Abstract
The main goal of the conference is to promote the interest in the current digital culture and its intersection with art and technology as an important research field, and also to create a common space for discussion and exchange of new experiences. It seeks to foster greater understanding about digital arts and culture across a wide spectrum of cultural, disciplinary, and professional practices. To this end, many scholars, teachers, researchers, artists, comput-er professionals, and others who are working within the broadly defined areas of digital arts, culture and education across the world, submitted their innovative work to the conference.

Abstract
In this paper we discuss the incompatibility between the notions of validity and impreciseness in the context of Dynamic Logics. To achieve that we consider the Lukasiewicz action lattice and its interval counterpart, we show how some validities fail in the context of intervals. In order to capture the properties of action lattices that remain valid for intervals we propose a new structure called Quasi-action Lattices which generalizes action lattices and is able to model both: The Lukasiewicz action lattice, L, and its interval counterpart, (sic). The notion of graded satisfaction relation is extended to quasi-action lattices. We demonstrate that, in the case of intervals, the relation of graded satisfaction is correct (cf. Theorem 3) with respect to the graded satisfaction relation on the Lukasiewicz action lattice. Although this theorem guarantees that satisfiability is preserved on intervals, we show that validity is not. We propose, then, to weaken the notion of validity on action lattices to designated validity on quasi-action lattices. In this context, Theorem 4 guarantees that the dynamic formula which are valid with respect to L will be designated valid with respect to (sic).

Abstract
Taking into consideration a current legal Portuguese framework about accessibility requirements for websites and mobile applications of the public sector, we present an e-Learning project aiming to enhance awareness about the need of the development of accessible Web contents, thus promoting digital inclusion. In this context, in this paper we present a description of a Massive Open Online Courses (MOOC) on Web accessibility entitled: "Inclusive Web - How to develop inclusive web contents?" In this paper, we described the creation of this MOOC, not only the program contents, learning methodologies and evaluation descriptions but also present satisfaction and learning results of this project. This first edition counted on 174 students, among them, 2 with special needs, from 4 different countries, mostly professionals who develop web content, such as: students, professionals and enthusiasts in the areas of Informatics, Multimedia, Information and Communication Technologies (ICT), Digital Media, Web Design, Teaching and Special Education. The feedback results showed that despite there were a few features that must be improved, overall the applicants enjoyed and stated that the course was a good learning resource to start in the Web Accessibility topic.

Abstract
This paper proposes an optimal bidding strategy for autonomous residential energy management systems. This strategy enables the system to manage its domestic energy production and consumption autonomously, and trade energy with the local market through a novel hybrid interval-stochastic optimization method. This work poses a residential energy management problem which consists of two stages: day-ahead and real-time. The uncertainty in electricity price and PV power generation is modeled by interval-based and stochastic scenarios in the day-ahead and real-time transactions between the smart home and local electricity market. Moreover, the implementation of a battery included to provide energy flexibility in the residential system. In this paper, the smart home acts as a price-taker agent in the local market, and it submits its optimal offering and bidding curves to the local market based on the uncertainties of the system. Finally, the performance of the proposed residential energy management system is evaluated according to the impacts of interval optimistic and flexibility coefficients, optimal bidding strategy, and uncertainty modeling. The evaluation has shown that the proposed optimal offering model is effective in making the home system robust and achieves optimal energy transaction. Thus, the results prove that the proposed optimal offering model for the domestic energy management system is more robust than its non-optimal offering model. Moreover, battery flexibility has a positive effect on the system's total expected profit. With regarding to the bidding strategy, it is not able to impact the smart home's behavior (as a consumer or producer) in the day-ahead local electricity market.

Abstract
This paper presents the design and experimental assessment of the control system for the UX-1 robot, a novel spherical underwater vehicle for flooded mine tunnel exploration. Propulsion and maneuvering are based on an innovative manifold system. First, the overall design concepts of the robot are presented. Then, a theoretical six degree-of-freedom (DOF) dynamic model of the system is derived. Based on the dynamic model, two control systems have been developed and tested, one based on the principle of nonlinear state feedback linearization and another based on a finite horizon linear quadratic regulator (LQR). A series of experimental tests have been carried out in a controlled environment to experimentally identify the complex parameters of the dynamic model. Furthermore, the two proposed controllers have been tested in underwater path tracking experiments designed to simulate navigation in mine tunnel environments. The experimental results demonstrated the effectiveness of both the proposed controllers and showed that the state feedback linearization controller outperforms the finite horizon LQR controller in terms of robustness and response time, while the LQR appears to be superior in terms of fall time.

Abstract
The feasibility of a compact, modular sensing system able to quantify the presence of nitrogen, phosphorus and potassium (NPK) in nutrient-containing fertilizer water was investigated. Direct UV-Vis spectroscopy combined with optical fibers were employed to design modular compact sensing systems able to record absorption spectra of nutrient solutions resulting from local producer samples. N, P, and K spectral interference was studied by mixtures of commercial fertilizer solutions to simulate real conditions in hydroponic productions. This study demonstrates that the use of bands for the quantification of nitrogen with linear or logarithmic regression models does not produce analytical grade calibrations. Furthermore, multivariate regression models, i.e., Partial Least Squares (PLS), which consider specimens interference, perform poorly for low absorbance nutrients. The high interference present in the spectra has proven to be solved by an innovative self-learning artificial intelligence algorithm that is able to find interference modes among a spectral database to produce consistent predictions. By correctly modeling the existing interferences, analytical grade quantification of N, P, and K has proven feasible. The results of this work open the possibility of real-time NPK monitoring in Micro-Irrigation Systems.