University of Ljubljana

About: University of Ljubljana is a education organization based out in Ljubljana, Slovenia. It is known for research contribution in the topics: Population & Liquid crystal. The organization has 17210 authors who have published 47013 publications receiving 1082684 citations. The organization is also known as: Univerza v Ljubljani.

Inflation and WMAP three year data: Features are still present

Abstract: The new 3 year WMAP data seem to confirm the presence of nonstandard large scale features in the cosmic microwave anisotropy power spectrum. While these features may hint at uncorrected experimental systematics, it is also possible to generate, in a cosmological way, oscillations on large angular scales by introducing a sharp step in the inflaton potential. Using current cosmological data, we derive constraints on the position, magnitude and gradient of a possible step. We show that a step in the inflaton potential, while strongly constrained by current data, is still allowed and may provide an interesting explanation to the currently measured deviations from the standard featureless spectrum. Moreover, we show that inflationary oscillations in the primordial power spectrum can significantly bias parameter estimates from standard ruler methods involving measurements of baryon oscillations.

Mucus Aggregates in the Adriatic Sea: An Overview of Stages and Occurrences

Abstract: . The wide range of macroscopic mucus aggregates in the Adriatic Sea is documented. These structures arc considered to be initially produced by diatoms. A differentiation into five states or stages: macroflocs, stringers, clouds, creamy surface layers, and gelatinous surface layers is proposed. This classification is based not only on size and shape, but also takes relative position in the water, stability, behavior, and effect on benthos into consideration. An interrelationship between these aggregates - as different manifestations or phases of the same phenomenon - is postulated. Macroflocs and stringers arc more common. Larger aggregates (clouds, creamy layers, gelatinous layers) arc less frequent. The general term “marine snow” is inadequate to describe the entire range of aggregate sizes and shapes, while the Italian designation “mare sporco” (dirty sea) is misleading. Two massive occurrences of dense clouds coupled with surface accumulations were recorded in the Adriatic in 1988 and 1989. The effect of the various stages on the shallow coastal ecosystem of the Northern Adriatic Sea is discussed.

Database dependency discovery: a machine learning approach

Abstract: Database dependencies, such as functional and multivalued dependencies, express the presence of structure in database relations, that can be utilised in the database design process. The discovery of database dependencies can be viewed as an induction problem, in which general rules (dependencies) are obtained from specific facts (the relation). This viewpoint has the advantage of abstracting away as much as possible from the particulars of the dependencies. The algorithms in this paper are designed such that they can easily be generalised to other kinds of dependencies.Like in current approaches to computational induction such as inductive logic programming, we distinguish between top-down algorithms and bottom-up algorithms. In a top-down approach, hypotheses are generated in a systematic way and then tested against the given relation. In a bottom-up approach, the relation is inspected in order to see what dependencies it may satisfy or violate. We give a simple (but inefficient) top-down algorithm, a bi-directional algorithm, and a bottom-up algorithm. In the case of functional dependencies, these algorithms have been implemented in the FDEP system and evaluated experimentally. The bottom-up algorithm is the most efficient of the three, and also outperforms other algorithms from the literature.

Long-term ST database: a reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia.

Abstract: The long-term ST database is the result of a multinational research effort. The goal was to develop a challenging and realistic research resource for development and evaluation of automated systems to detect transient ST segment changes in electrocardiograms and for supporting basic research into the mechanisms and dynamics of transient myocardial ischaemia. Twenty-four hour ambulatory ECG records were selected from routine clinical practice settings in the USA and Europe, between 1994 and 2000, on the basis of occurrence of ischaemic and non-ischaemic ST segment changes. Human expert annotators used newly developed annotation protocols and a specially developed interactive graphic editor tool (SEMIA) that supported paperless editing of annotations and facilitated international co-operation via the Internet. The database contains 86 two- and three-channel 24 h annotated ambulatory records from 80 patients and is stored on DVD-ROMs. The database annotation files contain ST segment annotations of transient ischaemic (1155) and heart-rate related ST episodes and annotations of non-ischaemic ST segment events related to postural changes and conduction abnormalities. The database is intended to complement the European Society of Cardiology ST-T database and the MIT-BIH and AHA arrhythmia databases. It provides a comprehensive representation of 'real-world' data, with numerous examples of transient ischaemic and non-ischaemic ST segment changes, arrhythmias, conduction abnormalities, axis shifts, noise and artifacts.