Desing and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d

Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.

This paper describes the basic tools to work with wireless sensors. TinyOShas a componentbased architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools ? all of which can be used asia or be further refined for a custom application. TinyOS was originally developed as a research project at the University of California Berkeley, but has since grown to have an international community of developers and users. Some algorithms concerning packet routing are shown. Incar entertainment systems can be based on wireless sensors in order to obtain information from Internet, but routing protocols must be implemented in order to avoid bottleneck problems. Ant Colony algorithms are really useful in such cases, therefore they can be embedded into the sensors to perform such routing task.

A New Method to Reduce Truncation Errors in Partial Spherical Near-Field Measurements

A new and effective method for reduction of truncation errors in partial spherical near-field (SNF) measurements is proposed. The method is useful when measuring electrically large antennas, where the measurement time with the classical SNF technique is prohibitively long and an acquisition over the whole spherical surface is not practical. Therefore, to reduce the data acquisition time, partial sphere measurement is usually made, taking samples over a portion of the spherical surface in the direction of the main beam. But in this case, the radiation pattern is not known outside the measured angular sector as well as a truncation error is present in the calculated far-field pattern within this sector. The method is based on the Gerchberg-Papoulis algorithm used to extrapolate functions and it is able to extend the valid region of the calculated far-field pattern up to the whole forward hemisphere. To verify the effectiveness of the method, several examples are presented using both simulated and measured truncated near-field data.

ITER fast plant system controller prototype based on PXIe platform

The ITER CODAC design identifies slow and fast plant system controllers (PSC). The gast OSCs are based on embedded technologies, permit sampling rates greater than 1 KHz, meet stringent real-time requirements, and will be devoted to data acquisition tasks and control purposes. CIEMAT and UPM have implemented a prototype of a fast PSC based on commercial off-the-shelf (COTS) technologies with PXI hardware and software based on EPICS

ITER Fast Plant System Controller Prototype Based on Commercial PXI Platform

The ITER CODAC design identifies slow and fast plant system controllers (PSC). The gast OSCs are based on embedded technologies, permit sampling rates greater than 1 KHz, meet stringent real-time requirements, and will be devoted to data acquisition tasks and control purposes. CIEMAT and UPM have implemented a prototype of a fast PSC based on commercial off-the-shelf (COTS) technologies with PXI hardware and software based on EPICS

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).

Aplicación de representación gráfica de datos y/o señales en entorno GNU/LINUX

El contenido de este PFC supone el desarrollo de una aplicación gráfica en el entorno GNU/LINUX. La aplicación debe representar en la pantalla gráficos procedentes de una fuente externa (un fichero, una tarjeta de adquisición de datos, otra aplicación, etc.) Debe permitir las siguientes funcionalidades: Representar la señal uniendo puntos o marcándolos como símbolos. Debe gestionar de forma adecuada el zoom. Debe permitir exportar la gráfica a formatos SVG y PDF. Debe permitir mostrar varias señales superpuestas para poder compararlas. Opcionalmente debe permitir arrastrar y soltar (“drag and drop”). ABSTRACT The content of the thesis is the development of a graphical application in GNU / Linux environment. The application must render graphics on the screen from an external source (a file, a data acquisition card, other applications, etc..) It must allow the following functionality: Joining dots represent the signal or marking them as symbols. Must properly manage the zoom. Allow export the graph to SVG and PDF formats. Allow display multiple signals superimposed for comparison. Optionally should allow drag and drop.

Implementación de instrumentación virtual con LaBVIEW

El objetivo del PFC es el diseño e implementación de una aplicación que funcione como osciloscopio, analizador de espectro y generador de funciones virtual, todo dentro de la misma aplicacion. Mediante una tarjeta de adquisición de datos tomaremos muestras de señales del mundo real (sistema analógico) para generar datos que puedan ser manipulados por un ordenador (sistema digital). Con esta misma tarjeta también se podrán generar señales básicas, tales como señales senoidales, cuadradas.... y además se ha añadido la funcionalidad de generar señales moduladas en frecuencia, señales tipo Chirp (usadas comúnmente tanto en aplicaciones sonar y radar, como en transmisión óptica) o PRN (ruido pseudo-aleatorio que consta de una secuencia determinista de pulsos que se repite cada periodo, usada comúnmente en receptores GPS), como también señales ampliamente conocidas como el ruido blanco Gaussiano o el ruido blanco uniforme. La aplicación mostrará con detalle las señales adquiridas y analizará de diversas maneras esas señales. Posee la función de enventanado de los tipos de ventana mas comunes, respuesta en frecuencia, transformada de Fourier, etc. La configuración es elegida por el usuario en un entorno amigable y de visualización atractiva. The objective of the PFC is the design and implementation of an application that works as oscilloscope, spectrum analyzer and virtual signal generator, all within the same application. Through a data acquisition card, the user can take samples of real-world signals (analog system) to generate data that can be manipulated by a computer (digital system). This same card can also generate basic signals, such as sine waves, square waves, sawtooth waves.... and further has added other functionalities as frequency modulated signals generation, Chirp signals type generation (commonly used in both sonar and radar applications, such as optical transmission) or PRN (pseudo-random noise sequence comprising a deterministic pulse that repeats every period, commonly used in GPS receivers). It also can generate widely known as Gaussian white noise signals or white noise uniform signals. The application will show in detail the acquired signals and will analyze these signals in different ways selected by the user. Windowing function has the most common window types, frequency response, Fourier transform are examples of what kind of analyzing that can be processed. The configuration is chosen by the user throught friendly and attractive displays and panels.

Development of low cost photovoltaic sensor for over-tree radiation assessment

The crop diseases sometimes are related to the irradiance that the crop receives. When an experiment requires the measurement of the irradiance, usually it results in an expensive data acquisition system. If it is necessary to check many test points, the use of traditional sensors will increase the cost of the experiment. By using low cost sensors based in the photovoltaic effect, it is possible to perform a precise test of irradiance with a reduced price. This work presents an experiment performed in Ademuz (Valencia, Spain) during September of 2011 to check the validity of low cost sensors based on solar cells.

Simulación de maniobras de buques con sistemas de propulsión no convencional en aguas poco profundas

Los requisitos cada vez más exigentes en cuanto a misiones, limitaciones operacionales y ambientales así como nuevas tecnologías, imponen permanentemente retos a los arquitectos navales para generar alternativas de buques y valorar su bondad en las primeras etapas del proyecto. Este es el caso de los Buques Patrulleros de Apoyo Fluvial Pesados PAF-P, que por requerimiento de la Armada Nacional de Colombia ha diseñado y construido COTECMAR. Los PAF-P, son buques fluviales cuya relación Manga-Calado excede la mayoría de los buques existentes (B/T=9,5), debido principalmente a las restricciones en el calado a consecuencia de la escasa profundidad de los ríos. Estos buques están equipados con sistemas de propulsión acimutales tipo “Pum-Jet”. Las particularidades del buque y del ambiente operacional, caracterizado por ríos tropicales con una variabilidad de profundidad dependiente del régimen de lluvias y sequía, así como la falta de canalización y la corriente, hacen que la maniobrabilidad y controlabilidad sean fundamentales para el cumplimiento de su misión; adicionalmente, no existen modelos matemáticos validados que permitan predecir en las primeras etapas del diseño la maniobrabilidad de este tipo de buques con los efectos asociados por profundidad. La presente tesis doctoral aborda el desarrollo de un modelo matemático para simulación de maniobrabilidad en aguas poco profundas de buques con relación manga-calado alta y con propulsores acimutales tipo “Pump-Jet”, cuyo chorro además de entregar el empuje necesario para el avance del buque, genera la fuerza de gobierno en función del ángulo de orientación del mismo, eliminando la necesidad de timones. El modelo matemático ha sido validado mediante los resultados obtenidos en las pruebas de maniobrabilidad a escala real del PAF-P, a través de la comparación de trayectorias, series temporales de las variables de estado más significativas y parámetros del círculo evolutivo como son diámetro de giro, diámetro táctico, avance y transferencia. El plan de pruebas se basó en técnicas de Diseño de Experimentos “DOE” para racionalizar el número de corridas en diferentes condiciones de profundidad, velocidad y orientación del chorro (ángulo de timón). En el marco de la presente investigación y para minimizar los errores por efectos ambientales y por inexactitud en los instrumentos de medición, se desarrolló un sistema de adquisición y procesamiento de datos de acuerdo con los lineamientos de ITTC. La literatura existente describe los efectos negativos de la profundidad en los parámetros de maniobrabilidad de buques convencionales (Efecto tipo S), principalmente las trayectorias descritas en los círculos evolutivos aumentan en la medida que disminuye la profundidad; no obstante, en buques de alta relación manga-calado, B/T=7,51 (Yoshimura, y otros, 1.988) y B/T=6,38 (Yasukawa, y otros, 1.995) ha sido reportado el efecto contrario (Efecto tipo NS Non Standart). Este último efecto sin embargo, ha sido observado mediante experimentación con modelos a escala pero no ha sido validado en pruebas de buques a escala real. El efecto tipo NS en buques dotados con hélice y timones, se atribuye al mayor incremento de la fuerza del timón comparativamente con las fuerzas del casco en la medida que disminuye la profundidad; en el caso de estudio, el fenómeno está asociado a la mejor eficiencia de la bomba de agua “Pump-Jet”, debido a la resistencia añadida en el casco por efecto de la disminución de la profundidad. Los resultados de las pruebas con buque a escala real validan el excelente desempeño de esta clase de buques, cumpliendo en exceso los criterios de maniobrabilidad existentes y muestran que el diámetro de giro y otras características de maniobrabilidad mejoran con la disminución de la profundidad en buques con alta relación manga-calado. ABSTRACT The increasingly demanding requirements in terms of missions, operational and environmental constraints as well as new technologies, constantly impose challenges to naval architects to generate alternatives and asses their performance in the early stages of design. That is the case of Riverine Support Patrol Vessel (RSPV), designed and built by COTECMAR for the Colombian Navy. RSPV are riverine ships with a Beam-Draft ratio exceeding most of existing ships (B/T=9,5), mainly due to the restrictions in draft as a result of shallow water environment. The ships are equipped with azimuthal propulsion system of the “Pump-Jet” type. The peculiarities of the ship and the operational environment, characterized by tropical rivers of variable depth depending on the rain and dry seasons, as well as the lack channels and the effect of water current, make manoeuvrability and controllability fundamental to fulfill its mission; on the other hand, there are not validated mathematical models available to predict the manoeuvrability of such ships with the associated water depth effects in the early stages of design. This dissertation addresses the development of a mathematical model for shallow waters’ manoeuvrability simulation of ships with high Beam-Draft ratio and azimuthal propulsion systems type “Pump-Jet”, whose stream generates the thrust required by the ship to advance and also the steering force depending on the orientation angle, eliminating the need of rudders. The mathematical model has been validated with the results of RSPV’s full scale manoeuvring tests, through a comparison of paths, time series of state variables and other parameters taken from turning tests, such as turning diameter, tactical diameter, advance and transfer. The test plan was developed applying techniques of Design of Experiments “DOE”, in order to rationalize the number of runs in different conditions of water depth, ship speed and jet stream orientation (rudder angle). A data acquisition and processing system was developed, following the guidelines of ITTC, as part of this research effort, in order to minimize errors by environmental effects and inaccuracy in measurement instruments, The negative effects of depth on manoeuvrability parameters for conventional ships (Effect Type S: the path described by the ship during turning test increase with decrease of water depth), has been documented in the open literature; however for wide-beam ships, B/T=7,51 (Yoshimura, y otros, 1.988) and B/T=6,38 (Yasukawa, y otros, 1.995) has been reported the opposite effect (Type NS). The latter effect has been observed thru model testing but until now had not been validated with full-scale results. In ships with propellers and rudders, type NS effect is due to the fact that increment of rudder force becomes larger than hull force with decrease of water depth; in the study case, the phenomenon is associated with better efficiency of the Pump-Jet once the vessel speed becomes lower, due to hull added resistance by the effect of the decrease of water depth. The results of full scale tests validates the excellent performance of this class of ships, fulfilling the manoeuvrability criteria in excess and showing that turning diameter and other parameters in high beam-draft ratio vessels do improve with the decrease of depth.

Semi-supervised subspace clustering and applications to neuroscience

Machine learning techniques are used for extracting valuable knowledge from data. Nowa¬days, these techniques are becoming even more important due to the evolution in data ac¬quisition and storage, which is leading to data with different characteristics that must be exploited. Therefore, advances in data collection must be accompanied with advances in machine learning techniques to solve new challenges that might arise, on both academic and real applications. There are several machine learning techniques depending on both data characteristics and purpose. Unsupervised classification or clustering is one of the most known techniques when data lack of supervision (unlabeled data) and the aim is to discover data groups (clusters) according to their similarity. On the other hand, supervised classification needs data with supervision (labeled data) and its aim is to make predictions about labels of new data. The presence of data labels is a very important characteristic that guides not only the learning task but also other related tasks such as validation. When only some of the available data are labeled whereas the others remain unlabeled (partially labeled data), neither clustering nor supervised classification can be used. This scenario, which is becoming common nowadays because of labeling process ignorance or cost, is tackled with semi-supervised learning techniques. This thesis focuses on the branch of semi-supervised learning closest to clustering, i.e., to discover clusters using available labels as support to guide and improve the clustering process. Another important data characteristic, different from the presence of data labels, is the relevance or not of data features. Data are characterized by features, but it is possible that not all of them are relevant, or equally relevant, for the learning process. A recent clustering tendency, related to data relevance and called subspace clustering, claims that different clusters might be described by different feature subsets. This differs from traditional solutions to data relevance problem, where a single feature subset (usually the complete set of original features) is found and used to perform the clustering process. The proximity of this work to clustering leads to the first goal of this thesis. As commented above, clustering validation is a difficult task due to the absence of data labels. Although there are many indices that can be used to assess the quality of clustering solutions, these validations depend on clustering algorithms and data characteristics. Hence, in the first goal three known clustering algorithms are used to cluster data with outliers and noise, to critically study how some of the most known validation indices behave. The main goal of this work is however to combine semi-supervised clustering with subspace clustering to obtain clustering solutions that can be correctly validated by using either known indices or expert opinions. Two different algorithms are proposed from different points of view to discover clusters characterized by different subspaces. For the first algorithm, available data labels are used for searching for subspaces firstly, before searching for clusters. This algorithm assigns each instance to only one cluster (hard clustering) and is based on mapping known labels to subspaces using supervised classification techniques. Subspaces are then used to find clusters using traditional clustering techniques. The second algorithm uses available data labels to search for subspaces and clusters at the same time in an iterative process. This algorithm assigns each instance to each cluster based on a membership probability (soft clustering) and is based on integrating known labels and the search for subspaces into a model-based clustering approach. The different proposals are tested using different real and synthetic databases, and comparisons to other methods are also included when appropriate. Finally, as an example of real and current application, different machine learning tech¬niques, including one of the proposals of this work (the most sophisticated one) are applied to a task of one of the most challenging biological problems nowadays, the human brain model¬ing. Specifically, expert neuroscientists do not agree with a neuron classification for the brain cortex, which makes impossible not only any modeling attempt but also the day-to-day work without a common way to name neurons. Therefore, machine learning techniques may help to get an accepted solution to this problem, which can be an important milestone for future research in neuroscience. Resumen Las técnicas de aprendizaje automático se usan para extraer información valiosa de datos. Hoy en día, la importancia de estas técnicas está siendo incluso mayor, debido a que la evolución en la adquisición y almacenamiento de datos está llevando a datos con diferentes características que deben ser explotadas. Por lo tanto, los avances en la recolección de datos deben ir ligados a avances en las técnicas de aprendizaje automático para resolver nuevos retos que pueden aparecer, tanto en aplicaciones académicas como reales. Existen varias técnicas de aprendizaje automático dependiendo de las características de los datos y del propósito. La clasificación no supervisada o clustering es una de las técnicas más conocidas cuando los datos carecen de supervisión (datos sin etiqueta), siendo el objetivo descubrir nuevos grupos (agrupaciones) dependiendo de la similitud de los datos. Por otra parte, la clasificación supervisada necesita datos con supervisión (datos etiquetados) y su objetivo es realizar predicciones sobre las etiquetas de nuevos datos. La presencia de las etiquetas es una característica muy importante que guía no solo el aprendizaje sino también otras tareas relacionadas como la validación. Cuando solo algunos de los datos disponibles están etiquetados, mientras que el resto permanece sin etiqueta (datos parcialmente etiquetados), ni el clustering ni la clasificación supervisada se pueden utilizar. Este escenario, que está llegando a ser común hoy en día debido a la ignorancia o el coste del proceso de etiquetado, es abordado utilizando técnicas de aprendizaje semi-supervisadas. Esta tesis trata la rama del aprendizaje semi-supervisado más cercana al clustering, es decir, descubrir agrupaciones utilizando las etiquetas disponibles como apoyo para guiar y mejorar el proceso de clustering. Otra característica importante de los datos, distinta de la presencia de etiquetas, es la relevancia o no de los atributos de los datos. Los datos se caracterizan por atributos, pero es posible que no todos ellos sean relevantes, o igualmente relevantes, para el proceso de aprendizaje. Una tendencia reciente en clustering, relacionada con la relevancia de los datos y llamada clustering en subespacios, afirma que agrupaciones diferentes pueden estar descritas por subconjuntos de atributos diferentes. Esto difiere de las soluciones tradicionales para el problema de la relevancia de los datos, en las que se busca un único subconjunto de atributos (normalmente el conjunto original de atributos) y se utiliza para realizar el proceso de clustering. La cercanía de este trabajo con el clustering lleva al primer objetivo de la tesis. Como se ha comentado previamente, la validación en clustering es una tarea difícil debido a la ausencia de etiquetas. Aunque existen muchos índices que pueden usarse para evaluar la calidad de las soluciones de clustering, estas validaciones dependen de los algoritmos de clustering utilizados y de las características de los datos. Por lo tanto, en el primer objetivo tres conocidos algoritmos se usan para agrupar datos con valores atípicos y ruido para estudiar de forma crítica cómo se comportan algunos de los índices de validación más conocidos. El objetivo principal de este trabajo sin embargo es combinar clustering semi-supervisado con clustering en subespacios para obtener soluciones de clustering que puedan ser validadas de forma correcta utilizando índices conocidos u opiniones expertas. Se proponen dos algoritmos desde dos puntos de vista diferentes para descubrir agrupaciones caracterizadas por diferentes subespacios. Para el primer algoritmo, las etiquetas disponibles se usan para bus¬car en primer lugar los subespacios antes de buscar las agrupaciones. Este algoritmo asigna cada instancia a un único cluster (hard clustering) y se basa en mapear las etiquetas cono-cidas a subespacios utilizando técnicas de clasificación supervisada. El segundo algoritmo utiliza las etiquetas disponibles para buscar de forma simultánea los subespacios y las agru¬paciones en un proceso iterativo. Este algoritmo asigna cada instancia a cada cluster con una probabilidad de pertenencia (soft clustering) y se basa en integrar las etiquetas conocidas y la búsqueda en subespacios dentro de clustering basado en modelos. Las propuestas son probadas utilizando diferentes bases de datos reales y sintéticas, incluyendo comparaciones con otros métodos cuando resulten apropiadas. Finalmente, a modo de ejemplo de una aplicación real y actual, se aplican diferentes técnicas de aprendizaje automático, incluyendo una de las propuestas de este trabajo (la más sofisticada) a una tarea de uno de los problemas biológicos más desafiantes hoy en día, el modelado del cerebro humano. Específicamente, expertos neurocientíficos no se ponen de acuerdo en una clasificación de neuronas para la corteza cerebral, lo que imposibilita no sólo cualquier intento de modelado sino también el trabajo del día a día al no tener una forma estándar de llamar a las neuronas. Por lo tanto, las técnicas de aprendizaje automático pueden ayudar a conseguir una solución aceptada para este problema, lo cual puede ser un importante hito para investigaciones futuras en neurociencia.

Design and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications?it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ?Activity Monitor? has been designed and implemented: a personal health-persuasive application that provides feedback on the user?s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user?s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.

Energy payback time of grid connected pv systems: comparison between tracking and fixed systems

A review of existing studies about LCA of PV systems has been carried out. The data from this review have been completed with our own figures in order to calculate the Energy Payback Time of double and horizontal axis tracking and fixed systems. The results of this metric span from 2 to 5 years for the latitude and global irradiation ranges of the geographical area comprised between −10◦ to 10◦ of longitude, and 30◦ to 45◦ of latitude. With the caution due to the uncertainty of the sources of information, these results mean that a GCPVS is able to produce back the energy required for its existence from 6 to 15 times during a life cycle of 30 years. When comparing tracking and fixed systems, the great importance of the PV generator makes advisable to dedicate more energy to some components of the system in order to increase the productivity and to obtain a higher performance of the component with the highest energy requirement. Both double axis and horizontal axis trackers follow this way, requiring more energy in metallic structure, foundations and wiring, but this higher contribution is widely compensated by the improved productivity of the system.

Caracterización e instrumentación de sensores de ultrasonidos

El propósito de este proyecto de �fin de carrera es la caracterización e instrumentación de un sensor de ultrasonidos modelado por el tutor de este proyecto: Don César Briso Rodrí��guez. Una vez realizado el modelado de dicho sensor, simulando tanto sus caracter�í�sticas f�í�sicas, como sus caracterí��sticas eléctricas, se procede a la intrumentación y uso del mismo. La parte de intrumentaci�ón incluye tanto la electrónica que ser��á necesaria para la excitación del piezoeléctrico, en el modo de emisi�ón, como para la recepción de los pulsos el�éctricos generados por el sensor, como respuesta a los ecos recibidos, y su adecuación a niveles de señal correctos para la adquisici�ón, en el modo de escucha. Tras la adecuaci�ón de las señales para la adquisici�ón, éstas ser�án digitalizadas, tratadas y representadas por pantalla en un PC, a trav�es de una tarjeta de adquisición de datos por puerto USB encargada del muestreo de las señales de respuesta ya tratadas y su posterior enví��o al software de control y representaci�ón desarrollado en este proyecto. El entorno de usuario, el software de control de la tarjeta de adquisición y el software de tratamiento y representaci�ón se ha desarrollado con Visual Basic 2008 y las utilidades gr�áfi�cas de las librer��ías OpenGL. ABSTRACT The purpose of this project is to limit the characterization and implementation of an ultrasonic sensor modeled by Mr. C�ésar Briso Rodr��íguez. Once the sensor modeling by simulating physical characteristics and electrical characteristics, we proceed to the instrumentation and use. This section includes electronic instrumentation that would be necessary for the piezoelectric excitation in the emission mode and for receiving electrical pulses generated by the sensor in response to the received echoes, and matching signal levels right to acquire, in the reception mode. After the adjustment of the signals for the acquisition, these signals will be digitalized, processed and represented on the screen on a PC through a data acquisition card by USB port. Acquisition card is able to sample the response signals and transmit the samples to representation and control software developed in this project. The user interface, the acquisition card control software and processing and representation software has been developed with Visual Basic 2008 and OpenGL graphical libraries.

Optical memory with twisted nematic liquid crystal (TNLC) devices

A design for obtaining memory in optical bistability with liquid crystals is reported. This design uses optical feedback on a twisted nematie liquid crystal ( TNLC ) through an optoelectronic system. A constant input light is the read-out and its value depends on the desired initial working point, usually at the bottom of the T(V) vs. V curve. Light levels depend on the feedback. An input light pulse change the working point to the top of the transmission curve. When this pulse vanishes, the working point remains at the upper part of the curve. Hence a memory function is obtained. Minimum pulse width needed was 1msec. ON-OPF ratio was 100:3.