. However, only a few use systematic methods and have been demonstrated with replicable empirical studies. We describe a systematic approach for refactoring systems to microservice architectures that uses static analysis to determine the system's structure and dynamic analysis to understand its actual behavior. A prototype of a tool was built using this approach (MonoBreaker) and was used to conduct a case study on a real-world software project. The goal was to assess the feasibility and benefits of a systematic approach to decomposition that combines static and dynamic analysis. The three study participants regarded as positive the decomposition proposed by our tool, and considered that it showed improvements over approaches that rely only on static analysis.

Abstract
The continuous spreading of the Internet-of-Things across application domains, aided by the continuous growth on the number of devices and systems that are Internet-connected, created both a rise in the complexity of these systems and made noticeable a lack of human resources with the expertise to design, develop and maintain them. Recent works try to mitigate these issues by creating solutions that abstract the complexity of the systems, such as using visual programming languages. Node-RED, as one of the most common solutions for the visual development IoT systems, stills has several limitations, such as the lack of observability and inadequate debugging mechanisms. In this work, we address some of these limitations by enhancing Node-RED with new features that improve the user's system development, debugging, and understanding tasks. We proceed to empirically evaluate the impact of these enhancements, concluding that, overall, such enhancements reduce the development time and the number of failed attempts to deploy the system.