Abstract
Serious games is a field of research that has evolved substantially with valuable contributions to many application domains and areas. Patients often consider traditional rehabilitation approaches to be repetitive and boring, making it difficult for them to maintain their ongoing interest and to assure the completion of the treatment program. This chapter reviews serious games and the natural and multimodal user interfaces for the health rehabilitation domain. Specifically, it details a framework for the development of serious games that integrates a rich set of features that can be used to improve the designed games with direct benefits to the rehabilitation process. Highlighted features include natural and multimodal interaction, social skills (collaboration and competitiveness), and progress monitoring. Due to the rich set of features supported by the framework, the games' rehabilitation efficacy can be enhanced primarily from an increase in the patient's motivation when exercising the rehabilitation tasks. A preliminary test of the framework with elderly users is described. © 2018, IGI Global.

Abstract
Lisbon is one of the European cities where NO2 and PK10 legal limit values are still exceeded, leading to an Air Quality Plan applicable up to 2020. The developed work combined a detailed emission inventory, monitoring data, and modelling in order to assess if the proposed emission abatement scenarios, focused on the road transport sector, were able to tackle exceedances. A maximum decrease of 14% for PM10 concentrations was achieved, and of 21% for NO2, providing compliance. PM10 smallest reduction is related with higher weight of regional background sources, while for NO2 local traffic has more influence on concentrations.

Abstract
We present ?Soniferous Resonances?, an ongoing collection of electroacoustic composition pieces that intersect music, digital technologies and architecture. The creative impetus supporting this research is grounded in the interchange of the following two concepts: 1) the phenomenological exploration of the aural architecture [1], particularly the reverberation as a sonic effect [2] through music performance and 2) the real time sound analysis of both the performance and the reverberation (i.e. impulse responses) intervallic content — which ultimately leads to a generic control over consonance/dissonance (C/D). Their conceptual and morphological nature can be understood as sonic improvisations where the interaction of sound producing bodies (e.g. saxophone) with the real (e.g. performance space) and the imaginary (i.e. computer) acoustic response of a space results in formal elements mirroring their physical surroundings. Particular emphasis is given to spectromorphological manipulations by a large array of “contrasting” digital reverberations with extended control over the sound mass [3] and its musical interval content across a continuum between pitched and consonant to unpitched and dissonant sounds. Two digital applications developed by the authors are seminal in Soniferous Resonances?: Wallace [4] and MusikVerb [5]. The first is a navigable user-control surface that offers a fluid manipulation of audio signals to be convolved with several “contrasting” digital reverberations. The second offers refined (compositional) control over the interval content and/or C/D levels computed from the perceptually-inspired Tonal Interval Space [6] resulting in an automatically adaptation of harmonic content in real time. Soniferous Resonances? aims at pushing the boundaries of musical performances that are formally tied to its surrounding space, as well as triggering new concepts and greater awareness about the sublime qualities of experiencing aural architecture.

Abstract
This paper presents an empirical assessment of the General Lot-Sizing and Scheduling Problem (GLSP) under demand uncertainty by means of a budget-uncertainty set robust optimization and a two-stage stochastic programming with recourse model. We have also developed a systematic procedure based on Monte Carlo simulation to compare both models in terms of protection against uncertainty and computational tractability. The extensive computational experiments cover different instances characteristics, a considerable number of combinations between budgets of uncertainty and variability levels for the robust optimization model, as well as an increasing number of scenarios and probability distribution functions for the stochastic programming model. Furthermore, we have devised some guidelines for decision-makers to evaluate a priori the most suitable uncertainty modeling approach according to their preferences.

Abstract
In this paper, we present YAKE!, a novel feature-based system for multi-lingual keyword extraction from single documents, which supports texts of different sizes, domains or languages. Unlike most systems, YAKE! does not rely on dictionaries or thesauri, neither it is trained against any corpora. Instead, we follow an unsupervised approach which builds upon features extracted from the text, making it thus applicable to documents written in many different languages without the need for external knowledge. This can be beneficial for a large number of tasks and a plethora of situations where the access to training corpora is either limited or restricted. In this demo, we offer an easy to use, interactive session, where users from both academia and industry can try our system, either by using a sample document or by introducing their own text. As an add-on, we compare our extracted keywords against the output produced by the IBM Natural Language Understanding (IBM NLU) and Rake system. YAKE! demo is available at http://bit.ly/YakeDemoECIR2018. A python implementation of YAKE! is also available at PyPi repository (https://pypi.python.org/pypi/yake/).

Abstract
It is becoming more and more important to study methods for protecting sensitive data in computer and communication systems from unauthorized access, use, modification, destruction or deletion. Sensitive data include intellectual properties, payment information, personal files, personal credit card and other information depending on the business and the industry. Therefore, data leakage is considered an emerging security threat to organizations and companies. In this paper we present a static analysis method for information flow analysis in Java bytecode with exceptions. Exceptions are special events that break the normal execution flow. They can be used as a device to leak high security data since exception throwing can be accurately driven. The proposed analysis is capable of tracing information flow caused by exceptions by identifying instruction handler protected instructions as virtual control instructions. A malicious Java applet that clones the user secret PIN through exceptions is shown.