Abstract
There exist many dataflow applications with timing constraints that require real-time guarantees on safe execution without violating their deadlines. Extraction of timing parameters (offsets, deadlines, periods) from these applications enables the use of real-time scheduling and analysis techniques, and provides guarantees on satisfying timing constraints. However, existing extraction techniques require the transformation of the dataflow application from highly expressive dataflow computational models, for example, Synchronous Dataflow (SDF) and Cyclo-Static Dataflow (CSDF) to Homogeneous Synchronous Dataflow (HSDF). This transformation can lead to an exponential increase in the size of the application graph that significantly increases the runtime of the analysis. In this article, we address this problem by proposing an offline heuristic algorithm called slack-based merging. The algorithm is a novel graph reduction technique that helps in speeding up the process of timing parameter extraction and finding a feasible real-time schedule, thereby reducing the overall design time of the real-time system. It uses two main concepts: (a) the difference between the worst-case execution time of the SDF graph's firings and its timing constraints (slack) to merge firings together and generate a reducedsize HSDF graph, and (b) the novel concept of merging called safe merge, which is a merge operation that we formally prove cannot cause a live HSDF graph to deadlock. The results show that the reduced graph (1) respects the throughput and latency constraints of the original application graph and (2) typically speeds up the process of extracting timing parameters and finding a feasible real-time schedule for real-time dataflow applications. They also show that when the throughput constraint is relaxed with respect to the maximal throughput of the graph, the merging algorithm is able to achieve a larger reduction in graph size, which in turn results in a larger speedup of the real-time scheduling algorithms.

Abstract

Abstract
In this paper the synthesis of a rotational speed closed-loop control system based on a fractional-order proportional-integral (FOPI) controller is presented. In particular, it is proposed the use of the SCoMR-FOPI procedure as the controller tuning method for an unmanned aerial vehicle's propulsion unit. In this framework, both the Hermite-Biehler and Pontryagin theorems are used to predefine a stability region for the controller. Several simulations were conducted in order to try to answer the questions - is the FOPI controller good enough to be an alternative to more complex FOPID controllers? In what circumstances can it be advantageous over the ubiquitous PID? How robust this fractional-order controller is regarding the parametric uncertainty of considered propulsion unit model?

Abstract
This work further clarifies how the MULTIS architecture can be used for integration of virtual worlds in learning management system (LMS) for organizational management of e-learning activities, as an extension to a previous work published in the proceedings of VEAI 2016. Current LMSs provide minimal support for educational use in an organizational context, and other integration efforts assume that educators are inside the virtual world, accessing the LMS as an external service. Our approach enables educators to set up and manage virtual world activities from within the traditional LMS Web interface as an integral part of the overall educational activities of a course. The MULTIS architecture foresees several alternative communication channels between LMS and virtual worlds, including the spooling of automated clients or "bots" and the flexibility to inject code if necessary and possible. In this work, we detail the application of this architecture and its approach in several sample scenarios, based on previous analysis of integration requirements. It is the result of a joint effort by academic and corporate teams, implemented and tested in the Formare LMS for OpenSimulator and Second Life Grid virtual world platforms.

Abstract
Robotic technologies are continuously transforming the domestic and the industrial environments. Recently the Robotic Operating System (ROS), has been widely adopted both by industry and academia, becoming one of the most popular middleware frameworks for developing robot applications. Guaranteeing the correct behaviour of robotic systems is, however, challenging due to their potential for parameterization and heterogeneity. Although different approaches exist, focusing on concrete domain spaces for specific scenarios, no general approach to reason about ROS systems has yet arisen. This paper proposes an approach to model and verify ROS systems using real time properties, focusing on one of the main features of ROS, the communication between nodes. It takes low-level parameters into account, such as queue sizes and timeouts, and uses timed automata as the modelling language. The robot Kobuki is used as a complex case study, over which properties are automatically verified using the UPPAAL model checker, enabling the identification of problematic parameter combinations.

Abstract
The safety-critical real-time embedded domain increasingly demands the use of parallel architectures to fulfill performance requirements. Such architectures require the use of parallel programming models to exploit the underlying parallelism. This paper evaluates the applicability of using OpenMP, a widespread parallel programming model, with Ada, a language widely used in the safety-critical domain. Concretely, this paper shows that applying the OpenMP tasking model to exploit fine-grained parallelism within Ada tasks does not impact on programs safeness and correctness, which is vital in the environments where Ada is mostly used. Moreover, we compare the OpenMP tasking model with the proposal of Ada extensions to define parallel blocks, parallel loops and reductions. Overall, we conclude that the OpenMP tasking model can be safely used in such environments, being a promising approach to exploit fine-grain parallelism in Ada tasks, and we identify the issues which still need to be further researched.