Object-Based Greenhouse Mapping Using Very High Resolution Satellite Data and Landsat 8 Time Series

Greenhouse mapping through remote sensing has received extensive attention over the last decades. In this article, the innovative goal relies on mapping greenhouses through the combined use of very high resolution satellite data (WorldView-2) and Landsat 8 Operational Land Imager (OLI) time series within a context of an object-based image analysis (OBIA) and decision tree classification. Thus, WorldView-2 was mainly used to segment the study area focusing on individual greenhouses. Basic spectral information, spectral and vegetation indices, textural features, seasonal statistics and a spectral metric (Moment Distance Index, MDI) derived from Landsat 8 time series and/or WorldView-2 imagery were computed on previously segmented image objects. In order to test its temporal stability, the same approach was applied for two different years, 2014 and 2015. In both years, MDI was pointed out as the most important feature to detect greenhouses. Moreover, the threshold value of this spectral metric turned to be extremely stable for both Landsat 8 and WorldView-2 imagery. A simple decision tree always using the same threshold values for features from Landsat 8 time series and WorldView-2 was finally proposed. Overall accuracies of 93.0% and 93.3% and kappa coefficients of 0.856 and 0.861 were attained for 2014 and 2015 datasets, respectively

Spreadsheet as a didactic tool to teach and learn financial math

In this document we propose a methodology to teach financial mathematics, using a spreadsheet as a didactic tool. We describe the traditional education process in a specific topic of mathematics, “debt restructuring and modeling with equivalent-equation” from the theoretical explanation to design a financial simulator programmed in a spreadsheet. After this, the result will be verified and validated by the designed software.TIC, Financial mathematics, teaching-learning process, financial tools.

Earnings management and corporate social responsibility

By drawing on stakeholder-agency theory and the earnings management framework, we hypothesize a positive connection between corporate social responsibility and earnings management. We argue that earnings management damages the interests of stakeholders. Hence, managers who manipulate earnings can deal with stakeholder activism and vigilance by resorting to corporate social responsibility (CSR) practices. Furthermore, CSR is a powerful tool that can be used to garner support from stakeholders and, therefore, provides an avenue for entrenchment to those managers that manipulate earnings, so as to reduce significantly their chances of being fired. Finally, we expect that the positive connection between corporate social responsibility and financial performance is negatively moderated when combined with earnings management practices. We demonstrate empirically our theoretical contention by making use of a database comprising 593 firms from 26 nations for the period 2002-2004

Ciclo de Mejora Docente para la asignatura de Diseño y aplicaciones multimedia del Grado en Comunicación Audiovisual

Experiencia de diseño, realización y autoevaluación de un ciclo de mejora de 12 horas para la asignatura de Diseño y Aplicaciones Multimedia del Grado en Comunicación Audiovisual en la Universidad de Sevilla durante el curso 2018/2019

An Intelligent Traction Control for Motorcycles

The appearance of anti-lock braking systems (ABS) and traction control systems (TCS) have been some of the most major developments in vehicle safety. These systems have been evolving since their origin, always keeping the same objective, by using increasingly sophisticated algorithms and complex brake and torque control architectures. The aim of this work is to develop and implement a new control model of a traction control system to be installed on a motorcycle, regulating the slip in traction and improving dynamic performance of two-wheeled vehicles. This paper presents a novel traction control algorithm based on the use of Artificial Neural Networks (ANN) and Fuzzy Logic. An ANN is used to estimate the optimal slip of the surface the vehicle is moving on. A fuzzy logic control block, which makes use of the optimal slip provided by the ANN, is developed to control the throttle position. Two control blocks have been tuned. The first control block has been tuned according to the experience of an expert operator. The second one has been optimized using Evolutionary Computation (EC). Simulation shows that the use of EC can improve the fuzzy logic based control algorithm, obtaining better results than those produced with the control tuned only by experience.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech