Lukas Barth

Experimental Comparison of Semantic Word Clouds

We study the problem of computing semantics-preserving word clouds in which semantically related words are close to each other. We implement three earlier algorithms for creating word clouds and three new ones. We define several metrics for quantitative evaluation of the resulting layouts. Then the algorithms are compared according to these metrics, using two data sets of documents from Wikipedia and research papers. We show that two of our new algorithms outperform all the others by placing many more pairs of related words so that their bounding boxes are adjacent. Moreover, this improvement is not achieved at the expense of significantly worsened measurements for the other metrics.

Semantic Word Cloud Representations: Hardness and Approximation Algorithms

We study a geometric representation problem, where we are given a set \(\mathcal B\) of axis-aligned rectangles (boxes) with fixed dimensions and a graph with vertex set \(\mathcal B\). The task is to place the rectangles without overlap such that two rectangles touch if the graph contains an edge between them. We call this problem Contact Representation of Word Networks (Crown). It formalizes the geometric problem behind drawing word clouds in which semantically related words are close to each other. Here, we represent words by rectangles and semantic relationships by edges.

A comprehensive modelling framework for demand side flexibility in smart grids

The increasing share of renewable energy generation in the electricity system comes with significant challenges, such as the volatility of renewable energy sources. To tackle those challenges, demand side management is a frequently mentioned remedy. However, measures of demand side management need a high level of flexibility to be successful. Although extensive research exists that describes, models and optimises various processes with flexible electrical demands, there is no unified notation. Additionally, most descriptions are very process-specific and cannot be generalised. In this paper, we develop a comprehensive modelling framework to mathematically describe demand side flexibility in smart grids while integrating a majority of constraints from different existing models. We provide a universally applicable modelling framework for demand side flexibility and evaluate its practicality by looking at how well Mixed-Integer Linear Program solvers are able to optimise the resulting models, if applied to artificially generated instances. From the evaluation, we derive that our model improves the performance of previous models while integrating additional flexibility characteristics.

Exploiting flexibility in smart grids at scale

Large parts of the worldwide energy system are undergoing drastic changes at the moment. Two of these changes are the increasing share of intermittent generation technologies and the advent of the smart grid. A possible application of smart grids is demand response, i.e., the ability to influence and control power demand to match it with fluctuating generation. We present a heuristic approach to coordinate large amounts of time-flexible loads in a smart grid with the aim of peak shaving with a focus on algorithmic efficiency. A practical evaluation shows that our approach scales to large instances and produces results that come close to optimality.

How much demand side flexibility do we need?: Analyzing where to exploit flexibility in industrial processes

We introduce a novel approach to demand side management: Instead of using flexibility that needs to be defined by a domain expert, we identify a small subset of processes of e. g. an industrial plant that would yield the largest benefit if they were time-shiftable. To find these processes we propose, implement and evaluate a framework that takes power usage time series of industrial processes as input and recommends which processes should be made flexible to optimize for several objectives as output. The technique combines and modifies a motif discovery algorithm with a scheduling algorithm based on mixed-integer programming. We show that even with small amounts of newly introduced flexibility, significant improvements can be achieved, and that the proposed algorithms are feasible for realistically sized instances. We thoroughly evaluate our approach based on real-world power demand data from a small electronics factory.

Dataset accompanying "How much demand side flexibility do we need? - Analyzing where to exploit flexibility in industrial processes"

We introduce a novel approach to demand side management: Instead of using flexibility that needs to be defined by a domain expert, we identify a small subset of processes of e. g. an industrial plant that would yield the largest benefit if they were time-shiftable. To find these processes we propose, implement and evaluate a framework that takes power usage time series of industrial processes as input and recommends which processes should be made flexible to optimize for several objectives as output. The technique combines and modifies a motif discovery algorithm with a scheduling algorithm based on mixed-integer programming. We show that even with small amounts of newly introduced flexibility, significant improvements can be achieved, and that the proposed algorithms are feasible for realistically sized instances. We thoroughly evaluate our approach based on real-world power demand data from a small electronics factory.

On the readability of leaders in boundary labeling

External labeling deals with annotating features in images with labels that are placed outside of the image and are connected by curves (so-called leaders) to the corresponding features. While external labeling has been extensively investigated from a perspective of automatization, the research on its readability has been neglected. In this article, we present the first formal user study on the readability of leader types in boundary labeling, a special variant of external labeling that considers rectangular image contours. We consider the four most studied leader types (straight, L-shaped, diagonal, and S-shaped) with respect to their performance, that is, whether and how fast a viewer can assign a feature to its label and vice versa. We give a detailed analysis of the results regarding the readability of the four models and discuss their aesthetic qualities based on the users’ preference judgments and interviews. As a consequence of our experiment, we can generally recommend L-shaped leaders as the best compromise between measured task performance and subjective preference ratings, while straight and diagonal leaders received mixed ratings in the two measures. S-shaped leaders are generally not recommended from a practical point of view.