An approach to automatic learning assessment based on the computational theory of perceptions

E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor. This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra’s algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHs

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.

Implementation of the Heated Pulsed Theory using actively heated fiber optics: measurements of soil volumetric water content and soil volumetric heat capacity

Existe una creciente necesidad de hacer el mejor uso del agua para regadío. Una alternativa eficiente consiste en la monitorización del contenido volumétrico de agua (θ), utilizando sensores de humedad. A pesar de existir una gran diversidad de sensores y tecnologías disponibles, actualmente ninguna de ellas permite obtener medidas distribuidas en perfiles verticales de un metro y en escalas laterales de 0.1-1,000 m. En este sentido, es necesario buscar tecnologías alternativas que sirvan de puente entre las medidas puntuales y las escalas intermedias. Esta tesis doctoral se basa en el uso de Fibra Óptica (FO) con sistema de medida de temperatura distribuida (DTS), una tecnología alternativa de reciente creación que ha levantado gran expectación en las últimas dos décadas. Específicamente utilizamos el método de fibra calentada, en inglés Actively Heated Fiber Optic (AHFO), en la cual los cables de Fibra Óptica se utilizan como sondas de calor mediante la aplicación de corriente eléctrica a través de la camisa de acero inoxidable, o de un conductor eléctrico simétricamente posicionado, envuelto, alrededor del haz de fibra óptica. El uso de fibra calentada se basa en la utilización de la teoría de los pulsos de calor, en inglés Heated Pulsed Theory (HPP), por la cual el conductor se aproxima a una fuente de calor lineal e infinitesimal que introduce calor en el suelo. Mediante el análisis del tiempo de ocurrencia y magnitud de la respuesta térmica ante un pulso de calor, es posible estimar algunas propiedades específicas del suelo, tales como el contenido de humedad, calor específico (C) y conductividad térmica. Estos parámetros pueden ser estimados utilizando un sensor de temperatura adyacente a la sonda de calor [método simple, en inglés single heated pulsed probes (SHPP)], ó a una distancia radial r [método doble, en inglés dual heated pulsed probes (DHPP)]. Esta tesis doctoral pretende probar la idoneidad de los sistemas de fibra óptica calentada para la aplicación de la teoría clásica de sondas calentadas. Para ello, se desarrollarán dos sistemas FO-DTS. El primero se sitúa en un campo agrícola de La Nava de Arévalo (Ávila, España), en el cual se aplica la teoría SHPP para estimar θ. El segundo sistema se desarrolla en laboratorio y emplea la teoría DHPP para medir tanto θ como C. La teoría SHPP puede ser implementada con fibra óptica calentada para obtener medidas distribuidas de θ, mediante la utilización de sistemas FO-DTS y el uso de curvas de calibración específicas para cada suelo. Sin embargo, la mayoría de aplicaciones AHFO se han desarrollado exclusivamente en laboratorio utilizando medios porosos homogéneos. En esta tesis se utiliza el programa Hydrus 2D/3D para definir tales curvas de calibración. El modelo propuesto es validado en un segmento de cable enterrado en una instalación de fibra óptica y es capaz de predecir la respuesta térmica del suelo en puntos concretos de la instalación una vez que las propiedades físicas y térmicas de éste son definidas. La exactitud de la metodología para predecir θ frente a medidas puntuales tomadas con sensores de humedad comerciales fue de 0.001 a 0.022 m3 m-3 La implementación de la teoría DHPP con AHFO para medir C y θ suponen una oportunidad sin precedentes para aplicaciones medioambientales. En esta tesis se emplean diferentes combinaciones de cables y fuentes emisoras de calor, que se colocan en paralelo y utilizan un rango variado de espaciamientos, todo ello en el laboratorio. La amplitud de la señal y el tiempo de llegada se han observado como funciones del calor específico del suelo. Medidas de C, utilizando esta metodología y ante un rango variado de contenidos de humedad, sugirieron la idoneidad del método, aunque también se observaron importantes errores en contenidos bajos de humedad de hasta un 22%. La mejora del método requerirá otros modelos más precisos que tengan en cuenta el diámetro del cable, así como la posible influencia térmica del mismo. ABSTRACT There is an increasing need to make the most efficient use of water for irrigation. A good approach to make irrigation as efficient as possible is to monitor soil water content (θ) using soil moisture sensors. Although, there is a broad range of different sensors and technologies, currently, none of them can practically and accurately provide vertical and lateral moisture profiles spanning 0-1 m depth and 0.1-1,000 m lateral scales. In this regard, further research to fulfill the intermediate scale and to bridge single-point measurement with the broaden scales is still needed. This dissertation is based on the use of Fiber Optics with Distributed Temperature Sensing (FO-DTS), a novel approach which has been receiving growing interest in the last two decades. Specifically, we employ the so called Actively Heated Fiber Optic (AHFO) method, in which FO cables are employed as heat probe conductors by applying electricity to the stainless steel armoring jacket or an added conductor symmetrically positioned (wrapped) about the FO cable. AHFO is based on the classic Heated Pulsed Theory (HPP) which usually employs a heat probe conductor that approximates to an infinite line heat source which injects heat into the soil. Observation of the timing and magnitude of the thermal response to the energy input provide enough information to derive certain specific soil thermal characteristics such as the soil heat capacity, soil thermal conductivity or soil water content. These parameters can be estimated by capturing the soil thermal response (using a thermal sensor) adjacent to the heat source (the heating and the thermal sources are mounted together in the so called single heated pulsed probe (SHPP)), or separated at a certain distance, r (dual heated pulsed method (DHPP) This dissertation aims to test the feasibility of heated fiber optics to implement the HPP theory. Specifically, we focus on measuring soil water content (θ) and soil heat capacity (C) by employing two types of FO-DTS systems. The first one is located in an agricultural field in La Nava de Arévalo (Ávila, Spain) and employ the SHPP theory to estimate θ. The second one is developed in the laboratory using the procedures described in the DHPP theory, and focuses on estimating both C and θ. The SHPP theory can be implemented with actively heated fiber optics (AHFO) to obtain distributed measurements of soil water content (θ) by using reported soil thermal responses in Distributed Temperature Sensing (DTS) and with a soil-specific calibration relationship. However, most reported AHFO applications have been calibrated under laboratory homogeneous soil conditions, while inexpensive efficient calibration procedures useful in heterogeneous soils are lacking. In this PhD thesis, we employ the Hydrus 2D/3D code to define these soil-specific calibration curves. The model is then validated at a selected FO transect of the DTS installation. The model was able to predict the soil thermal response at specific locations of the fiber optic cable once the surrounding soil hydraulic and thermal properties were known. Results using electromagnetic moisture sensors at the same specific locations demonstrate the feasibility of the model to detect θ within an accuracy of 0.001 to 0.022 m3 m-3. Implementation of the Dual Heated Pulsed Probe (DPHP) theory for measurement of volumetric heat capacity (C) and water content (θ) with Distributed Temperature Sensing (DTS) heated fiber optic (FO) systems presents an unprecedented opportunity for environmental monitoring. We test the method using different combinations of FO cables and heat sources at a range of spacings in a laboratory setting. The amplitude and phase-shift in the heat signal with distance was found to be a function of the soil volumetric heat capacity (referred, here, to as Cs). Estimations of Cs at a range of θ suggest feasibility via responsiveness to the changes in θ (we observed a linear relationship in all FO combinations), though observed bias with decreasing soil water contents (up to 22%) was also reported. Optimization will require further models to account for the finite radius and thermal influence of the FO cables, employed here as “needle probes”. Also, consideration of the range of soil conditions and cable spacing and jacket configurations, suggested here to be valuable subjects of further study and development.

Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

Theory for normal and impaired experience-dependent plasticity in neocortex of adult rats

We model experience-dependent plasticity in the cortical representation of whiskers (the barrel cortex) in normal adult rats, and in adult rats that were prenatally exposed to alcohol. Prenatal exposure to alcohol (PAE) caused marked deficits in experience-dependent plasticity in a cortical barrel-column. Cortical plasticity was induced by trimming all whiskers on one side of the face except two. This manipulation produces high activity from the intact whiskers that contrasts with low activity from the cut whiskers while avoiding any nerve damage. By a computational model, we show that the evolution of neuronal responses in a single barrel-column after this sensory bias is consistent with the synaptic modifications that follow the rules of the Bienenstock, Cooper, and Munro (BCM) theory. The BCM theory postulates that a neuron possesses a moving synaptic modification threshold, θM, that dictates whether the neuron's activity at any given instant will lead to strengthening or weakening of its input synapses. The current value of θM changes proportionally to the square of the neuron's activity averaged over some recent past. In the model of alcohol impaired cortex, the effective θM has been set to a level unattainable by the depressed levels of cortical activity leading to “impaired” synaptic plasticity that is consistent with experimental findings. Based on experimental and computational results, we discuss how elevated θM may be related to (i) reduced levels of neurotransmitters modulating plasticity, (ii) abnormally low expression of N-methyl-d-aspartate receptors (NMDARs), and (iii) the membrane translocation of Ca2+/calmodulin-dependent protein kinase II (CaMKII) in adult rat cortex subjected to prenatal alcohol exposure.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.

On the ordering, enumeration and ranking of k-ary trees /

"UILU-ENG 77 1706."

Picture analysis by graph transformation,

"Supported in part by the Department of Computer Science and the Atomic Energy Commission under contract US AEC AT(11-1)2118."

Parallel algorithms for network routing problems and recurrences /

"Grant no. US NSF MCS75-21758."

On algorithms for finding all circuits of a graph

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A generalization of Ramsey theory for graphs /

Bibliography: p. 16.

Generation and comparison of equivalent equation sets in a general purpose simulation and modeling package /

"C00-2383-0018."

A graph-structure transformation model for picture parsing,

"COO-2118-0031."