Abstract
The multitude of Wireless Sensor Networks (WSNs) environments, being typically resource-constrained, clearly benefit from properties such as adaptiveness and energy-awareness, in particular, in presence of demanding data gathering applications. This paper proposes a self-adaptive, energy-aware sensing scheme for WSNs (e-LiteSense), which aims at self-adjusting the data gathering process to each specific WSN context, capturing accurately the behaviour of physical parameters of interest yet reducing the sensing overhead. The adaptive scheme relies on a set of low-complexity rules capable of auto-regulate the sensing frequency according to the parameters variability and energy levels. The proof-of-concept resorts to real-world datasets to provide evidence of e-LiteSense ability to optimise the data gathering process according to energy levels, improving the trade-off between accuracy and WSN lifetime.

Abstract
As a consequence of the technological advances and the widespread use of mobile devices to access information and communication in the last decades, mobile learning has become a spontaneous learning model, providing a more flexible and collaborative technology-based learning. Thus, mobile technologies can create new opportunities for enhancing the pupils' learning experiences. This chapter presents the development of a game to assist teaching and learning, aiming to help students acquire knowledge in the field of geometry. The game was intended to develop the following competences in primary school learners (8-10 years): a better visualization of geometric objects on a plane and in space; understanding of the properties of geometric solids; and familiarization with the vocabulary of geometry. Findings show that by using the game, students have improved around 35% the hits of correct responses to the classification and differentiation between edge, vertex, and face in 3D solids.

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. © 2018, IGI Global.

Abstract
Technological evolution impacts the research and development of new solutions, as well as consumers’ expectations and behaviors. With the advent of the new millennium, collaboration systems and technologies were introduced to support ordinary cooperative work and inter-dependent, socially and culturally mediated practices as integral units of everyday life settings. Nevertheless, existing classification systems are limited in scope to analyze technological developments and capture the intellectual structure of a field, understood as an abstraction of the collective knowledge of its researchers and their socially mediated activities. Ten years after the introduction of Mittleman et al.’s taxonomy, we build upon earlier work and adopt this classification scheme to provide a descriptive, taxonomy-based analysis of four distinct venues focused on collaborative computing research: ACM CSCW, ACM GROUP, ECSCW, and CRIWG. The proposal consists of achieving evidence on technical attributes and impacts towards characterizing the evolution of socio-technical systems via (and for) taxonomic modeling. This study can also constitute an important step towards the emergence of new, potentially more valid and robust evaluation studies combining Grounded Theory with alternative methods and techniques.

Abstract
We present Dolphin, an extensible programming language for autonomous vehicle networks. A Dolphin program expresses an orchestrated execution of tasks defined compositionally for multiple vehicles. Building upon the base case of elementary one-vehicle tasks, the built-in operators include support for composing tasks in several forms, for instance according to concurrent, sequential, or event-based task flow. The language is implemented as a Groovy DSL, facilitating extension and integration with external software packages, in particular robotic toolkits. The paper describes the Dolphin language, its integration with an open-source toolchain for autonomous vehicles, and results from field tests using unmanned underwater vehicles (UUVs) and unmanned aerial vehicles (UAVs).

Abstract