Self-Organized Maps

Se han obtenido los siguientes resultados: (1) Estudio de topologías bidimensionales alternativas: se muestra la importancia de topologías alternativas basadas en áreas ajenas como las teselaciones. (2) Estudio comparativo de topologías en una, dos y tres dimensiones: se revela la influencia de la dimensión en el funcionamiento de una SOM a escala local y global. (3) Estudio de alternativas al movimiento euclídeo: se propone y presenta la alternativa FRSOM al algoritmo SOM clásico. En FRSOM, las neuronas esquivan barreras predefinidas en su movimiento. Las conclusiones más relevantes que emanan de esta Tesis Doctoral son las siguientes: (1) La calidad del clustering y de la preservación topológica de una SOM puede ser mejorada mediante el uso de topologías alternativas y también evitando regiones prohibidas que no contribuyan significativamente al Error Cuadrático Medio (ECM). (2) La dimensióon de la SOM que obtiene mejores resultados es la propia dimensión intrínseca de los datos. Además, en general, valores bajos para la dimensión de la SOM producen mejores resultados en términos del ECM, y valores altos ocasionan mejor aprendizaje de la estructura de los datos.Los mapas auto-organizados o redes de Kohonen (SOM por sus siglas en inglés, self-organizing map) fueron introducidos por el profesor finlandés Teuvo Kalevi Kohonen en los años 80. Un mapa auto-organizado es una herramienta que analiza datos en muchas dimensiones con relaciones complejas entre ellos y los reduce o representa en, usualmente, una, dos o tres dimensiones. La propiedad más importante de una SOM es que preserva las propiedades topológicas de los datos, es decir, que datos próximos aparecen próximos en la representación. La literatura relacionada con los mapas auto-organizados y sus aplicaciones es muy diversa y numerosa. Las neuronas en un mapa auto-organizado clásico están distribuidas en una topología (o malla) bidimensional cuadrada o hexagonal y las distancias entre ellas son distancias euclídeas. Una de las disciplinas de investigación en SOM consiste en la modificación y generalización del algoritmo SOM. Esta Tesis Doctoral por compendio de publicaciones se centra en esta línea de investigación. En concreto, los objetivos desarrollados han sido el estudio de topologías bidimensionales alternativas, el estudio comparativo de topologías de una, dos y tres dimensiones y el estudio de variaciones para la distancia y movimientos euclídeos. Estos objetivos se han abordado mediante el método científico a través de las siguientes fases: aprehensión de resultados conocidos, planteamiento de hipótesis, propuesta de métodos alternativos, confrontación de métodos mediante experimentación, aceptación y rechazo de las diversas hipótesis mediante métodos estadísticos

Assessing system architectures: the Canonical Decomposition Fuzzy Comparative methodology

The impacts of decisions made during the selection of the system architecture propagate throughout the entire system lifecycle. The challenge for system architects is to perform a realistic assessment of an inherently ambiguous system concept. Subject matter expert interpretations, intuition, and heuristics are performed quickly and guide system development in the right overall direction, but these methods are subjective and unrepeatable. Traditional analytical assessments dismiss complexity in a system by assuming severability between system components and are intolerant of ambiguity. To be defensible, a suitable methodology must be repeatable, analytically rigorous, and yet tolerant of ambiguity. The hypothesis for this research is that an architecture assessment methodology capable of achieving these objectives is possible by drawing on the strengths of existing approaches while addressing their collective weaknesses. The proposed methodology is the Canonical Decomposition Fuzzy Comparative approach. The theoretical foundations of this methodology are developed and tested through the assessment of three physical architectures for a peer-to-peer wireless network. An extensible modeling framework is established to decompose high-level system attributes into technical performance measures suitable for analysis via computational modeling. Canonical design primitives are used to assess antenna performance in the form of a comparative analysis between the baseline free space gain patterns and the installed gain patterns. Finally, a fuzzy inference system is used to interpret the comparative feature set and offer a numerical assessment. The results of this experiment support the hypothesis that the proposed methodology is well suited for exposing integration sensitivity and assessing coupled performance in physical architecture concepts --Abstract, page iii

Using signal processing, evolutionary computation, and machine learning to identify transposable elements in genomes

About half of the human genome consists of transposable elements (TE's), sequences that have many copies of themselves distributed throughout the genome. All genomes, from bacterial to human, contain TE's. TE's affect genome function by either creating proteins directly or affecting genome regulation. They serve as molecular fossils, giving clues to the evolutionary history of the organism. TE's are often challenging to identify because they are fragmentary or heavily mutated. In this thesis, novel features for the detection and study of TE's are developed. These features are of two types. The first type are statistical features based on the Fourier transform used to assess reading frame use. These features measure how different the reading frame use is from that of a random sequence, which reading frames the sequence is using, and the proportion of use of the active reading frames. The second type of feature, called side effect machine (SEM) features, are generated by finite state machines augmented with counters that track the number of times the state is visited. These counters then become features of the sequence. The number of possible SEM features is super-exponential in the number of states. New methods for selecting useful feature subsets that incorporate a genetic algorithm and a novel clustering method are introduced. The features produced reveal structural characteristics of the sequences of potential interest to biologists. A detailed analysis of the genetic algorithm, its fitness functions, and its fitness landscapes is performed. The features are used, together with features used in existing exon finding algorithms, to build classifiers that distinguish TE's from other genomic sequences in humans, fruit flies, and ciliates. The classifiers achieve high accuracy (> 85%) on a variety of TE classification problems. The classifiers are used to scan large genomes for TE's. In addition, the features are used to describe the TE's in the newly sequenced ciliate, Tetrahymena thermophile to provide information for biologists useful to them in forming hypotheses to test experimentally concerning the role of these TE's and the mechanisms that govern them

Smart hierarchical WiFi localization system for indoors

Premio Extraordinario de Doctorado de la UAH en el año académico 2013-2014En los últimos años, el número de aplicaciones para smartphones y tablets ha crecido rápidamente. Muchas de estas aplicaciones hacen uso de las capacidades de localización de estos dispositivos. Para poder proporcionar su localización, es necesario identificar la posición del usuario de forma robusta y en tiempo real. Tradicionalmente, esta localización se ha realizado mediante el uso del GPS que proporciona posicionamiento preciso en exteriores. Desafortunadamente, su baja precisión en interiores imposibilita su uso. Para proporcionar localización en interiores se utilizan diferentes tecnologías. Entre ellas, la tecnología WiFi es una de las más usadas debido a sus importantes ventajas tales como la disponibilidad de puntos de acceso WiFi en la mayoría de edificios y que medir la señal WiFi no tiene coste, incluso en redes privadas. Desafortunadamente, también tiene algunas desventajas, ya que en interiores la señal es altamente dependiente de la estructura del edificio por lo que aparecen otros efectos no deseados, como el efecto multicamino o las variaciones de pequeña escala. Además, las redes WiFi están instaladas para maximizar la conectividad sin tener en cuenta su posible uso para localización, por lo que los entornos suelen estar altamente poblados de puntos de acceso, aumentando las interferencias co-canal, que causan variaciones en el nivel de señal recibido. El objetivo de esta tesis es la localización de dispositivos móviles en interiores utilizando como única información el nivel de señal recibido de los puntos de acceso existentes en el entorno. La meta final es desarrollar un sistema de localización WiFi para dispositivos móviles, que pueda ser utilizado en cualquier entorno y por cualquier dispositivo, en tiempo real. Para alcanzar este objetivo, se propone un sistema de localización jerárquico basado en clasificadores borrosos que realizará la localización en entornos descritos topológicamente. Este sistema proporcionará una localización robusta en diferentes escenarios, prestando especial atención a los entornos grandes. Para ello, el sistema diseñado crea una partición jerárquica del entorno usando K-Means. Después, el sistema de localización se entrena utilizando diferentes algoritmos de clasificación supervisada para localizar las nuevas medidas WiFi. Finalmente, se ha diseñado un sistema probabilístico para seguir la posición del dispositivo en movimiento utilizando un filtro Bayesiano. Este sistema se ha probado en un entorno real, con varias plantas, obteniendo un error medio total por debajo de los 3 metros

Wireless distributed intelligence in personal applications

Tietokoneet ovat historian kuluessa kehittyneet keskustietokoneista hajautettujen, langattomasti toimivien järjestelmien suuntaan. Elektroniikalla toteutetut automaattiset toiminnot ympärillämme lisääntyvät kiihtyvällä vauhdilla. Tällaiset sovellukset lisääntyvät tulevaisuudessa, mutta siihen soveltuva tekniikka on vielä kehityksen alla ja vaadittavia ominaisuuksia ei aina löydy. Nykyiset lyhyen kantaman langattoman tekniikan standardit ovat tarkoitettu lähinnä teollisuuden ja multimedian käyttöön, siksi ne ovat vain osittain soveltuvia uudenlaisiin ympäristöälykkäisiin käyttötarkoituksiin. Ympäristöälykkäät sovellukset palvelevat enimmäkseen jokapäiväistä elämäämme, kuten turvallisuutta, kulunvalvontaa ja elämyspalveluita. Ympäristöälykkäitä ratkaisuja tarvitaan myös hajautetussa automaatiossa ja kohteiden automaattisessa seurannassa. Tutkimuksen aikana Seinäjoen ammattikorkeakoulussa on tutkittu lyhyen kantaman langatonta tekniikkaa: suunniteltu ja kehitetty pienivirtaisia radionappeja, niitten ohjelmointiympäristöä sekä langattoman verkon synkronointia, tiedonkeruuta ja reititystä. Lisäksi on simuloitu eri reititystapoja, sisäpaikannusta ja kaivinkoneen kalibrointia soveltaen mm. neurolaskentaa. Tekniikkaa on testattu myös käytännön sovelluksissa. Ympäristöälykkäät sovellusalueet ovat ehkä nopeimmin kasvava lähitulevaisuuden ala tietotekniikassa. Tutkitulla tekniikalla on runsaasti uusia haasteita ihmisten hyvinvointia, terveyttä ja turvallisuutta lisäävissä sovelluksissa, kuten myös teollisuuden uusissa sovelluksissa, esimerkiksi älykkäässä energiansiirtoverkossa.The development of computing is moving from mainframe computers to distributed intelligence with wireless features. The automated functions around us, in the form of small electronic devices, are increasing and the pace is continuously accelerating. The number of these applications will increase in the future, but suitable features needed are lacking and suitable technology development is still ongoing. The existing wireless short-range standards are mostly suitable for use in industry and in multimedia applications, but they are only partly suitable for the new network feature demands of the ambient intelligence applications. The ambient intelligent applications will serve us in our daily lives: security, access control and exercise services. Ambient intelligence is also adopted by industry in distributed amorphous automation, in access monitoring and the control of machines and devices. During this research, at Seinäjoki University of Applied Sciences, we have researched, designed and developed short-range wireless technology: low-power radio buttons with a programming environment for them as well as synchronization, data collecting and routing features for the wireless network. We have simulated different routing methods, indoor positioning and excavator calibration using for example neurocomputing. In addition, we have tested the technology in practical applications. The ambient intelligent applications are perhaps the area growing the most in information technology in the future. There will be many new challenges to face to increase welfare, health, security, as well as industrial applications (for example, at factories and in smart grids) in the future.fi=vertaisarvioitu|en=peerReviewed

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Air Force Institute of Technology Research Report 2010

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physic

Artificial neural networks modeling and simulation of the in-vitro nanoparticles - cell interactions

Ankara : The Department ofIndustrial Engineering, Bilkent University, 2012.Thesis (Master's) -- Bilkent University, 2012.Includes bibliographical references leaves 54-56.In this research a prediction model for cellular uptake efficiency of nanoparticles (NPs), which is the rate of NPs adhered to the cell surface or entered into the cell, is investigated via Artificial Neural Network (ANN) method. Prediction of cellular uptake rate of NPs is an important study considering the technical limitations of volatile environment of organism and the time limitation of conducting numerous experiments for thousands of possible variations of different variables that have an impact on NP uptake rate. Moreover, this study constitutes a basis for the targeted drug delivery and cell-level detection, treatment and diagnoses of existing pathologies through simulating experimental procedure of NP-Cell interactions. Accordingly, this study will accelerate nano-medicine researches. The research focuses on constructing a proper ANN model based on multilayered feed-forward back-propagation algorithm for prediction of cellular uptake efficiency which depends on NP type, NP size, NP surface charge, concentration and time. NP types for in-vitro NP-healthy cell interaction analysis are polymethyl methacrylate (PMMA), silica and polylactic acid (PLA) all of whose shapes are spheres. The proposed ANN model has been developed on MATLAB Programming Language by optimizing number of hidden layers, node numbers and training functions. The data sets for training and testing of the network are provided through in-vitro NP-cell interaction experiments conducted by a Nano-Medicine Research Center in Turkey. The dispersion characteristics and cell interactions of the different nanoparticles in organisms are explored through constructing and implementing an optimal prediction model using ANNs. Simulating the possible interactions of targeted nanoparticles with cells via ANN model could lead to a more rapid, more convenient and less expensive approach in comparison to numerous experimental variations.Cenk, NeslihanM.S