Abstract
E-commerce is a field that changed how consumers purchase and interact with products. Although, inherent limitations such as the difficulty of testing the products first-hand before a purchase can compromise consumers' trust in online purchases. Virtual Reality (VR) has been investigated as a tool to solve limitations in several fields and how we can harness its potential to improve the overall user experience. This study analysed how immersive VR (IVR) could solve these limitations by allowing consumers to test products beforehand. We have studied how the Novelty Factor (evaluated by the users' past VR experience) and Immersive Tendencies correlate with the users' Purchase Intention and Memory (how well they remember the product's characteristics). We have analysed a sample of 38 participants (21 males) from 18 to 28 years old. Participants experienced a refrigerator with an interactive touchscreen in an IVR setup and were guided through its functionalities. Results indicated that memory of the product's characteristics was positively correlated with how recently they experienced VR. No correlations were found in the female sample. A negative correlation between Purchase Intention and Memory of the product's characteristics was found in the male sample. We concluded that IVR applications could become helpful for both consumers and online shops in an e-commerce context regardless of the Novelty Factor and Immersive Tendencies of consumers. However, differences between genders should be further investigated.

Abstract

Abstract
Network comparison is a widely used tool for analysing complex systems, with applications in varied domains including comparison of protein interactions or highlighting changes in structure of trade networks. In recent years, a number of network comparison methodologies based on the distribution of graphlets (small connected network subgraphs) have been introduced. In particular, NetEmd has recently achieved state of the art performance in undirected networks. In this work, we propose an extension of NetEmd to directed networks and deal with the significant increase in complexity of graphlet structure in the directed case by denoising through linear projections. Simulation results show that our framework is able to improve on the performance of a simple translation of the undirected NetEmd algorithm to the directed case, especially when networks differ in size and density.

Abstract
Nowadays, the consumption of media content has been growing rapidly and consistently, driven by an easy access to Video on Demand platforms. In this context, licensing is needed to ensure that filmmakers receive rightful payment for their content and ensure that their rights as content owners are respected. The traditional licensing process, which is heavily dependent on third parties (legal entities) to mediate the transaction, is very long, costly, and complex, which is a barrier to smaller independent filmmakers. The solution proposed in this work, to address this problem, is to create a business-to-business marketplace platform supported by a Blockchain licensing module. This module takes advantage of Blockchain technology to ensure the licensing requirements and to provide a secure, practical and straightforward way to license media in a decentralised paradigm. The result of this work was validated though a prototype, and a global assessment of the system's usability was performed using the System Usability Scale, where it got the best possible grade.

Abstract

Abstract