A methodology for the implementation and continuous improvement of social responsibility (RS) and financial responsibility

This work sets out an innovative methodology that aims to facilitate the implementation and continuous improvement of Social Responsibility. It is a methodology that takes account of strategic-economic, social and environmental questions and allows measuring the impact of each of these aspects on the stakeholders and on each of the value areas. It can be extrapolated to all kinds of organisations regardless of their size and sector and admits scaleable models. A marked feature that sets it aside from other methodologies is that it eliminates subjectivity from the qualitative aspects and introduces an algorithm to quantify them.

An example of integration between en economic and an hydrologic model in the framework of water resource management problems

Growing scarcity, increasing demand and bad management of water resources are causing weighty competition for water and consequently managers are facing more and more pressure in an attempt to satisfy users? requirement. In many regions agriculture is one of the most important users at river basin scale since it concentrates high volumes of water consumption during relatively short periods (irrigation season), with a significant economic, social and environmental impact. The interdisciplinary characteristics of related water resources problems require, as established in the Water Framework Directive 2000/60/EC, an integrated and participative approach to water management and assigns an essential role to economic analysis as a decision support tool. For this reason, a methodology is developed to analyse the economic and environmental implications of water resource management under different scenarios, with a focus on the agricultural sector. This research integrates both economic and hydrologic components in modelling, defining scenarios of water resource management with the goal of preventing critical situations, such as droughts. The model follows the Positive Mathematical Programming (PMP) approach, an innovative methodology successfully used for agricultural policy analysis in the last decade and also applied in several analyses regarding water use in agriculture. This approach has, among others, the very important capability of perfectly calibrating the baseline scenario using a very limited database. However one important disadvantage is its limited capacity to simulate activities non-observed during the reference period but which could be adopted if the scenario changed. To overcome this problem the classical methodology is extended in order to simulate a more realistic farmers? response to new agricultural policies or modified water availability. In this way an economic model has been developed to reproduce the farmers? behaviour within two irrigation districts in the Tiber High Valley. This economic model is then integrated with SIMBAT, an hydrologic model developed for the Tiber basin which allows to simulate the balance between the water volumes available at the Montedoglio dam and the water volumes required by the various irrigation users.

Grid Global Behavior Prediction

Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach.

Assessing urban mobility through participatory scenario building and combined utility-regret assessment

La planificación de la movilidad sostenible urbana es una tarea compleja que implica un alto grado de incertidumbre debido al horizonte de planificación a largo plazo, la amplia gama de paquetes de políticas posibles, la necesidad de una aplicación efectiva y eficiente, la gran escala geográfica, la necesidad de considerar objetivos económicos, sociales y ambientales, y la respuesta del viajero a los diferentes cursos de acción y su aceptabilidad política (Shiftan et al., 2003). Además, con las tendencias inevitables en motorización y urbanización, la demanda de terrenos y recursos de movilidad en las ciudades está aumentando dramáticamente. Como consecuencia de ello, los problemas de congestión de tráfico, deterioro ambiental, contaminación del aire, consumo de energía, desigualdades en la comunidad, etc. se hacen más y más críticos para la sociedad. Esta situación no es estable a largo plazo. Para enfrentarse a estos desafíos y conseguir un desarrollo sostenible, es necesario considerar una estrategia de planificación urbana a largo plazo, que aborde las necesarias implicaciones potencialmente importantes. Esta tesis contribuye a las herramientas de evaluación a largo plazo de la movilidad urbana estableciendo una metodología innovadora para el análisis y optimización de dos tipos de medidas de gestión de la demanda del transporte (TDM). La metodología nueva realizado se basa en la flexibilización de la toma de decisiones basadas en utilidad, integrando diversos mecanismos de decisión contrariedad‐anticipada y combinados utilidad‐contrariedad en un marco integral de planificación del transporte. La metodología propuesta incluye dos aspectos principales: 1) La construcción de escenarios con una o varias medidas TDM usando el método de encuesta que incorpora la teoría “regret”. La construcción de escenarios para este trabajo se hace para considerar específicamente la implementación de cada medida TDM en el marco temporal y marco espacial. Al final, se construyen 13 escenarios TDM en términos del más deseable, el más posible y el de menor grado de “regret” como resultado de una encuesta en dos rondas a expertos en el tema. 2) A continuación se procede al desarrollo de un marco de evaluación estratégica, basado en un Análisis Multicriterio de Toma de Decisiones (Multicriteria Decision Analysis, MCDA) y en un modelo “regret”. Este marco de evaluación se utiliza para comparar la contribución de los distintos escenarios TDM a la movilidad sostenible y para determinar el mejor escenario utilizando no sólo el valor objetivo de utilidad objetivo obtenido en el análisis orientado a utilidad MCDA, sino también el valor de “regret” que se calcula por medio del modelo “regret” MCDA. La función objetivo del MCDA se integra en un modelo de interacción de uso del suelo y transporte que se usa para optimizar y evaluar los impactos a largo plazo de los escenarios TDM previamente construidos. Un modelo de “regret”, llamado “referencedependent regret model (RDRM)” (modelo de contrariedad dependiente de referencias), se ha adaptado para analizar la contribución de cada escenario TDM desde un punto de vista subjetivo. La validación de la metodología se realiza mediante su aplicación a un caso de estudio en la provincia de Madrid. La metodología propuesta define pues un procedimiento técnico detallado para la evaluación de los impactos estratégicos de la aplicación de medidas de gestión de la demanda en el transporte, que se considera que constituye una herramienta de planificación útil, transparente y flexible, tanto para los planificadores como para los responsables de la gestión del transporte. Planning sustainable urban mobility is a complex task involving a high degree of uncertainty due to the long‐term planning horizon, the wide spectrum of potential policy packages, the need for effective and efficient implementation, the large geographical scale, the necessity to consider economic, social, and environmental goals, and the traveller’s response to the various action courses and their political acceptability (Shiftan et al., 2003). Moreover, with the inevitable trends on motorisation and urbanisation, the demand for land and mobility in cities is growing dramatically. Consequently, the problems of traffic congestion, environmental deterioration, air pollution, energy consumption, and community inequity etc., are becoming more and more critical for the society (EU, 2011). Certainly, this course is not sustainable in the long term. To address this challenge and achieve sustainable development, a long‐term perspective strategic urban plan, with its potentially important implications, should be established. This thesis contributes on assessing long‐term urban mobility by establishing an innovative methodology for optimizing and evaluating two types of transport demand management measures (TDM). The new methodology aims at relaxing the utility‐based decision‐making assumption by embedding anticipated‐regret and combined utilityregret decision mechanisms in an integrated transport planning framework. The proposed methodology includes two major aspects: 1) Construction of policy scenarios within a single measure or combined TDM policy‐packages using the survey method incorporating the regret theory. The purpose of building the TDM scenarios in this work is to address the specific implementation in terms of time frame and geographic scale for each TDM measure. Finally, 13 TDM scenarios are built in terms of the most desirable, the most expected and the least regret choice by means of the two‐round Delphi based survey. 2) Development of the combined utility‐regret analysis framework based on multicriteria decision analysis (MCDA). This assessment framework is used to compare the contribution of the TDM scenario towards sustainable mobility and to determine the best scenario considering not only the objective utility value obtained from the utilitybased MCDA, but also a regret value that is calculated via a regret‐based MCDA. The objective function of the utility‐based MCDA is integrated in a land use and transport interaction model and is used for optimizing and assessing the long term impacts of the constructed TDM scenarios. A regret based model, called referente dependent regret model (RDRM) is adapted to analyse the contribution of each TDM scenario in terms of a subjective point of view. The suggested methodology is implemented and validated in the case of Madrid. It defines a comprehensive technical procedure for assessing strategic effects of transport demand management measures, which can be useful, transparent and flexible planning tool both for planners and decision‐makers.

Advanced Characterisation of a Coffee Fermenting Tank by Multi-distributed Wireless Sensors: Spatial Interpolation and Phase Space Graphs

The fermentation stage is considered to be one of the critical steps in coffee processing due to its impact on the final quality of the product. The objective of this work is to characterise the temperature gradients in a fermentation tank by multi-distributed, low-cost and autonomous wireless sensors (23 semi-passive TurboTag® radio-frequency identifier (RFID) temperature loggers). Spatial interpolation in polar coordinates and an innovative methodology based on phase space diagrams are used. A real coffee fermentation process was supervised in the Cauca region (Colombia) with sensors submerged directly in the fermenting mass, leading to a 4.6 °C temperature range within the fermentation process. Spatial interpolation shows a maximum instant radial temperature gradient of 0.1 °C/cm from the centre to the perimeter of the tank and a vertical temperature gradient of 0.25 °C/cm for sensors with equal polar coordinates. The combination of spatial interpolation and phase space graphs consistently enables the identification of five local behaviours during fermentation (hot and cold spots).

Impacts of global change on iberian forest ecosystems inferred from the spanish national forest inventory = Impactos del cambio global en ecosistemas forestales ibéricos a partir del inventario forestal nacional

Los efectos del cambio global sobre los bosques son una de las grandes preocupaciones de la sociedad del siglo XXI. Algunas de sus posibles consecuencias como son los efectos en la producción, la sostenibilidad, la pérdida de biodiversidad o cambios en la distribución y ensamblaje de especies forestales pueden tener grandes repercusiones sociales, ecológicas y económicas. La detección y seguimiento de estos efectos constituyen uno de los retos a los que se enfrentan en la actualidad científicos y gestores forestales. En base a la comparación de series históricas del Inventario Forestal Nacional Español (IFN), esta tesis trata de arrojar luz sobre algunos de los impactos que los cambios socioeconómicos y ambientales de las últimas décadas han generado sobre nuestros bosques. En primer lugar, esta tesis presenta una innovadora metodología con base geoestadística que permite la comparación de diferentes ciclos de inventario sin importar los diferentes métodos de muestreo empleados en cada uno de ellos (Capítulo 3). Esta metodología permite analizar cambios en la dinámica y distribución espacial de especies forestales en diferentes gradientes geográficos. Mediante su aplicación, se constatarán y cuantificarán algunas de las primeras evidencias de cambio en la distribución altitudinal y latitudinal de diferentes especies forestales ibéricas, que junto al estudio de su dinámica poblacional y tasas demográficas, ayudarán a testar algunas hipótesis biogeográficas en un escenario de cambio global en zonas de especial vulnerabilidad (Capítulos 3, 4 y 5). Por último, mediante la comparación de ciclos de parcelas permanentes del IFN se ahondará en el conocimiento de la evolución en las últimas décadas de especies invasoras en los ecosistemas forestales del cuadrante noroccidental ibérico, uno de los más afectados por la invasión de esta flora (Capítulo 6). ABSTRACT The effects of global change on forests are one of the major concerns of the XXI century. Some of the potential impacts of global change on forest growth, productivity, biodiversity or changes in species assembly and spatial distribution may have great ecological and economic consequences. The detection and monitoring of these effects are some of the major challenges that scientists and forest managers face nowadays. Based on the comparison of historical series of the Spanish National Forest Inventory (NFI), this thesis tries to shed some light on some of the impacts driven by recent socio-economic and environmental changes on our forest ecosystems. Firstly, this thesis presents an innovative methodology based on geostatistical techniques that allows the comparison of different NFI cycles regardless of the different sampling methods used in each of them (Chapter 3). This methodology, in conjunction with other statistical techniques, allows to analyze changes in the spatial distribution and population dynamics of forest species along different geographic gradients. By its application, this thesis presents some of the first evidences of changes in species distribution along different geographical gradients in the Iberian Peninsula. The analysis of these findings, of species population dynamics and demographic rates will help to test some biogeographical hypothesis on forests under climate change scenarios in areas of particular vulnerability (Chapters 3, 4 and 5). Finally, by comparing NFI cycles with permanent plots, this thesis increases our knowledge about the patterns and processes associated with the recent evolution of invasive species in the forest ecosystems of North-western Iberia, one of the areas most affected by the invasion of allien species at national scale (Chapter 6).

Identifying wind power ramp causes from multivariate datasets: a methodological proposal and its application to reanalysis data.

Forecasting abrupt variations in wind power generation (the so-called ramps) helps achieve large scale wind power integration. One of the main issues to be confronted when addressing wind power ramp forecasting is the way in which relevant information is identified from large datasets to optimally feed forecasting models. To this end, an innovative methodology oriented to systematically relate multivariate datasets to ramp events is presented. The methodology comprises two stages: the identification of relevant features in the data and the assessment of the dependence between these features and ramp occurrence. As a test case, the proposed methodology was employed to explore the relationships between atmospheric dynamics at the global/synoptic scales and ramp events experienced in two wind farms located in Spain. The achieved results suggested different connection degrees between these atmospheric scales and ramp occurrence. For one of the wind farms, it was found that ramp events could be partly explained from regional circulations and zonal pressure gradients. To perform a comprehensive analysis of ramp underlying causes, the proposed methodology could be applied to datasets related to other stages of the wind-topower conversion chain.

Monitoring the communication competence in an innovative context of project management learning

This document presents an innovative, formal educational initiative that is aimed at enhancing the development of engineering students' specific competences. The subject of project management is the common theoretical and practical framework that articulates an experience that is carried out by multidisciplinary groups. Full utilization of Web 2.0 platforms and Project Based Learning constitutes the applied methodology. More specifically, this study focuses on monitoring communication competence when working in virtual environments, providing an ad-hoc rubric as a final result.

Development of a methodology and tool to evaluate the impact of ICT measures on road transport emissions

The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems).The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome.

The environmental and economic effects of innovative measures in urban parcels delivery

The main scope of this research is to identify and evaluate solutions to redesign the parcels delivery logistic process to achieve higher level of quality, lower operational costs, energy consumptions and air pollution. The study is starting from the analysis of the delivery process managed by a leader company operating in Rome. Main delivery flows, personnel and fleet management costs, quality performances and environmental impacts are investigated. The results of this analysis are benchmarked with other European situations. On the basis of the feedback of this analysis, a set of operational measures, potentially able tackle the objectives, are identified and assessed by means of a simulative approach. The assessment is based on environmental and economic indicators allowing the comparison between new and reference scenarios from the viewpoints of the key players: operator, customer and Society. Moreover, the operational measures are combined into alternative packages by looking for the sets capable to maximize the benefits for the key players. The methodology, tested on Rome case study, is general and flexible enough to be extended to parcels delivery problem in different urban contexts, as well as to similar urban distribution problems (e.g. press, food, security, school)