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This paper presents the design of intelligent models and architectures for global learning-oriented cooperation. The research work brings our current investigations towards the definition of a general development methodology for global intelligent systems. We use a basic top-down approach to analyze global cooperation, adding more natural intelligence into our models. Then we design, integrate and adapt software architectures to be able to extract the computational requirements of our systems at an appropriate level of abstraction. Our architectural designs serve to dynamically generate cooperative knowledge and behaviour using hybrid registries and intelligent engines. The registries store knowledge and behaviour descriptions. The functional engines control knowledge delivery processes and behaviour executions involving single and composite actions. All these elements are evaluated using a designing case study in current Sustainable Development Goals for education. This last part of the paper also discusses how our intelligent models and architectures can be further developed adding implementation details based on recent technologies.

Backtesting represents a set of techniques that aim to evaluate trading strategies on historical data in order to verify their effectiveness before applying them to a market in real time. This requires processing large amounts of data from different periods and applying different simulation techniques to them. In general, these types of tools are not very popular for reasons such as the amount of data that must be evaluated and maintained, the computational resources that are required, and the need to have a deep conceptual understanding of these techniques in order to use them. This article presents a web application that implements a set of backtesting functionalities that allow evaluating different trading strategies, managing portfolios, representing the results of simulations, and optimizing a stock portfolio, all from an intuitive and visual interface that makes these techniques accessible to new investors in this field.

Violence involving firearms in the USA is a very important problem. As a consequence, a large number of crimes of this type are recorded every year. However, the solutions proposed have not managed to reduce the number of this type of crime. One of the cities with a large number of violent crimes is New York City. The number of crimes is not homogeneous and depends on the district where they occur. This paper proposes to study the information about the crimes in which firearms are involved with the aim of characterizing the factors on which the occurrence of this type of crime depends, such as the levels of poverty and culture. Since the districts are not homogeneous, the information has been analyzed at the district level. For this, data from the open data portal of the city of New York have been used and machine-learning techniques have been used. The results have shown that the variables on which they depend are different in each district.

Meteorological phenomena is an area in which a large amount of data is generated and where it is more difficult to make predictions about events that will occur due to the high number of variables on which they depend. In general, for this, probabilistic models are used that offer predictions with a margin of error, so that in many cases they are not very good. Due to the aforementioned conditions, the use of machine learning algorithms can serve to improve predictions. This article describes an exploratory study of the use of machine learning to make predictions about the phenomenon of rain. To do this, a set of data was taken as an example that describes the measurements gathered on rainfall in the main cities of Australia in the last 10 years, and some of the main machine learning algorithms were applied (knn, decision tree, random forest, and neural networks). The results show that the best model is based on neural networks.

Software engineering is a complicated subject for computer engineering students since the explained knowledge and necessary competencies are more related to engineering as a general knowledge area than to computer science. This article describes a software engineering learning application that aims to provide a solution to this problem. Two ideas are used for this. On the one hand, to facilitate its use it has been implemented as an Android app (in this way it can be used anywhere and at any time). In addition, and on the other hand, a gamification system has been implemented with different learning paths that adapt to the learning styles of each student. In this way, the student is motivated by competing with other classmates, and on the other hand, the application adapts to the way of learning that each one has.

In all areas of knowledge, there is a set of basic concepts or ideas that are essential to understand. A very common problem that arises among students is the difficulty in acquiring these concepts. One way to solve this problem is by carrying out small knowledge tests where these concepts are put into practice. To develop these tests there are multiple options, however, in general, the applications that allow for these tests to be implemented are usually very complex and are often included within other larger systems. This article describes a tool to develop short online courses that presents an interface and a functionality that allows a teacher to create and manage courses in a very simple and intuitive way. In the same way, it offers the student an Android app to be able to access the courses published by the teacher to be able to take them, as well as to manage all the activity of it.

In recent decades, electronic books have revolutionized the publishing world. In this sense, an area of application is education, where electronic books can be used as educational resources to implement learning strategies about content and in eLearning environments. For this, it is necessary to introduce interactive elements in the electronic books that turn the reader into an active actor in the reading process. However, ebooks have a limitation regarding their creation process. In this sense, the tools can be user-oriented or programmer-oriented. The former are intuitive to use and have user-friendly interfaces, but they offer a reduced number of functionalities to add to books. The second are aimed at programmers, allowing for the implementation of any functionality, but limiting the number of content creators who can use them. The main motivation of this work is to propose an intermediate solution that offers a wide number of functionalities while not requiring deep programming knowledge to use them. In this sense, the solution of this article is novel since it proposes the use of extensible markup language (XML) documents to specify the structure of the electronic book in such a way that its processing will lead to the electronic book.

A general problem in large cities is mobility. Every day, there are incidents (accidents, construction, or meteorological events) that increase the duration of the journeys in a city and exert negative effects on the lives of citizens. A particular case of this situation is communications with airports. Shuttles are a type of private transport service that operates in airports. The number of passengers carried by shuttles is small. Moreover, shuttles transport passengers to their final destinations and their prices are more competitive than those other private services. However, shuttle services have a limitation with respect to their routes due to the many different destinations of passengers. For this reason, it is important to be able to calculate the best route to optimize the journey. This work presents an Android application that implements a value-added service to plan the route of a shuttle and manage its service (passengers, journeys, routes, etc.). This application combines information from different sources, such as geolocation information from the shuttle driver’s mobile phone, information on the passengers, and results obtained from the service offered by MapBox to calculate the optimized route between several destinations.