Abstract
Testing is one of the most important activities to ensure the quality of a software system. This paper proposes and discusses the TSL (Test Specification Language) that adopts a model-based testing approach for both human-readable and computer-executable specifications of test cases. TSL is strongly inspired on the grammar, nomenclature and writing style as defined by the RSLingo RSL, which is a rigorous requirements specification language. Both RSL and TSL are controlled natural languages that share common concepts such as data entities, use cases and state machines. However, by applying black-box functional testing design techniques, TSL includes and supports four complementary testing strategies, namely: domain analysis testing; use case tests; state machine testing; and acceptance criteria. This paper focuses on the first three testing strategies of TSL. Finally, a simple but effective case study illustrates the overall approach and supports the discussion.

Abstract
Electric vehicle (EV) charging infrastructure rollout iswell underway in several power systems, namelyNorthAmerica, Japan, Europe, and China. In order to support EVcharging infrastructures design and operation, little attempt has been made to develop indicator-based methods characterising such networks across different regions. This study defines an assessment methodology, composed by eight indicators, allowing a comparison among EV public charging infrastructures. The proposed indicators capture the following: energy demand from EVs, energy use intensity, charger's intensity distribution, the use time ratios, energy use ratios, the nearest neighbour distance between chargers and availability, the total service ratio, and the carbon intensity as an environmental impact indicator. We apply the methodology to a dataset from ElaadNL, a reference smart charging provider in The Netherlands, using open source geographic information system (GIS) and R software. The dataset reveals higher energy intensity in six urban areas and that 50% of energy supplied comes from 19.6% of chargers. Correlations of spatial density are strong and nearest neighbouring distances range from 1101 to 9462 m. Use time and energy use ratios are 11.21% and 3.56%. The average carbon intensity is 4.44 gCO2eq/MJ. Finally, the indicators are used to assess the impact of relevant public policies on the EV charging infrastructure use and roll-out.

Abstract
A multi-loop control strategy based on a six-order dynamic model of the modular multilevel converter (MMC) is presented in this paper for the high-voltage direct current (HVDC) applications. For the initial analysis of the operation of MMC, a capability curve based on active and reactive power of the MMC is achieved through a part of the six order dynamic equations. According to the MMC's control aims, the first loop known as the outer loop is designed based on passivity control theory to force the MMC state variables to follow their reference values. As the second loop with the use of sliding mode control, the central loop should provide appropriate performance for the MMC under variations of the MMC's parameters. Another main part of the proposed controller is defined for the third inner loop to accomplish the accurate generation of reference values. Also, for a deeper analysis of the MMC's dc link voltage stability, two phase diagrams of the dc-link voltage are assessed. Matlab/Simulink environment is used to thoroughly validate the ability of the proposed control technique for control of the MMC in HVDC application under both load and MMC's parameters changes.

Abstract
In this paper, a new decomposing strategy is proposed to solve the power flow problem in the large-scale multienergy carrier (MEC) systems, including gas, electrical, and heating subnetworks. This strategy has been equipped with a novel noniterative method named holomorphic embedding (HE) to solve the energy flow of the electrical subnetwork. Moreover, it benefits from the less-computational graph method for solving the energy flows of the heating subnetwork. The HE method unlike initial-guess iterative methods guarantees to find the power flow solution, if there is a solution. In addition, it finds only the operational power flow solution without concern about the convergence of the solution. In the proposed strategy, the decomposing method decouples various energy flows of subnetworks without losing the major benefits of the simultaneous analysis of the subnetworks and losing accuracy. Moreover, the proposed decomposing strategy has more reliability and faster computation time than the Newton-Raphson technique. In order to demonstrate the efficiency and superiority of the proposed decomposing strategy on solving large-scale MEC systems, the strategy is tested on three large-scale case studies.

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.