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

Abstract
Over the years, workers have joined in producer organizations to face the difficulties that the capitalist market poses to them. Together they can gain efficiency and equity compared to big companies, and they can gain bargaining power over the product market. In our case, we target smallholder farmers who face many difficulties in increasing their welfare. To overcome them, they group together in producer organizations such as cooperatives. With the development of technology, it became possible for these cooperatives of workers to use the Web to operate - such type of organization and operation is called a Platform Cooperative (PC). This paper presents a multi-agent based modeling of Farmers' Coalition Formation (FCF) for smallholder farmers so that they can operate by means of a Platform cooperative. We present the design of a characteristic function that calculates the coalition values in this context, finds the best way of partitioning the farmers into smaller groups and divides the payoff in a stable manner. We empirically analyze the model using value distributions. The results show that forming coalitions is profitable for farmers. We also proved that the model ensures a fair distribution of the payoff among the farmers.

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.