MOBSY: Integration of vision and dialogue in service robots

Abstract. This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics. Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level. We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute.     

Biosorption of heavy metals by Saccharomyces cerevisiae: Effects of nutrient conditions

Studies took place to investigate the effects of different nutrient conditions on the biosorption ability and selectivity of heavy metals by Saccharomyces cerevisiae. After having grown in media supplemented with additional glucose, ammonium, phosphate or cysteine, the yeast was exposed to an equimolar solution of lead, cadmium, zinc and copper. Lead removal from a mixed solution was significantly higher than that of copper, followed by zinc and cadmium. Generally, yeasts from cysteine-rich media showed greatest sorption capacity whereas phosphate addition influenced zinc selectivity. In addition, glucose, fructose and sucrose as carbon sources were examined. Cultures grown in glucose had a better uptake than those cultivated with fructose at an incubation time of 30 min.     

The relationship between coffee consumption and serum cholesterol under consideration of smoking history

To provide insight into the stream of Medicare payments over time, a sixteen-year longitudinal study examines three age cohorts of beneficiaries, looking separately at beneficiaries who died during the study period and those who survived. The common wisdom that a small minority of the population accounts for a large majority of health care expenditures is tempered when health care use is examined over an extended period of time. By putting high average costs in the final years of life in the context of a cohort's total lifetime experience, the study shows a leveling of spending over time, resulting in a lower concentration of health care resources on a small fraction of the population.     

Using neural networks to select wavelet features for breast cancerdiagnosis

This study focuses on improving microcalcification classification by establishing an efficient computer-aided diagnosis system that extracts Daubechies-4 and biorthogonal wavelet features. These wavelets were chosen because they have been used in military target recognition and fingerprint recognition research with images characterized by low contrast, similar to mammography. Feature selection techniques are employed to further increase classification performance. The artificial neural network feature selection techniques are complemented by a conventional decision boundary-based feature selection method. The results using the wavelet features are compared to more conventional measures of image texture, angular second moment, and Karhunen Loeve coefficients. The use of alternative signal processing to compare wavelet and neural techniques allows for a measure of the problem difficulty. It is concluded that advances and contributions have been made with the introduction of two novel feature extraction methods for breast cancer diagnosis, wavelets and eigenmasses. Additionally, feature selection techniques are demonstrated, compared, and validated, transforming adequate discrimination power into promising classification results     

Advances in Modeling and Simulation of Grinding Processes

In the last decade the relevance of modeling and simulation of grinding processes has significantly risen which is caused by industrial needs and is indicated by the number of publications and research activities in this area. This keynote paper results from a collaborative work within the STC G and gives an overview of the current state of the art in modeling and simulation of grinding processes: Physical process models (analytical and numerical models) and empirical process models (regression analysis, artificial neural net models) as well as heuristic process models (rule based models) are taken into account, and outlined with respect to their achievements in this paper. The models are characterized by the process parameters such as grinding force, grinding temperature, etc. as well as work results including surface topography and surface integrity. Furthermore, the capabilities and the limitations of the presented model types and simulation approaches will be exemplified.     

Reported food intake and distribution of body fat: a repeated cross-sectional study

Background  

Body mass, as well as distribution of body fat, are predictors of both diabetes and cardiovascular disease. In Northern Sweden, despite a marked increase in average body mass, prevalence of diabetes was stagnant and myocardial infarctions decreased. A more favourable distribution of body fat is a possible contributing factor.     

Intrinsic plagiarism analysis

Research in automatic text plagiarism detection focuses on algorithms that compare suspicious documents against a collection of reference documents. Recent approaches perform well in identifying copied or modified foreign sections, but they assume a closed world where a reference collection is given. This article investigates the question whether plagiarism can be detected by a computer program if no reference can be provided, e.g., if the foreign sections stem from a book that is not available in digital form. We call this problem class intrinsic plagiarism analysis; it is closely related to the problem of authorship verification. Our contributions are threefold. (1) We organize the algorithmic building blocks for intrinsic plagiarism analysis and authorship verification and survey the state of the art. (2) We show how the meta learning approach of Koppel and Schler, termed “unmasking”, can be employed to post-process unreliable stylometric analysis results. (3) We operationalize and evaluate an analysis chain that combines document chunking, style model computation, one-class classification, and meta learning.     

DuD Recht

DuD Recht

DuD Recht     

Coping with large design spaces: design problem solving in fluidic engineering

This paper is about tool support for knowledge-intensive engineering tasks. In particular, it introduces software technology to assist the design of complex technical systems. There is a long tradition in automated design problem solving in the field of artificial intelligence, where, especially in the early stages, the search paradigm dictated many approaches. Later, in the so-called modern period, a better problem understanding led to the development of more adequate problem solving techniques. However, search still constitutes an indispensable part in computer-based design problem solving—albeit many human problem solvers get by without (almost). We tried to learn lessons from this observation, and one is presented in this paper. We introduce design problem solving by functional abstraction which follows the motto: construct a poor solution with little search, which then must be repaired. For the domain of fluidic engineering we have operationalized the paradigm by the combination of several high-level techniques. The red thread of this paper is design automation, but the presented technology does also contribute in the following respects: (a) productivity enhancement by relieving experts from auxiliary and routine tasks; (b) formulation, exchange, and documentation of knowledge about design; (c) requirements engineering, feasibility analysis, and validation. This research was supported by DFG grants Schw 120/56-3, KL 529/10-3, KL 529/7-3, and KL 529/10-1.     

Fame in the sciences: a culturomics approach

Scientometrics - Although scientists, like many other professionals, aspire to fame and recognition, research in the emergent field of fame and celebrity has as yet neglected to explore their fame...