Abstract
In a growing number of domains, the provisioning of end-to-end services to the users depends on the proper interoperation of multiple products, forming a new distributed system. To ensure interoperability and the integrity of this new distributed system, it is important to conduct integration tests that verify not only the interactions with the environment but also the interactions between the system components. Integration test scenarios for that purpose may be conveniently specified by means of UML sequence diagrams, possibly allowing multiple execution paths. The automation of such integration tests requires that test components are also distributed, with a local tester deployed close to each system component, and a central tester coordinating the local testers. In such a test architecture, it is important to minimize the communication overhead during test execution. Hence, in this paper we investigate conditions upon which conformance errors can be detected locally (local observability) and test inputs can be decided locally (local controllability) by the local testers, without the need for exchanging coordination messages between the test components during test execution. The conditions are specified in a formal specification language that allows executing and validating the specification. Examples of test scenarios are also presented, illustrating local observability and controllability problems associated with optional messages without corresponding acknowledgment messages, races and non-local choices. © 2017 IEEE.

Abstract
This article presents four state-space models for high pressure gas pipelines, departing from a system of nonlinear partial differential equations. The models were derived taking advantage of an electrical analogy and are very accurate and simple, therefore suitable for network simulation and analysis. The models' simulation is compared with the data obtained with Simone (R), a commercial simulator of gas transport and distribution networks used by many european companies, and exhibit similar accuracy.

Abstract
There is currently a significant interest in consumer electronics in applications and devices that monitor and improve the user's well-being. This is one of the key aspects in the development of ambient intelligence systems. Nonetheless, existing approaches are generally based on physiological sensors, which are intrusive and cannot be realistically used, especially in ambient intelligence in which the transparency, pervasiveness and sensitivity are paramount. We put forward a new approach to the problem in which user behavioral cues are used as an input to assess inner state. This innovative approach has been validated by research in the last years and has characteristics that may enable the development of true unobtrusive, pervasive and sensitive ambient intelligent systems. © 2017 by SCITEPRESS - Science and Technology Publications, Lda.

Abstract
We propose and apply two methods to estimate pupil plane phase discontinuities for two realistic scenarios on the very large telescope (VLT) and Keck. The methods use both phase diversity and a form of image sharpening. For the case of VLT, we simulate the "low wind effect" (LWE) that is responsible for focal plane errors in the spectro-polarimetric high contrast exoplanet research (SPHERE) system in low wind and good seeing conditions. We successfully estimate the simulated LWE using both methods and show that they are complimentary to one another. We also demonstrate that single image phase diversity (also known as phase retrieval with diversity) is also capable of estimating the simulated LWE when using the natural defocus on the SPHERE/differential tip tilt sensor (DTTS) imager. We demonstrate that phase diversity can estimate the LWE to within 30-nm root mean square wavefront error (RMS WFE), which is within the allowable tolerances to achieve a target SPHERE contrast of 10-6. Finally, we simulate 153-nm RMS of piston errors on the mirror segments of Keck and produce NIRC2 images subject to these effects. We show that a single, diverse image with 1.5 waves (peak-to-valley) of focus can be used to estimate this error to within 29-nm RMS WFE, and a perfect correction of our estimation would increase the Strehl ratio of an NIRC2 image by 12%.

Abstract
This paper presents a robust optimization problem of the flexible bidirectional power management of a smart distribution network and harmonic compensation of nonlinear loads using electric vehicles (EVs) equipped with bidirectional chargers. The base deterministic model of the proposed problem is as mixed-integer nonlinear programming (MINLP), having the objective function to minimize the economic and technical indices subject to harmonic load flow equations, EVs constraints, system operation and harmonic indices limits. This model is converted to a mixed-integer linear programming (MILP) model in the next step. In the proposed MILP model, the active, reactive and apparent loads, electrical energy, reactive power and harmonic current prices, as well as EVs characteristics, are considered uncertain parameters. Accordingly, two alternative robust optimization approaches have been implemented for the conditions of having both the probability distribution function or the bounded uncertainty in the proposed MILP problem model. The proposed model is tested on distribution networks to demonstrate its efficiency and performance. The results show that the MINLP model can be substituted by the proposed high-speed MILP model. In addition, the capacity of the injecting power of EVs is reduced in the worst case scenario with respect to the scenario that is used in the deterministic model, while the consumed power of loads and EVs and energy price increases in this scenario. Finally, the payment of EV owners is reduced by considering EVs power and harmonic control.

Abstract
Networking and collaboration, at different levels and through differentiated mechanisms, have become increasingly relevant and popular as an effective means for delivering public policy over the past two decades. The variety of forms of collaboration that emerge in educational scenarios makes it hard to reach general conclusions about the effectiveness of collaboration in general and of inter-institutional networks in particular. The university environment is particularly challenging in this respect as typically different agendas for collaboration and competition co-exist and are often promoted by very same entities. Although no ‘one-fits-all’ model exists for the establishment of a network of universities, the prime result of the research reported in this paper is that the concept of such a network is a most promising instrument for delivering specific services within the high education universe. In this context, the paper discusses the potential of these networks for the design of educational programmes for the GCIO (Government Chief Information Officer) function and proposes a set of guidelines to successfully establish such networks. © 2017, IFIP International Federation for Information Processing.