Recent insights into xerogel and aerogel mineral composites for CO 2 mineral sequestration

Supercritically dried composites have already been analysed and proposed as carbon dioxide sequesters. However, the economical and energetic costs of the supercritical drying process had to be re-evaluated, and were eventually found not to enhance the feasibility of the proposed route for CO2 mineral sequestration. Different composites series were synthesised with the only difference being the drying method. The structures of the porous matrix were characterised as well as their ability to capture CO2. The first results showed that the xerogel matrix is as good a host as the aerogel one, and also avoids expensive procedures such as supercritical drying for sample preparation without losing CO2 capture capacity and enhancing the efficiency of the whole carbon sequestration process. In this case, the sample preparation was simplified as much as possible, with the aim of reducing energetic and economic costs. Although good carbonation efficiencies were obtained with these cheap samples, the first results showed that previous high carbonation efficiencies could not be repeated.Junta de Andalucía TEP115Ministerio de Ciencia e Innovación PIA42008-3

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

Towards hand biometrics in mobile devices

The increasing demand of security oriented to mobile applications has raised the attention to biometrics, as a proper and suitable solution for providing secure environment to mobile devices. With this aim, this document presents a biometric system based on hand geometry oriented to mobile devices, involving a high degree of freedom in terms of illumination, hand rotation and distance to camera. The user takes a picture of their own hand in the free space, without requiring any flat surface to locate the hand, and without removals of rings, bracelets or watches. The proposed biometric system relies on an accurate segmentation procedure, able to isolate hands from any background; a feature extraction, invariant to orientation, illumination, distance to camera and background; and a user classification, based on k-Nearest Neighbor approach, able to provide an accurate results on individual identification. The proposed method has been evaluated with two own databases collected with a HTC mobile. First database contains 120 individuals, with 20 acquisitions of both hands. Second database is a synthetic database, containing 408000 images of hand samples in different backgrounds: tiles, grass, water, sand, soil and the like. The system is able to identify individuals properly with False Reject Rate of 5.78% and False Acceptance Rate of 0.089%, using 60 features (15 features per finger

Towards hand biometrics in mobile devices

The increasing demand of security oriented to mobile applications has raised the attention to biometrics, as a proper and suitable solution for providing secure environment to mobile devices. With this aim, this document presents a biometric system based on hand geometry oriented to mobile devices, involving a high degree of freedom in terms of illumination, hand rotation and distance to camera. The user takes a picture of their own hand in the free space, without requiring any flat surface to locate the hand, and without removals of rings, bracelets or watches. The proposed biometric system relies on an accurate segmentation procedure, able to isolate hands from any background; a feature extraction, invariant to orientation, illumination, distance to camera and background; and a user classification, based on k-Nearest Neighbor approach, able to provide an accurate results on individual identification. The proposed method has been evaluated with two own databases collected with a HTC mobile. First database contains 120 individuals, with 20 acquisitions of both hands. Second database is a synthetic database, containing 408000 images of hand samples in different backgrounds: tiles, grass, water, sand, soil and the like. The system is able to identify individuals properly with False Reject Rate of 5.78% and False Acceptance Rate of 0.089%, using 60 features (15 features per finger

Towards hand biometrics in mobile devices

The increasing demand of security oriented to mobile applications has raised the attention to biometrics, as a proper and suitable solution for providing secure environment to mobile devices. With this aim, this document presents a biometric system based on hand geometry oriented to mobile devices, involving a high degree of freedom in terms of illumination, hand rotation and distance to camera. The user takes a picture of their own hand in the free space, without requiring any flat surface to locate the hand, and without removals of rings, bracelets or watches. The proposed biometric system relies on an accurate segmentation procedure, able to isolate hands from any background; a feature extraction, invariant to orientation, illumination, distance to camera and background; and a user classification, based on k-Nearest Neighbor approach, able to provide an accurate results on individual identification. The proposed method has been evaluated with two own databases collected with a HTC mobile. First database contains 120 individuals, with 20 acquisitions of both hands. Second database is a synthetic database, containing 408000 images of hand samples in different backgrounds: tiles, grass, water, sand, soil and the like. The system is able to identify individuals properly with False Reject Rate of 5.78% and False Acceptance Rate of 0.089%, using 60 features (15 features per finger

A robustness verification system for mobile phone authentication based on gestures using Linear Discriminant Analysis

This article evaluates an authentication technique for mobiles based on gestures. Users create a remindful identifying gesture to be considered as their in-air signature. This work analyzes a database of 120 gestures of different vulnerability, obtaining an Equal Error Rate (EER) of 9.19% when robustness of gestures is not verified. Most of the errors in this EER come from very simple and easily forgeable gestures that should be discarded at enrollment phase. Therefore, an in-air signature robustness verification system using Linear Discriminant Analysis is proposed to infer automatically whether the gesture is secure or not. Different configurations have been tested obtaining a lowest EER of 4.01% when 45.02% of gestures were discarded, and an optimal compromise of EER of 4.82% when 19.19% of gestures were automatically rejected

Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performanc

Procedure to use phosphogypsum industrial waste for mineral CO 2 sequestration

Industrial wet phosphoric acid production in Huelva (SW Spain) has led to the controversial stockpiling of waste phosphogypsum by-products, resulting in the release of significant quantities of toxic impurities in salt marshes in the Tinto river estuary. In the framework of the fight against global climate change and the effort to reduce carbon dioxide emissions, a simple and efficient procedure for CO 2 mineral sequestration is presented in this work, using phosphogypsum waste as a calcium source. Our results demonstrate the high efficiency of portlandite precipitation by phosphogypsum dissolution using an alkaline soda solution. Carbonation experiments performed at ambient pressure and temperature resulted in total conversion of the portlandite into carbonate. The fate of trace elements present in the phosphogypsum waste was also investigated, and trace impurities were found to be completely transferred to the final calcite. We believe that the procedure proposed here should be considered not only as a solution for reducing old stockpiles of phosphogypsum wastes, but also for future phosphoric acid and other gypsum-producing industrial processes, resulting in more sustainable production.Junta de Andalucía TEP115Ministerio de Ciencia e Innovación PIA42008-3

Nuevos Algoritmos y Ataques a Sistemas de Identificación Biométrica basados en Reconocimiento de Iris

En este trabajo se recogen dos enfoques claramente de_nidos: Primeramente, se propone una mejora a los sistemas actuales de detecci _on de iris, tanto en detecci_on de pupila, como en detecci_on de iris en s__ misma. Dichos algoritmos rompen con el esquema cl_asico de aislamiento de iris, y proponen una nueva idea en este campo. Adem_as, se utilizar_an bases de datos actuales para la evaluaci_on de los resultados. Por otro lado, se presenta un esquema de ataque a un sistema de iris en el que a partir del patr_on biom_etrico se reproduce una imagen de iris capaz de confundir a dicho sistema, mediante la utilizaci_on de algoritmos gen_eticos. Este novedoso procedimiento, no existe nada parecido en la literatura actual, permitir__a a un determinado usuario falsi_car su identidad, utilizando simplemente el patr_on biom_etrico de iris de otro usuario. Los resultados de este algoritmo muestran como esto es factible. Adem_as, no existe en la literatura nada similar en cuesti_on de ataques de este tipo a un sistema de iris

Creating an Iris Image from a given Iris Template

An Iris Detection System is known to be one of the strongest systems in terms of security. One of the main security aspects of this system relays on the incapability to reconstruct the original iris image from the iris template, i.e. that binary string able to provide the enough information to identify and/or authenticate a certain user. However, this paper proposes a method in order to carry out the solution for such a problem. The algorithm is based on evolutionary strategies, and intends to find an image whose iris template attends to be so similar as required to a given iris template. Results will highlight how this algorithm achieves the required aim, and how the performance can be as accurate as desired