Abstract

Abstract
We present a procedure for splitting processes in a process algebra with multiactions and data (the untimed subset of the specification language mCRL2). This splitting procedure cuts a process into two processes along a set of actions A: Roughly, one of these processes contains no actions from A, while the other process contains only actions from A. We state and prove a theorem asserting that the parallel composition of these two processes is provably equal from a set of axioms (sound and complete with respect to strong bisimilarity) to the original process under some appropriate notion of synchronization. We apply our splitting procedure to the process algebraic semantics of the coordination language Reo: Using this procedure and its related theorem, we formally establish the soundness of splitting Reo connectors along the boundaries of their (a)synchronous regions in implementations of Reo. Such splitting can significantly improve the performance of connectors as shown elsewhere.

Abstract
The growing dependence of our society on increasingly complex software systems makes software testing ever more important and challenging. In many domains, several independent systems, forming a distributed and heterogeneous system of systems, are involved in the provisioning of end-to-end services to users. However, existing test automation techniques provide little tool support for properly testing such systems. Hence, we propose an approach and toolset architecture for automating the testing of end-to-end services in distributed and heterogeneous systems, comprising a visual modeling environment, a test execution engine, and a distributed test monitoring and control infrastructure. The only manual activity required is the description of the participants and behavior of the services under test with UML sequence diagrams, which are translated to extended Petri nets for efficient test input generation and test output checking at runtime. A real world example from the Ambient Assisted Living domain illustrates the approach.

Abstract
Machine learning processes consist in collecting data, obtaining a model and applying it to a given task. Given a new task, the standard approach is to restart the learning process and obtain a new model. However, previous learning experience can be exploited to assist the new learning process. The two most studied approaches for this are meta-learning and transfer learning. Metalearning can be used for selecting the predictive model to use on a new dataset. Transfer learning allows the reuse of knowledge from previous tasks. However, when multiple heterogeneous tasks are available as potential sources for transfer, the question is which one to use. One approach to address this problem is metalearning. In this paper we investigate the feasibility of this approach. We propose a method to transfer weights from a source trained neural network to initialize a network that models a potentially very different target dataset. Our experiments with 14 datasets indicate that this method enables faster convergence without significant difference in accuracy provided that the source task is adequately chosen. This means that there is potential for applying metalearning to support transfer between heterogeneous datasets.

Abstract
Eyesight is an important sense that helps humans to avoid dangers and navigate in our world. Blind people usually have enhanced accuracy and sensibility of their other natural senses in order to sense their surroundings. But sometimes this is not enough because the human senses can be affected by external sources of noise or disease. That is why technology has been used to develop many assistive tools. Artifacts like white canes or braille compasses help blind people moving around in the environment. In this article, the use of a system that detects and recognize nearby objects or obstacles is proposed, giving an audible feedback to the user. It is designed as a wireless system in order to be comfortable to be carried by the user. The system helps visual impaired people to move around in indoor or outdoor scenarios. The goals of this blind guide system is to detect obstacles that white canes or dogs cannot, extending its detection range. © 2016 ACM.

Abstract
The emergence of complex supply chains is one of the most important consequences of globalization. The management of these supply chains requires increased efforts by organizations that, on one hand, are increasingly pressured by customers in terms of service levels, on the other hand, must manage their suppliers from various locations and with different local requirements. In this context, an appropriate management of information flows is needed to create the adequate visibility level for managing supply chain risk. This chapter presents an overview on the concepts of risk management, visibility and information management in supply chains. This study proposes a conceptual framework for the selection of risk mitigation strategies in the supply chain and characterizes the external and internal information flows decision makers need to implement two categories of risk mitigation strategies: redundancy and flexibility. © 2017, IGI Global.