2022
Authors
Esmaeili, M; Shafie khah, M; Catalao, JPS;
Publication
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
Abstract
Due to the gas consumption of some power plants for electricity generation and providing an acceptable level of flexibility, the interaction of natural gas markets and electricity markets is inevitable. One of the main challenges of policymakers in the energy sector coupling is the investigation of such interactions. Our main goal is to analyze the effect of the penetration of renewable energy resources on the behavior of gas markets and vice versa from the policymaker's viewpoint. Moreover, we tend to study the effect of an external shock on the behavior of the whole system and the role of renewable resources in mitigating these side effects. Therefore, we used System Dynamic Approach to model the long-term behavior of the natural gas markets to extend the existed models of the electricity markets behavior and couple these markets. The Net Present Value method was used for the economic assessment of the investment in the development of gas reserves, and new stock and flow variables were defined to simulate this development. The simulations are performed for four scenarios by using a valid case study. Considering the results of simulations and sensitivity analysis, as the wind capacity incentive rose, the gas and electricity prices declined and their fluctuation increased during the time horizon. Although the effect of the gas market shock on the system depends on the time of occurrence, as the penetration of renewable units increased, the severity of its side effects decreased and the price jumps in the markets were mitigated.
2022
Authors
Forero, J; Bernardes, G; Mendes, M;
Publication
ACM Multimedia
Abstract
Emotional Machines is an interactive installation that builds affective virtual environments through spoken language. In response to the existing limitations of emotion recognition models incorporating computer vision and electrophysiological activity, whose sources are hindered by a head-mounted display, we propose the adoption of speech emotion recognition (from the audio signal) and semantic sentiment analysis. In detail, we use two machine learning models to predict three main emotional categories from high-level semantic and low-level speech features. Output emotions are mapped to audiovisual representation by an end-To-end process. We use a generative model of chord progressions to transfer speech emotion into music and a synthesized image from the text (transcribed from the user's speech). The generated image is used as the style source in the style-Transfer process onto an equirectangular projection image target selected for each emotional category. The installation is an immersive virtual space encapsulating emotions in spheres disposed into a 3D environment. Thus, users can create new affective representations or interact with other previous encoded instances using joysticks. © 2022 Owner/Author.
2022
Authors
Machado, D; Costa, VS; Brandao, P;
Publication
2022 27TH IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (IEEE ISCC 2022)
Abstract
Finger-pricking is the traditional procedure for glycaemia monitoring. It is an invasive method where the person with diabetes is required to prick their finger. In recent years, continuous-glucose monitoring (CGM), a new and more convenient method of glycaemia monitoring, has become prevalent. CGM provides continuous access to glycaemic values without the need of finger-pricking. Data mining can be used to understand glycaemic values, and to ideally warn users of abnormal situations. CGM provides significantly more data than finger-pricking. Thus, the amount and value of CGM data ultimately questions the role of finger-pricking for glycaemic studies. In this work we use the OhioT1DM data set in order to study the importance of finger-prick-based data. We use Random Forest as a classification method, a robust method that tends to obtain quality results. Our results indicate that, although more demanding and scarcer, finger-prick-based glycaemic values have a significant role on diabetes management and on data mining.
2022
Authors
Martins, J; Gonçalves, R; Branco, F;
Publication
UNIVERSAL ACCESS IN THE INFORMATION SOCIETY
Abstract
Even though being perceived as a novel approach, multiple authors claim that the digital transition of all sectors in society started when information and communication technologies (ICT) started to be an integral part of our daily lives. The education sector currently represents one of the contexts where the use of ICT is more promising and allows to reach greater benefits, mostly due to the wide range of tools, applications, and management and methodological approaches that are associated with e-learning. With the above in mind, a bibliometric analysis of the e-learning adoption topic has been performed, aiming on delivering a detailed analysis of the status of the topic. This analysis was carried out by analyzing the scientific literature indexed in the Scopus database that addressed the multiple stages of the e-learning adoption process (i.e., acceptance, adoption, and use). Our study analyzed 896 documents published between 1989 and 2021, of which 98.3% represented papers published in journals and conference proceedings.
2022
Authors
Dias, J; Carvalho, D; Reis, A; Barroso, J; Rocha, T;
Publication
Proceedings - 2022 5th International Conference on Information and Computer Technologies, ICICT 2022
Abstract
The main purpose for conducting this research is to analyze the core advantages and disadvantages of automatic assessment tools. With this in mind, we considered two different web sites of two distinct Portuguese Universities and compare the accessibility and usability issues found, aiming at identifying core problems through errors / warnings. This outcome will help us understand the weaknesses of such automatic tools and, thus, suggest features that could be added to improve their analysis. These findings will serve as a basis for a proposal of a new type of platform capable of making any web or mobile application accessible to all types of users, regardless of their impairments (e.g., blindness, deafness, motor or intellectual disabilities). © 2022 IEEE.
2022
Authors
Pereira, LS; Coelho, J; Rodrigues, A; Guerreiro, J; Guerreiro, T; Duarte, C;
Publication
PROCEEDINGS OF THE 24TH INTERNATIONAL ACM SIGACCESS CONFERENCE ON COMPUTERS AND ACCESSIBILITY, ASSETS 2022
Abstract
User-generated content plays a key role in social networking, allowing a more active participation, socialisation, and collaboration among users. In particular, media content has been gaining a lot of ground, allowing users to express themselves through different types of formats such as images, GIFs and videos. The majority of this growing type of online visual content remains inaccessible to a part of the population, in particular for those who have a visual disability, despite available tools to mitigate this source of exclusion. We sought to understand how people are perceiving this type of online content in their networks and how support tools are being used. To do so, we conducted a user study, with 258 social network users through an online questionnaire, followed by interviews with 20 of them-7 blind users and 13 sighted users. Results show how the different approaches being employed by major platforms may not be sufficient to address this issue properly. Our findings reveal that users are not always aware of the possibility and the benefits of adopting accessible practices. From the general perspectives of end-users experiencing accessible practices, concerning barriers encountered, and motivational factors, we also discuss further approaches to create more user engagement and awareness. © 2022 Owner/Author.
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