GiViP: A Visual Profiler for Distributed Graph Processing Systems

Analyzing large-scale graphs provides valuable insights in different application scenarios. While many graph processing systems working on top of distributed infrastructures have been proposed to deal with big graphs, the tasks of profiling and debugging their massive computations remain time consuming and error-prone. This paper presents GiViP, a visual profiler for distributed graph processing systems based on a Pregel-like computation model. GiViP captures the huge amount of messages exchanged throughout a computation and provides an interactive user interface for the visual analysis of the collected data. We show how to take advantage of GiViP to detect anomalies related to the computation and to the infrastructure, such as slow computing units and anomalous message patterns.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

VizKid: A Behavior Capture and Visualization System of Adult-Child Interaction

Abstract. We present VizKid, a capture and visualization system for supporting the analysis of social interactions between two individuals. The development of this system is motivated by the need for objective measures of social approach and avoidance behaviors of children with autism. VizKid visualizes the position and orientation of an adult and a child as they interact with one another over an extended period of time. We report on the design of VizKid and its rationale

Mechanical stretching and chemical pyloroplasty to prevent delayed gastric emptying after esophageal cancer resection-a meta-analysis and review of the literature

Background Delayed gastric emptying (DGE) occurs in up to 40% of patients after esophageal resection and prolongs recovery and hospital stay. Surgically pyloroplasty does not effectively prevent DGE. Recently published methods include injection of botulinum toxin (botox) in the pylorus and mechanical interventions as preoperative endoscopic dilatation of the pylorus. The aim of this study was to investigate the efficacy of those methods with respect to the newly published Consensus definition of DGE. Methods A systematic literature search using CENTRAL, Medline, and Web of Science was performed to identify studies that described pre- or intraoperative botox injection or mechanical stretching methods of the pylorus in patients undergoing esophageal resection. Frequency of DGE, anastomotic leakage rates, and length of hospital stay were analyzed. Outcome data were pooled as odd's ratio (OR) or mean difference using a random-effects model. Risk of bias was assessed using the Robins-I tool for non-randomized trials. Results Out of 391 articles seven retrospective studies described patients that underwent preventive botulinum toxin injection and four studies described preventive mechanical stretching of the pylorus. DGE was not affected by injection of botox (OR 0.87, 95% confidence interval [CI] 0.37-2.03, P = 0.75), whereas mechanical stretching resulted in significant reduction of DGE (OR 0.26, 95% CI 0.14-0.5, P < 0.0001). Conclusion Mechanical stretching of the pylorus, but not injection of botox reduces DGE after esophageal cancer resection. A newly developed consensus definition should be used before the conduction of a large-scale randomized-controlled trial

Separation efficiency and particle size distribution in relation to manure type and storage conditions

Timeslices are often used to draw and visualize dynamic graphs. While timeslices are a natural way to think about dynamic graphs, they are routinely imposed on continuous data. Often, it is unclear how many timeslices to select: too few timeslices can miss temporal features such as causality or even graph structure while too many timeslices slows the drawing computation. We present a model for dynamic graphs which is not based on timeslices, and a dynamic graph drawing algorithm, DynNoSlice, to draw graphs in this model. In our evaluation, we demonstrate the advantages of this approach over timeslicing on continuous data sets.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Temporal Multivariate Networks

Networks that evolve over time, or dynamic graphs, have been of interest to the areas of information visualization and graph drawing for many years. Typically, its the structure of the dynamic graph that evolves as vertices and edges are added or removed from the graph. In a multivariate scenario, however, attributes play an important role and can also evolve over time. In this chapter, we characterize and survey methods for visualizing temporal multivariate networks. We also explore future applications and directions for this emerging area in the fields of information visualization and graph drawing