Red de mentoría en entornos universitarios españoles: presente y futuro

El Programa Mentor se concibió con dos objetivos claramente definidos: La orientación a los estudiantes de nuevo ingreso, por parte de compañeros de cursos superiores, con el fin de facilitar su adaptación e integración académica y social en la vida del Centro. La formación de los estudiantes de segundo ciclo como mentores de estudiantes de nuevo ingreso, potenciando en ellos habilidades sociales, de relación, orientación y liderazgo extrapolables al desarrollo personal o profesional

Aplicaciones de la biometría en seguridad

Hoy en día se ve cada vez más necesarios los mecanismos que permitan evitar la suplantación de la identidad de un individuo, tanto a nivel de servicios telemáticos, transferencias bancarias, redes sociales, etc. Por lo que la identificación biométrica del usuario se ha convertido en uno de los mecanismos de seguridad que no se debe obviar. En esta charla se verán en primer lugar el estado actual de las técnicas biométricas más desarrolladas: huella, iris, cara, mano, así como las emergentes hoy en día y sus diversas aplicaciones en seguridad. En la segunda parte de la charla se esbozarán las principales líneas de investigación en las que actualmente se está prestando mayor atención: la biometría multimodal y la criptobiometría

La mentoría entre compañeros en la universidad: un medio para la acogida e integración de los alumnos de nuevo ingreso

En este trabajo se describe la puesta en marcha y desarrollo de un sistema de mentorías por compañeros en la Universidad Politécnica de Madrid en el que alumnos de últimos cursos (mentores), ayudan, orientan y aconsejan a alumnos de nuevo ingreso facilitando su integración en la vida universitaria, desde el punto de vista académico, social y administrativo. Este Proyecto, iniciado en 2002-03 en la ETSI de Telecomunicación de la Universidad Politécnica de Madrid, ha sido el germen de la que ahora es la Red Temática de Mentoría en entornos universitarios, formada hasta ahora por 12 universidades españolas en las que se han implantado sistemas de mentoría por compañeros manteniendo las características propias e idiosincrasia de cada universidad

El papel del currículo en el camino a la educación inclusiva en Andalucía: claves de una investigación de tesis doctoral

This paper synthesizes the most relevant aspects of a doctoral thesis research plan, whose general objective is to characterize and analyze the role of the curricula as a factor of educational exclusion/inclusion in Andalusia. Determining the components of an inclusive curricula, the methodologies and didactic strategies consistent with it and knowing reports of experiences of good inclusive practices in this line, will be the backbone on which this research will be developed from a qualitative approach. The field work is based on an initial exploratory study where information is collected through interviews with five experts in inclusive education in Spain, in order to reveal the key aspects that can focus the theoretical framework, as well as determine the main dimensions of inquiry about the theme. The collection of information continues with informants belonging to the educational administration, specialists in inclusive teaching methodologies and three case studies of good curricular practices in centers that favor inclusive environments in the compulsory stages. Finally, the field work will be closed by returning the information collected to university professors who train the future teachers of the stages studied, in order to inquire about the subject also from this perspective. Explaining how we will face each one of these stages is the object of the story that articulates this work, which will end with the progress of the results of a preliminary analysis of the information collected so far and the conclusions derived from the planning process and start a doctoral thesis research.Este trabajo sintetiza los aspectos más relevantes de una investigación de tesis doctoral en curso, cuyo objetivo general es caracterizar y analizar el papel del currículo como factor de exclusión/inclusión educativa en Andalucía. Determinar los componentes de un currículo inclusivo, las metodologías y estrategias didácticas coherentes con el mismo y conocer relatos de experiencias de buenas prácticas inclusivas en esta línea, supondrán el eje vertebrador sobre el que se desarrollará esta investigación desde un enfoque cualitativo. El trabajo de campo parte de un estudio exploratorio inicial donde se recaba información mediante entrevistas a cinco expertas y expertos en educación inclusiva de España, de cara a desvelar los aspectos clave que permitan centrar el marco teórico, así como determinar las principales dimensiones de indagación sobre la temática. La recogida de información continúa con informantes pertenecientes a la administración educativa, especialistas en metodologías didácticas inclusivas y tres estudios de caso de buenas prácticas curriculares en centros que favorecen entornos inclusivos en las etapas obligatorias. Finalmente, se cerrará el trabajo de campo devolviendo la información recabada a grupos de docentes universitarios que forman al futuro profesorado de las etapas estudiadas, para así indagar sobre la temática también desde esta perspectiva. Explicar cómo afrontaremos cada una de estas etapas es el objeto del relato que articula este trabajo, que tendrá como colofón el avance de resultados de un análisis preliminar de la información recabada hasta el momento y las conclusiones que se derivan del proceso de planificar e iniciar una investigación de tesis doctoral

Minimal template size for Iris-Recognition

A method to achieve improvement in template size for an iris-recognition system is reported. To achieve this result, the biological characteristics of the human iris have been studied. Processing has been performed by image processing techniques, isolating the iris and enhancing the area of study, after which multi resolution analysis is made. Reduction of the pattern obtained has been obtained via statistical study

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