Virtual Reality (VR) has the capacity to be used in cognitive rehabilitation interventions for diagnostic and training purposes. This technology allows the development of proposals that traditionally have been only implemented using physical elements that imply greater resources and a lesser degree of automation. This work presents an immersive virtual reality (IVR) application (the Cupboard task) for the evaluation of memory in a more ecological way and based on an activity of daily living (ADL). To appraise its construct validity, we have carried out a comparative study with a traditional method of memory assessment (method of loci). To check for any association between performance and age, performance with years of education, and reaction time with age, the Pearson's correlation was used. One-way ANOVA was used to check for differences in performance by gender. We also performed a reliability analysis with a two way mixed effects model where people effects are random and measures effects are fixed. Therefore, intra-class correlation coefficient with absolute agreement was reckoned to assess the consistency or concordance of the measures made by both the method of loci and the cupboard IVR task. Both tasks were evaluated on a sample of 22 healthy participants who voluntarily took part in the experiment. The results obtained showed a high degree of concordance between both memory performance measures, which assumes good clinical relevance. In addition, other age-related effects were found, common to memory assessment tasks. This work showed that it is possible to use an IVR application to successfully assess everyday memory. We have also demonstrated the potential of IVR to develop valid tests that assess memory functions reliably and efficiently and within ecologically valid contexts. The results obtained open the door to its use in clinical settings for cognitive training (and promoting cognitive health) of patients with mild cognitive impairment (MCI), severe cognitive impairment (SCI) such as Alzheimer or Dementia, etc., with full guarantees of application, although it must first be validated through a randomized control trial (RCT). The degree of usability of the Cupboard task was very high according to the test carried out by the participants.

The last decade has witnessed a steep growth in multimedia traffic due to real‐time content delivery such as in online games and video conferencing. In some contexts, MANETs play a key role in the hyperconnectivity of everything in multimedia services. In this context, this work proposes a new scheduling approach based on context‐aware mobile nodes for their connectivity. The contribution relies on reporting not only the locations of devices in the network but also their movement identified by sensors. In order to illustrate this approach, we have developed a novel agent‐based simulator called MASEMUL for illustrating the proposed approach. The results show that a movement‐aware scheduling strategy defined with the proposed approach has decreased the ratio of channel interruptions over another common strategy in mobile networks.

Abstract This work presents an extensive case study on modelling the DAX (Deutscher Aktienindex) index and United States Oil Fund (USO) exchange‐traded fund (Etf) time series with the financial agent‐based system learning financial agent‐based simulator (L‐FABS) that exploits simulated annealing as a learning method. The USO Etf time series is highly correlated with oil price behaviour, and the DAX index is based on the weighted and accumulated behaviour of the share prices of some of the largest companies traded on the Frankfurt Stock Exchange. These two time series are driven by completely different economic factors and thus provide two diverse empirical settings to evaluate the effectiveness of our methodology. Our experimentation shows that a relatively simple computational representation of real financial markets is effective in capturing the overall behaviour of the time series with varying approximation levels while the prediction target is moved into the future. The reported experimental investigation of L‐FABS shows that it is robust notwithstanding the learning method used and the data sets exploited. L‐FABS indeed produced a relatively low approximation error in several settings even when evaluated with respect to other modelling approaches, for example, 0.88% and 1.61% errors on average for 1 day ahead experiments in, respectively, DAX index and USO Etf.

The Internet of Vehicles (IoV) provides new opportunities for the coordination of vehicles for enhancing safety and transportation performance. Vehicles can be coordinated for avoiding collisions by communicating their positions when near to each other, in which the information flow is indexed by their geographical positions or the ones in road maps. Vehicles can also be coordinated to ameliorate traffic jams by sharing their locations and destinations. Vehicles can apply optimization algorithms to reduce the overuse of certain streets without excessively enlarging the paths. In this way, traveling time can be reduced. However, IoV also brings security challenges, such as keeping safe from virtual hijacking. In particular, vehicles should detect and isolate the hijacked vehicles ignoring their communications. The current work presents a technique for enhancing security by applying certain prioritization rules, using digital certificates, and applying trust and reputation policies for detecting hijacked vehicles. We tested the proposed approach with a novel agent-based simulator about security in Internet of Things (IoT) for vehicle-to-vehicle communications. The experiments focused on the scenario of avoidance of collisions with hijacked vehicles misinforming other vehicles. The results showed that the current approach increased the average speed of vehicles with a 64.2% when these are giving way to other vehicles in a crossing by means of IoT.

The impact of Internet of Things has been revolutionized in all fields of life, but its impact on the healthcare system has been significant due to its cutting edge transition. The role of Internet of Things becomes more dominant when it is supported by the features of mobile computing. The mobile computing extends the functionality of IoT in healthcare environment by bringing a massive support in the form of mobile health (m-health). In this research, a systematic literature review protocol is proposed to study how mobile computing assists IoT applications in healthcare, contributes to the current and future research work of IoT in the healthcare system, brings privacy and security in health IoT devices, and affects the IoT in the healthcare system. Furthermore, the intentions of the paper are to study the impacts of mobile computing on IoT in healthcare environment or smart hospitals in light of our systematic literature review protocol. The proposed study reports the papers that were included based on filtering process by title, abstract, and contents, and a total of 116 primary studies were included to support the proposed research. These papers were then analysed for research questions defined for the proposed study.

Sensor networks and Internet of Things (IoT) are useful for many purposes such as military defense, sensing in smart homes, precision agriculture, underwater monitoring in aquaculture, and ambient‐assisted living for healthcare. Efficient and secure data forwarding is essential to maintain seamless communications and to provide fast services. However, IoT devices and sensors usually have low processing capabilities and vulnerabilities. For example, attacks such as the Distributed Denial of Service (DDoS) can easily hinder sensor networks and IoT devices. In this context, the current approach presents an agent‐based simulation solution for exploring strategies for defending from different DDoS attacks. The current work focuses on obtaining low‐consuming defense strategies in terms of processing capabilities, so that these can be applied in sensor networks and IoT devices. The experimental results show that the simulator was useful for (a) defining defense and attack strategies, (b) assessing the effectiveness of defense strategies against attack ones, and (c) defining efficient defense strategies with low response times.

Software-defined networks (SDNs) have become a mechanism to separate the control plane and the data plane in the communication in networks. SDNs involve several challenges around their security and their confidentiality. Ideally, SDNs should incorporate autonomous and adaptive systems for controlling the routing to be able to isolate network resources that may be malfunctioning or whose security has been compromised with malware. The current work introduces a novel agent-based framework that simulates SDN isolation protocols by means of trust and reputation models. This way, SDN programmers may estimate the repercussions of certain isolation protocols based on trust models before actually deploying the protocol into the network.

Smart cities still need the appropriate tools for allowing researchers to contribute in this growing field that will change the comfort and qualities of live of citizens. Smart cities can provide services such as informing of the less overcrowded tourist routes, path-finding for avoiding traffic jams, search services for parking, collecting tree branches from streets, and the finding of the nearest available public electric bicycles or cars. The levels of urgencies differ from some situations to others. Examples of urgent matters are the fast transportation critical patients and the removal of obstacles in main roads. Since smart cities are meant to manage huge amounts of requests, priorities should be automated and managed in a flexible way for new scenarios. Smart cities may need citizens to report the service priorities. However, citizens may have different criteria and could abuse the highest priority levels hindering the service performance for really urgent matters. A novel agent-based simulation open-source framework is proposed for testing different policies for normalizing and controlling self-reported priorities, with its simulator called ABS-SmartPriority. This approach is illustrated by simulating two different policies, in which the smart policy outperformed the one used as the control mechanism.

Accurate student identification has usually been considered important in the field of e-learning. Nowadays, there are several technologies to identify students and one of them is facial authentication (by means of biometrics), which allows user identities to be authenticated and verified based on their physiological features of their faces. There is actually a high demand of students wanting to gain admission to e-learning programs. Therefore, it is crucial for this kind of education to be as adequate and recognized as any other. For this purpose, it is necessary to verify the students’ identity when they are doing their homework using the Learning Management Systems (LMSs) such as Moodle platform. The main objective of this research is to analyze student perceptions about the development and implementation of facial authentication for e-learning within the Moodle platform in different Hispanic speaking countries (Spain, Dominican Republic and Colombia). This analysis also takes into account the different kinds of activities such as continuous evaluation activities, learning activities and tests. Furthermore, the students were surveyed after using the facial authentication tool within Moodle, so this study also collects the student perceptions when being facial authenticated while performing e-learning activities.

The FIPA Methodology Technical Committee has proposed a method engineering approach for multi-agent systems development. This approach consists on defining method fragments from agent-oriented software engineering methodologies. Developers combine fragments to define a customized development process. In this line of research, the contribution of this paper is a set of method fragments that are assisted by model transformations, in order to allow engineers to better develop multi-agent systems in an automated way. This set of method fragments is grounded on the experience the development process of two multi-agent systems. This paper presents the formalization of the fragments and an example of the automation of a fragment with a model transformation.