Abstract
Device identity management and authentication are one of the critical and primary security challenges in IoT. In order to decrease the IoT attack surface and provide protection from security threats such as introduction of fake IoT nodes and identity theft, IoT requires scalable device identity management systems and resilient device authentication mechanisms. Existing mechanisms for device identity management and device authentication were not designed for huge number of devices and therefore are not suitable for IoT environments. This work presents results of a blockchain-based identity management approach with consensus authentication, as a scalable solution for IoT device authentication management. Our identity management approach relies on having a blockchain secure tamper proof registry and lightweight consensus-based identity authentication.

Abstract
In a world in permanent (r)evolution that revolves around money, seeking new ways to contain costs, better allocate resources, and, overall, improve performance is a constant across all fields. Hence, the use of computational methods based on operational research and statistical science is crucial for achieving an appropriate combination of efficiency and effectiveness, especially in domains where the decision-making process is a complex task. This is where Data Envelopment Analysis (DEA) comes in. However, as a non-parametric and, usually, purely objective technique, DEA makes up for what it lacks in incorporating preference information with flexibility and adaptability, which is particularly important in areas where the decision-makers' judgments are crucial. This work proposes a cutting-edge and original approach to fill in this knowledge gap by linking DEA and multiple criteria decision-making with an additive DEA model that takes into account criteria interactivity, by using an inference methodology to determine their weights, and decision-makers' preference information incorporation, by taking advantage of the Choquet multiple criteria preference aggregation model. Thus, this approach was applied to a case study of performance assessment of Portuguese National Healthcare Service secondary healthcare providers across robustness-testing perspectives, generating credible weights stemmed from the decision-maker's judgments and yielding acceptable and valid results.

Abstract
Graphs with a large number of nodes and edges are difficult to visualize. Semantic graphs add to the challenge since their nodes and edges have types and this information must be mirrored in the visualization. A common approach to cope with this difficulty is to omit certain nodes and edges, displaying sub-graphs of smaller size. However, other transformations can be used to summarize semantic graphs and this research explores a particular one, both to reduce the graph's size and to focus on its path patterns. A-graphs are a novel kind of graph designed to highlight path patterns using this kind of summarization. They are composed of a-nodes connected by a-edges, and these reflect respectively edges and nodes of the semantic graph. A-graphs trade the visualization of nodes and edges by the visualization of graph path patterns involving typed edges. Thus, they are targeted to users that require a deep understanding of the semantic graph it represents, in particular of its path patterns, rather than to users wanting to browse the semantic graph's content. A-graphs help programmers querying the semantic graph or designers of semantic measures interested in using it as a semantic proxy. Hence, a-graphs are not expected to compete with other forms of semantic graph visualization but rather to be used as a complementary tool. This paper provides a precise definition both of a-graphs and of the mapping of semantic graphs into a-graphs. Their visualization is obtained with a-graphs diagrams. A web application to visualize and interact with these diagrams was implemented to validate the proposed approach. Diagrams of well-known semantic graphs are presented to illustrate the use of agraphs for discovering path patterns in different settings, such as the visualization of massive semantic graphs, the codification of SPARQL or the definition of semantic measures. The validation with large semantic graphs is the basis for a discussion on the insights provided by a-graphs on large semantic graphs: the difference between a-graphs and ontologies, path pattern visualization using a-graphs and the challenges posed by large semantic graphs.

Abstract
Traditionally farmers have used their perceptual sensorial systems to diagnose and monitor their crops health and needs. However, humans possess five basic perceptual systems with accuracy levels that can change from human to human which are largely dependent on the stress, experience, health and age. To overcome this problem, in the last decade, with the help of the emergence of smartphone technology, new agronomic applications were developed to reach better, cost-effective, more accurate and portable diagnosis systems. Conventional smartphones are equipped with several sensors that could be useful to support near real-time usual and advanced farming activities at a very low cost. Therefore, the development of agricultural applications based on smartphone devices has increased exponentially in the last years. However, the great potential offered by smartphone applications is still yet to be fully realized. Thus, this paper presents a literature review and an analysis of the characteristics of several mobile applications for use in smart/precision agriculture available on the market or developed at research level. This will contribute to provide to farmers an overview of the applications type that exist, what features they provide and a comparison between them. Also, this paper is an important resource to help researchers and applications developers to understand the limitations of existing tools and where new contributions can be performed.

Abstract
The utilization of an Energy Management System (EMS) for the optimum scheduling of generation units, as well as demand side resources is essential due to the high penetration of Distributed Energy Resources (DERs) in microgrids (MGs), to achieve the desired objectives. As a result of the restructuring of the power systems and increasing the electricity prices during some periods in a day, demand side programs have been highly valuable by electricity customers. In this paper, a Demand Response (DR) model has been proposed to present the behavior of responsive controllable loads in response to the DR calls. Moreover, optimal scheduling of energy resources is developed for a typical MG by considering the presence of both electrical and thermal demands. Combined Heat and Power (CHP) units, boilers, wind turbines, storage devices, demand response resources (DRRs), as well as the power exchange possibility with the upstream wholesale market are the energy resources that have been considered as the portfolio of the decision maker. Furthermore, the uncertainty resources of the wind speeds and electrical load are handled by the Information Gap Decision Theory (IGDT) method. The performance of the proposed framework is comprehensively analyzed on the IEEE 33-bus test system. The advantage of the proposed methodology under the uncertainty conditions is analyzed by the Monte-Carlo simulation method when the different realization of the wind power and electrical load are considered.

Abstract
Around the world, there is a great concern with the emission of greenhouse gases, creating great interest in turning the energy systems more sustainable. Multi-energy systems are considered as a potential solution to help to this cause and in recent years, it has gained much attention from both research and industry. In this paper, an optimization model is proposed to use the flexibility of multi-energy systems to mitigate the uncertainty associated with wind generation. The differences between the flexibility provided by multi-energy systems and electrical storage systems in the network were studied. The results prove that the flexibility of the multi-energy systems can benefit the system in several aspects and provide insights on which is the best approach to take full advantage of renewable resources even when a high degree of uncertainty is present.