Abstract
Optimizing the operation of heating, ventilation, and air-conditioning (HVAC) systems is a challenging task that requires the modeling of complex nonlinear relationships among the HVAC load, indoor temperature, and outdoor environment. This article proposes a new strategy for optimal operation of an HVAC system in a commercial building. The system for indoor temperature control is divided into three sub-systems, each of which is modeled using an artificial neural network (ANN). The ANNs are then interconnected and integrated into an optimization problem for temperature set-point scheduling. The problem is reformulated to determine the optimal set-points using a deterministic search algorithm. After the optimal scheduling has been initiated, the ANNs undergo online learning repeatedly, mitigating overfitting. Case studies are conducted to analyze the performance of the proposed strategy, compared to strategies with a pre-determined temperature set-point, an ideal physics-based building model, and other types of machine learning-based modeling and scheduling methods. The case study results confirm that the proposed strategy is effective in terms of the HVAC energy cost, practical applicability, and training data requirements.

Abstract
Natural disasters such as earthquakes, hurricanes, and other extreme weather events along with human sabotage attacks pose serious risks to critical infrastructures especially electrical energy systems. Hardening and operational actions are the measures to improve the resiliency of the power systems against extreme events. The long-term hardening actions strive to organize the reinforcement of power system infrastructures which accomplished at the pre-events stage. Besides, the short-term operational measures such as network reconfiguration and generation scheduling are applied to form the multiple microgrids aimed at increasing the flexibility of the power system to cope with the severe events. These measures are taken during and after the occurrence of the disasters. In this paper, an integrated framework has been proposed to increase the resiliency of distribution system. In the proposed framework, there are two models so called defender-attacker-defender which are made to find the best possible solution in order to reduce the load-shedding of the system during extreme events. In the first model, the hardening measures are examined at the first level to increase the robustness of the system. The worst scenarios with the highest load-shedding are calculated in the second level and subsequently reconfiguration is performed in the third level to decrease the load-shedding. In the second model, the first and second levels specify the best reinforcement plan and the worst attack scenario respectively, and in the third level, optimal distributed generation placement is accomplished to supply the demand during islanding mode of microgrids. The proposed models are organized as tri-level mixed integer optimization problem and column constraint generation algorithm is utilized to make them computationally obedient. At the end, we have implemented the suggested models on the well-known IEEE 33-bus and 69-bus systems to prove their effectiveness and applicability at improving the resiliency of the distribution systems.

Abstract
The increasing replacement of conventional generators by variable renewable energy sources is reducing the flexibility of the power system, and consequently reducing its reliability indexes. To compensate for this reduction of flexibility, market participation of aggregators of multi-energy systems has been proposed in the literature. Under this scope, this paper presents a network-secure bidding optimization strategy to assist aggregators of multi-energy systems calculating electricity (energy and reserve), gas and carbon bids, considering multi-energy network constraints. This strategy is a distributed approach based on the alternating direction method of multipliers, where the aggregator collaborates with the operators of electricity, gas and heat networks to calculate network-secure bids. The proposed strategy is benchmarked against two other approaches. The results show that the newly developed strategy computes multi-energy and network-secure bids with execution times that suit the timelines of the electricity, gas, and carbon markets. The joint optimization of multi-energy systems reduced the aggregator's costs by 89% compared to a single energy-vector approach. Furthermore, two sensibility studies were also performed. The first study revealed that in the presence of slow ramp-rate resources (e.g. combined heat and power systems), aggregator's costs can decrease up to 87% when considering slower response times to the secondary reserve signal. In the second study, it was observed that the bidding behavior of the aggregator only starts changing significantly with carbon prices higher than 200euro/tCO2.

Abstract
Since the beginning of the XXI century, we have been witnessing a significant shift in the media landscape towards enhanced immersive audiovisual manifestations, from controlled research environments to gradual production market penetration. Virtual reality, augmented reality, mixed reality, extended reality, 360 degrees video, and digital games are representative examples of these immersive technologies. Spatial audio design and production are instrumental to the immersive experience. As Ambisonics techniques do potentially mean more expense - in memory, processing power, and production budget -, limited exploration in the development of new composition and production methodologies across popular music production has been considered beyond the traditional stereophonic format. Our work details a post-production case study using spatial audio, namely High Order Ambisonics. The case study is a Brazilian popular song, remixed using 3rd order Ambisonics from a multitrack recording session composed of monophonic and stereophonic audio tracks. The song encompasses a unique approach for audio spatialization guided by hierarchical audio content attributes across multiple structural time scales and musical contexts. The evaluation of our production process adopted iterative heuristic assessments comparing technical decisions and aesthetic intentions in fostering an augmented spatial audio song. A set of technical guidelines and good practices on how and why to positioning audio in space are abstracted from our case study evaluation, which critically advances the theory and practice of popular musical audio production in immersive technologies.

Abstract
New language technologies are coming, thanks to the huge and competing private investment fuelling rapid progress; we can either understand and foresee their effects, or be taken by surprise and spend our time trying to catch up. This report scketches out some transformative new technologies that are likely to fundamentally change our use of language. Some of these may feel unrealistically futuristic or far-fetched, but a central purpose of this report - and the wider LITHME network - is to illustrate that these are mostly just the logical development and maturation of technologies currently in prototype. But will everyone benefit from all these shiny new gadgets? Throughout this report we emphasise a range of groups who will be disadvantaged and issues of inequality. Important issues of security and privacy will accompany new language technologies. A further caution is to re-emphasise the current limitations of AI. Looking ahead, we see many intriguing opportunities and new capabilities, but a range of other uncertainties and inequalities. New devices will enable new ways to talk, to translate, to remember, and to learn. But advances in technology will reproduce existing inequalities among those who cannot afford these devices, among the world’s smaller languages, and especially for sign language. Debates over privacy and security will flare and crackle with every new immersive gadget. We will move together into this curious new world with a mix of excitement and apprehension - reacting, debating, sharing and disagreeing as we always do. Plug in, as the human-machine era dawns.

Abstract
Trabalhos científicos apresentados na conferência IV INTERNATIONAL FORUM ON MANAGEMENT: As Organizações na Era Digital, Desafios para a Sustentabilidade, que se realizou na Universidade Aberta nos dias 5 a 7 de março de 2020. Os trabalhos científicos com preponderância nos temas: economia, gestão turismo e sustentabilidade, estão apresentados nos formatos de poster, resumo alargado ou artigo completo (full paper), em português, espanhol ou inglês, tendo sido previamente submetidos a uma rigorosa avaliação (blind review) por uma comissão científica internacional.