Représentation et identification des hypersurfaces

L’objectif à moyen terme de ce travail est d’explorer quelques formulations des problèmes d’identification de forme et de reconnaissance de surface à partir de mesures ponctuelles. Ces problèmes ont plusieurs applications importantes dans les domaines de l’imagerie médicale, de la biométrie, de la sécurité des accès automatiques et dans l’identification de structures cohérentes lagrangiennes en mécanique des fluides. Par exemple, le problème d’identification des différentes caractéristiques de la main droite ou du visage d’une population à l’autre ou le suivi d’une chirurgie à partir des données générées par un numériseur. L’objectif de ce mémoire est de préparer le terrain en passant en revue les différents outils mathématiques disponibles pour appréhender la géométrie comme variable d’optimisation ou d’identification. Pour l’identification des surfaces, on explore l’utilisation de fonctions distance ou distance orientée, et d’ensembles de niveau comme chez S. Osher et R. Fedkiw ; pour la comparaison de surfaces, on présente les constructions des métriques de Courant par A. M. Micheletti en 1972 et le point de vue de R. Azencott et A. Trouvé en 1995 qui consistent à générer des déformations d’une surface de référence via une famille de difféomorphismes. L’accent est mis sur les fondations mathématiques sous-jacentes que l’on a essayé de clarifier lorsque nécessaire, et, le cas échéant, sur l’exploration d’autres avenues.

Input usage, output mix and industry deregulation: an analysis of the Australian dairy manufacturing industry

In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

Geometry and combinatorics of the cutting angle method

Lower approximation of Lipschitz functions plays an important role in deterministic global optimization. This article examines in detail the lower piecewise linear approximation which arises in the cutting angle method. All its local minima can be explicitly enumerated, and a special data structure was designed to process them very efficiently, improving previous results by several orders of magnitude. Further, some geometrical properties of the lower approximation have been studied, and regions on which this function is linear have been identified explicitly. Connection to a special distance function and Voronoi diagrams was established. An application of these results is a black-box multivariate random number generator, based on acceptance-rejection approach.

Input usage, output mix and industry deregulation: an analysis of the Australian dairy manufacturing industry

In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

M-Dimension : multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models

Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network.

We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols.

Faster and parameter-free discord search in quasi-periodic time series

Time series discord has proven to be a useful concept for time-series anomaly identification. To search for discords, various algorithms have been developed. Most of these algorithms rely on pre-building an index (such as a trie) for subsequences. Users of these algorithms are typically required to choose optimal values for word-length and/or alphabet-size parameters of the index, which are not intuitive. In this paper, we propose an algorithm to directly search for the top-K discords, without the requirement of building an index or tuning external parameters. The algorithm exploits quasi-periodicity present in many time series. For quasi-periodic time series, the algorithm gains significant speedup by reducing the number of calls to the distance function.

Energy productivity and total-factor productivity in the Australian construction industry

There is urgent need to consider energy consumption when measuring total-factor productivity in the construction industry. This paper adopts the Malmquist index method to investigate the factors affecting the energy productivity of the Australian construction industry and compares them with those decomposed from the total-factor productivity. An input-oriented distance function and a contemporaneous benchmark technology are employed to develop the data envelopment analysis models. The Malmquist productivity index is decomposed into the technological change, pure technical efficiency change and activity effect to gain comprehensive insights into changes of construction productivity in the Australian states and territories over the past two decades. Research results show that both energy productivity and total-factor productivity improved in Australia, particularly related to technological development. The pure technical efficiency and activity indices changed slightly over time or across regions. This study demonstrates that there exists a linkage between energy productivity and total-factor productivity through their technological and technical efficiency changes. The Australian construction industry could enhance these two productivities by introducing advanced technologies and implementing them efficiently.

Swarm-based descriptor combination and its application for image classification

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudos de técnicas de reinicialização em métodos level-set e suas aplicações em escoamentos bifásicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

PRoSPer: perceptual similarity queries in medical CBIR systems through user profiles

In this paper, we present a novel approach to perform similarity queries over medical images, maintaining the semantics of a given query posted by the user. Content-based image retrieval systems relying on relevance feedback techniques usually request the users to label relevant/irrelevant images. Thus, we present a highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The profiles maintain the settings desired for each user, allowing tuning of the similarity assessment, which encompasses the dynamic change of the distance function employed through an interactive process. Experiments on medical images show that the method is effective and can improve the decision making process during analysis.

Estudio comparativo de medidas de distancia para histogramas en problemas de reidentificación

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Efficiency in Managing the Environment and the Opportunity Cost of Pollution Abatement

Using the directional distance function we study a cross section of 110 countries to examine the efficiency of management of the tradeoffs between pollution and income. The DEA model is reformulated to permit 'reverse disposability' of the bad output. Further, we interpret the optimal solution of the multiplier form of the DEA model as an iso-inefficiency line. This permits us to measure the shadow cost of the bad output for a country that is in the interior, rather than on the frontier of the production possibilities set. We also compare the relative environmental performance of countries in terms of emission intensity adjusted for technical efficiency. Only 10% of the countries are found to be on the frontier. Also, there is considerable inter-country variation in the imputed opportunity cost of CO2 reduction. Further, differences in technical efficiency contribute substantially to differences in the observed levels of CO2 intensity.

Multiple Hashing Integration for Real-Time Large Scale Part-to-Part Video Matching

A real-time large scale part-to-part video matching algorithm, based on the cross correlation of the intensity of motion curves, is proposed with a view to originality recognition, video database cleansing, copyright enforcement, video tagging or video result re-ranking. Moreover, it is suggested how the most representative hashes and distance functions - strada, discrete cosine transformation, Marr-Hildreth and radial - should be integrated in order for the matching algorithm to be invariant against blur, compression and rotation distortions: (R; _) 2 [1; 20]_[1; 8], from 512_512 to 32_32pixels2 and from 10 to 180_. The DCT hash is invariant against blur and compression up to 64x64 pixels2. Nevertheless, although its performance against rotation is the best, with a success up to 70%, it should be combined with the Marr-Hildreth distance function. With the latter, the image selected by the DCT hash should be at a distance lower than 1.15 times the Marr-Hildreth minimum distance.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Diversification economies and specialisation efficiencies in a mixed food and coffee smallholder farming system in Papua New Guinea

Smallholder farming systems in Papua New Guinea are characterised by an integrated set of cash cropping and subsistence food cropping activities. In the Highlands provinces, the subsistence food crop sub-system is dominated by sweet potato production. Coffee dominates the cash cropping sub-system, but a limited number of food crops are also grown for cash sale. The dynamics between sub-systems can influence the scope for complementarity between, and technical efficiency of, their operations, especially in light of the seasonality of demand for household labour and management inputs within the farming system. A crucial element of these dynamic processes is diversification into commercial agricultural production, which can influence factor productivity and the efficiency of crop production where smallholders maintain a strong production base in subsistence foods. In this study we use survey data from households engaged in coffee and food crop production in the Benabena district of Eastern Highlands Province to derive technical efficiency indices for each household over two years. A stochastic input distance function approach is used to establish whether diversification economies exist and whether specialisation in coffee, subsistence food or cash food production significantly influences technical efficiency on the sampled smallholdings. Diversification economics are weakly evident between subsistence food production and both coffee and cash food production, but diseconomies of diversification are discerned between coffee and cash food production. A number of factors are tested for their effects on technical efficiency. Significant technical efficiency gains are made from diversification among broad cropping enterprises.