An optimization method for conceptual design in engineering systems based on high order singular value decomposition

Se presenta un nuevo método de diseño conceptual en Ingeniería Aeronáutica basado el uso de modelos reducidos, también llamados modelos sustitutos (‘surrogates’). Los ingredientes de la función objetivo se calculan para cada indiviudo mediante la utilización de modelos sustitutos asociados a las distintas disciplinas técnicas que se construyen mediante definiciones de descomposición en valores singulares de alto orden (HOSVD) e interpolaciones unidimensionales. Estos modelos sustitutos se obtienen a partir de un número limitado de cálculos CFD. Los modelos sustitutos pueden combinarse, bien con un método de optimización global de tipo algoritmo genético, o con un método local de tipo gradiente. El método resultate es flexible a la par que mucho más eficiente, computacionalmente hablando, que los modelos convencionales basados en el cálculo directo de la función objetivo, especialmente si aparecen un gran número de parámetros de diseño y/o de modelado. El método se ilustra considerando una versión simplificada del diseño conceptual de un avión. Abstract An optimization method for conceptual design in Aeronautics is presented that is based on the use of surrogate models. The various ingredients in the target function are calculated for each individual using surrogates of the associated technical disciplines that are constructed via high order singular value decomposition and one dimensional interpolation. These surrogates result from a limited number of CFD calculated snapshots. The surrogates are combined with an optimization method, which can be either a global optimization method such as a genetic algorithm or a local optimization method, such as a gradient-like method. The resulting method is both flexible and much more computationally efficient than the conventional method based on direct calculation of the target function, especially if a large number of free design parameters and/or tunablemodeling parameters are present. The method is illustrated considering a simplified version of the conceptual design of an aircraft empennage.

Clasificación de madera estructural de gran escuadría de Pinus sylvestris l. mediante métodos no destructivos

Esta Tesis Doctoral aborda el estudio de algunas técnicas no destructivas para la clasificación de madera de pino silvestre (Pinus sylvestris L.) de procedencia española y de gruesa escuadría para uso estructural. Para la estimación del módulo de elasticidad y de la resistencia se han aplicado técnicas basadas en la propagación de una onda a través de la madera: onda de ultrasonidos (Sylvatest) o de impacto (Microsecond Timer) en dirección longitudinal, o vibración en dirección longitudinal y transversal (PLG). Para la estimación de la densidad se han utilizado métodos puntuales basados en el penetrómetro (Pilodyn) y en la resistencia al arranque de un tornillo. Las variables obtenidas han sido relacionadas con los resultados de la clasificación visual y con las propiedades de la madera determinadas mediante ensayo mecánico. Además, se ha estudiado la influencia de la humedad de la madera en la velocidad de propagación de la onda para definir factores de corrección a los equipos comerciales utilizados en esta Tesis Doctoral. La muestra de estudio está formada por 244 piezas procedentes de El Espinar, Segovia, con dimensiones nominales 150 x 200 x 4000 mm (218 piezas) y 100 x 150 x 3000 mm (26 piezas). De todas las piezas se tomaron datos de dimensiones, contenido de humedad y clasificación visual según la norma UNE 56544. En las primeras 218 vigas se aplicaron las técnicas de ultrasonidos, onda de impacto y vibraciones, se determinó la densidad de cada pieza completa y se ensayaron según la norma UNE-EN 408 para obtener el módulo de elasticidad global (en todos los casos) y local (en un porcentaje), así como de la tensión de rotura. Se extrajeron tres rebanadas para los ensayos puntuales y para el cálculo de la densidad. En las otras 26 piezas se repitieron los ensayos (transmisión de onda, vibración y clasificación visual) durante el proceso de secado natural, desde que la madera se encontraba húmeda (en torno al 40 %) hasta la humedad de equilibrio higroscópico (en torno al 9%). Respecto a la clasificación visual no se han observado diferencias significativas entre la calidad MEG o las rechazadas. Se han estudiado las consecuencias del secado (principalmente las deformaciones) y no se ha encontrado justificación para que estos defectos penalicen la clasificación. Para la densidad, el mayor R2 obtenido ha sido de un 47% a partir del uso combinado de los dos equipos puntuales (penetrómetro y arranque de tornillo). Para el módulo de elasticidad y la tensión de rotura, la mejor relación se ha obtenido a partir de la técnica de vibración longitudinal, con unos coeficientes de 79% y un 52% respectivamente. Se ha estimado que el aumento de un punto porcentual en el contenido de humedad de la madera produce una pérdida de velocidad de onda del 0,58% para Sylvatest y Microsecond Timer, y del 0,71% para PLG. Estos valores son generalizables para un rango de humedades entre 9 y 25 %. Abstract This Doctoral Thesis approach the study of some non-destructive techniques as a classification method for structural use of Scots pine wood of Spanish origin with large cross section. To estimate the modulus of elasticity and strength have been used techniques based on the propagation of a wave through the timber: ultrasonic wave (Sylvatest) or stress wave (Microsecond Timer) in longitudinal direction, or vibration in longitudinal and transversal direction (PLG). Local probing methods have been applied to estimate the density, based on penetrometer (Pilodyn) and the screw withdrawal resistance meter. The different variables obtained were compared with the results of the visual grading and the values of the properties of the wood determined by the standardized test of the pieces. Furthermore, the influence of the moisture content of the wood on the velocity of propagation of the waves through the timber has been analyzed in order to establish a correction factor for the commercial devices used in this Doctoral Thesis. The sample tested consists of 244 pieces from El Espinar, Segovia, with nominal dimensions 150 x 200 x 4000 mm (218 pieces) and 100 x 150 x 3000 mm (26 pieces). Data collection about dimensions, moisture content and visual grading according to the UNE 56544 standard were carried out on all the pieces. The first 218 pieces were tested by non destructive techniques based on ultrasonic wave, stress wave and vibration, the density was measured on each piece and bending test according to the UNE-EN 408 standard was carried out for calculating the global modulus of elasticity (all the pieces) and the local one (only a representative group), as well as the bending strength. Three slices were removed for implementing the local probing and to calculate the density. In the other 26 pieces the tests (wave transmission, vibration and visual grading) were repeated during the natural drying process, from wet timber (around 40 % moisture content) up to the equilibrium moisture content (around 9%). Regarding the visual grading no significant differences were observed between MEG or rejected pieces. The effects of drying (deformations) have been studied, and justification for the specification hasn't been found. To estimate the density, the greater R2 obtained was 47% by using both penetrometer and screw withdrawal. For the modulus of elasticity and bending strength, the best relationship has been found with the longitudinal vibration, with coefficients of 79% and 52% respectively. It has been estimated that an increase of a point of the moisture content of the wood produces a decrease on the velocity obtained from ultrasonic or stress wave of 0,58%, and 0,71 % for the one obtained from vibration. Those values can be generalized for a range of moisture content from 9 to 25 %.

Collaborative data stream mining in ubiquitous environments using dynamic classifier selection

In ubiquitous data stream mining applications, different devices often aim to learn concepts that are similar to some extent. In these applications, such as spam filtering or news recommendation, the data stream underlying concept (e.g., interesting mail/news) is likely to change over time. Therefore, the resultant model must be continuously adapted to such changes. This paper presents a novel Collaborative Data Stream Mining (Coll-Stream) approach that explores the similarities in the knowledge available from other devices to improve local classification accuracy. Coll-Stream integrates the community knowledge using an ensemble method where the classifiers are selected and weighted based on their local accuracy for different partitions of the feature space. We evaluate Coll-Stream classification accuracy in situations with concept drift, noise, partition granularity and concept similarity in relation to the local underlying concept. The experimental results show that Coll-Stream resultant model achieves stability and accuracy in a variety of situations using both synthetic and real world datasets.

Constructing a Canonical form of a Matrix in Several Problems about Combinatorial Designs

Partially supported by the Bulgarian Science Fund contract with TU Varna, No 487.

Classification of Biomedical Signals using the Dynamics of the False Nearest Neighbours (DFNN) Algorithm

* This study was supported in part by the Natural Sciences and Engineering Research Council of Canada, and by the Gastrointestinal Motility Laboratory (University of Alberta Hospitals) in Edmonton, Alberta, Canada.

Biologically inspired features for scene classification in video surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper. © 2010 IEEE.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

Analysis and recognition of similar environmental sounds

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Land use / land cover change detection: an object oriented approach, Münster, Germany

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Testing Nelder-Mead Based Repulsion Algorithms for Multiple Roots of Nonlinear Systems via a Two-Level Factorial Design of Experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Urban land cover change detection analysis and modeling spatio-temporal Growth dynamics using Remote Sensing and GIS Techniques: A case study of Dhaka, Bangladesh

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Functional Class in Children with Idiopathic Dilated Cardiomyopathy. A pilot Study

Abstract Background: Idiopathic dilated cardiomyopathy (IDCM), most common cardiac cause of pediatric deaths, mortality descriptor: a low left ventricular ejection fraction (LVEF) and low functional capacity (FC). FC is never self reported by children. Objective: The aims of this study were (i) To evaluate whether functional classifications according to the children, parents and medical staff were associated. (iv) To evaluate whether there was correlation between VO2 max and Weber's classification. Method: Prepubertal children with IDCM and HF (by previous IDCM and preserved LVEF) were selected, evaluated and compared. All children were assessed by testing, CPET and functional class classification. Results: Chi-square test showed association between a CFm and CFp (1, n = 31) = 20.6; p = 0.002. There was no significant association between CFp and CFc (1, n = 31) = 6.7; p = 0.4. CFm and CFc were not associated as well (1, n = 31) = 1.7; p = 0.8. Weber's classification was associated to CFm (1, n = 19) = 11.8; p = 0.003, to CFp (1, n = 19) = 20.4; p = 0.0001and CFc (1, n = 19) = 6.4; p = 0.04). Conclusion: Drawing were helpful for children's self NYHA classification, which were associated to Weber's stratification.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.