Abstract
The recent advances made in human-computer interaction have allowed us to manipulate digital contents exploiting recognitionbased technologies. However, no work has been reported that evaluates how these interfaces influence the performance of different user groups. With the appearance of multiple sensors and controllers for hand gesture recognition, it becomes important to understand if these groups have similar performance levels concerning gestural interaction, and if some sensors could induce better results than others when dealing with users of different age brackets. In this respect, it could also be important to realize if the device's sensor accuracy in terms of hand / full body recognition influences interaction performance. We compare two gesturesensing devices (Microsoft Kinect and Leap Motion) using Fitts' law to evaluate target acquisition performances, with relation to users' age differences. In this article, we present the results of an experiment implemented to compare the groups' performance using each of the devices and also realize which one could yield better results. 60 subjects took part in this study and they were asked to select 50 targets on the screen as quickly and accurately as possible using one of the devices. Overall, there was a statistically significant difference in terms of performance between the groups in the selection task. On the other hand, users' performance showed to be rather consistent when comparing both devices side by side in each group of users, which may imply that the device itself does not influence performance but actually the type of group does. © 2015 ACM.

Abstract
With the thriving of different natural interaction paradigms-such as gesture-based interfaces-it becomes important to understand how these novel interfaces can influence users' performance when it comes to their age. Recent advances made in human-computer interaction allow us to manipulate digital contents more intuitively; however, no work has yet been reported that systematically evaluates how gestural interfaces may influence the performance of different user groups. Different optical sensors, which allow human body acquisition with reliable accuracy, have been released, and with the appearance of such controllers for gesture recognition, it becomes important to understand if different age-related groups display similar performance levels concerning gestural interaction, or, on the other hand, if specific sensors could induce better results than others when dealing with users of different age brackets. In this article, we compare two gesture-sensing devices (Microsoft Kinect and Leap Motion) using the Fitts' law model to evaluate target acquisition performance, with relation to three user groups: children, young adults and older adults. This case study involved 60 participants that were asked to perform a simple continuous selection task as quickly and accurately as possible using one of the devices for gestural recognition. Indeed, performance results showed statistically significant differences among the age groups in the selection task accomplished. However, when considering the users' performance with regard to both input devices compared side by side, there were no significant differences in each group of users. We believe this situation could imply that the device itself might not have influenced the users' performance, but actually the users' age might. The participants feedback was interesting on account of their behaviors and preferences: Although there are no significant differences in performance, there could be when it comes to user preference.

Abstract
Previous findings have shown that users with intellectual disabilities navigate the Web more easily and with greater interest when images are used to represent hyperlinks (Rocha, 2008; 2014; Rocha et al., 2012). Although images can be better for navigation purposes, there is a need to understand how these images should be designed to enhance users' interaction with digital content for this particular group of people. The purpose of this study is to measure the user's preference for image-type representation (Object, Action and Universe), within four different categories (music, movies, sports, games). The sample consisted of 20 individuals with intellectual disabilities, their ages ranging from 22 to 49 years old. The results showed that they preferred less complex images, namely object representative images, and that categories had no effect.

Abstract

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
Nowadays, tourism faces the technology progress challenge. Tourists are changing the way they search for information and the way they buy tourism products and services. Therefore, becomes important to analyze the influence of relevant digital marketing tools on low density tourism regions success, measured through destination image, tourists’ satisfaction and loyalty. The main aim of this article is to demonstrate the theoretical support of a model about the impact of digital marketing tools technologies on low density tourism region. To achieve this purpose, a literature review will be used as a methodological basis. This study also intends to contribute to the scientific debate through the improvement of knowledge in digital marketing tools applied to tourism and for this industry stakeholders. © 2018, Springer International Publishing AG, part of Springer Nature.