Integral development of an Agricultural Training Center to ensure food security in Glory Special Needs Primary School. Kitgum, Uganda. DANIEL

El presente proyecto, titulado “Integral development of an Agricultural Training Center to ensure food security in Glory Special Needs Primary School. Kitgum, Uganda” fue llevado a cabo de Julio de 2011 a Febrero de 2012 en la escuela primaria Glory Special Needs, dedicada a la atención y educación de jóvenes discapacitados, en Kitgum, Uganda. El proyecto se realizó con la colaboración del grupo de cooperación de la ETSI Agrónomos, AgSystems, la Fundación AmigoSolidarios y la ONG local NUCBACD. Su objetivo principal fue el desarrollo y puesta en marcha de un centro de capacitación Agrícola para dotar de igualdad de oportunidades a los jóvenes con discapacidad de Kitgum, potenciando y favoreciendo su integración en la comunidad, y garantizar así la seguridad alimentaria de los 137 alumnos internos en la escuela Glory Special Needs. El trabajo realizado supuso una acción relevante en Kitgum, superando la visión de una economía familiar basada en las actividades agrícolas, para centrarse en la profesionalización de la Agricultura como motor económico de la región. Este documento presenta una descripción de las principales actividades que se desarrollaron con el fin de alcanzar el objetivo planteado, desde un punto de vista educativo, sostenible e inclusivo. Para conseguirlo, se plantearon tres lineas de trabajo: - Programa productivo. - Programa educativo. - Programa organizativo.

Analysis of the impact of globalization and economic growth on food security in developing countries

A pesar de los importantes avances en la reducción del hambre, la seguridad alimentaria continúa siendo un reto de dimensión internacional. La seguridad alimentaria es un concepto amplio y multidimensional, cuyo análisis abarca distintas escalas y horizontes temporales. Dada su complejidad, la identificación de las causas de la inseguridad alimentaria y la priorización de las medias para abordarlas, son dos cuestiones que suscitan un intenso debate en la actualidad. El objetivo de esta tesis es evaluar el impacto de la globalización y el crecimiento económico en la seguridad alimentaria en los países en desarrollo, desde una perspectiva macro y un horizonte temporal a largo plazo. La influencia de la globalización se aborda de una manera secuencial. En primer lugar, se analiza la relación entre la inversión público-privada en infraestructuras y las exportaciones agrarias. A continuación, se estudia el impacto de las exportaciones agrarias en los indicadores de seguridad alimentaria. El estudio del impacto del crecimiento económico aborda los cambios paralelos en la distribución de la renta, y cómo la inequidad influye en el comportamiento de la seguridad alimentaria nacional. Además, se analiza en qué medida el crecimiento económico contribuye a acelerar el proceso de mejora de la seguridad alimentaria. Con el fin de conseguir los objetivos mencionados, se llevan a cabo varios análisis econométricos basados en datos de panel, en el que se combinan datos de corte transversal de 52 países y datos temporales comprendidos en el periodo 1991-2012. Se analizan tanto variables en niveles como variables en tasas de cambio anual. Se aplican los modelos de estimación de efectos variables y efectos fijos, ambos en niveles y en primeras diferencias. La tesis incluye cuatro tipos de modelos econométricos, cada uno de ellos con sus correspondientes pruebas de robustez y especificaciones. Los resultados matizan la importancia de la globalización y el crecimiento económico como mecanismos de mejora de la seguridad alimentaria en los países en desarrollo. Se obtienen dos conclusiones relativas a la globalización. En primer lugar, los resultados sugieren que la promoción de las inversiones privadas en infraestructuras contribuye a aumentar las exportaciones agrarias. En segundo lugar, se observa que las exportaciones agrarias pueden tener un impacto negativo en los indicadores de seguridad alimentaria. La combinación de estas dos conclusiones sugiere que la apertura comercial y financiera no contribuye por sí misma a la mejora de la seguridad alimentaria en los países en desarrollo. La apertura internacional de los países en desarrollo ha de ir acompañada de políticas e inversiones que desarrollen sectores productivos de alto valor añadido, que fortalezcan la economía nacional y reduzcan su dependencia exterior. En relación al crecimiento económico, a pesar del incuestionable hecho de que el crecimiento económico es una condición necesaria para reducir los niveles de subnutrición, no es una condición suficiente. Se han identificado tres estrategias adicionales que han de acompañar al crecimiento económico con el fin de intensificar su impacto positivo sobre la subnutrición. Primero, es necesario que el crecimiento económico sea acompañado de una distribución más equitativa de los ingresos. Segundo, el crecimiento económico ha de reflejarse en un aumento de inversiones en salud, agua y saneamiento y educación. Se observa que, incluso en ausencia de crecimiento económico, mejoras en el acceso a agua potable contribuyen a reducir los niveles de población subnutrida. Tercero, el crecimiento económico sostenible en el largo plazo parece tener un mayor impacto positivo sobre la seguridad alimentaria que el crecimiento económico más volátil o inestable en el corto plazo. La estabilidad macroeconómica se identifica como una condición necesaria para alcanzar una mayor mejora en la seguridad alimentaria, incluso habiéndose mejorado la equidad en la distribución de los ingresos. Por último, la tesis encuentra que los países en desarrollo analizados han experimentado diferentes trayectorias no lineales en su proceso de mejora de sus niveles de subnutrición. Los resultados sugieren que un mayor nivel inicial de subnutrición y el crecimiento económico son responsables de una respuesta más rápida al reto de la mejora de la seguridad alimentaria. ABSTRACT Despite the significant reductions of hunger, food security still remains a global challenge. Food security is a wide concept that embraces multiple dimensions, and has spatial-temporal scales. Because of its complexity, the identification of the drivers underpinning food insecurity and the prioritization of measures to address them are a subject of intensive debate. This thesis attempts to assess the impact of globalization and economic growth on food security in developing countries with a macro level scale (country) and using a long-term approach. The influence of globalization is addressed in a sequential way. First, the impact of public-private investment in infrastructure on agricultural exports in developing countries is analyzed. Secondly, an assessment is conducted to determine the impact of agricultural exports on food security indicators. The impact of economic growth focuses on the parallel changes in income inequality and how the income distribution influences countries' food security performance. Furthermore, the thesis analyzes to what extent economic growth helps accelerating food security improvements. To address the above mentioned goals, various econometric models are formulated. Models use panel data procedures combining cross-sectional data of 52 countries and time series data from 1991 to 2012. Yearly data are expressed both in levels and in changes. The estimation models applied are random effects estimation and fixed effects estimations, both in levels and in first differences. The thesis includes four families of econometric models, each with its own set of robustness checks and specifications. The results qualify the relevance of globalization and economic growth as enabling mechanisms for improving food security in developing countries. Concerning globalization, two main conclusions can be drawn. First, results showed that enhancing foreign private investment in infrastructures contributes to increase agricultural exports. Second, agricultural exports appear to have a negative impact on national food security indicators. These two conclusions suggest that trade and financial openness per se do not contribute directly to improve food security in development countries. Both measures should be accompanied by investments and policies to support the development of national high value productive sectors, to strengthen the domestic economy and reduce its external dependency. Referring to economic growth, despite the unquestionable fact that income growth is a pre-requisite for reducing undernourishment, results suggest that it is a necessary but not a sufficient condition. Three additional strategies should accompany economic growth to intensifying its impact on food security. Firstly, it is necessary that income growth should be accompanied by a better distribution of income. Secondly, income growth needs to be followed by investments and policies in health, sanitation and education to improve food security. Even if economic growth falters, sustained improvements in the access to drinking water may still give rise to reductions in the percentage of undernourished people. And thirdly, long-term economic growth appears to have a greater impact on reducing hunger than growth regimes that combine periods of growth peaks followed by troughs. Macroeconomic stability is a necessary condition for accelerating food security. Finally, the thesis finds that the developing countries analyzed have experienced different non-linear paths toward improving food security. Results also show that a higher initial level of undernourishment and economic growth result in a faster response for improving food security.

Cognitive strategies for security in wireless sensor networks

Las redes de sensores inalámbricas son uno de los sectores con más crecimiento dentro de las redes inalámbricas. La rápida adopción de estas redes como solución para muchas nuevas aplicaciones ha llevado a un creciente tráfico en el espectro radioeléctrico. Debido a que las redes inalámbricas de sensores operan en las bandas libres Industrial, Scientific and Medical (ISM) se ha producido una saturación del espectro que en pocos años no permitirá un buen funcionamiento. Con el objetivo de solucionar este tipo de problemas ha aparecido el paradigma de Radio Cognitiva (CR). La introducción de las capacidades cognitivas en las redes inalámbricas de sensores permite utilizar estas redes para aplicaciones con unos requisitos más estrictos respecto a fiabilidad, cobertura o calidad de servicio. Estas redes que aúnan todas estas características son llamadas redes de sensores inalámbricas cognitivas (CWSNs). La mejora en prestaciones de las CWSNs permite su utilización en aplicaciones críticas donde antes no podían ser utilizadas como monitorización de estructuras, de servicios médicos, en entornos militares o de vigilancia. Sin embargo, estas aplicaciones también requieren de otras características que la radio cognitiva no nos ofrece directamente como, por ejemplo, la seguridad. La seguridad en CWSNs es un aspecto poco desarrollado al ser una característica no esencial para su funcionamiento, como pueden serlo el sensado del espectro o la colaboración. Sin embargo, su estudio y mejora es esencial de cara al crecimiento de las CWSNs. Por tanto, esta tesis tiene como objetivo implementar contramedidas usando las nuevas capacidades cognitivas, especialmente en la capa física, teniendo en cuenta las limitaciones con las que cuentan las WSNs. En el ciclo de trabajo de esta tesis se han desarrollado dos estrategias de seguridad contra ataques de especial importancia en redes cognitivas: el ataque de simulación de usuario primario (PUE) y el ataque contra la privacidad eavesdropping. Para mitigar el ataque PUE se ha desarrollado una contramedida basada en la detección de anomalías. Se han implementado dos algoritmos diferentes para detectar este ataque: el algoritmo de Cumulative Sum y el algoritmo de Data Clustering. Una vez comprobado su validez se han comparado entre sí y se han investigado los efectos que pueden afectar al funcionamiento de los mismos. Para combatir el ataque de eavesdropping se ha desarrollado una contramedida basada en la inyección de ruido artificial de manera que el atacante no distinga las señales con información del ruido sin verse afectada la comunicación que nos interesa. También se ha estudiado el impacto que tiene esta contramedida en los recursos de la red. Como resultado paralelo se ha desarrollado un marco de pruebas para CWSNs que consta de un simulador y de una red de nodos cognitivos reales. Estas herramientas han sido esenciales para la implementación y extracción de resultados de la tesis. ABSTRACT Wireless Sensor Networks (WSNs) are one of the fastest growing sectors in wireless networks. The fast introduction of these networks as a solution in many new applications has increased the traffic in the radio spectrum. Due to the operation of WSNs in the free industrial, scientific, and medical (ISM) bands, saturation has ocurred in these frequencies that will make the same operation methods impossible in the future. Cognitive radio (CR) has appeared as a solution for this problem. The networks that join all the mentioned features together are called cognitive wireless sensor networks (CWSNs). The adoption of cognitive features in WSNs allows the use of these networks in applications with higher reliability, coverage, or quality of service requirements. The improvement of the performance of CWSNs allows their use in critical applications where they could not be used before such as structural monitoring, medical care, military scenarios, or security monitoring systems. Nevertheless, these applications also need other features that cognitive radio does not add directly, such as security. The security in CWSNs has not yet been explored fully because it is not necessary field for the main performance of these networks. Instead, other fields like spectrum sensing or collaboration have been explored deeply. However, the study of security in CWSNs is essential for their growth. Therefore, the main objective of this thesis is to study the impact of some cognitive radio attacks in CWSNs and to implement countermeasures using new cognitive capabilities, especially in the physical layer and considering the limitations of WSNs. Inside the work cycle of this thesis, security strategies against two important kinds of attacks in cognitive networks have been developed. These attacks are the primary user emulator (PUE) attack and the eavesdropping attack. A countermeasure against the PUE attack based on anomaly detection has been developed. Two different algorithms have been implemented: the cumulative sum algorithm and the data clustering algorithm. After the verification of these solutions, they have been compared and the side effects that can disturb their performance have been analyzed. The developed approach against the eavesdropping attack is based on the generation of artificial noise to conceal information messages. The impact of this countermeasure on network resources has also been studied. As a parallel result, a new framework for CWSNs has been developed. This includes a simulator and a real network with cognitive nodes. This framework has been crucial for the implementation and extraction of the results presented in this thesis.

Latin American Agricultural Trade: The Role of the WTO in Sustainable Virtual Water Flows, European Association of Agricultural Economists

International agricultural trade has been growing significantly during the last decade. Many countries rely on imports to ensure adequate food supplies to the people. A few are becoming food baskets of the world. This process raises issues about the food security in depending countries and potentially unsustainable land and water use in exporting countries. In this paper, we analyse the impacts of amplified farm trade on natural resources, especially water. Farm exports and imports of five Latin America countries (Brazil, Argentina, Mexico, Peru and Chile) are examined carefully. A preliminary analysis indicates that virtual water imports can save valuable water resources in water-short countries, such as Mexico and Chile. Major exporting countries, including Brazil and Argentina, have become big exporters due to abundant natural resource endowments. The opportunity costs of agricultural production in those countries are identified as being low, because of the predominant green water use. It is concluded that virtual water trade can be a powerful tool to alleviate water stress in semi-arid countries. However, for exporting nations a sustainable water use can only be guaranteed if environmental production costs are fully reflected in the commodity prices. There is no basis for erecting environmental trade tariffs on exporters though. Setting up legal foundations for them in full compliance with WTOs processes would be a daunting task.

Gaussian Multiscale Aggregation oriented to Hand Biometric Segmentation in Mobile Devices

New trends in biometrics are oriented to mobile devices in order to increase the overall security in daily actions like bank account access, e-commerce or even document protection within the mobile. However, applying biometrics to mobile devices imply challenging aspects in biometric data acquisition, feature extraction or private data storage. Concretely, this paper attempts to deal with the problem of hand segmentation given a picture of the hand in an unknown background, requiring an accurate result in terms of hand isolation. For the sake of user acceptability, no restrictions are done on background, and therefore, hand images can be taken without any constraint, resulting segmentation in an exigent task. Multiscale aggregation strategies are proposed in order to solve this problem due to their accurate results in unconstrained and complicated scenarios, together with their properties in time performance. This method is evaluated with a public synthetic database with 480000 images considering different backgrounds and illumination environments. The results obtained in terms of accuracy and time performance highlight their capability of being a suitable solution for the problem of hand segmentation in contact-less environments, outperforming competitive methods in literature like Lossy Data Compression image segmentation (LDC).

New Technique for Static Target Detection in Dense-Multipath Urban Environments

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range with a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, new uses of Unmanned Aerial Vehicles (UAVs) for civilian-security applications force SAR systems to work in much more complex scenes such as urban environments. Consequently, multiple-bounce returns are additionally superposed to direct-scatter echoes. They are known as ghost images, since they obscure true target image and lead to poor resolution. All this may involve a significant problem in applications related to surveillance and security. In this work, an innovative multipath mitigation technique is presented in which Time Reversal (TR) concept is applied to SAR images when the target is concealed in clutter, leading to TR-SAR technique. This way, the effect of multipath is considerably reduced ?or even removed?, recovering the lost resolution due to multipath propagation. Furthermore, some focusing indicators such as entropy (E), contrast (C) and Rényi entropy (RE) provide us with a good focusing criterion when using TR-SAR.

Detecting unknown attacks in wireless sensor networks that contain mobile nodes

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

PUE attack detection in CWSNs using anomaly detection techniques

Cognitive wireless sensor network (CWSN) is a new paradigm, integrating cognitive features in traditional wireless sensor networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in cognitive wireless sensor networks is an important problem since these kinds of networks manage critical applications and data. The specific constraints of WSN make the problem even more critical, and effective solutions have not yet been implemented. Primary user emulation (PUE) attack is the most studied specific attack deriving from new cognitive features. This work discusses a new approach, based on anomaly behavior detection and collaboration, to detect the primary user emulation attack in CWSN scenarios. Two non-parametric algorithms, suitable for low-resource networks like CWSNs, have been used in this work: the cumulative sum and data clustering algorithms. The comparison is based on some characteristics such as detection delay, learning time, scalability, resources, and scenario dependency. The algorithms have been tested using a cognitive simulator that provides important results in this area. Both algorithms have shown to be valid in order to detect PUE attacks, reaching a detection rate of 99% and less than 1% of false positives using collaboration.

PUE attack detection in CWSN using collaboration and learning behavior

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Offices For Benetton, Samara, Russia (2010)

An office building for the Benetton Group in the center of Samara, an industrial city in Russia on the banks of the Volga River = Se trata de hacer un edificio de oficinas para el Grupo Benetton en el centro de Samara, la ciudad industrial rusa a orillas del río Volga. [Proyecto]

Abstraction carrying code and resource-awareness

Proof-Carrying Code (PCC) is a general approach to mobile code safety in which the code supplier augments the program with a certifícate (or proof). The intended benefit is that the program consumer can locally validate the certifícate w.r.t. the "untrusted" program by means of a certifícate checker—a process which should be much simpler, eíñcient, and automatic than generating the original proof. Abstraction Carrying Code (ACC) is an enabling technology for PCC in which an abstract model of the program plays the role of certifícate. The generation of the certifícate, Le., the abstraction, is automatically carried out by an abstract interpretation-based analysis engine, which is parametric w.r.t. different abstract domains. While the analyzer on the producer side typically has to compute a semantic fixpoint in a complex, iterative process, on the receiver it is only necessary to check that the certifícate is indeed a fixpoint of the abstract semantics equations representing the program. This is done in a single pass in a much more efficient process. ACC addresses the fundamental issues in PCC and opens the door to the applicability of the large body of frameworks and domains based on abstract interpretation as enabling technology for PCC. We present an overview of ACC and we describe in a tutorial fashion an application to the problem of resource-aware security in mobile code. Essentially the information computed by a cost analyzer is used to genérate cost certificates which attest a safe and efficient use of a mobile code. A receiving side can then reject code which brings cost certificates (which it cannot validate or) which have too large cost requirements in terms of computing resources (in time and/or space) and accept mobile code which meets the established requirements.

Contribución a la automatización de sistemas de respuesta frente a intrusiones mediante ontologías

La seguridad en redes informáticas es un área que ha sido ampliamente estudiada y objeto de una extensa investigación en los últimos años. Debido al continuo incremento en la complejidad y sofisticación de los ataques informáticos, el aumento de su velocidad de difusión, y la lentitud de reacción frente a las intrusiones existente en la actualidad, se hace patente la necesidad de mecanismos de detección y respuesta a intrusiones, que detecten y además sean capaces de bloquear el ataque, y mitiguen su impacto en la medida de lo posible. Los Sistemas de Detección de Intrusiones o IDSs son tecnologías bastante maduras cuyo objetivo es detectar cualquier comportamiento malicioso que ocurra en las redes. Estos sistemas han evolucionado rápidamente en los últimos años convirtiéndose en herramientas muy maduras basadas en diferentes paradigmas, que mejoran su capacidad de detección y le otorgan un alto nivel de fiabilidad. Por otra parte, un Sistema de Respuesta a Intrusiones (IRS) es un componente de seguridad que puede estar presente en la arquitectura de una red informática, capaz de reaccionar frente a los incidentes detectados por un Sistema de Detección de Intrusiones (IDS). Por desgracia, esta tecnología no ha evolucionado al mismo ritmo que los IDSs, y la reacción contra los ataques detectados es lenta y básica, y los sistemas presentan problemas para ejecutar respuestas de forma automática. Esta tesis doctoral trata de hacer frente al problema existente en la reacción automática frente a intrusiones, mediante el uso de ontologías, lenguajes formales de especificación de comportamiento y razonadores semánticos como base de la arquitectura del sistema de un sistema de respuesta automática frente a intrusiones o AIRS. El objetivo de la aproximación es aprovechar las ventajas de las ontologías en entornos heterogéneos, además de su capacidad para especificar comportamiento sobre los objetos que representan los elementos del dominio modelado. Esta capacidad para especificar comportamiento será de gran utilidad para que el AIRS infiera la respuesta óptima frente a una intrusión en el menor tiempo posible. Abstract Security in networks is an area that has been widely studied and has been the focus of extensive research over the past few years. The number of security events is increasing, and they are each time more sophisticated, and quickly spread, and slow reaction against intrusions, there is a need for intrusion detection and response systems to dynamically adapt so as to better detect and respond to attacks in order to mitigate them or reduce their impact. Intrusion Detection Systems (IDSs) are mature technologies whose aim is detecting malicious behavior in the networks. These systems have quickly evolved and there are now very mature tools based on different paradigms (statistic anomaly-based, signature-based and hybrids) with a high level of reliability. On the other hand, Intrusion Response System (IRS) is a security technology able to react against the intrusions detected by IDS. Unfortunately, the state of the art in IRSs is not as mature as with IDSs. The reaction against intrusions is slow and simple, and these systems have difficulty detecting intrusions in real time and triggering automated responses. This dissertation is to address the existing problem in automated reactions against intrusions using ontologies, formal behaviour languages and semantic reasoners as the basis of the architecture of an automated intrusion response systems or AIRS. The aim is to take advantage of ontologies in heterogeneous environments, in addition to its ability to specify behavior of objects representing the elements of the modeling domain. This ability to specify behavior will be useful for the AIRS in the inference process of the optimum response against an intrusion, as quickly as possible.