Introducing Interactivity in Disaster Recovery Simulations

Crowd simulations are widely used to study and predict the human behavior in disaster scenarios. In this paper, we introduce real-time user interactivity into the simulation process of virtual environments (e.g., buildings with rooms and doors between them). We develop a new tactical path-planning model that translates the interactive virtual environment into an abstract graph in order to calculate the shortest paths in real time. Our extension of the Vadere simulation framework with interactivity features allows the users to better understand the actual problem situations and to analyze them. Our experiments demonstrate the effectiveness of the approach by simulating the evacuation of students in groups and as individuals from the Schloss Muenster (the administrative building of the University of Muenster) in Germany. During simulation run time, the user can interact with the virtual environment spontaneously (e.g., by opening and closing doors) while our model recalculates the shortest paths for agents in real time.

Scalable robust graph and feature extraction for arbitrary vessel networks in large volumetric datasets

Background Recent advances in 3D imaging technologies provide novel insights to researchers and reveal finer and more detail of examined specimen, especially in the biomedical domain, but also impose huge challenges regarding scalability for automated analysis algorithms due to rapidly increasing dataset sizes. In particular, existing research towards automated vessel network analysis does not always consider memory requirements of proposed algorithms and often generates a large number of spurious branches for structures consisting of many voxels. Additionally, very often these algorithms have further restrictions such as the limitation to tree topologies or relying on the properties of specific image modalities. Results We propose a scalable iterative pipeline (in terms of computational cost, required main memory and robustness) that extracts an annotated abstract graph representation from the foreground segmentation of vessel networks of arbitrary topology and vessel shape. The novel iterative refinement process is controlled by a single, dimensionless, a-priori determinable parameter. Conclusions We are able to, for the first time, analyze the topology of volumes of roughly 1 TB on commodity hardware, using the proposed pipeline. We demonstrate improved robustness in terms of surface noise, vessel shape deviation and anisotropic resolution compared to the state of the art. An implementation of the presented pipeline is publicly available in version 5.1 of the volume rendering and processing engine Voreen.

Entity Alignment for Cross-lingual Knowledge Graph with Graph Convolutional Networks

Graph convolutional network (GCN) is a promising approach that has recently been used to resolve knowledge graph alignment. In this paper, we propose a new method to entity alignment for cross-lingual knowledge graph. In the method, we design a scheme of attribute embedding for GCN training. Furthermore, GCN model utilizes the attribute embedding and structure embedding to abstract graph features simultaneously. Our preliminary experiments show that the proposed method outperforms the state-of-the-art GCN-based method.

An Interdisciplinary Model of Context Morphology

Using an abstract graph model we describe a hypothetical transformation of a literary entity through the active connections in the graph. First, we weakly define a set of transformations (“morphology”) over a particular entity as a series of the recent activities distinguishing them into categories according to their effect on the entity. Second, to our conjecture, the emerging paths of forms are slowly abandoning the original “birth context”, shaping a decreased, cleaned set of entities, to replace the gap with entities derived from the dynamic set of “recipient context”.

Research on SketchUp Application in Graphing of Civil Engineering

This paper introduces to the application of the software---SketchUp in teaching process, which will make the abstract graph visualize, inspire students’ interest and help them to have a better grasp of civil engineering structure. We use SketchUp to create models, assist the teaching of civil engineering Graphing and recognition, improve students’ space imagination and cultivate their creativity.

RIGIDLY ACHIRAL HYPERBOLIC SPATIAL GRAPHS IN 3-MANIFOLDS

This paper provides a method for realizing an involution on an abstract graph, which does not restrict to an orientation-preserving automorphism on any cycle, by a rigidly achiral hyperbolic spatial embedding into the double of a compact connected orientable 3-manifold with non-empty aspherical boundary. As an application, we show that these hyperbolic spatial graphs are divided into two infinite families consisting of those which are homologically peripheral and those which are not.