Euler diagrams are an accessible and effective visualisation of data involving simple set-theoretic relationships. Efficient algorithms to quickly compute the abstract regions of an Euler diagram ...upon curve addition and removal have previously been developed (the single marked point approach, SMPA), but a strict set of drawing conventions (called well-formedness conditions) were enforced, meaning that some abstract diagrams are not representable as concrete diagrams. We present a new methodology (the multiple marked point approach, MMPA) enabling online region computation for Euler diagrams under the relaxation of the drawing convention that zones must be connected regions. Furthermore, we indicate how to extend the methods to deal with the relaxation of any of the drawing conventions, with the use of concurrent line segments case being of particular importance. We provide complexity analysis and compare the MMPA with the SMPA. We show that these methods are theoretically no worse than other comparators, whilst our methods apply to any case, and are likely to be faster in practise due to their online nature. The machinery developed for the concurrency case could be of use in Euler diagram drawing techniques (in the context of the Euler Graph), and in computer graphics (e.g. the development of an advanced variation of a winged edge data structure that deals with concurrency). The algorithms are presented for generic curves; specialisations such as utilising fixed geometric shapes for curves may occur in applications which can enhance capabilities for fast computations of the algorithms' input structures. We provide an implementation of these algorithms, utilising ellipses, and provide time-based experimental data for benchmarking purposes.
•Methodology (MMPA) for efficient online region computations for generalised Euler diagrams.•Capable of drawing convention relaxations, including concurrency and disconnected zones.•Complexity analysis demonstrates trade-off with non-generalised Euler diagram method.•Implementation realizing algorithms for specialized case of ellipse based diagrams.•Experimental data provided for benchmarking purposes.
We consider the problem of selecting a minimum size subset of nodes in a network that allows to activate all the nodes of the network. We present a fast and simple algorithm that, in real-life ...networks, produces solutions that outperform the ones obtained by using the best algorithms in the literature. We also investigate the theoretical performances of our algorithm and give proofs of optimality for some classes of graphs. From an experimental perspective, experiments also show that the performance of the algorithms correlates with the modularity of the analyzed network. Moreover, the more the influence among communities is hard to propagate, the less the performances of the algorithms differ. On the other hand, when the network allows some propagation of influence between different communities, the gap between the solutions returned by the proposed algorithm and by the previous algorithms in the literature increases.
Simulation models are becoming an increasingly popular tool for the analysis and optimization of complex real systems in different fields. Finding an optimal system design requires performing a large ...sweep over the parameter space in an organized way. Hence, the model optimization process is extremely demanding from a computational point of view, as it requires careful, time-consuming, complex orchestration of coordinated executions. In this paper, we present the design of SOF (Simulation Optimization and exploration Framework in the cloud), a framework which exploits the computing power of a cloud computational environment in order to carry out effective and efficient simulation optimization strategies. SOF offers several attractive features. Firstly, SOF requires “zero configuration”, as it does not require any additional software installed on the remote node; only standard Apache Hadoop and SSH access are sufficient. Secondly, SOF is transparent to the user, since the user is totally unaware that the system operates on a distributed environment. Finally, SOF is highly customizable and programmable, since it enables the running of different simulation optimization scenarios using diverse programming languages – provided that the hosting platform supports them – and different simulation toolkits, as developed by the modeler. The tool has been fully developed and is available on a public repository11SOF GitHub public repository, https://github.com/isislab-unisa/sof. under the terms of the open source Apache License. It has been tested and validated on several private platforms, such as a dedicated cluster of workstations, as well as on public platforms, including the Hortonworks Data Platform and Amazon Web Services Elastic MapReduce solution.
This paper reports on experiments devoted to explore the role of specific attributes of humanoid virtual agents that may influence elderly users’ perception and attitude, determining their acceptance ...and adoption as assistive devices. In particular, it investigates elderly preference on agents’ gender and the role of the agents’ ability to use voice during the interaction. To this aim two different groups of seniors were involved in the experiments. The first group evaluated talking virtual agents, the second one the same virtual agents, but silenced. The data shows that elderly users, independently from their gender, prefer to interact with female agents, especially when they are able to talk to them, revealing the role played by the voice. Furthermore, it was found a significant effect of the elderly level of experience with technology: when interacting with agents with voice, elderly users with high technological experience were less interested and considered the proposed agents less attractive and appealing, while just the opposite occurred when interacting with silenced agents.
Many modern computing platforms—notably clouds and desktop grids—exhibit dynamic heterogeneity: the availability and computing power of their constituent resources can change unexpectedly and ...dynamically, even in the midst of a computation. We introduce a new quality metric, area, for schedules that execute computations having interdependent constituent chores (jobs, tasks, etc.) on such platforms. Area measures the average number of tasks that a schedule renders eligible for execution at each step of a computation. Even though the definition of area does not mention and properties of host platforms (such as volatility), intuition suggests that rendering tasks eligible at a faster rate will have a benign impact on the performance of volatile platforms—and we report on simulation experiments that support this intuition. We derive the basic properties of the area metric and show how to efficiently craft area-maximizing (A-M) schedules for several classes of significant computations. Simulations that compare A-M scheduling against heuristics ranging from lightweight ones (e.g., FIFO) to computationally intensive ones suggest that A-M schedules complete computations on volatile heterogeneous platforms faster than their competition, by percentages that vary with computation structure and platform behavior—but are often in the double digits.
► Modern platforms are highly volatile and this precludes the use of usual scheduling. ► We introduce a new quality metric, Area, for scheduling modern computing platforms. ► We derive the basic properties of the Area metric. ► We devise Area Maximizing schedules for several well known computation dags. ► We present simulations that show the benefits of our strategies.
Agent-based simulation models are an increasingly popular tool for research and management in many fields. In executing such simulations “speed” is one of the most general and important issues ...because of the size and complexity of simulations. But another important issue is the effectiveness of the solution, which consists of how easily usable and portable the solutions are for the users, i.e. the programmers of the distributed simulation. Our study, then, is aimed at efficient and effective distribute simulations by adopting a framework-level approach, with our design and implementation of a framework, D-Mason, which is a parallel version of the Mason library for writing and running simulations of agent-based simulation models. In particular, besides the efficiency due to workload distribution with small overhead, D-Mason at a framework level proves itself effective since it enables the scientists that use the framework (domain expert but with limited knowledge of distributed programming) only minimally aware of the fact that the simulation is running on a distributed environment. Then, we present tests that compare D-Mason against Mason in order to assess the improved scalability and D-Mason capability to exploit heterogeneous distributed hardware. Our tests also show that several massive simulations that are impossible to execute on Mason (e.g. because of CPU and/or memory requirements) can be easily performed using D-Mason.
PDF
