Linear Optimization over Permutation Groups

For a permutation group given by a set of generators, the problem of finding "special" group members is NP-hard in many cases. E.g., this is true for the problem of finding a permutation with a minimum number of fixed points or a permutation with a minimal Hamming distance from a given permutation. Many of these problems can be modeled as linear optimization problems over permutation groups. We develop a polyhedral approach to this general problem and derive an exact and practically fast algorithm based on the branch&cut-technique

An Integer Programming Approach to Fuzzy Symmetry Detection

The problem of exact symmetry detection in general graphs has received much attention recently. In spite of its NP-hardness, two different algorithms have been presented that in general can solve this problem quickly in practice. However, as most graphs do not admit any exact symmetry at all, the much harder problem of fuzzy symmetry detection arises: a minimal number of certain modifications of the graph should be allowed in order to make it symmetric. We present a general approach to this problem: we allow arbitrary edge deletions and edge creations; every single modification can be given an individual weight. We apply integer programming techniques to solve this problem exactly or heuristically and give runtime results for a first implementation

Data Linking - Linking survey data with geospatial, social media, and sensor data (Version 1.0)

Survey data are still the most commonly used type of data in the quantitative social sciences. However, as not everything that is of interest to social scientists can be measured via surveys, and the self-report data they provide have certain limitations, such as recollection or social desirability bias, researchers have increasingly used other types of data that are not specifically created for research. These data are often called "found data" or "non-designed data" and encompass a variety of different data types. Naturally, these data have their own sets of limitations. One way of combining the unique strengths of survey data and these other data types and dealing with some of their respective limitations is to link them. This guideline first describes why linking survey data with other types of data can be useful for researchers. After that, it focuses on the linking of survey data with three types of data that are becoming increasingly popular in the social sciences: geospatial data, social media data, and sensor data. Following a discussion of the advantages and challenges associated with linking survey data with these types of data, the guideline concludes by comparing their similarities, presenting some general recommendations regarding linking surveys with other types of (found/non-designed) data, and providing an outlook on current developments in survey research with regard to data linking

A Fast Layout Algorithm for k-Level Graphs

In this paper, we present a fast layout algorithm for k-level graphs with given permutations of the vertices on each level. The algorithm can be used in particular as a third phase of the Sugiyama algorithm (1981). The Sugiyama algorithm computes a layout for an arbitrary graph by (1) converting it into a k-level graph, (2) reducing the number of edge crossings by permuting the vertices on the levels, and (3) assigning y-coordinates to the levels and x-coordinates to the vertices. In the layouts generated by our algorithm, every edge will have at most two bends, and will be drawn vertically between these bends

Drawing cycles in networks

In this paper we show how a graph that contains a specified cycle can be drawn in the plane such that the cycle is drawn circularly while the rest of the graph is layouted orthogonally. We also show how to extend this algorithm to deal with a set of disjoint cycles at once

Planarization With Fixed Subgraph Embedding

The visualization of metabolic networks using techniques of graph drawing has recently become an important research area. In order to ease the analysis of these networks, readable layouts are required in which certain known network components are easily recognizable. In general, the topology of the drawings produced by traditional graph drawing algorithms does not reflect the biologists' expert knowledge on particular substructures of the underlying network. To deal with this problem we present a constrained planarization method---an algorithm which computes a graph layout in the plane preserving the predefined shape for the specified substructures while minimizing the overall number of edge-crossings

Planarization With Fixed Subgraph Embedding

The visualization of metabolic networks using techniques of graph drawing has recently become an important research area. In order to ease the analysis of these networks, readable layouts are required in which certain known network components are easily recognizable. In general, the topology of the drawings produced by traditional graph drawing algorithms does not reflect the biologists' expert knowledge on particular substructures of the underlying network. To deal with this problem we present a constrained planarization method---an algorithm which computes a graph layout in the plane preserving the predefined shape for the specified substructures while minimizing the overall number of edge-crossings

Drawing cycles in networks

In this paper we show how a graph that contains a specified cycle can be drawn in the plane such that the cycle is drawn circularly while the rest of the graph is layouted orthogonally. We also show how to extend this algorithm to deal with a set of disjoint cycles at once

Voluntary undergraduate technical skills training course to prepare students for clerkship assignment: tutees’ and tutors’ perspectives

BACKGROUND: Skills lab training has become a widespread tool in medical education, and nowadays, skills labs are ubiquitous among medical faculties across the world. An increasingly prevalent didactic approach in skills lab teaching is peer-assisted learning (PAL), which has been shown to be not only effective, but can be considered to be on a par with faculty staff-led training. The aim of the study is to determine whether voluntary preclinical skills teaching by peer tutors is a feasible method for preparing medical students for effective workplace learning in clerkships and to investigate both tutees’ and tutors’ attitudes towards such an intervention. METHODS: A voluntary clerkship preparation skills course was designed and delivered. N = 135 pre-clinical medical students visited the training sessions. N = 10 tutors were trained as skills-lab peer tutors. Voluntary clerkship preparation skills courses as well as tutor training were evaluated by acceptance ratings and pre-post self-assessment ratings. Furthermore, qualitative analyses of skills lab tutors’ attitudes towards the course were conducted following principles of grounded theory. RESULTS: Results show that a voluntary clerkship preparation skills course is in high demand, is highly accepted and leads to significant changes in self-assessment ratings. Regarding qualitative analysis of tutor statements, clerkship preparation skills courses were considered to be a helpful and necessary asset to preclinical medical education, which benefits from the tutors’ own clerkship experiences and a high standardization of training. Tutor training is also highly accepted and regarded as an indispensable tool for peer tutors. CONCLUSIONS: Our study shows that the demand for voluntary competence-oriented clerkship preparation is high, and a peer tutor-led skills course as well as tutor training is well accepted. The focused didactic approach for tutor training is perceived to be effective in preparing tutors for their teaching activity in this context. A prospective study design would be needed to substantiate the results objectively and confirm the effectiveness