A framework for the analysis and optimization of delay in multiview video coding schemes

Esta tesis presenta un novedoso marco de referencia para el análisis y optimización del retardo de codificación y descodificación para vídeo multivista. El objetivo de este marco de referencia es proporcionar una metodología sistemática para el análisis del retardo en codificadores y descodificadores multivista y herramientas útiles en el diseño de codificadores/descodificadores para aplicaciones con requisitos de bajo retardo. El marco de referencia propuesto caracteriza primero los elementos que tienen influencia en el comportamiento del retardo: i) la estructura de predicción multivista, ii) el modelo hardware del codificador/descodificador y iii) los tiempos de proceso de cuadro. En segundo lugar, proporciona algoritmos para el cálculo del retardo de codificación/ descodificación de cualquier estructura arbitraria de predicción multivista. El núcleo de este marco de referencia consiste en una metodología para el análisis del retardo de codificación/descodificación multivista que es independiente de la arquitectura hardware del codificador/descodificador, completada con un conjunto de modelos que particularizan este análisis del retardo con las características de la arquitectura hardware del codificador/descodificador. Entre estos modelos, aquellos basados en teoría de grafos adquieren especial relevancia debido a su capacidad de desacoplar la influencia de los diferentes elementos en el comportamiento del retardo en el codificador/ descodificador, mediante una abstracción de su capacidad de proceso. Para revelar las posibles aplicaciones de este marco de referencia, esta tesis presenta algunos ejemplos de su utilización en problemas de diseño que afectan a codificadores y descodificadores multivista. Este escenario de aplicación cubre los siguientes casos: estrategias para el diseño de estructuras de predicción que tengan en consideración requisitos de retardo además del comportamiento tasa-distorsión; diseño del número de procesadores y análisis de los requisitos de velocidad de proceso en codificadores/ descodificadores multivista dado un retardo objetivo; y el análisis comparativo del comportamiento del retardo en codificadores multivista con diferentes capacidades de proceso e implementaciones hardware. ABSTRACT This thesis presents a novel framework for the analysis and optimization of the encoding and decoding delay for multiview video. The objective of this framework is to provide a systematic methodology for the analysis of the delay in multiview encoders and decoders and useful tools in the design of multiview encoders/decoders for applications with low delay requirements. The proposed framework characterizes firstly the elements that have an influence in the delay performance: i) the multiview prediction structure ii) the hardware model of the encoder/decoder and iii) frame processing times. Secondly, it provides algorithms for the computation of the encoding/decoding delay of any arbitrary multiview prediction structure. The core of this framework consists in a methodology for the analysis of the multiview encoding/decoding delay that is independent of the hardware architecture of the encoder/decoder, which is completed with a set of models that particularize this delay analysis with the characteristics of the hardware architecture of the encoder/decoder. Among these models, the ones based in graph theory acquire special relevance due to their capacity to detach the influence of the different elements in the delay performance of the encoder/decoder, by means of an abstraction of its processing capacity. To reveal possible applications of this framework, this thesis presents some examples of its utilization in design problems that affect multiview encoders and decoders. This application scenario covers the following cases: strategies for the design of prediction structures that take into consideration delay requirements in addition to the rate-distortion performance; design of number of processors and analysis of processor speed requirements in multiview encoders/decoders given a target delay; and comparative analysis of the encoding delay performance of multiview encoders with different processing capabilities and hardware implementations.

Control of a Teleoperation System by State Convergence with Variable Time Delay

In this paper, we propose a novel control scheme for bilateral teleoperation of n degree-of-freedom (DOF) nonlinear robotic systems with time-varying communication delay. We consider that the human operator contains a constant force on the local manipulator. The local and remote manipulators are coupled using state convergence control scheme. By choosing a Lyapunov-Krasovskii functional, we show that the local-remote teleoperation system is asymptotically stable. It is also shown that, in the case of reliable communication protocols, the proposed scheme guarantees that the remote manipulator tracks the delayed trajectory of the local manipulator. The time delay of communication channel is assumed to be unknown and randomly time varying, but the upper bounds of the delay interval and the derivative of the delay are assumed to be known.

Stability Analysis of Teleoperation System by State Convergence with Variable Time Delay

We propose a novel control scheme for bilateral teleoperation of n degree-of-freedom (DOF) nonlinear robotic systems with time-varying communication delay. A major contribution from this work lies in the demonstration that the structure of a state convergence algorithm can be also applied to nth-order nonlinear teleoperation systems. By choosing a Lyapunov Krasovskii functional, we show that the local-remote teleoperation system is asymptotically stable. The time delay of communication channel is assumed to be unknown and randomly time varying, but the upper bounds of the delay interval and the derivative of the delay are assumed to be known.

Design and Test of a High QoS Radio Network for CBTC Systems in Subway Tunnels

Communications Based Train Control Systems require high quality radio data communications for train signaling and control. Actually most of these systems use 2.4GHz band with proprietary radio transceivers and leaky feeder as distribution system. All them demand a high QoS radio network to improve the efficiency of railway networks. We present narrow band, broad band and data correlated measurements taken in Madrid underground with a transmission system at 2.4 GHz in a test network of 2 km length in subway tunnels. The architecture proposed has a strong overlap in between cells to improve reliability and QoS. The radio planning of the network is carefully described and modeled with narrow band and broadband measurements and statistics. The result is a network with 99.7% of packets transmitted correctly and average propagation delay of 20ms. These results fulfill the specifications QoS of CBTC systems.

Selection of TDOA Parameters for MDM Speaker Diarization

Several methods to improve multiple distant microphone (MDM) speaker diarization based on Time Delay of Arrival (TDOA) features are evaluated in this paper. All of them avoid the use of a single reference channel to calculate the TDOA values and, based on different criteria, select among all possible pairs of microphones a set of pairs that will be used to estimate the TDOA's. The evaluated methods have been named the "Dynamic Margin" (DM), the "Extreme Regions" (ER), the "Most Common" (MC), the "Cross Correlation" (XCorr) and the "Principle Component Analysis" (PCA). It is shown that all methods improve the baseline results for the development set and four of them improve also the results for the evaluation set. Improvements of 3.49% and 10.77% DER relative are obtained for DM and ER respectively for the test set. The XCorr and PCA methods achieve an improvement of 36.72% and 30.82% DER relative for the test set. Moreover, the computational cost for the XCorr method is 20% less than the baseline.

Speaker Diarization Based on Intensity Channel Contribution

The time delay of arrival (TDOA) between multiple microphones has been used since 2006 as a source of information (localization) to complement the spectral features for speaker diarization. In this paper, we propose a new localization feature, the intensity channel contribution (ICC) based on the relative energy of the signal arriving at each channel compared to the sum of the energy of all the channels. We have demonstrated that by joining the ICC features and the TDOA features, the robustness of the localization features is improved and that the diarization error rate (DER) of the complete system (using localization and spectral features) has been reduced. By using this new localization feature, we have been able to achieve a 5.2% DER relative improvement in our development data, a 3.6% DER relative improvement in the RT07 evaluation data and a 7.9% DER relative improvement in the last year's RT09 evaluation data.

A linear chained approach for service invocation in IP multimedia subsystem.

IP Multimedia Subsystem (IMS) is considered to provide multimedia services to users through an IP-based control plane. The current IMS service invocation mechanism, however, requires the Serving-Call Session Control Function (S-CSCF) invokes each Application Server (AS) sequentially to perform service subscription pro?le, which results in the heavy load of the S-CSCF and the long session set-up delay. To solve this issue, this paper proposes a linear chained service invocation mechanism to invoke each AS consecutively. By checking all the initial Filter Criteria (iFC) one-time and adding the addresses of all involved ASs to the ?Route? header, this new approach enables multiple services to be invoked as a linear chain during a session. We model the service invocation mechanisms through Jackson networks, which are validated through simulations. The analytic results verify that the linear chained service invocation mechanism can effectively reduce session set-up delay of the service layer and decrease the load level of the S-CSCF

Integrable high order UWB pulse photonic generator based on cross phase modulation in a SOA-MZI

We propose and experimentally demonstrate a potentially integrable optical scheme to generate high order UWB pulses. The technique is based on exploiting the cross phase modulation generated in an InGaAsP Mach-Zehnder interferometer containing integrated semiconductor optical amplifiers, and is also adaptable to different pulse modulation formats through an optical processing unit which allows to control of the amplitude, polarity and time delay of the generated taps.

Extracción de conocimientos de la diabetes tipo 1 utilizando la metodología de "Data Mining"

La diabetes mellitus es un trastorno en la metabolización de los carbohidratos, caracterizado por la nula o insuficiente segregación de insulina (hormona producida por el páncreas), como resultado del mal funcionamiento de la parte endocrina del páncreas, o de una creciente resistencia del organismo a esta hormona. Esto implica, que tras el proceso digestivo, los alimentos que ingerimos se transforman en otros compuestos químicos más pequeños mediante los tejidos exocrinos. La ausencia o poca efectividad de esta hormona polipéptida, no permite metabolizar los carbohidratos ingeridos provocando dos consecuencias: Aumento de la concentración de glucosa en sangre, ya que las células no pueden metabolizarla; consumo de ácidos grasos mediante el hígado, liberando cuerpos cetónicos para aportar la energía a las células. Esta situación expone al enfermo crónico, a una concentración de glucosa en sangre muy elevada, denominado hiperglucemia, la cual puede producir a medio o largo múltiples problemas médicos: oftalmológicos, renales, cardiovasculares, cerebrovasculares, neurológicos… La diabetes representa un gran problema de salud pública y es la enfermedad más común en los países desarrollados por varios factores como la obesidad, la vida sedentaria, que facilitan la aparición de esta enfermedad. Mediante el presente proyecto trabajaremos con los datos de experimentación clínica de pacientes con diabetes de tipo 1, enfermedad autoinmune en la que son destruidas las células beta del páncreas (productoras de insulina) resultando necesaria la administración de insulina exógena. Dicho esto, el paciente con diabetes tipo 1 deberá seguir un tratamiento con insulina administrada por la vía subcutánea, adaptado a sus necesidades metabólicas y a sus hábitos de vida. Para abordar esta situación de regulación del control metabólico del enfermo, mediante una terapia de insulina, no serviremos del proyecto “Páncreas Endocrino Artificial” (PEA), el cual consta de una bomba de infusión de insulina, un sensor continuo de glucosa, y un algoritmo de control en lazo cerrado. El objetivo principal del PEA es aportar al paciente precisión, eficacia y seguridad en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. El PEA se instala mediante vía subcutánea, por lo que, el retardo introducido por la acción de la insulina, el retardo de la medida de glucosa, así como los errores introducidos por los sensores continuos de glucosa cuando, se descalibran dificultando el empleo de un algoritmo de control. Llegados a este punto debemos modelar la glucosa del paciente mediante sistemas predictivos. Un modelo, es todo aquel elemento que nos permita predecir el comportamiento de un sistema mediante la introducción de variables de entrada. De este modo lo que conseguimos, es una predicción de los estados futuros en los que se puede encontrar la glucosa del paciente, sirviéndonos de variables de entrada de insulina, ingesta y glucosa ya conocidas, por ser las sucedidas con anterioridad en el tiempo. Cuando empleamos el predictor de glucosa, utilizando parámetros obtenidos en tiempo real, el controlador es capaz de indicar el nivel futuro de la glucosa para la toma de decisones del controlador CL. Los predictores que se están empleando actualmente en el PEA no están funcionando correctamente por la cantidad de información y variables que debe de manejar. Data Mining, también referenciado como Descubrimiento del Conocimiento en Bases de Datos (Knowledge Discovery in Databases o KDD), ha sido definida como el proceso de extracción no trivial de información implícita, previamente desconocida y potencialmente útil. Todo ello, sirviéndonos las siguientes fases del proceso de extracción del conocimiento: selección de datos, pre-procesado, transformación, minería de datos, interpretación de los resultados, evaluación y obtención del conocimiento. Con todo este proceso buscamos generar un único modelo insulina glucosa que se ajuste de forma individual a cada paciente y sea capaz, al mismo tiempo, de predecir los estados futuros glucosa con cálculos en tiempo real, a través de unos parámetros introducidos. Este trabajo busca extraer la información contenida en una base de datos de pacientes diabéticos tipo 1 obtenidos a partir de la experimentación clínica. Para ello emplearemos técnicas de Data Mining. Para la consecución del objetivo implícito a este proyecto hemos procedido a implementar una interfaz gráfica que nos guía a través del proceso del KDD (con información gráfica y estadística) de cada punto del proceso. En lo que respecta a la parte de la minería de datos, nos hemos servido de la denominada herramienta de WEKA, en la que a través de Java controlamos todas sus funciones, para implementarlas por medio del programa creado. Otorgando finalmente, una mayor potencialidad al proyecto con la posibilidad de implementar el servicio de los dispositivos Android por la potencial capacidad de portar el código. Mediante estos dispositivos y lo expuesto en el proyecto se podrían implementar o incluso crear nuevas aplicaciones novedosas y muy útiles para este campo. Como conclusión del proyecto, y tras un exhaustivo análisis de los resultados obtenidos, podemos apreciar como logramos obtener el modelo insulina-glucosa de cada paciente. ABSTRACT. The diabetes mellitus is a metabolic disorder, characterized by the low or none insulin production (a hormone produced by the pancreas), as a result of the malfunctioning of the endocrine pancreas part or by an increasing resistance of the organism to this hormone. This implies that, after the digestive process, the food we consume is transformed into smaller chemical compounds, through the exocrine tissues. The absence or limited effectiveness of this polypeptide hormone, does not allow to metabolize the ingested carbohydrates provoking two consequences: Increase of the glucose concentration in blood, as the cells are unable to metabolize it; fatty acid intake through the liver, releasing ketone bodies to provide energy to the cells. This situation exposes the chronic patient to high blood glucose levels, named hyperglycemia, which may cause in the medium or long term multiple medical problems: ophthalmological, renal, cardiovascular, cerebrum-vascular, neurological … The diabetes represents a great public health problem and is the most common disease in the developed countries, by several factors such as the obesity or sedentary life, which facilitate the appearance of this disease. Through this project we will work with clinical experimentation data of patients with diabetes of type 1, autoimmune disease in which beta cells of the pancreas (producers of insulin) are destroyed resulting necessary the exogenous insulin administration. That said, the patient with diabetes type 1 will have to follow a treatment with insulin, administered by the subcutaneous route, adapted to his metabolic needs and to his life habits. To deal with this situation of metabolic control regulation of the patient, through an insulin therapy, we shall be using the “Endocrine Artificial Pancreas " (PEA), which consists of a bomb of insulin infusion, a constant glucose sensor, and a control algorithm in closed bow. The principal aim of the PEA is providing the patient precision, efficiency and safety regarding the normalization of the glycemic control and hypoglycemia risk reduction". The PEA establishes through subcutaneous route, consequently, the delay introduced by the insulin action, the delay of the glucose measure, as well as the mistakes introduced by the constant glucose sensors when, decalibrate, impede the employment of an algorithm of control. At this stage we must shape the patient glucose levels through predictive systems. A model is all that element or set of elements which will allow us to predict the behavior of a system by introducing input variables. Thus what we obtain, is a prediction of the future stages in which it is possible to find the patient glucose level, being served of input insulin, ingestion and glucose variables already known, for being the ones happened previously in the time. When we use the glucose predictor, using obtained real time parameters, the controller is capable of indicating the future level of the glucose for the decision capture CL controller. The predictors that are being used nowadays in the PEA are not working correctly for the amount of information and variables that it need to handle. Data Mining, also indexed as Knowledge Discovery in Databases or KDD, has been defined as the not trivial extraction process of implicit information, previously unknown and potentially useful. All this, using the following phases of the knowledge extraction process: selection of information, pre- processing, transformation, data mining, results interpretation, evaluation and knowledge acquisition. With all this process we seek to generate the unique insulin glucose model that adjusts individually and in a personalized way for each patient form and being capable, at the same time, of predicting the future conditions with real time calculations, across few input parameters. This project of end of grade seeks to extract the information contained in a database of type 1 diabetics patients, obtained from clinical experimentation. For it, we will use technologies of Data Mining. For the attainment of the aim implicit to this project we have proceeded to implement a graphical interface that will guide us across the process of the KDD (with graphical and statistical information) of every point of the process. Regarding the data mining part, we have been served by a tool called WEKA's tool called, in which across Java, we control all of its functions to implement them by means of the created program. Finally granting a higher potential to the project with the possibility of implementing the service for Android devices, porting the code. Through these devices and what has been exposed in the project they might help or even create new and very useful applications for this field. As a conclusion of the project, and after an exhaustive analysis of the obtained results, we can show how we achieve to obtain the insulin–glucose model for each patient.

Factores de riesgo que inciden negativamente en los cumplimientos de tiempo y coste programados en la ejecución de proyectos de edificios de uso hotelero en España

Las desviaciones de tiempo y coste constituyen un fenómeno muy frecuente en la industria de la construcción. Existe un gran número de proyectos que no se terminan en el plazo y el tiempo estipulados, y esto parece que se ha convertido más en la norma que en la excepción. Los proyectos de construcción son heterogéneos por naturaleza y pueden llegar a ser muy complejos, involucrando numerosos procesos y expuestos a infinidad de variables y factores que pueden afectar el cumplimiento de los objetivos de tiempo y coste. Las desviaciones de tiempo y coste no favorecen ni al promotor ni al resto de equipos participantes del proyecto, dando lugar además la mayoría de las veces a situaciones de conflictos y relaciones adversas entre participantes del proyecto. Es por todo ello que surge la necesidad de atender a una estrategia de gestión de riesgos eficaz, como herramienta esencial de la gestión de proyectos para contribuir al éxito de los mismos. Es preciso considerar también que los proyectos de construcción pueden presentar distintas características específicas según el tipo de proyecto de que se traten. El presente trabajo de investigación estudia concretamente los proyectos de edificios de uso hotelero, los cuales pueden presentar estructuras organizativas muy diversas, incluyendo numerosos agentes participantes y procesos que a su vez se desarrollan en un entorno que ya es muy dinámico por su propia naturaleza. En el sector hotelero el cumplimiento de los objetivos de tiempo y coste del proyecto son especialmente importantes ya que cualquier retraso en la fecha de apertura estimada del hotel se traducirá en pérdidas importantes de negocio y cuota de mercado y podrá llevar asociadas también repercusiones importantes en otros aspectos relacionados con la operativa hotelera. Si se conocen las causas que originan tales desviaciones de tiempo y coste, se podrán establecer las correspondientes medidas de actuación para anticiparnos a ellas y que no se produzcan, siendo ésta la base del propósito de esta tesis. Así, la identificación de riesgos supone el primer paso para una gestión de riesgos eficaz, fundamental para contribuir al éxito de un proyecto. El contexto de la investigación delimita como lugar geográfico de estudio España, donde el sector turístico constituye un motor importante de la economía y en el que la eficiencia y competitividad debe estar reflejada también en el proceso del proyecto edificatorio, minimizándose los retrasos y sobrecostes. El presente estudio investiga por tanto los factores de riesgo más críticos que dan lugar a desviaciones de tiempo y coste en proyectos de edificios de uso hotelero en España. A partir del análisis de la literatura existente se genera una propuesta de identificación de factores de riesgo, que se analiza mediante un análisis cualitativo basado en la opinión de expertos y estudio de casos específicos. De los resultados de este análisis se determinan los niveles críticos para cada factor de riesgo, se comparan además las percepciones de niveles de riesgo según distintos tipos de grupos profesionales, y se establece un procedimiento en cuanto a prioridad de acción de respuesta. Así, se desarrolla una propuesta final de identificación y matriz de factores de riesgo con el objetivo de que pueda servir de base a propietarios, empresas gestoras y otros participantes de proyectos hoteleros para diseñar un plan de gestión de riesgos eficaz, contribuyendo de este modo al éxito del proyecto en cuanto a cumplimiento de objetivos de tiempo y coste programados. ABSTRACT Cost and schedule overruns constitute a very frequent phenomenon in the construction industry. A large number of construction projects do not finish on the estimated time and cost, and this scenario seems to be becoming the norm rather than the exception. Construction projects are heterogeneous by nature and they can become very complex as they involve a large number of processes which are subject to many variables and factors that may give rise to time and cost overruns. Time and cost overruns cause dissatisfaction not only to owners but all stakeholders involved in the project, leading most of the times to undesirable situations of conflicts and adversarial relationships between project participants. Hence, it becomes necessary to adopt an effective risk management strategy as an essential part of project management in order to achieve project success. Construction projects may have different characteristics depending on the type of project. This research specifically focuses on hotel construction projects. Hotel projects usually involve complex organizational structures, including many project participants and processes which develop in an environment that is already dynamic by nature. In this type of projects, the achievement of time and cost objectives is particularly important, as any delay of the hotel opening date will result in significant loss of business and market share and may also involve key important implications related to hotel operations. If the risk factors that lead to time and cost overrun are known in advance, preventive actions could be established in order to avoid them, so that time and cost overruns are minimized. This constitutes the aim of this research, being risk identification the first step of any effective risk management strategy for project success. The context of this research is focused on a particular geographical area, being this Spain. Tourism in Spain is a major contributor to the Spanish economy, and efficiency and competiveness should also be reflected in the building processes of the hotel industry, where delays and cost overruns should be kept to the minimum. The aim of this study is to explore the most critical risk factors leading to time and cost overruns in hotel construction projects in Spain. From the analysis of the literature review, a proposal of a risk identification framework is developed, which will be further analyzed by a qualitative assessment based on expert opinions and the study of specific case studies. From the results of this assessment, the levels of risk criticality are determined for the identified factors, a comparison of the perceptions of risk levels among different groups of respondents is also carried out, and a procedure for prioritization of factors in terms of needs of response is established. A final proposal of a risk register matrix framework is then developed in order to assist hotel owners, project management companies or other hotel project stakeholders, and provide them with a base to design their own specific risk management plans, contributing in this way to project success with regards to the achievement of cost and time objectives.

Area-delay Trade-offs of Texture Decompressors for a Graphics Processing Unit

Graphics Processing Units have become a booster for the microelectronics industry. However, due to intellectual property issues, there is a serious lack of information on implementation details of the hardware architecture that is behind GPUs. For instance, the way texture is handled and decompressed in a GPU to reduce bandwidth usage has never been dealt with in depth from a hardware point of view. This work addresses a comparative study on the hardware implementation of different texture decompression algorithms for both conventional (PCs and video game consoles) and mobile platforms. Circuit synthesis is performed targeting both a reconfigurable hardware platform and a 90nm standard cell library. Area-delay trade-offs have been extensively analyzed, which allows us to compare the complexity of decompressors and thus determine suitability of algorithms for systems with limited hardware resources.

Pulse shortening of gain switched single mode semiconductor lasers using a variable delay interferometer

We propose a pulse shaping and shortening technique for pulses generated from gain switched single mode semiconductor lasers, based on a Mach Zehnder interferometer with variable delay. The spectral and temporal characteristics of the pulses obtained with the proposed technique are investigated with numerical simulations. Experiments are performed with a Distributed Feedback laser and a Vertical Cavity Surface Emitting Laser, emitting at 1.5 µm, obtaining pulse duration reduction of 25-30%. The main asset of the proposed technique is that it can be applied to different devices and pulses, taking advantage of the flexibility of the gain switching technique.

Electrically tunable delay for trains of optical pulses

A technique to implement an electrically tunable delay line with high bandwidth for trains of ultrashort optical pulses is presented. The system is based on the temporal self-imaging effect in fiber gratings and electrooptic modulation.

Synthesis of arbitrary group delay responses with all-pass optical cavities structures

We propose a systematic method for the synthesis of arbitrary group delay responses by using allpass structures of coupled optical cavities. Optimum structure parameters design, in terms of filter order and accuracy, are obtained.

Influence of delay time on regularity estimation for voice pathology detection

The employment of nonlinear analysis techniques for automatic voice pathology detection systems has gained popularity due to the ability of such techniques for dealing with the underlying nonlinear phenomena. On this respect, characterization using nonlinear analysis typically employs the classical Correlation Dimension and the largest Lyapunov Exponent, as well as some regularity quantifiers computing the system predictability. Mostly, regularity features highly depend on a correct choosing of some parameters. One of those, the delay time �, is usually fixed to be 1. Nonetheless, it has been stated that a unity � can not avoid linear correlation of the time series and hence, may not correctly capture system nonlinearities. Therefore, present work studies the influence of the � parameter on the estimation of regularity features. Three � estimations are considered: the baseline value 1; a � based on the Average Automutual Information criterion; and � chosen from the embedding window. Testing results obtained for pathological voice suggest that an improved accuracy might be obtained by using a � value different from 1, as it accounts for the underlying nonlinearities of the voice signal.