An evolutionary algorithm for the surface structure problem

Many macroscopic properties: hardness, corrosion, catalytic activity, etc. are directly related to the surface structure, that is, to the position and chemical identity of the outermost atoms of the material. Current experimental techniques for its determination produce a “signature” from which the structure must be inferred by solving an inverse problem: a solution is proposed, its corresponding signature computed and then compared to the experiment. This is a challenging optimization problem where the search space and the number of local minima grows exponentially with the number of atoms, hence its solution cannot be achieved for arbitrarily large structures. Nowadays, it is solved by using a mixture of human knowledge and local search techniques: an expert proposes a solution that is refined using a local minimizer. If the outcome does not fit the experiment, a new solution must be proposed again. Solving a small surface can take from days to weeks of this trial and error method. Here we describe our ongoing work in its solution. We use an hybrid algorithm that mixes evolutionary techniques with trusted region methods and reuses knowledge gained during the execution to avoid repeated search of structures. Its parallelization produces good results even when not requiring the gathering of the full population, hence it can be used in loosely coupled environments such as grids. With this algorithm, the solution of test cases that previously took weeks of expert time can be automatically solved in a day or two of uniprocessor time.

A guided heuristic approach to the MEG inverse problem.

There is general agreement within the scientific community in considering Biology as the science with more potential to develop in the XXI century. This is due to several reasons, but probably the most important one is the state of development of the rest of experimental and technological sciences. In this context, there are a very rich variety of mathematical tools, physical techniques and computer resources that permit to do biological experiments that were unbelievable only a few years ago. Biology is nowadays taking advantage of all these newly developed technologies, which are been applied to life sciences opening new research fields and helping to give new insights in many biological problems. Consequently, biologists have improved a lot their knowledge in many key areas as human function and human diseases. However there is one human organ that is still barely understood compared with the rest: The human brain. The understanding of the human brain is one of the main challenges of the XXI century. In this regard, it is considered a strategic research field for the European Union and the USA. Thus, there is a big interest in applying new experimental techniques for the study of brain function. Magnetoencephalography (MEG) is one of these novel techniques that are currently applied for mapping the brain activity1. This technique has important advantages compared to the metabolic-based brain imagining techniques like Functional Magneto Resonance Imaging2 (fMRI). The main advantage is that MEG has a higher time resolution than fMRI. Another benefit of MEG is that it is a patient friendly clinical technique. The measure is performed with a wireless set up and the patient is not exposed to any radiation. Although MEG is widely applied in clinical studies, there are still open issues regarding data analysis. The present work deals with the solution of the inverse problem in MEG, which is the most controversial and uncertain part of the analysis process3. This question is addressed using several variations of a new solving algorithm based in a heuristic method. The performance of those methods is analyzed by applying them to several test cases with known solutions and comparing those solutions with the ones provided by our methods.

DROMO formulation for planar motions: Solution to the Tsien Problem

The two-body problem subject to a constant radial thrust is analyzed as a planar motion. The description of the problem is performed in terms of three perturbation methods: DROMO and two others due to Deprit. All of them rely on Hansen?s ideal frame concept. An explicit, analytic, closed-form solution is obtained for this problem when the initial orbit is circular (Tsien problem), based on the DROMO special perturbation method, and expressed in terms of elliptic integral functions. The analytical solution to the Tsien problem is later used as a reference to test the numerical performance of various orbit propagation methods, including DROMO and Deprit methods, as well as Cowell and Kustaanheimo?Stiefel methods.

New On-Line Excitation-System Ground Fault Location Method Tested in a 106 MVA Synchronous Generator

In this paper, a novel excitation-system ground-fault location method is described and tested in a 106 MVA synchronous machine. In this unit, numerous rotor ground-fault trips took place always about an hour after the synchronization to the network. However, when the field winding insulation was checked after the trips, there was no failure. The data indicated that the faults in the rotor were caused by centrifugal forces and temperature. Unexpectedly, by applying this new method, the failure was located in a cable between the excitation transformer and the automatic voltage regulator. In addition, several intentional ground faults were performed along the field winding with different fault resistance values, in order to test the accuracy of this method to locate defects in rotor windings of large generators. Therefore, this new on-line rotor ground-fault detection algorithm is tested in high-power synchronous generators with satisfactory results.

Diseño y banco de test VHDL de un procesador que realice la ICT para HEVC

Se va a realizar un estudio de la codificación de imágenes sobre el estándar HEVC (high-effiency video coding). El proyecto se va a centrar en el codificador híbrido, más concretamente sobre la aplicación de la transformada inversa del coseno que se realiza tanto en codificador como en el descodificador. La necesidad de codificar vídeo surge por la aparición de la secuencia de imágenes como señales digitales. El problema principal que tiene el vídeo es la cantidad de bits que aparecen al realizar la codificación. Como consecuencia del aumento de la calidad de las imágenes, se produce un crecimiento exponencial de la cantidad de información a codificar. La utilización de las transformadas al procesamiento digital de imágenes ha aumentado a lo largo de los años. La transformada inversa del coseno se ha convertido en el método más utilizado en el campo de la codificación de imágenes y video. Las ventajas de la transformada inversa del coseno permiten obtener altos índices de compresión a muy bajo coste. La teoría de las transformadas ha mejorado el procesamiento de imágenes. En la codificación por transformada, una imagen se divide en bloques y se identifica cada imagen a un conjunto de coeficientes. Esta codificación se aprovecha de las dependencias estadísticas de las imágenes para reducir la cantidad de datos. El proyecto realiza un estudio de la evolución a lo largo de los años de los distintos estándares de codificación de video. Se analiza el codificador híbrido con más profundidad así como el estándar HEVC. El objetivo final que busca este proyecto fin de carrera es la realización del núcleo de un procesador específico para la ejecución de la transformada inversa del coseno en un descodificador de vídeo compatible con el estándar HEVC. Es objetivo se logra siguiendo una serie de etapas, en las que se va añadiendo requisitos. Este sistema permite al diseñador hardware ir adquiriendo una experiencia y un conocimiento más profundo de la arquitectura final. ABSTRACT. A study about the codification of images based on the standard HEVC (high-efficiency video coding) will be developed. The project will be based on the hybrid encoder, in particular, on the application of the inverse cosine transform, which is used for the encoder as well as for the decoder. The necessity of encoding video arises because of the appearance of the sequence of images as digital signals. The main problem that video faces is the amount of bits that appear when making the codification. As a consequence of the increase of the quality of the images, an exponential growth on the quantity of information that should be encoded happens. The usage of transforms to the digital processing of images has increased along the years. The inverse cosine transform has become the most used method in the field of codification of images and video. The advantages of the inverse cosine transform allow to obtain high levels of comprehension at a very low price. The theory of the transforms has improved the processing of images. In the codification by transform, an image is divided in blocks and each image is identified to a set of coefficients. This codification takes advantage of the statistic dependence of the images to reduce the amount of data. The project develops a study of the evolution along the years of the different standards in video codification. In addition, the hybrid encoder and the standard HEVC are analyzed more in depth. The final objective of this end of degree project is the realization of the nucleus from a specific processor for the execution of the inverse cosine transform in a decoder of video that is compatible with the standard HEVC. This objective is reached following a series of stages, in which requirements are added. This system allows the hardware designer to acquire a deeper experience and knowledge of the final architecture.