Numerical resolution of Emden's equation using Adomian polynomials

Purpose: In this paper the authors aim to show the advantages of using the decomposition method introduced by Adomian to solve Emden's equation, a classical non‐linear equation that appears in the study of the thermal behaviour of a spherical cloud and of the gravitational potential of a polytropic fluid at hydrostatic equilibrium. Design/methodology/approach: In their work, the authors first review Emden's equation and its possible solutions using the Frobenius and power series methods; then, Adomian polynomials are introduced. Afterwards, Emden's equation is solved using Adomian's decomposition method and, finally, they conclude with a comparison of the solution given by Adomian's method with the solution obtained by the other methods, for certain cases where the exact solution is known. Findings: Solving Emden's equation for n in the interval [0, 5] is very interesting for several scientific applications, such as astronomy. However, the exact solution is known only for n=0, n=1 and n=5. The experiments show that Adomian's method achieves an approximate solution which overlaps with the exact solution when n=0, and that coincides with the Taylor expansion of the exact solutions for n=1 and n=5. As a result, the authors obtained quite satisfactory results from their proposal. Originality/value: The main classical methods for obtaining approximate solutions of Emden's equation have serious computational drawbacks. The authors make a new, efficient numerical implementation for solving this equation, constructing iteratively the Adomian polynomials, which leads to a solution of Emden's equation that extends the range of variation of parameter n compared to the solutions given by both the Frobenius and the power series methods.This work has been supported by the Ministerio de Ciencia e Innovación, project TIN2009-10581

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.This work has been supported by the Spanish Ministerio de Ciencia e Innovación (www.micinn.es), project TIN2009-10581

Learning a Swarm Foraging Behavior with Microscopic Fuzzy Controllers Using Deep Reinforcement Learning

This article presents a macroscopic swarm foraging behavior obtained using deep reinforcement learning. The selected behavior is a complex task in which a group of simple agents must be directed towards an object to move it to a target position without the use of special gripping mechanisms, using only their own bodies. Our system has been designed to use and combine basic fuzzy behaviors to control obstacle avoidance and the low-level rendezvous processes needed for the foraging task. We use a realistically modeled swarm based on differential robots equipped with light detection and ranging (LiDAR) sensors. It is important to highlight that the obtained macroscopic behavior, in contrast to that of end-to-end systems, combines existing microscopic tasks, which allows us to apply these learning techniques even with the dimensionality and complexity of the problem in a realistic robotic swarm system. The presented behavior is capable of correctly developing the macroscopic foraging task in a robust and scalable way, even in situations that have not been seen in the training phase. An exhaustive analysis of the obtained behavior is carried out, where both the movement of the swarm while performing the task and the swarm scalability are analyzed.This work was supported by the Ministerio de Ciencia, Innovación y Universidades (Spain), project RTI2018-096219-B-I00. Project co-financed with FEDER funds

Modelling Oil-Spill Detection with Swarm Drones

Nowadays, swarm robotics research is having a great increase due to the benefits derived from its use, such as robustness, parallelism, and flexibility. Unlike distributed robotic systems, swarm robotics emphasizes a large number of robots, and promotes scalability. Among the multiple applications of such systems we could find are exploring unstructured environments, resource monitoring, or distributed sensing. Two of these applications, monitoring, and perimeter/area detection of a given resource, have several ecological uses. One of them is the detection and monitoring of pollutants to delimit their perimeter and area accurately. Maritime activity has been increasing gradually in recent years. Many ships carry products such as oil that can adversely affect the environment. Such products can produce high levels of pollution in case of being spilled into sea. In this paper we will present a distributed system which monitors, covers, and surrounds a resource by using a swarm of homogeneous low cost drones. These drones only use their local sensory information and do not require any direct communication between them. Taking into account the properties of this kind of oil spills we will present a microscopic model for a swarm of drones, capable of monitoring these spills properly. Furthermore, we will analyse the proper macroscopic operation of the swarm. The analytical and experimental results presented here show the proper evolution of our system.This work has been supported by the Spanish Ministerio de Ciencia e Innovación, Project TIN2009-10581

Potencialidad productiva y rendimientos cerealícolas en la agricultura catalana contemporánea (1820-1935) Resumen

El objeto del articulo es la evolución de los rendimientos cerealícolas en Cataluña entre 1820 Y 1835. A partir de la reconstrucción de tres series de rendimientos, elaboradas con datos procedentes de contabilidades privadas y correspondientes a distintas zonas geográficas (Osona, Segarra, Solsonés y Urgell), se analizan las tendencias a largo plazo de los rendimientos cerealícolas y las variaciones en la intensidad de sus fluctuaciones interanuales. Los resultados procedentes de estas series se contrastan con datos puntuales procedentes de otras fuentes documentales y se comparan con las informaciones disponibles sobre otras comarcas catalanas para, finalmente, plantear hasta qué punto las dotaciones medioambientales fueron el factor explicativo básico de las disparidades comarcales en los rendimientos agrícolas catalanes.The aim of this article is and elucidation of the pattern of cereals yields in Catalonia between 1820 and 1835. From a reconstruction of three time series of yields derived from data in private account books and related to distinct geographical areas (Osona, Segarra, Solsonès, Urgell) the long term tendencies and the variation in the intensity of annual fluctuations are analysed. The results are contrasted with specific data from other documentary sources and compared with the available information on other parts of Catalonia in order to consider how far environmental factors can be regarded as the basis reason for the disparities in cereal yields between different parts of Catalonia

La utilización de las NTIC en la enseñanza de la mecànica

Es bien sabido que el diseño clásico, por las cadencias usuales de trabajo y por las dificultades de cálculo, solía basarse en un análisis cinemático y, como mucho, estático de las máquinas. Actualmente es posible y, además, necesario hacer un estudio completo. Señalemos ahora que la presente comunicación es una aplicación de la metodología propuesta anteriormente. En el caso actual se aplican las NTIC al análisis cinemático de una máquina, como preámbulo a un ulterior estudio dinámico. Digamos, por su relevancia didáctica, que se utilizarán varias cámaras para visualizar los movimientos de un punto dado respecto a observadores distintos; este tema en su presentación tradicional suele presentar dificultades para los alumnos.Eje: Educación universitaria: Experiencias uso NTICRed de Universidades con Carreras en Informática (RedUNCI

La utilización de las NTIC en la enseñanza de la mecànica

Es bien sabido que el diseño clásico, por las cadencias usuales de trabajo y por las dificultades de cálculo, solía basarse en un análisis cinemático y, como mucho, estático de las máquinas. Actualmente es posible y, además, necesario hacer un estudio completo. Señalemos ahora que la presente comunicación es una aplicación de la metodología propuesta anteriormente. En el caso actual se aplican las NTIC al análisis cinemático de una máquina, como preámbulo a un ulterior estudio dinámico. Digamos, por su relevancia didáctica, que se utilizarán varias cámaras para visualizar los movimientos de un punto dado respecto a observadores distintos; este tema en su presentación tradicional suele presentar dificultades para los alumnos.Eje: Educación universitaria: Experiencias uso NTICRed de Universidades con Carreras en Informática (RedUNCI

A macroscopic model for high intensity radiofrequency signal detection in swarm robotics systems

In recent years, there has been a growing interest in resource location in unknown environments for robotic systems, which are composed of multiple simple robots rather than one highly capable robot [M. Sempere, F. Aznar, M. Pujol, and R. Rizo, On cooperative swarm foraging for simple, non explicitly connected, agents, 2010]. This tradeoff reduces the design and hardware complexity of the robots and removes single point failures, but adds complexity in algorithm design. The challenge is to programme a swarm of simple robots, with minimal intercommunication and individual capability, to perform a useful task as a group. This paper is focused on finding the highest intensity area of a radiofrequency (RF) signal in urban environments. These signals are usually more intense near the city centre and its proximity, since in these zones the risk of signal saturation is high. RF radiation (RFR) is boosted or blocked mainly depending on orography or building structures. RF providers need to supply enough coverage, setting up different antennas to be able to provide a minimum quality of service. We will define a micro/macroscopic mathematical model to efficiently study a swarm robotic system, predict their long-term behaviour and gain insight into the system design. The macroscopic model will be obtained from Rate Equations, describing the dynamics of the swarm collective behaviour. In our experimental section, the Campus of the University of Alicante will be used to simulate our model. Three RFR antennas will be taken into account, one inside our Campus and the other two in its perimeter. Several tests, that show the convergence of the swarm towards the RFR, will be presented. In addition, the obtained RFR maps and the macroscopic behaviour of the swarm will be discussed.This work has been supported by the Spanish Ministerio de Ciencia e Innovación, project TIN2009-10581

El Barceloneta I. Una embarcación medieval a tingladillo en Barcelona

El año 2008 una intervención arqueológica en un solar cercano al port vell de Barcelona permitió estudiar y localizar una importante área del puerto medieval de la ciudad entre el que destacaria el muelle construido en el año 1477 y un pecio de construcción de casco previo y a tingladillo. El presente artículo realiza una aproximación al pecio Barceloneta I desde diferentes enfoques como los estudios palinológicos, dedrocronológicos, además del estudio histórico y arquitectónico. El conjunto de resultados permite situar la embarcación como la evidencia material de las complejas redes de comunicación maritima entre Altántico y el Mediterráneo en época Bajo Medieval, así como avanzar en el conocimiento de la construcción naval en éste periodo.Untzi Museoa - Museo maritimoPeer Reviewe

A swarm behaviour for jellyfish bloom detection

In this paper we will deal with the issue of swarm behaviour for jellyfish detection using UAVs (unmanned aerial vehicles). Swarm behaviour is inspired by the functioning of biological swarms. They are characterized by being fully distributed, scalable and fault-tolerant. Initially, we will study the behaviour of jellyfish and their impact and interaction with industry. Motivated by the need to improve current detection systems, we will propose a swarm behaviour that will be formalized with a microscopic model. We will discuss both the convergence and the scalability of the model. Finally, a macroscopic model will be provided to predict the probability that an individual is placed in a position at a given moment.This work has been carried out by the project “Intelligent Swarm Systems of Unmanned Aerial Vehicles for Security and Surveillance” TIN2013-40982-R, Ministerio de Economía y Competitividad, Spain. Project co-financed with FEDER funds