Multi-objective Optimization Framework for Trade-Off Among Pedestrian Delays and Vehicular Emissions at Signal-Controlled Intersections

Traffic congestion has several adverse effects on urban traffic networks. Increased travel times of vehicles, with the addition of excessive greenhouse emissions, can be listed as harmful effects. To address these issues, transportation engineers aim to reduce private car usage, reduce travel times through different control strategies, and mitigate harmful effects on urban networks. In this study, we introduce an innovative approach to optimizing traffic signal control settings. This methodology takes into account both pedestrian delays and vehicular emissions. Non-dominated sorting genetic algorithm-II and Multiobjective Artificial Bee Colony algorithms are adopted to solve the multi-objective optimization problem. The vehicular emissions are modeled through the MOVES3 emission model and integrated into the utilized microsimulation environment. Initially, the proposed framework is tested on a hypothetical test network, followed by a real-world case study. Results indicate a significant improvement in pedestrian delays and lower emissions

Component-wise conditionally unbiased widely linear MMSE estimation

AbstractBiased estimators can outperform unbiased ones in terms of the mean square error (MSE). The best linear unbiased estimator (BLUE) fulfills the so called global conditional unbiased constraint when treated in the Bayesian framework. Recently, the component-wise conditionally unbiased linear minimum mean square error (CWCU LMMSE) estimator has been introduced. This estimator preserves a quite strong (namely the CWCU) unbiased condition which in effect sufficiently represents the intuitive view of unbiasedness. Generally, it is global conditionally biased and outperforms the BLUE in a Bayesian MSE sense. In this work we briefly recapitulate CWCU LMMSE estimation under linear model assumptions, and additionally derive the CWCU LMMSE estimator under the (only) assumption of jointly Gaussian parameters and measurements. The main intent of this work, however, is the extension of the theory of CWCU estimation to CWCU widely linear estimators. We derive the CWCU WLMMSE estimator for different model assumptions and address the analytical relationships between CWCU WLMMSE and WLMMSE estimators. The properties of the CWCU WLMMSE estimator are deduced analytically, and compared by simulation to global conditionally unbiased as well as WLMMSE counterparts with the help of a parameter estimation example and a data estimation/channel equalization application

Caracterización del Edema Macular Diabético mediante análisis automático de Tomografías de Coherencia Óptica

Programa Oficial de Doctorado en Computación. 5009V01[Abstract] Diabetic Macular Edema (DME) is one of the most important complications of diabetes and a leading cause of preventable blindness in the developed countries. Among the di erent image modalities, Optical Coherence Tomography (OCT) is a non-invasive, cross-sectional and high-resolution imaging technique that is commonly used for the analysis and interpretation of many retinal structures and ocular disorders. In this way, the development of Computer-Aided Diagnosis (CAD) systems has become relevant over the recent years, facilitating and simplifying the work of the clinical specialists in many relevant diagnostic processes, replacing manual procedures that are tedious and highly time-consuming. This thesis proposes a complete methodology for the identi cation and characterization of DMEs using OCT images. To do so, the system combines and exploits di erent clinical knowledge with image processing and machine learning strategies. This automatic system is able to identify and characterize the main retinal structures and several pathological conditions that are associated with the DME disease, following the clinical classi cation of reference in the ophthalmological eld. Despite the complexity and heterogeneity of this relevant ocular pathology, the proposed system achieved satisfactory results, proving to be robust enough to be used in the daily clinical practice, helping the clinicians to produce a more accurate diagnosis and indicate adequate treatments[Resumen] El Edema Macular Diabético (EMD) es una de las complicaciones más importantes de la diabetes y una de las principales causas de ceguera prevenible en los países desarrollados. Entre las diferentes modalidades de imagen, la Tomografía de Coherencia Óptica (TCO) es una técnica de imagen no invasiva, transversal y de alta resolución que se usa comúnmente para el análisis e interpretación de múltiples estructuras retinianas y trastornos oculares. De esta manera, el desarrollo de los sistemas de Diagnóstico Asistido por Ordenador (DAO) se ha vuelto relevante en los últimos años, facilitando y simplificando el trabajo de los especialistas clínicos en muchos procesos diagnósticos relevantes, reemplazando procedimientos manuales que son tediosos y requieren mucho tiempo. Esta tesis propone una metodología completa para la identificación y caracterización de EMDs utilizando imágenes TCO. Para ello, el sistema desarrollado combina y explota diferentes conocimientos clínicos con estrategias de procesamiento de imágenes y aprendizaje automático. Este sistema automático es capaz de identificar y caracterizar las principales estructuras retinianas y diferentes afecciones patológicas asociadas con el EMD, siguiendo la clasificación clínica de referencia en el campo oftalmológico. A pesar de la complejidad de esta relevante patología ocular, el sistema propuesto logró resultados satisfactorios, demostrando ser lo sufi cientemente robusto como para ser usado en la práctica clínica diaria, ayudando a los médicos a producir diagnósticos más precisos y tratamientos más adecuados.[Resumo] O Edema Macular Diabético ( EMD) é unha das complicacións máis importantes da diabetes e unha das principais causas de cegueira prevenible nos países desenvoltos. Entre as diferentes modalidades de imaxe, a Tomografía de Coherencia Óptica ( TCO) é unha técnica de imaxe non invasiva, transversal e de alta resolución que se usa comunmente para a análise e interpretación de múltiples estruturas retinianas e trastornos oculares. Desta maneira, o desenvolvemento dos sistemas de Diagnóstico Asistido por Computador ( DAO) volveuse relevante nos últimos anos, facilitando e simplificando o traballo dos especialistas clínicos en moitos procesos diagnósticos relevantes, substituíndo procedementos manuais que son tediosos e requiren moito tempo. Esta tese propón unha metodoloxía completa para a identificación e caracterización de EMDs utilizando imaxes TCO. Para iso, o sistema desenvolto combina e explota diferentes coñecementos clínicos con estratexias de procesamento de imaxes e aprendizaxe automático. Este sistema automático é capaz de identificar e caracterizar as principais estruturas retinianas e diferentes afeccións patolóxicas asociadas co EMD, seguindo a clasificación clínica de referencia no campo oftalmolóxico. A pesar da complexidade desta relevante patoloxía ocular, o sistema proposto logrou resultados satisfactorios, demostrando ser o sufi cientemente robusto como para ser usado na práctica clínica diaria, axudando aos médicos para producir diagnósticos máis precisos e tratamentos máis adecuados

Aplicación de técnicas de pruebas automáticas basadas en propiedades a los diferentes niveles de prueba del software

[Resumen]Las pruebas son una de las actividades clave en el desarrollo de software, puesto que ayudan a detectar defectos que, de otro modo, pasarían desapercibidos hasta que el software sea desplegado. Sin embargo, al contrario que en otras etapas del ciclo de vida del software, como son el análisis, el diseño o la implementación, para las que existen metodologías y técnicas bien definidas y ampliamente aceptadas en la comunidad informática, junto con herramientas que permiten llevar a cabo dichas tareas, no hay una uniformidad sobre las metodologías, técnicas o herramientas a utilizar para llevar a cabo las pruebas del software de una manera eficiente y eficaz. Este hecho provoca que, muchas veces, éstas sean omitidas o no realizadas con todo el rigor necesario. Esta tesis presenta una aproximación, basada en propiedades y puramente funcional, para la realización de las pruebas del software, que intenta paliar estos problemas. Para ello, se definen metodologías y técnicas de pruebas, integradas en el proceso de desarrollo de software, que pueden ser aplicadas a los diferentes niveles de pruebas del software. Así, pueden utilizarse para llevar a cabo pruebas unitarias y de componente, en las que se comprueba que cada componente individual se comporta de la manera esperada, pruebas de integración, que comprueban las interacciones de los componentes que forman parte de un sistema, y pruebas de sistema, que se encargan de comprobar diferentes aspectos del sistema como un todo. Además, se utiliza un lenguaje de especificación de pruebas común en todas las aproximaciones desarrolladas, el lenguaje de programación funcional Erlang, y las metodologías se definen de manera independiente a la estructura del software concreto a probar o el lenguaje de programación en el que éste esté implementado. Por último, cabe destacar que el uso de estas metodologías y técnicas de pruebas se ilustra a través de un ejemplo industrial, en concreto, el sistema VoDKATV. Este sistema ofrece acceso a servicios multimedia (canales de televisión, videoclub, aplicaciones, juegos, entre otros) a través de diferentes tipos de dispositivos, como, por ejemplo, televisiones, ordenadores, tabletas o móviles. Con respecto a la arquitectura, el sistema VoDKATV está compuesto por múltiples componentes implementados con diferentes tecnologías (Java, Erlang, C, etc.) que se integran entre sí. La complejidad de este sistema permite ilustrar cada una de las metodologías y técnicas de pruebas desarrolladas con un ejemplo real

Designing a human-centred, mobile interface to support real-time flood forecasting and warning system

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThere is a demand for human-centred technology which improves the management of flood events. This thesis describes the development, design and evaluation of a mobile GIS-based hydrological model. The application provides hydrological forecasts and issues flood warnings. The thesis reports on the usability and practicality of the application. The application, a mobile-based hydrological modelling system, permits the integrated handling of real-time rainfall data from a wireless monitoring network. A spatially distributed GIS-based model integrates this incoming data, approximating real-time, to generate data on catchment hydrology and runoff. The data can be accessed from any android-based mobile computer or mobile phone. It may be further analysed online using several GIS and numerical functions. A human-centred approach to design was taken. Design guidelines for a user-centric application were developed and deployed in the first prototype. There was intensive consultation with potential users. Particular attention was paid to the ease of use of the mobile interface. Users’ needs and attitudes were relevant in the achievement of a highly functional but intuitive interface. The first prototype underwent intensive testing with users. After the initial testing of the first prototype an interactive approach was taken to development. This generated a high-fidelity prototype which was matched to the taxonomy from a user’s mental model. Users were interrogated under controlled laboratory conditions as they performed predefined tasks which were selected to generate data across all aspects of the system and to identify weaknesses. Subsequent to this work there was a major prototype re-design. User test data, identified issues and an improved mental taxonomy closer were used to further refine the application. Of particular note was new functionality which aligned with user expectations and enhanced the applications credibility. The final evaluation of the system was undertaken with diverse subjects. Overall, the subjects considered the system efficient and effective. Users said the system was easy to learn and integrate into their work. Task completion rates were satisfactory. The final interviews with users confirmed that the application was ready to proceed to the implementation phase

IberSPEECH 2020: XI Jornadas en Tecnología del Habla and VII Iberian SLTech

IberSPEECH2020 is a two-day event, bringing together the best researchers and practitioners in speech and language technologies in Iberian languages to promote interaction and discussion. The organizing committee has planned a wide variety of scientific and social activities, including technical paper presentations, keynote lectures, presentation of projects, laboratories activities, recent PhD thesis, discussion panels, a round table, and awards to the best thesis and papers. The program of IberSPEECH2020 includes a total of 32 contributions that will be presented distributed among 5 oral sessions, a PhD session, and a projects session. To ensure the quality of all the contributions, each submitted paper was reviewed by three members of the scientific review committee. All the papers in the conference will be accessible through the International Speech Communication Association (ISCA) Online Archive. Paper selection was based on the scores and comments provided by the scientific review committee, which includes 73 researchers from different institutions (mainly from Spain and Portugal, but also from France, Germany, Brazil, Iran, Greece, Hungary, Czech Republic, Ucrania, Slovenia). Furthermore, it is confirmed to publish an extension of selected papers as a special issue of the Journal of Applied Sciences, “IberSPEECH 2020: Speech and Language Technologies for Iberian Languages”, published by MDPI with fully open access. In addition to regular paper sessions, the IberSPEECH2020 scientific program features the following activities: the ALBAYZIN evaluation challenge session.Red Española de Tecnologías del Habla. Universidad de Valladoli