A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.     

Unpopuläre E-Mail-Verschlüsselung – Auflösung des Henne-Ei-Problems

E-Mail-Verschlüsselung könnte längst flächendeckend Verwendung finden. Der Beitrag gibt eine Antwort auf die Frage, warum dies nicht der Fall ist–und macht Vorschläge, was getan werden sollte, um dies zu ändern.     

Fast online graph clustering via Erd?s-Rényi mixture

In the context of graph clustering, we consider the problem of simultaneously estimating both the partition of the graph nodes and the parameters of an underlying mixture of affiliation networks. In numerous applications the rapid increase of data size over time makes classical clustering algorithms too slow because of the high computational cost. In such situations online clustering algorithms are an efficient alternative to classical batch algorithms. We present an original online algorithm for graph clustering based on a Erd?s-Rényi graph mixture. The relevance of the algorithm is illustrated, using both simulated and real data sets. The real data set is a network extracted from the French political blogosphere and presents an interesting community organization.     

Processing and interactive editing of huge point clouds from 3D scanners

This paper describes a new out-of-core multi-resolution data structure for real-time visualization, interactive editing and externally efficient processing of large point clouds. We describe an editing system that makes use of the novel data structure to provide interactive editing and preprocessing tools for large scanner data sets. Using the new data structure, we provide a complete tool chain for 3D scanner data processing, from data preprocessing and filtering to manual touch-up and real-time visualization. In particular, we describe an out-of-core outlier removal and bilateral geometry filtering algorithm, a toolset for interactive selection, painting, transformation, and filtering of huge out-of-core point-cloud data sets and a real-time rendering algorithm, which all use the same data structure as storage backend. The interactive tools work in real-time for small model modifications. For large scale editing operations, we employ a two-resolution approach where editing is planned in real-time and executed in an externally efficient offline computation afterwards. We evaluate our implementation on example data sets of sizes up to 63 GB, demonstrating that the proposed technique can be used effectively in real-world applications.     

Experimental measurement of a time-varying optical path difference by the small-aperture beam technique

We discuss the use of time series of the jitter angle of multiple, small-aperture probe beams (the small-aperture beam technique, or SABT) as they emerge from a turbulent, optically active flow-field to quantify the time-varying optical path difference (OPD). The flow field studied is that for the transitionally turbulent region of a two-dimensional heated jet. Techniques to construct a complete time series of instantaneous realizations of the OPD are first applied to a numerically generated flow field and then to an experimental flow field. The SABT sensor's measurement accuracy is assessed, and its application to flow fields that differ from the numerical heated jet is discussed.     

Health learning materials support in South Africa compared with other developing countries

An investigation was carried out in to thyroid hormones (TSH, T3, T4) and lipid parameters (total cholesterol, LDL cholesterol, HDL cholesterol, triglyceride) in 136 adolescents (94 femals, average age 13 years). An iodine deficiency (grade II-II) with respect to the daily urine excretion per 1,73 m2 BSA was found in 75%. With few exceptions the serum levels of TSH and T4 were in the normal range. In 36% of the patients we noticed compensatory elevated T3 levels. Correlations between thyroid hormones TSH, T4, renal iodine excretion and the volume of thyroid glands were not detectable, only T3 showed a dignificant positive correlation to the thyroid gland volume. The average values of lipids in patients were found to be higher than in normals. We consider the changed lipids as a sign of a disturbed efficacy of thyroid hormones. The regional insufficient iodine supply causes goiters and to a high degree the observed hyperchole-sterolemia, too. Our results underline the necessity of a common iodine salt prophylaxis as well as the treatment of "harmless" goiters in puberty.     

Iris recognition: Analysis of the error rates regarding the accuracy of the segmentation stage

Iris recognition has been widely used in several scenarios with very satisfactory results. As it is one of the earliest stages, the image segmentation is in the basis of the process and plays a crucial role in the success of the recognition task. In this paper we analyze the relationship between the accuracy of the iris segmentation process and the error rates of three typical iris recognition methods. We selected 5000 images of the UBIRIS, CASIA and ICE databases that the used segmentation algorithm can accurately segment and artificially simulated four types of segmentation inaccuracies. The obtained results allowed us to conclude about a strong relationship between translational segmentation inaccuracies – that lead to errors in phase – and the recognition error rates.