Displaying a boundary in graphic and symbolic “wait” displays: Duration estimates and users’ preferences

Two experiments assessed the effect of displaying a boundary on duration estimates and preference ratings for dynamic displays that were shown while users waited for the system's response. Displays were either symbolic (changing numbers) or graphic (increasing rectangles) and could contain a boundary that indicated when the interval was expected to be over. Duration estimates were similar for symbolic and graphic displays and for displays with and without a boundary. However, when the displays were encountered successively, participants assessed the graphic displays as having shorter durations than the symbolic displays. Faster rates of change in both types of displays led to increased duration estimates. Although displaying a boundary did not affect duration estimates, participants preferred displays in which a boundary was shown and preferred the graphic displays over the symbolic displays. Hence, bounded graphic displays are recommended as “wait” displays for computerized applications.     

Job-shop scheduling in a body shop

We study a generalized job-shop problem called the body shop scheduling problem (BSSP). This problem arises from the industrial application of welding in a car body production line, where possible collisions between industrial robots have to be taken into account. BSSP corresponds to a job-shop problem where the operations of a job have to follow alternating routes on the machines, certain operations of different jobs are not allowed to be processed at the same time and after processing an operation of a certain job a machine might be unavailable for a given time for operations of other jobs. As main results we will show that for three jobs and four machines the special case where only one machine is used by more than one job is already $\mathcal NP $ -hard. This also implies that the single machine scheduling problem that asks for a makespan minimal schedule of three chains of operations with delays between the operations of a chain is $\mathcal NP $ -hard. On the positive side, we present a polynomial algorithm for the two job case and a pseudo-polynomial algorithm together with an FPTAS  for an arbitrary but constant number of jobs. Hence for a constant number of jobs we fully settle the complexity status of the problem.     

Nonparametric Bayesian Image Segmentation

Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model for histogram clustering which automatically determines the number of segments when spatial smoothness constraints on the class assignments are enforced by a Markov Random Field. A Dirichlet process prior controls the level of resolution which corresponds to the number of clusters in data with a unique cluster structure. The resulting posterior is efficiently sampled by a variant of a conjugate-case sampling algorithm for Dirichlet process mixture models. Experimental results are provided for real-world gray value images, synthetic aperture radar images and magnetic resonance imaging data.     

SEMPA – Ein Ansatz des Semantischen Prozessmanagements zur Planung von Prozessmodellen

Currently process modeling is mostly done manually. Therefore, the initial design of process models as well as changes to process models which are frequently necessary to react to new market developments or new regulations are time-consuming tasks. In this paper we introduce SEMPA, an approach for the partly automatic planning of process models. Using ontologies to semantically describe actions – as envisioned in Semantic Business Process Management –, a process model for a specified problem setting can be created automatically. In comparison to existing planning algorithms our approach creates process models including control structures and is able to cope with complex and numerical input and output parameters of actions. The prototypical implementation as well as an example taken from the financial services domain illustrate the practical benefit of our approach.     

Effect of Berezinskii-Kosterlitz-Thouless vortex fluctuations on the nuclear spin relaxation rate

In this work we examine the influence of the diffusive motion of vortices in highly anisotropic high-T_c superconductors near the Berezinskii-Kosterlitz-Thouless (BKT) transition temperature T _bkt on the spin-lattice relaxation rate T ₁ ^–1 .We find a jump in T ₁ ^–1 at the temperature T _bkt .     

The shadow approach: An orphan detection protocol for mobile agents

Orphan detection in distributed systems is a well-researched field for which many solutions exist. These solutions exploit well defined parent-child relationships given in distributed systems. But they are not applicable in mobile agent systems, since no similar natural relationship between agents exist. Thus new protocols have to be developed. In this paper one such protocol for controlling mobile mobile agents and for orphan detection is presented. The shadow approach presented in this paper uses the idea of a placeholder (shadow) which is assigned by the agent system to each new agent. This defines an artificial relationship between agents and shadow. The shadow records the location of all dependent agents. Removing the root shadow implies that all dependent agents are declared orphan and are eventually be terminated. We introduce agent proxies that create a path from shadow to every agent. In an extension of the basic protocol we additionally allow the shadow to be mobile.The shadow approach can be used for termination of groups of agents even if the exact location of each single agent is not known.     

Spatially Varying Mixtures Incorporating Line Processes for Image Segmentation

Spatially varying mixture models are characterized by the dependence of their mixing proportions on location (contextual mixing proportions) and they have been widely used in image segmentation. In this work, Gauss-Markov random field (MRF) priors are employed along with spatially varying mixture models to ensure the preservation of region boundaries in image segmentation. To preserve region boundaries, two distinct models for a line process involved in the MRF prior are proposed. The first model considers edge preservation by imposing a Bernoulli prior on the normally distributed local differences of the contextual mixing proportions. It is a discrete line process model whose parameters are computed by variational inference. The second model imposes Gamma prior on the Student’s-t distributed local differences of the contextual mixing proportions. It is a continuous line process whose parameters are also automatically estimated by the Expectation-Maximization (EM) algorithm. The proposed models are numerically evaluated and two important issues in image segmentation by mixture models are also investigated and discussed: the constraints to be imposed on the contextual mixing proportions to be probability vectors and the MRF optimization strategy in the frameworks of the standard and variational EM algorithm.