Treatment of geophysical data as a non-stationary process

ABSTRACT: The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.

Imageamento multifoco de refletores sísmicos

A simulação de uma seção sísmica de afastamento-nulo (ZO) a partir de dados de cobertura múltipla para um meio 2-D, através do empilhamento, é um método de imageamento de reflexão sísmica muito utilizado, que permite reduzir a quantidade de dados e melhorar a relação sinal/ruído. Segundo Berkovitch et al. (1999) o método Multifoco está baseado na Teoria do Imageamento Homeomórfico e consiste em empilhar dados de cobertura múltipla com distribuição fonte-receptor arbitrária de acordo com uma nova correção de sobretempo, chamada Multifoco. Esta correção de sobretempo esta baseada numa aproximação esférica local da frente de onda focalizante na vizinhança da superfície da terra. Este método permite construir uma seção sísmica no domínio do tempo de afastamento nulo aumentando a relação sinal/ruído. A técnica Multifoco não necessita do conhecimento a priori de um macro-modelo de velocidades. Três parâmetros são usados para descrever a aproximação de tempo de trânsito, Multifoco, os quais são: 1) o ângulo de emergência do raio de afastamento nulo ou raio de reflexão normal (β₀), 2) a curvatura da frente de onda no Ponto de Incidência Normal (R_NIP) e 3) curvatura da frente de Onda Normal (R_N). Sendo também necessário a velocidade próximo a superfície da terra. Neste trabalho de tese aplico esta técnica de empilhamento Multifoco para dados de cobertura múltipla referidos a modelos de velocidade constante e modelo heterogêneos, com o objetivo de simular seções sísmicas afastamento-nulo. Neste caso, como se trata da solução de um problema direto, o macro-modelo de velocidades é considerado conhecido a priori. No contexto do problema inverso tem-se que os parâmetros R_NIP, R_N e β₀ podem ser determinados a partir da análise de coerência aplicada aos dados sísmicos de múltipla cobertura. Na solução deste problema a função objetivo, a ser otimizada, é definida pelo cálculo da máxima coerência existente entre os dados na superfície de empilhamento sísmico. Neste trabalho de tese nos discutimos a sensibilidade da aproximação do tempo de trânsito usado no empilhamento Multifoco, como uma função dos parâmetros R_NIP, R_N e β₀. Esta análise de sensibilidade é feita de três diferentes modos: 1) a primeira derivada da função objetivo, 2) a medida de coerência, denominada semelhança, e 3) a sensibilidade no Empilhamento Multifoco.

Analytic perturbation theory for bound states in the transfer matrix spectrum of weakly correlated lattice ferromagnetic spin systems

We consider general d-dimensional lattice ferromagnetic spin systems with nearest neighbor interactions in the high temperature region ('beta' << 1). Each model is characterized by a single site apriori spin distribution taken to be even. We also take the parameter 'alfa' = ('S POT.4') - 3 '(S POT.2') POT.2' > 0, i.e. in the region which we call Gaussian subjugation, where ('S POT.K') denotes the kth moment of the apriori distribution. Associated with the model is a lattice quantum field theory known to contain a particle of asymptotic mass -ln 'beta' and a bound state below the two-particle threshold. We develop a 'beta' analytic perturbation theory for the binding energy of this bound state. As a key ingredient in obtaining our result we show that the Fourier transform of the two-point function is a meromorphic function, with a simple pole, in a suitable complex spectral parameter and the coefficients of its Laurent expansion are analytic in 'beta'.

Finding negative event oriented patterns in long temporal sequences

Pattern discovery in a long temporal event sequence is of great importance in many application domains. Most of the previous work focuses on identifying positive associations among time stamped event types. In this paper, we introduce the problem of defining and discovering negative associations that, as positive rules, may also serve as a source of knowledge discovery. In general, an event-oriented pattern is a pattern that associates with a selected type of event, called a target event. As a counter-part of previous research, we identify patterns that have a negative relationship with the target events. A set of criteria is defined to evaluate the interestingness of patterns associated with such negative relationships. In the process of counting the frequency of a pattern, we propose a new approach, called unique minimal occurrence, which guarantees that the Apriori property holds for all patterns in a long sequence. Based on the interestingness measures, algorithms are proposed to discover potentially interesting patterns for this negative rule problem. Finally, the experiment is made for a real application.

The integration of multi-source data to improve the classification of remotely sensed images

The number of remote sensing platforms and sensors rises almost every year, yet much work on the interpretation of land cover is still carried out using either single images or images from the same source taken at different dates. Two questions could be asked of this proliferation of images: can the information contained in different scenes be used to improve the classification accuracy and, what is the best way to combine the different imagery? Two of these multiple image sources are MODIS on the Terra platform and ETM+ on board Landsat7, which are suitably complementary. Daily MODIS images with 36 spectral bands in 250-1000 m spatial resolution and seven spectral bands of ETM+ with 30m and 16 days spatial and temporal resolution respectively are available. In the UK, cloud cover may mean that only a few ETM+ scenes may be available for any particular year and these may not be at the time of year of most interest. The MODIS data may provide information on land cover over the growing season, such as harvest dates, that is not present in the ETM+ data. Therefore, the primary objective of this work is to develop a methodology for the integration of medium spatial resolution Landsat ETM+ image, with multi-temporal, multi-spectral, low-resolution MODIS \Terra images, with the aim of improving the classification of agricultural land. Additionally other data may also be incorporated such as field boundaries from existing maps. When classifying agricultural land cover of the type seen in the UK, where crops are largely sown in homogenous fields with clear and often mapped boundaries, the classification is greatly improved using the mapped polygons and utilising the classification of the polygon as a whole as an apriori probability in classifying each individual pixel using a Bayesian approach. When dealing with multiple images from different platforms and dates it is highly unlikely that the pixels will be exactly co-registered and these pixels will contain a mixture of different real world land covers. Similarly the different atmospheric conditions prevailing during the different days will mean that the same emission from the ground will give rise to different sensor reception. Therefore, a method is presented with a model of the instantaneous field of view and atmospheric effects to enable different remote sensed data sources to be integrated.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

Chain Split and Computations in Practical Rule Mining

A novel association rule mining algorithm is composed, using the unit cube chain decomposition structures introduced in [HAN, 1966; TON, 1976]. [HAN, 1966] established the chain split theory. [TON, 1976] invented an excellent chain computation framework which brings chain split into the practical domain. We integrate these technologies around the rule mining procedures. Effectiveness is related to the intention of low complexity of rules mined. Complexity of the procedure composed is complementary to the known Apriori algorithm which is defacto standard in rule mining area.

Improving the predictability of time series by chaotic parameter estimation

Limited literature regarding parameter estimation of dynamic systems has been identified as the central-most reason for not having parametric bounds in chaotic time series. However, literature suggests that a chaotic system displays a sensitive dependence on initial conditions, and our study reveals that the behavior of chaotic system: is also sensitive to changes in parameter values. Therefore, parameter estimation technique could make it possible to establish parametric bounds on a nonlinear dynamic system underlying a given time series, which in turn can improve predictability. By extracting the relationship between parametric bounds and predictability, we implemented chaos-based models for improving prediction in time series. ^ This study describes work done to establish bounds on a set of unknown parameters. Our research results reveal that by establishing parametric bounds, it is possible to improve the predictability of any time series, although the dynamics or the mathematical model of that series is not known apriori. In our attempt to improve the predictability of various time series, we have established the bounds for a set of unknown parameters. These are: (i) the embedding dimension to unfold a set of observation in the phase space, (ii) the time delay to use for a series, (iii) the number of neighborhood points to use for avoiding detection of false neighborhood and, (iv) the local polynomial to build numerical interpolation functions from one region to another. Using these bounds, we are able to get better predictability in chaotic time series than previously reported. In addition, the developments of this dissertation can establish a theoretical framework to investigate predictability in time series from the system-dynamics point of view. ^ In closing, our procedure significantly reduces the computer resource usage, as the search method is refined and efficient. Finally, the uniqueness of our method lies in its ability to extract chaotic dynamics inherent in non-linear time series by observing its values. ^

Managing the multiplicities of graduate level education! Are Master’s students’ expectations matched by their experiences?

With rapid increases in student fees reflecting moves towards a QUASI Market model of Higher Education in the UK and across much of the Western World[1], many universities find themselves having to meet progressively higher levels of student expectations[2]. This is particularly the case at undergraduate level, where increases in fees over the past decade have far exceeded inflation. Yet with so much attention on ‘consumer savvy’ undergraduates, the question of whether Master’s level students’ expectations are matched by their experiences is one which remains largely unanswered. Grounded in an empirically grounded approach to learning and teaching developed by the paper authors[3], this paper sets out to being to answer this question. In doing so it makes a distinctive contribution to debates about graduate level engineering education and concludes with a number of recommendations. Discussion: The ‘MSc: Managing Expectations’ Project analyses the expectations and experiences of Graduate level Engineering Management Students over a two year period. Focusingon the ‘student experience’, three main concepts are identified as being particular relevant to enhancing learning [3]: Relationships: Variety: Synergy. Relationships: Based on empirical research, the significance of Relationships within the academic environment is discussed with particular attention being paid to the value of students’ social and academic support networks, including academic tutoring. Variety: Grounded in a statistical analysis of ‘engagement data’ together with survey and interview findings, the concept of variety critically examines students’ perspectives and experiencesof different approaches to learning and teaching. Synergy: Possibly the most important concept discussed within this paper, the need for constructively aligned curriculum is extended to reflect the students’ apriori knowledge and experienceas well as employer and societal demands and expectations. The conclusion brings the different concepts within the discussion together, providing a set of practical recommendations for colleagues working both at graduate and undergraduate level. References 1.Gibbs, P. (2001) "Higher education as a market: a problem or solution?." Studies in Higher Education 26. 1. pp. 85-94. 2.Tricker, T., (2005) Student Expectations-How do we measure up. University of Sheffield. Available from: http://www.persons.org.uk/tricker%20paper.pdf Accessed 9/10/14 3.Clark, R. & Andrews, J. (2014). Relationships, Variety & Synergy [RVS]: The Vital Ingredients for Scholarship in Engineering Education? A Case-Study. European Journal of Engineering Education. 39.6. pp. 585-600.

AN ASSESSMENT OF FLOW REGIME MAPS AND A NUMERICAL HEAT TRANSFER CORRELATION FOR THE STRATIFIED/ANNULAR REGIME OF SHEAR-DRIVEN INTERNAL CONDENSING FLOWS

Several modern-day cooling applications require the incorporation of mini/micro-channel shear-driven flow condensers. There are several design challenges that need to be overcome in order to meet those requirements. The difficulty in developing effective design tools for shear-driven flow condensers is exacerbated due to the lack of a bridge between the physics-based modelling of condensing flows and the current, popular approach based on semi-empirical heat transfer correlations. One of the primary contributors of this disconnect is a lack of understanding caused by the fact that typical heat transfer correlations eliminate the dependence of the heat transfer coefficient on the method of cooling employed on the condenser surface when it may very well not be the case. This is in direct contrast to direct physics-based modeling approaches where the thermal boundary conditions have a direct and huge impact on the heat transfer coefficient values. Typical heat transfer correlations instead introduce vapor quality as one of the variables on which the value of the heat transfer coefficient depends. This study shows how, under certain conditions, a heat transfer correlation from direct physics-based modeling can be equivalent to typical engineering heat transfer correlations without making the same apriori assumptions. Another huge factor that raises doubts on the validity of the heat-transfer correlations is the opacity associated with the application of flow regime maps for internal condensing flows. It is well known that flow regimes influence heat transfer rates strongly. However, several heat transfer correlations ignore flow regimes entirely and present a single heat transfer correlation for all flow regimes. This is believed to be inaccurate since one would expect significant differences in the heat transfer correlations for different flow regimes. Several other studies present a heat transfer correlation for a particular flow regime - however, they ignore the method by which extents of the flow regime is established. This thesis provides a definitive answer (in the context of stratified/annular flows) to: (i) whether a heat transfer correlation can always be independent of the thermal boundary condition and represented as a function of vapor quality, and (ii) whether a heat transfer correlation can be independently obtained for a flow regime without knowing the flow regime boundary (even if the flow regime boundary is represented through a separate and independent correlation). To obtain the results required to arrive at an answer to these questions, this study uses two numerical simulation tools - the approximate but highly efficient Quasi-1D simulation tool and the exact but more expensive 2D Steady Simulation tool. Using these tools and the approximate values of flow regime transitions, a deeper understanding of the current state of knowledge in flow regime maps and heat transfer correlations in shear-driven internal condensing flows is obtained. The ideas presented here can be extended for other flow regimes of shear-driven flows as well. Analogous correlations can also be obtained for internal condensers in the gravity-driven and mixed-driven configuration.