Abstract
Technology plays a key role in daily life of people with special needs, being a mean of integration or even communication with society. By built up experience, we find that support tools play a crucial part in empowerment of persons with special needs and small advances may represent shifts and opportunities. The diversity of solutions and the need for dedicated hardware to each feature represents a barrier to its use, compromising the success of the solutions against, among others, problems of usability and scale. This paper aims to explore the concept of inclusive collaboration to enhance the mutual interaction and assistance. The proposed approach combines and generalizes the usage of human computation in a collaborative environment with assistive technologies creating redundancy and complementarity in the solutions provided, contributing to enhance the quality of life of people with special needs and the elderly. The CanIHelp platform is an embodiment of the concept as a result from an orchestrated model using mechanisms of collective intelligence through social inclusion initiatives. The platform features up for integrating assistive technologies, collaborative tools and multiple multimedia communication channels, accessible through multimodal interfaces for universal access. A discussion of the impacts of fostering collaboration and broadening from the research concepts to the societal impacts is presented. As final remarks a set of future research challenges and guidelines are identified.

Abstract
Manufacturing environments require a real-time adaptation and optimization method to dynamically and intelligently maintain the current scheduling plan feasible. This way, the organization keeps clients satisfied and achieves its objectives (costs are minimized and profits maximized). This paper proposes an optimization approach - Selection Constructive based Hyper-heuristic for Dynamic Scheduling - to deal with these dynamic events, with the main goal of maintaining the current scheduling plan feasible and robust as possible. The development of this dynamic adaptation approach is inspired on evolutionary computation and hyper-heuristics. Our empirical results show that a selection constructive hyper-heuristic could be advantageous on solving dynamic adaptation optimization problems. © 2015 AISTI.

Abstract
The article will present the development of the tool FEUPAutom, used at the Faculty of Engineering of the University of Porto (FEUP) in the automation engineering Technological & Scientific area. In FEUP, the pressure to deliver well trained engineers is steadily high in the last two decades, thus producing a well-known situation of massification in Higher Education Institutions, namely in engineering degrees. In the school year of 2013/14, the course where the tool was used had about 270 students, despite quite low retention rates. The article also includes a brief characterization of the engineering program, course and expected outcomes in full alignment with the ideas promoted by the EUR-ACE referential for the accreditation of engineering programs and also in strong consonance with the ideas defended by the Bologna process. The course includes lab work and a part of those uses Problem Based Learning (PBL) methodology. In the last decade, the professors of the mentioned course have tried to limit the usage of real world industrial equipments because of budget concerns, always without hindering the learning process. Adequate simulation tools were sought on the market but not found, mainly because the needs of a full blown engineer are frequently not the same as those of an early engineering student. At that point, the decision was made to develop an in-house tool, adequate for students. Industrial-grade equipment was not totally set aside, only reserved for latter stages and the actual usage strategy allowed the number of equipments to be halved. The article will go on briefly describing the FEUPAutom tool and new strategies available for lab classes and PBL. As control groups would be unethical, students' quiz data from the two last editions of the course are used to evaluate learning (self-assessed). Grading strategy and coordination with the university's LMS is also addressed. Final grades of the course and satisfaction are also discussed. The students' assessment is that the FEUPAutom tool is very useful for the learning process and easier to use than the available industrial counterpart. Continuous improvement efforts have tried to push students to adequate PBL work only possible with the tool, with some results hinting deep learning in the technical area at stake. Some final thoughts, lessons learned and future work are also present in the article.

Abstract
Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Abstract
This paper describes an exploration towards the transposition of service science principles into design guidelines. This aims at capturing value co-creation service interactions embedding customer experience in service design and delivery activities. The new Socio-Technical Systems Engineering (STSE) process is proposed to guide improved design, and it is exemplified with a new real time service that provides integrated information for trip planning in a city. The STSE process supports a high level visual modelling approach assisted by model execution and simulation tools. From a service engineering perspective, the outcomes of this process are artefacts that automatically support consistency among design steps and effective integration of customer experience and stakeholder requirements through iterative cycles related to service design. The application of the STSE process in the design of an exploratory case study of a real time information and travel planning service is validated through simulation using an executable representation of requirements. It can be executed over more complex transport service offerings, with different resource allocation algorithms, or different public transport planning services over a sample of real users requesting information. Results of such a simulation are beneficial for the users, for the service providers, and for the authorities managing public transport in city or metropolitan areas.

Abstract
Over 250 million people, worldwide, are affected by chronic lung conditions such as Asthma and COPD. These can cause breathlessness, a harsh decrease in quality of life and, if left undetected or not properly managed, even death. In this paper, we approached part of the lines of development suggested upon earlier work. This concerned the development of a system design for a smartphone lung function classification app, which would only use recordings from the built-in microphone. A more systematic method to evaluate the relevant combinations of methods was devised and an additional set of 44 recordings was used for testing purposes. The previous 101 were kept for training the models. The results enabled to further reduce the signal processing pipeline leading to the use of 6 envelopes, per recording, half of the previous amount. An analysis of the classification performances is provided for both previous tasks: differentiation into Normal from Abnormal lung function, and between multiple lung function patterns. The results from this project encourage further development of the system.