798 resultados para Multi-scale hierarchical framework


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In the Finnish university society the commercialization research projects has not been a focus of interest until now. The reasons for the growing interest towards commercialization research projects are their possibility to develop our economy simultaneously by providing new technologies and products. This study focuses on the examination of what kind of high-technology oriented research can be commercialized and how. The aim is to generate understanding of how commercialization research projects should proceed and to find concrete ways of improving the of commercialization research projects. As its research method, the study analyzes four different university high-technology research projects which have been commercially oriented and have to some degree been able to commercialize the product or technology developed during the research phase. The data has been gathered mainly by semi-structured interviews of people involved in these particular projects or cases. The findings from the interviews have been reflected to the final reports of the projects, provided by TEKES, and later on the data gained has been compared to each other. Also a literature review has been produced about the subject of commercializing university research with the purpose of providing known theories and framework connected with the subject. The study reveals five main factors related to commercializing high-tech research. These factors are: The Team, Market potential and competitiveness, Product and technology, Funding and Steering Group. Also the uncertainties related to these factors have been addressed. As a conclusion the study provides the main aspects that should be considered when starting a commercialization research project. Also a combining hierarchical framework has been provided related to the five factors presented. In Chapter 5 the study addresses the main tasks or steps to be taken in order to get public funding for a commercially oriented research project and later on the actual steps to be executed in order to successfully commercialize these high-tech research projects.

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L'apprentissage machine (AM) est un outil important dans le domaine de la recherche d'information musicale (Music Information Retrieval ou MIR). De nombreuses tâches de MIR peuvent être résolues en entraînant un classifieur sur un ensemble de caractéristiques. Pour les tâches de MIR se basant sur l'audio musical, il est possible d'extraire de l'audio les caractéristiques pertinentes à l'aide de méthodes traitement de signal. Toutefois, certains aspects musicaux sont difficiles à extraire à l'aide de simples heuristiques. Afin d'obtenir des caractéristiques plus riches, il est possible d'utiliser l'AM pour apprendre une représentation musicale à partir de l'audio. Ces caractéristiques apprises permettent souvent d'améliorer la performance sur une tâche de MIR donnée. Afin d'apprendre des représentations musicales intéressantes, il est important de considérer les aspects particuliers à l'audio musical dans la conception des modèles d'apprentissage. Vu la structure temporelle et spectrale de l'audio musical, les représentations profondes et multiéchelles sont particulièrement bien conçues pour représenter la musique. Cette thèse porte sur l'apprentissage de représentations de l'audio musical. Des modèles profonds et multiéchelles améliorant l'état de l'art pour des tâches telles que la reconnaissance d'instrument, la reconnaissance de genre et l'étiquetage automatique y sont présentés.

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Ce projet de recherche évalue la réponse à court terme de coléoptères phloeophages et xylophages (Cerambycidae et Scolytinae) à différentes intensités de coupes partielles (0, 25 et 40% de la surface terrière prélevée) afin de déterminer la viabilité de cette méthode sylvicole en forêt boréale. Disposant de 12 parcelles expérimentales (4 répétitions pour chaque intensité de coupe) dans une sapinière à bouleau blanc située au sud de la forêt boréale (Québec, Canada), nous avons évalué l’abondance, la diversité ainsi que l’établissement (taux d’attaque) de ces deux groupes d’insectes, et ce dès la première année suivant la coupe. L’échantillonnage a été réalisé à l’aide de pièges à interception multidirectionnelle et de l’écorçage de sections de 3 espèces d’arbres exposées dans l’ensemble des parcelles. Nos résultats montrent une plus grande activité/abondance des deux taxons (abondance 5 à 6 fois plus élevée) ainsi qu’une composition en espèces différente et plus diversifiée dans les peuplements partiellement coupés (25 et 40%). De plus, la présence et la distribution d’espèces colonisant habituellement des hôtes affaiblis (e.g., Trypodendron lineatum, Rhagium inquisitor) – et pouvant donc réduire la valeur économique d’arbres résiduels – a été recensée et semble être favorisée entres autres par l’ouverture de la canopée et des blessures physiques faites aux arbres pendant les opérations sylvicoles. Par ailleurs, l’approche combinant différentes techniques d’échantillonnage a permis une meilleure compréhension des mécanismes de localisation/sélection d’hôte (variant en fonction de l’espèce), un aspect important de la dynamique des insectes pour l’évaluation des risques suite aux coupes forestières. Sur la base de cette étude à court terme, il ne semblerait pas y avoir de différence significative sur les risques pour le milieu quant à l’augmentation d’activité des Cerambycidae et Scolytinae entre les deux traitements de coupe appliqués. Il reste cependant indispensable de vérifier la validité de ces résultats sur une plus longue période afin d’établir des plans d’aménagement forestier durables pour la forêt boréale.

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Les régions nordiques à pergélisol seront largement affectées par l'augmentation prévue des températures. Un nombre croissant d’infrastructures qui étaient autrefois construites avec confiance sur des sols gelés en permanence commencent déjà à montrer des signes de détérioration. Les processus engendrés par la dégradation du pergélisol peuvent causer des dommages importants aux infrastructures et entrainer des coûts élevés de réparation. En conséquence, le contexte climatique actuel commande que la planification des projets dans les régions nordiques s’effectue en tenant compte des impacts potentiels de la dégradation du pergélisol. Ce mémoire porte sur l’utilisation de systèmes d’information géographique (SIG) appliqués à l’évaluation du potentiel d’aménagement des territoires situés en milieu de pergélisol. En utilisant une approche SIG, l’objectif est d’élaborer une méthodologie permettant de produire des cartes d'évaluation des risques afin d’aider les collectivités nordiques à mieux planifier leur environnement bâti. Une analyse multi-échelle du paysage est nécessaire et doit inclure l'étude des dépôts de surface, la topographie, ainsi que les conditions du pergélisol, la végétation et les conditions de drainage. La complexité de l'ensemble des interactions qui façonnent le paysage est telle qu'il est pratiquement impossible de rendre compte de chacun d'eux ou de prévoir avec certitude la réponse du système suite à des perturbations. Ce mémoire présente aussi certaines limites liées à l’utilisation des SIG dans ce contexte spécifique et explore une méthode innovatrice permettant de quantifier l'incertitude dans les cartes d'évaluation des risques.

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Le réalisme des objets en infographie exige de simuler adéquatement leur apparence sous divers éclairages et à différentes échelles. Une solution communément adoptée par les chercheurs consiste à mesurer avec l’aide d’appareils calibrés la réflectance d’un échantillon de surface réelle, pour ensuite l’encoder sous forme d’un modèle de réflectance (BRDF) ou d’une texture de réflectances (BTF). Malgré des avancées importantes, les données ainsi mises à la portée des artistes restent encore très peu utilisées. Cette réticence pourrait s’expliquer par deux raisons principales : (1) la quantité et la qualité de mesures disponibles et (2) la taille des données. Ce travail propose de s’attaquer à ces deux problèmes sous l’angle de la simulation. Nous conjecturons que le niveau de réalisme du rendu en infographie produit déjà des résultats satisfaisants avec les techniques actuelles. Ainsi, nous proposons de précalculer et encoder dans une BTF augmentée les effets d’éclairage sur une géométrie, qui sera par la suite appliquée sur les surfaces. Ce précalcul de rendu et textures étant déjà bien adopté par les artistes, il pourra mieux s’insérer dans leurs réalisations. Pour nous assurer que ce modèle répond aussi aux exigences des représentations multi-échelles, nous proposons aussi une adaptation des BTFs à un encodage de type MIP map.

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In recent years, governments, international institutions, and a broad array of social movements have converged around what an OECD report has described as an emerging “global anti-poverty consensus.” This new global social policy agenda has changed the terms of the debate between the left and the right, and redefined the world of policy possibilities, in global but also in domestic politics. This article proposes a constructivist interpretation of this multi-scale shift in discourse, and discusses the political and policy implications of the new global politics of poverty.

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The objective of the present study is to understand the spatial and temporal variability of sea surface temperature(SST), precipitable water, zonal and meridional components of wind stress over the tropical Indian Ocean to understand the different scales of variability of these features of Indian Ocean. Empirical Orthogonal Function (EOF) and wavelet analysis techniques are utilized to understand the standing oscillations and multi scale oscillations respectively. The study has been carried out over Indian Ocean and South Indian Ocean. For the present study, NCEP/NCAR(National Center for Environmental Prediction National Center for Atmospheric Research) reanalyzed daily fields of sea surface temperature, zonal and meridional surface wind components and precipitable water amount during 1960-1998 are used. The principle of EOF analysis and the methodology used for the analysis of spatial and temporal variance modes.

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Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

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Resumen: Este trabajo estudia los resultados en matemáticas y lenguaje de 32000 estudiantes en la prueba saber 11 del 2008, de la ciudad de Bogotá. Este análisis reconoce que los individuos se encuentran contenidos en barrios y colegios, pero no todos los individuos del mismo barrio asisten a la misma escuela y viceversa. Con el fin de modelar esta estructura de datos se utilizan varios modelos econométricos, incluyendo una regresión jerárquica multinivel de efectos cruzados. Nuestro objetivo central es identificar en qué medida y que condiciones del barrio y del colegio se correlacionan con los resultados educacionales de la población objetivo y cuáles características de los barrios y de los colegios están más asociadas al resultado en las pruebas. Usamos datos de la prueba saber 11, del censo de colegios c600, del censo poblacional del 2005 y de la policía metropolitana de Bogotá. Nuestras estimaciones muestran que tanto el barrio como el colegio están correlacionados con los resultados en las pruebas; pero el efecto del colegio parece ser mucho más fuerte que el del barrio. Las características del colegio que están más asociadas con el resultado en las pruebas son la educación de los profesores, la jornada, el valor de la pensión, y el contexto socio económico del colegio. Las características de los barrios más asociadas con el resultado en las pruebas son, la presencia de universitarios en la UPZ, un clúster de altos niveles de educación y nivel de crimen en el barrio que se correlaciona negativamente. Los resultados anteriores fueron hallados teniendo en cuenta controles familiares y personales.

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La configuración de lugares como áreas de protección ambiental puede ser vista como un proceso técnico y objetivo, en el que se crean políticas públicas que definen prácticas adecuadas e inadecuadas en el lugar. Pero esta configuración es un proceso histórico y negociado. Este se construye en contante diálogo entre diferentes actores que se preocupan por definir qué es la naturaleza y el cuidado ambiental, y las percepciones que individuos que habitan en o cerca a estos lugares construyen en su diario vivir. Es así como la configuración socioambiental de lugares como áreas de protección ocurre por transformaciones en la forma de percibir un lugar, la relaciones con este y sobre todo, prácticas y relaciones que se traducen en formas de negociar nociones de naturaleza y cuidado ambiental. Esta negociación tiene grandes implicaciones en los individuos, particularmente en su subjetividad. Es decir, en hechos como la forma de nombrarlo, caminarlo, observar las especies, iniciar proyectos de agricultura orgánica, cambiar prácticas productivas, el cerramiento de zonas para proteger las fuentes de agua o zonas de vegetación. También sobre su subjetividad, la manera como se sienten frente al lugar, como juzgan sus acciones y las de otros y cómo construyen objetivos personales con respecto a la idea de cuidado ambiental.

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The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

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Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

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Recent coordinated observations of interplanetary scintillation (IPS) from the EISCAT, MERLIN, and STELab, and stereoscopic white-light imaging from the two heliospheric imagers (HIs) onboard the twin STEREO spacecraft are significant to continuously track the propagation and evolution of solar eruptions throughout interplanetary space. In order to obtain a better understanding of the observational signatures in these two remote-sensing techniques, the magnetohydrodynamics of the macro-scale interplanetary disturbance and the radio-wave scattering of the micro-scale electron-density fluctuation are coupled and investigated using a newly constructed multi-scale numerical model. This model is then applied to a case of an interplanetary shock propagation within the ecliptic plane. The shock could be nearly invisible to an HI, once entering the Thomson-scattering sphere of the HI. The asymmetry in the optical images between the western and eastern HIs suggests the shock propagation off the Sun–Earth line. Meanwhile, an IPS signal, strongly dependent on the local electron density, is insensitive to the density cavity far downstream of the shock front. When this cavity (or the shock nose) is cut through by an IPS ray-path, a single speed component at the flank (or the nose) of the shock can be recorded; when an IPS ray-path penetrates the sheath between the shock nose and this cavity, two speed components at the sheath and flank can be detected. Moreover, once a shock front touches an IPS ray-path, the derived position and speed at the irregularity source of this IPS signal, together with an assumption of a radial and constant propagation of the shock, can be used to estimate the later appearance of the shock front in the elongation of the HI field of view. The results of synthetic measurements from forward modelling are helpful in inferring the in-situ properties of coronal mass ejection from real observational data via an inverse approach.

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The CGIAR System conducts research to produce international public goods (IPG) that are of wide applicability creating a scientific base which speeds and broadens local adaptive development. Integrated natural resources management (INRM) research is sometimes seen to be very location specific and consequently does not lend itself readily to the production of IPGs. In this paper we analyse ways in which strategic approaches to INRM research can have broad international applicability and serve as useful foundations for the development of locally adapted technologies. The paper describes the evolution of the IPG concept within the CGIAR and elaborates on five major types of IPGs that have been generated from a varied set of recent INRM research efforts. CGIAR networks have both strengths and weaknesses in INRM research and application, with enormous differences in relative research and development capacities, responsibilities and data access of its partners, making programme process evolution critical to acceptance and participation. Many of the lessons learnt regarding challenges and corresponding IPG research approaches are relevant to designing and managing future multi-scale, multi-locational, coordinated INRM programmes involving broad-based partnerships to address complex environmental and livelihood problems for development.

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In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image pre-processing algorithm is proposed to reduce clutter noises by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers