Abstract
Navigation in virtual environments is important because it allows the exploration of the virtual worlds. This paper presents an objective performance evaluation (based on the Steering Law) of two types of navigation: natural (real walking) vs. not natural (gamepad). Steering Law was the objective performance metric chosen since it captures the relationship between the time to travel a path and the difficulty of that path. In addition to the performance, subjective metrics were also considered, namely the feeling of presence, cybersickness and user satisfaction. The participants had to complete a series of paths with different difficulty indices and the time that a participant took to go through each one was measured. Overall results show that navigation through real walking had better performance, presence, cybersickness, and satisfaction than the gamepad interface.

Abstract
The public transport system integrates a complex ecosystem, composed not only by transport operators and travellers but also by other services such as schools, firms, restaurants, museums, banks, and public establishments. Therefore, by adopting a holistic point of view, we propose a new service approach linking city services and public transport. This approach consists in partnerships that may include discounts, combined packages, reduced prices, deals and marketing campaigns, targeted to each specific audience. In order to develop these partnerships it is important to analyse the services located around the stations and the public transport usage. We use the city of Porto, Portugal, as an illustrative example and we rely on two data sources: Automated Fare Collection system data and business data points. The analysis of both datasets allowed us to determine the level of concentration of city services located around public transport stations and to identify the types of services that tend to agglomerate near the stations. We were also able to analyse the correlation between the number of travel card validations and the number of services located around the stations. Finally we present a case of a service exposure to different demographic segments.

Abstract
The paper describes the practical use of a model checking technique to contribute to the risk analysis of a new paediatric dialysis machine. The formal analysis focuses on one component of the system, namely the table-driven software controller which drives the dialysis cycle and deals with error management. The analysis provided evidence of the verification of risk control measures relating to the software component. The paper describes the productive dialogue between the developers of the device, who had no experience or knowledge of formal methods, and an analyst who had experience of using the formal analysis tools. There were two aspects to this dialogue. The first concerned the translation of safety requirements so that they preserved the meaning of the requirement. The second involved understanding the relationship between the software component under analysis and the broader concern of the system as a whole. The paper focuses on the process, highlighting how the team recognised the advantages over a more traditional testing approach.

Abstract
This paper presents the design of a robust pole placement controller for linear and time invariant systems described by models whose parameters are unknown but, with known bounds, using only plant, input, and output signals. The main objective is to locate the closed-loop poles within a region specified by an interval characteristic polynomial, chosen based on performance specifications and whose stability is guaranteed by Kharitonov’s theorem. The procedure to find a closed interval for each controller parameter is formulated us a nonlinear programming (NLP) problem and switching laws based on the variable structure adaptive pole placement control (VS-APPC) are used to estimate the unknown plant, parameters. This innovative strategy gives a fast, and non-oscillatory transient,, smooth control signal and robustness to large model parameter variations. Moreover, the constraints imposed by the interval controller meet the closed-loop performance requirements. Simulation results are presented for second order nonminimum phase plants, to illustrate the properties of the proposed technique. © 2017 ICIC International.

Abstract
The application of the Internet of Things to manufacturing is the driving force of the new industrial revolution (Industrie 4.0). In fact, most activities in the manufacturing industry can benefit from the data collected in the context of the industrial process. The Industrial Internet of Things (IIoT), whose pillars are the usage of IP communication between the devices and making the devices accessible through the Internet, can maximize the benefits of the information by the integration between multiple data sources, and by the ubiquitous fruition of the information itself. It is common belief that IIoT will transform companies and countries, opening up a new era of economic growth and competitiveness, since it has great potential for improving quality control, sustainable and green practices, supply chain traceability, and maintenance of the user in the loop. Anyway, a number of challenges arise in this context, related for example to adaptability and scalability, real-time communication and QoS, and system deployment and management. A communication middleware can support the IIoT vision by coping with these issues. This talk introduces the IIoT, discusses its benefits and challenges, and presents communication middleware developed in different sub-areas of IIoT (service-oriented industrial informatics [1], smart grids [2], maintenance of industrial machines [3]) that enable the IIoT vision.

Abstract
In this paper we study the energy saving potential of smart scale selection methods when using the Viola and Jones face detector running on smartphone devices. Our motivation is that cloud and edge-cloud multi-user environments may provide enough contextual information to create this type of scale selection algorithms. Given their non-trivial design, we must first inspect its actual benefits, before committing important research resources to actually produce relevant smart scale selection methods. Our experimental methodology in this paper assumes the optimum scenario of a perfect selection of scales for each image (drawn from ground truth annotation, using well-known public datasets), comparing it with the typical multi-scale geometrical progression approach of the Viola Jones algorithm, measuring both classification precision and recall, as well as algorithmic execution time and battery consumption on Android smartphone devices. Results show that if we manage to approximate this perfect scale selection, we obtain very significant energy savings, motivating a strong research investment on this topic.