Abstract
Crowdsourcing has shown to be a valuable problem-solving approach to handle the increasing complexity and scale of tasks for which the current AI algorithms are still struggling. Crowd intelligence can be particularly useful to train and supervise AI systems in a symbiotic, co-evolutionary relationship that raises long-term research challenges to the hybrid, crowd-computing design space. With the increase in the scale of mixed-initiative approaches, we need to gain a better understanding of the implications of crowd-powered systems as a scaffold for AI through the study of massive crowd-machine interactions. In this paper, we identify some open challenges and design implications for future crowd-AI hybrid systems. A framework is also proposed based on the practical challenges of addressing human-centered AI methods and processes.

Abstract
A substantial amount of work is often overlooked due to the exponential rate of growth in global scientific output across all disciplines. Current approaches for addressing this issue are usually limited in scope and often restrict the possibility of obtaining multidisciplinary views in practice. To tackle this problem, researchers can now leverage an ecosystem of citizens, volunteers and crowd workers to perform complex tasks that are either difficult for humans and machines to solve alone. Motivated by the idea that human crowds and computer algorithms have complementary strengths, we present an approach where the machine will learn from crowd behavior in an iterative way. This approach is embodied in the architecture of SciCrowd, a crowd-powered human-machine hybrid system designed to improve the analysis and processing of large amounts of publication records. To validate the proposal's feasibility, a prototype was developed and an initial evaluation was conducted to measure its robustness and reliability. We conclude this paper with a set of implications for design.

Abstract
The present study aims to translate and validate the Temple Presence Inventory (TPI) for the Portuguese context, respecting the maintenance of an equivalent semantics as well as the validity of its contents and concepts. This study also aims to verify the psychometric properties of the instrument (factor validity and internal consistency). The sample consisted of 455 individuals (male = 271, female = 184). The fidelity of the factors varied between 0.5 and 0.84. The confirmatory factor analysis produced a theoretical model with 38 items distributed among eight factors. The covariance between some residual errors of instrument items was considered, and the following fit indices were observed: chi 2/df = 2.073; GFI = 0.858; CFI = 0.887; RSMEA = 0.049; AIC = 1527. The results confirm the appropriateness of the version adapted to the Portuguese language of the TPI and that it can be used in research projects aiming to evaluate Presence in the Portuguese-speaking population (Europe).

Abstract
This investigation concerns the translation and validation of the ITC - Sense of Presence Inventory (ITC-SOPI) for the Portuguese-speaking population (in Europe), estimating the validity of the content and concepts and the maintenance of an equivalent semantics. It also sought to verify its psychometric properties, namely its factorial validity and internal consistency. The sample consisted of 459 individuals, 274 males and 185 females. The fidelity of the subscales varied between 0.67 and 0.89. Confirmatory factor analysis revealed a theoretical model of 35 items, divided by four factors. After fixing some of the residual errors between items, the following adjustment indexes were calculated: chi(2)/df = 2.301; goodness fit index = 0.860; comparative fitness index = 0.889; root mean square error of approximation = 0.053; Akaike's information criterion = 1420. Based on the observed results and the robustness of the sample size used, the obtained theoretical model shows that the ITC-SOPI is recommended to measure presence in virtual reality research projects with samples of Portuguese language speakers.

Abstract
With the appearance of innovative virtual reality (VR) technologies, the need to create immersive content arose. Although there are already some non-immersive solutions to address immersive audio-visual content, there are no solutions that allow the creation of immersive multisensory content. This work proposes a novel architecture for a collaborative immersive tool that allows the creation of multisensory VR experiences in real-time, thus promoting the expeditious development, adoption, and use of immersive systems and enabling the building of custom-solutions that can be used in an intuitive manner to support organizations' business initiatives. To validate the presented proposal, two approaches for the authoring tools (Desktop interface and Immersive interface) were subjected to a set of tests and evaluations consisting of a usability study that demonstrated not only the participants' acceptance of the authoring tool but also the importance of using immersive interfaces for the creation of such VR experiences.

Abstract
Virtual reality (VR) games have the potential to produce immersive experiences. To better explore the potential of VR games, it becomes necessary to understand what affects the player's presence in VR games. This work measures and compares the levels of presence and cybersickness in VR environments. Two games with different levels of interaction and narrative were compared. Presence and cybersickness were measured in a sample of 32 subjects using the IPQp questionnaire and a Portuguese version of the SSQ respectively. The results indicate that there were no differences in presence and cybersickness between the interaction and the narrative dimensions. To extend the study, the gender of participants was also considered an independent variable where we found significant differences in the metrics of presence and experienced realism, nausea and disorientation with female participants getting higher scores. © 2018 IEEE.