Cluster Analysis of Business Data

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Hierarchical cluster analysis of groups of individuals : application to business data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude

Formal Verification of Temporal Properties for Parametrized Concurrent Programs and Concurrent Data Structures

Los tipos de datos concurrentes son implementaciones concurrentes de las abstracciones de datos clásicas, con la diferencia de que han sido específicamente diseñados para aprovechar el gran paralelismo disponible en las modernas arquitecturas multiprocesador y multinúcleo. La correcta manipulación de los tipos de datos concurrentes resulta esencial para demostrar la completa corrección de los sistemas de software que los utilizan. Una de las mayores dificultades a la hora de diseñar y verificar tipos de datos concurrentes surge de la necesidad de tener que razonar acerca de un número arbitrario de procesos que invocan estos tipos de datos de manera concurrente. Esto requiere considerar sistemas parametrizados. En este trabajo estudiamos la verificación formal de propiedades temporales de sistemas concurrentes parametrizados, poniendo especial énfasis en programas que manipulan estructuras de datos concurrentes. La principal dificultad a la hora de razonar acerca de sistemas concurrentes parametrizados proviene de la interacción entre el gran nivel de concurrencia que éstos poseen y la necesidad de razonar al mismo tiempo acerca de la memoria dinámica. La verificación de sistemas parametrizados resulta en sí un problema desafiante debido a que requiere razonar acerca de estructuras de datos complejas que son accedidas y modificadas por un numero ilimitado de procesos que manipulan de manera simultánea el contenido de la memoria dinámica empleando métodos de sincronización poco estructurados. En este trabajo, presentamos un marco formal basado en métodos deductivos capaz de ocuparse de la verificación de propiedades de safety y liveness de sistemas concurrentes parametrizados que manejan estructuras de datos complejas. Nuestro marco formal incluye reglas de prueba y técnicas especialmente adaptadas para sistemas parametrizados, las cuales trabajan en colaboración con procedimientos de decisión especialmente diseñados para analizar complejas estructuras de datos concurrentes. Un aspecto novedoso de nuestro marco formal es que efectúa una clara diferenciación entre el análisis del flujo de control del programa y el análisis de los datos que se manejan. El flujo de control del programa se analiza utilizando reglas de prueba y técnicas de verificación deductivas especialmente diseñadas para lidiar con sistemas parametrizados. Comenzando a partir de un programa concurrente y la especificación de una propiedad temporal, nuestras técnicas deductivas son capaces de generar un conjunto finito de condiciones de verificación cuya validez implican la satisfacción de dicha especificación temporal por parte de cualquier sistema, sin importar el número de procesos que formen parte del sistema. Las condiciones de verificación generadas se corresponden con los datos manipulados. Estudiamos el diseño de procedimientos de decisión especializados capaces de lidiar con estas condiciones de verificación de manera completamente automática. Investigamos teorías decidibles capaces de describir propiedades de tipos de datos complejos que manipulan punteros, tales como implementaciones imperativas de pilas, colas, listas y skiplists. Para cada una de estas teorías presentamos un procedimiento de decisión y una implementación práctica construida sobre SMT solvers. Estos procedimientos de decisión son finalmente utilizados para verificar de manera automática las condiciones de verificación generadas por nuestras técnicas de verificación parametrizada. Para concluir, demostramos como utilizando nuestro marco formal es posible probar no solo propiedades de safety sino además de liveness en algunas versiones de protocolos de exclusión mutua y programas que manipulan estructuras de datos concurrentes. El enfoque que presentamos en este trabajo resulta ser muy general y puede ser aplicado para verificar un amplio rango de tipos de datos concurrentes similares. Abstract Concurrent data types are concurrent implementations of classical data abstractions, specifically designed to exploit the great deal of parallelism available in modern multiprocessor and multi-core architectures. The correct manipulation of concurrent data types is essential for the overall correctness of the software system built using them. A major difficulty in designing and verifying concurrent data types arises by the need to reason about any number of threads invoking the data type simultaneously, which requires considering parametrized systems. In this work we study the formal verification of temporal properties of parametrized concurrent systems, with a special focus on programs that manipulate concurrent data structures. The main difficulty to reason about concurrent parametrized systems comes from the combination of their inherently high concurrency and the manipulation of dynamic memory. This parametrized verification problem is very challenging, because it requires to reason about complex concurrent data structures being accessed and modified by threads which simultaneously manipulate the heap using unstructured synchronization methods. In this work, we present a formal framework based on deductive methods which is capable of dealing with the verification of safety and liveness properties of concurrent parametrized systems that manipulate complex data structures. Our framework includes special proof rules and techniques adapted for parametrized systems which work in collaboration with specialized decision procedures for complex data structures. A novel aspect of our framework is that it cleanly differentiates the analysis of the program control flow from the analysis of the data being manipulated. The program control flow is analyzed using deductive proof rules and verification techniques specifically designed for coping with parametrized systems. Starting from a concurrent program and a temporal specification, our techniques generate a finite collection of verification conditions whose validity entails the satisfaction of the temporal specification by any client system, in spite of the number of threads. The verification conditions correspond to the data manipulation. We study the design of specialized decision procedures to deal with these verification conditions fully automatically. We investigate decidable theories capable of describing rich properties of complex pointer based data types such as stacks, queues, lists and skiplists. For each of these theories we present a decision procedure, and its practical implementation on top of existing SMT solvers. These decision procedures are ultimately used for automatically verifying the verification conditions generated by our specialized parametrized verification techniques. Finally, we show how using our framework it is possible to prove not only safety but also liveness properties of concurrent versions of some mutual exclusion protocols and programs that manipulate concurrent data structures. The approach we present in this work is very general, and can be applied to verify a wide range of similar concurrent data types.

Conceptual knowledge discovery with frequent concept lattices

Knowledge discovery support environments include beside classical data analysis tools also data mining tools. For supporting both kinds of tools, a unified knowledge representation is needed. We show that concept lattices which are used as knowledge representation in Conceptual Information Systems can also be used for structuring the results of mining association rules. Vice versa, we use ideas of association rules for reducing the complexity of the visualization of Conceptual Information Systems.

Iceberg query lattices for datalog

In this paper we study two orthogonal extensions of the classical data mining problem of mining association rules, and show how they naturally interact. The first is the extension from a propositional representation to datalog, and the second is the condensed representation of frequent itemsets by means of Formal Concept Analysis (FCA). We combine the notion of frequent datalog queries with iceberg concept lattices (also called closed itemsets) of FCA and introduce two kinds of iceberg query lattices as condensed representations of frequent datalog queries. We demonstrate that iceberg query lattices provide a natural way to visualize relational association rules in a non-redundant way.

Classical Invariants for Principal Series and Isomorphisms of Root Data

We develop some new techniques to calculate the Schur indicator for self-dual irreducible Langlands quotients of the principal series representations. Using these techniques we derive some new formulas for the Schur indicator and the real-quaternionic indicator. We make progress towards developing an algorithm to decide whether or not two root data are isomorphic. When the derived group has cyclic center, we solve the isomorphism problem completely. An immediate consequence is a clean and precise classification theorem for connected complex reductive groups whose derived groups have cyclic center.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

HR Del REMNANT ANATOMY USING TWO-DIMENSIONAL SPECTRAL DATA AND THREE-DIMENSIONAL PHOTOIONIZATION SHELL MODELS

The HR Del nova remnant was observed with the IFU-GMOS at Gemini North. The spatially resolved spectral data cube was used in the kinematic, morphological, and abundance analysis of the ejecta. The line maps show a very clumpy shell with two main symmetric structures. The first one is the outer part of the shell seen in H alpha, which forms two rings projected in the sky plane. These ring structures correspond to a closed hourglass shape, first proposed by Harman & O'Brien. The equatorial emission enhancement is caused by the superimposed hourglass structures in the line of sight. The second structure seen only in the [O III] and [N II] maps is located along the polar directions inside the hourglass structure. Abundance gradients between the polar caps and equatorial region were not found. However, the outer part of the shell seems to be less abundant in oxygen and nitrogen than the inner regions. Detailed 2.5-dimensional photoionization modeling of the three-dimensional shell was performed using the mass distribution inferred from the observations and the presence of mass clumps. The resulting model grids are used to constrain the physical properties of the shell as well as the central ionizing source. A sequence of three-dimensional clumpy models including a disk-shaped ionization source is able to reproduce the ionization gradients between polar and equatorial regions of the shell. Differences between shell axial ratios in different lines can also be explained by aspherical illumination. A total shell mass of 9 x 10(-4) M(circle dot) is derived from these models. We estimate that 50%-70% of the shell mass is contained in neutral clumps with density contrast up to a factor of 30.

Geostatistical Mapping of Outfall Plume Dispersion Data gathered with an autonomous underwater vehicle

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute the experimental semivariogram which was fitted to three theoretical models: spherical, exponential and gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the near by beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume’s dilution are rare, these studies might be very helpful in the future for validation of dispersion models.

On the solubility of three disperse anthraquinone dyes in supercritical carbon dioxide: new experimental data and correlation

Solubility measurements of quinizarin. (1,4-dihydroxyanthraquinone), disperse red 9 (1-(methylamino) anthraquinone), and disperse blue 14 (1,4-bis(methylamino)anthraquinone) in supercritical carbon dioxide (SC CO2) were carried out in a flow type apparatus, at a temperature range from (333.2 to 393.2) K and at pressures from (12.0 to 40.0) MPa. Mole fraction solubility of the three dyes decreases in the order quinizarin (2.9 x 10(-6) to 2.9.10(-4)), red 9 (1.4 x 10(-6) to 3.2 x 10(-4)), and blue 14 (7.8 x 10(-8) to 2.2 x 10(-5)). Four semiempirical density based models were used to correlatethe solubility of the dyes in the SC CO2. From the correlation results, the total heat of reaction, heat of vaporization plus the heat of solvation of the solute, were calculated and compared with the results presented in the literature. The solubilities of the three dyes were correlated also applying the Soave-Redlich-Kwong cubic equation of state (SRK CEoS) with classical mixing rules, and the physical properties required for the modeling were estimated and reported.

On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Clustering an interval data set : are the main partitions similar to a priori partition?

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