Rank aggregation and belief revision dynamics

In this paper, we compare several popular rank aggregation methods by the accuracy of finding the true (correct) ranked list. Our research reveals that under most common circumstances simple methods such as the average or majority actually tend to outperform computationally-intensive distance-based methods. We then conduct a study to compare how actual people aggregate ranks in a group setting. Our finding is that individuals tend to adopt the group mean in a third of all revisions, making it the most popular strategy for belief revision

Forecasting the data cube

Forecasting time series data is crucial in a number of domains such as supply chain management and display advertisement. In these areas, the time series data to forecast is typically organized along multiple dimensions leading to a high number of time series that need to be forecasted. Most current approaches focus only on selection and optimizing a forecast model for a single time series. In this paper, we explore how we can utilize time series at different dimensions to increase forecast accuracy and, optionally, reduce model maintenance overhead. Solving this problem is challenging due to the large space of possibilities and possible high model creation costs. We propose a model configuration advisor that automatically determines the best set of models, a model configuration, for a given multi-dimensional data set. Our approach is based on a general process that iteratively examines more and more models and simultaneously controls the search space depending on the data set, model type and available hardware. The final model configuration is integrated into F2DB, an extension of PostgreSQL, that processes forecast queries and maintains the configuration as new data arrives. We comprehensively evaluated our approach on real and synthetic data sets. The evaluation shows that our approach significantly increases forecast query accuracy while ensuring low model costs

More practice in educational research? A study on practice perspectives in research projects

In der Studie wird untersucht, welche Formen und Ausprägungen der Einbeziehung von Praxisperspektiven in Forschungsprojekten realisiert werden. Es wird ein theoriegeleitetes Kodierschema vorgestellt und auf Interviews aus sieben Bildungsforschungsprojekten angewendet. Alle Forschenden berücksichtigen Praxisperspektiven in ihrer Arbeit, wobei hinsichtlich Erscheinungsformen und Ausmaß sowohl zwischen als auch innerhalb von Projekten deutliche Unterschiede bestehen. Profilanalysen verdeutlichen den Mehrwert einer mehrdimensionalen Betrachtung von Praxistransfer. (DIPF/Orig.)The study examines which forms and characteristics of the inclusion of practice perspectives are realized in research projects. A theory-based coding scheme is presented and applied to interviews from seven educational research projects. All researchers incorporate practice perspectives in their work, with significant differences in manifestations and extent both between and within projects. Profile analyses illustrate the added value of a multidimensional view of practice transfer. (DIPF/Orig.

Reasonable Doubt and Alternative Hypotheses: A Bayesian Analysis

A longstanding question is the extent to which "reasonable doubt" may be expressed simply in terms of a threshold degree of belief. In this context, we examine the extent to which learning about possible alternatives may alter one's beliefs about a target hypothesis, even when no new "evidence" linking them to the hypothesis is acquired. Imagine the following scenario: a crime has been committed and Alice, the police's main suspect has been brought to trial. There are several pieces of evidence that raise the probability that Alice committed the crime. Her attorney's defense strategy is not to challenge this evidence, but instead to provide personal details about Alice's neighbour, Jane. While Jane is one of many people the police spoke to, they saw no reason to investigate her further. You now learn that Jane, too, had access to the shed where the murder weapon was stored, just like Alice. To what extent should this alter your beliefs about Alice's guilt? In this paper, we provide a formal description of the problem and a solution indicating circumstances under which learning about Jane will more or less impact beliefs about Alice

How to Revise Beliefs from Conditionals: A New Proposal

A large body of work has demonstrated the utility of the Bayesian framework for capturing inference in both specialist and everyday contexts. However, the central tool of the framework, conditionalization via Bayes’ rule, does not apply directly to a common type of learning: the acquisition of conditional information. How should an agent change her beliefs on learning that “If A, then C”? This issue, which is central to both reasoning and argumentation, has recently prompted considerable research interest. In this paper, we critique a prominent proposal and provide a new, alternative, answer

Arbeitszeitbedarf für die Bewirtschaftung von Milchviehausläufen

As existing figures on working-time requirements for outdoor runs in cattle husbandry are often out of date or insufficiently detailed for individual use and in particular as few reliable work-economics data are available for ecological forms of farming, figures on working-time requirements and influencing variables for dung removal and spreading of litter in outdoor runs in cattle and pig farming were recorded as a subproject within the framework of the KTBL-KU 2005 project. This report presents the results for dairy cattle husbandry. The calculations are based on an outdoor run area of 6 m2 per cow. Each outdoor run cleaning operation takes between 0.1 and 1.3 MPmin per cow, depending on the method used and the herd size. If the run is spread with litter, these tasks take between 0.1 and 0.7 MPmin per operation per cow. The working time requirement for outdoor run maintenance breaks down into the sub-tasks of cleaning, spreading of litter (if carried out) and, depending on the method, inspection (scraper). Major savings can be expected from process and organisational optimisation

The bifunctional dihydrofolate reductase thymidylate synthase of Tetrahymena thermophila provides a tool for molecular and biotechnology applications

BACKGROUND: Dihydrofolate reductase (DHFR) and thymidylate synthase (TS) are crucial enzymes in DNA synthesis. In alveolata both enzymes are expressed as one bifunctional enzyme. RESULTS: Loss of this essential enzyme activities after successful allelic assortment of knock out alleles yields an auxotrophic marker in ciliates. Here the cloning, characterisation and functional analysis of Tetrahymena thermophila's DHFR-TS is presented. A first aspect of the presented work relates to destruction of DHFR-TS enzyme function in an alveolate thereby causing an auxotrophy for thymidine. A second aspect is to knock in an expression cassette encoding for a foreign gene with subsequent expression of the target protein. CONCLUSION: This system avoids the use of antibiotics or other drugs and therefore is of high interest for biotechnological applications