Abstract
Chord progressions are core elements of Western tonal harmony regulated by multiple theoretical and perceptual principles. Ideally, objective measures to evaluate chord progressions should reflect their tonal fitness. In this work, we propose an objective measure of the fitness of a chord progression within the Western tonal context computed in the Tonal Interval Space, where distances capture tonal music principles. The measure considers four parameters, namely tonal pitch distance, consonance, hierarchical tension and voice leading between the chords in the progression. We performed a listening test to perceptually assess the proposed tonal fitness measure across different chord progressions, and compared the results with existing related models. The perceptual rating results show that our objective measure improves the estimation of a chord progression’s tonal fitness in comparison with existing models. © Springer Nature Switzerland AG 2020.

Abstract
Two increasingly popular distributed energy resources (DERs), especially within the European context, are photovoltaic (PV) installations and electric vehicles (EVs). Numerous models have been proposed for optimal management thereof, such as Home Energy Management Systems (HEMSs) and EV parking lot management systems (EVPLMS). However, these approaches are often designed to benefit only one party without taking into account the effect of any other management systems. I.e., HEMSs are designed to only maximize the economic benefit of home owners, while EVPLMSs are designed to only maximize the profit of parking lot owners. In this study, the coordinated use of these systems is modeled and simulated to investigate whether a synergistic relationship exists in which consumers (EV owners) have an added economic benefit by the simultaneous operation of HEMSs and EVPLMSs. As such, a cost-benefit analysis is conducted from the point of view of the EV owners, utilizing a HEMS at home and an EVPLMS at work. The analysis was performed on case studies that are based on real facilities, locations, meteorological data, and electricity market prices in Porto, Portugal.

Abstract
We define EVL, a minimal higher-order functional language for dealing with generic events. The notion of generic event extends the well-known notion of event traditionally used in a variety of areas, such as database management, concurrency, reactive systems and cybersecurity. Generic events were introduced in the context of a metamodel to deal with obligations in access control systems. Event specifications are represented as records and we use polymorphic record types to type events in our language. We show how the higher-order capabilities of EVL can be used in the context of Complex Event Processing (CEP), to define higher-order parameterised functions that deal with the usual CEP techniques.

Abstract
Missing data is a problem often found in real-world datasets and it can degrade the performance of most machine learning models. Several deep learning techniques have been used to address this issue, and one of them is the Autoencoder and its Denoising and Variational variants. These models are able to learn a representation of the data with missing values and generate plausible new ones to replace them. This study surveys the use of Autoencoders for the imputation of tabular data and considers 26 works published between 2014 and 2020. The analysis is mainly focused on discussing patterns and recommendations for the architecture, hyperparameters and training settings of the network, while providing a detailed discussion of the results obtained by Autoencoders when compared to other state-of-the-art methods, and of the data contexts where they have been applied. The conclusions include a set of recommendations for the technical settings of the network, and show that Denoising Autoencoders outperform their competitors, particularly the often used statistical methods.

Abstract
We present a natural probabilistic variation of the multi-depot vehicle routing problem with pickup and delivery (MDVRPPD). In this paper, we present a variation of this deterministic problem, where each pair of pickup and delivery points are present with some probability, and their realization are only known after the routes are computed. We denote this stochastic version by S-MDVRPPD. One route for each depot must be computed satisfying precedence constraints, where each pickup point must appear before its delivery pair in the route. The objective is to find a solution with minimum expected traveling distance. We present a closed-form expression to compute the expected length of an a priori route under general probabilistic assumptions. To solve the S-MDVRPPD we propose an Iterated Local Search (ILS) that uses the Variable Neighborhood Descent (VND) as local search procedure. The proposed heuristic was compared with a Tabu Search (TS) algorithm based on a previous work. We evaluate the performance of these heuristics on a data set adapted from TSPLIB instances. The results show that the ILS proposed is efficient and effective to solve S-MDVRPPD. © 2020 Polish Information Processing Society - as it is since 2011.

Abstract
The support of video in the learning environment is nowadays used to many ends, for either for demonstration, research or share. It is intended to reinforce the space before and after class and introduce a new dynamic and interaction in the classroom itself. Pedagogical Innovation may be achieved by different approaches to motivate students and obtain better results. The Audiovisual didactic content has been in recent years disseminated, in the Physics domain, mainly through YouTube platform. Many aspects of video production activities can increase students' self-esteem, increase their satisfaction with the learning experience, promote a positive attitude towards the subject, provide students with lower level of understanding with a broad individual tutoring, encouraging students to discuss with each other, exchange their opinions, and compare the results of lab activities. On the other hand, video can support research activities, offering the researcher access to a rich data aggregation to investigate the learning processes. This paper presents a revision of the literature about the potential of using video annotation in the education context and, perspectives of teachers' use of collaborative annotation systems, to promote reflection, specifically in the domain of Physics, using an open source annotation tool. The creation of audiovisual references, either for quick access to parts of organized video annotated content by the teacher, knowledge building or revision by and for other students is analyzed. This study is complemented with a testbed, showing the potential of using audiovisual annotated content, within a k-12 context. Students were invited to select video content, annotate, organize and publish the annotations, which could support the learning process in the domain of Physics. Results show that most of the aspects under analysis received a positive evaluation, and students expressed a gain from oral lectures and access to new sources of learning. The only exception relates to the capacity of the approach to motivated students to the study of Physics, as most of the students did not see this methodology too much motivating. The impact of this research relates to alternative teaching / learning methods, within the Physics' domain, using online video annotation, in the support of traditional exposition and memorization methodologies.