Santos, G., Lopes, P., Guedes, D., Azevedo, D., Soares, F. (2023).
Using Artificial Intelligence to Prevent Drowsiness Based on Facial Recognition.
International Journal of Computers, 8, 45-52.
Gaspar, D., Simões, P., Lopes, O., Clara, J., & Reguenga, D. (2023).
Gestão do valor: Uma visão normativa.
RAE – Revista De Ativos De Engenharia, 1(2), 55–69.
DOI: 10.29073/rae.v1i2.713
Ferreira, B. M., Abrantes, J. L., Reis, M., Brambilla, F. R. (2023).
A Longitudinal Study on Sustainability Perceptions in Portugal.
Sustainability, 15(7), 5893.
https://doi.org/10.3390/su15075893
Pinto, A. P. S., Henriques, C. M. R., Cardoso, C. E. O. da S., & Neves, M. E. D. (2023).
Bank Credit and Trade Credit: The Case of Portuguese SMEs from 2010 to 2019.
Journal of Risk and Financial Management, 16(3), 170. MDPI AG.
Retrieved from http://dx.doi.org/10.3390/jrfm16030170
Mota, M., Melo, F., Henriques, C., Matos, A., Castelo-Branco, M., Monteiro, M., Cunha, M., Santos, M. (2023).
The relationship between acute pain and other types of suffering in pre-hospital trauma victims: An observational study.
International Emergency Nursing, 71(2023), 101375.
DOI: 10.1016/j.ienj.2023.101375
Ramos, C., Carvalho, M., Martins, S., Carvalho, J., Braga, M., Cardoso, M., Carvalho, A. B., Santos, E. (2023).
Recolha e estruturação da informação no âmbito de um estágio curricular.
E3 – Revista de Economia, Empresas e Empreendedores na CPLP, 9(1), 83-97.
doi: 10.29073/e3.v9i1.770
Principal Researcher:
Carlos Augusto da Silva Cunha
Duration: 2022 – 2024
Cised team members
Rui Pedro Amaro Duarte
The alignment of nutrition requirements with food plan creation, follow-up, and adjustment, demands the regular gathering of biometrics, food intake habits, physical activity, and energy consumption data. Analyzing these data in the context of individual objective accomplishment provides the feedback for dynamic adjustment of food plans required to build a nutrition control system. The introduction of sensors for data-gathering activities coupled with artificial intelligence algorithms for creating personalized models has transformed nutrition into an autonomous process that can be realized without or with the minimum intervention of the nutritionist. This process is based on a person’s data with a broader spectrum than those proportioned by the follow-up of traditional nutrition. For that reason, it is potentially also more effective. Also, data availability enables food plan adjustment in shorter cycles, helping reduce the time required to meet individual objectives. This project aims to develop a nutrition control system based on data gathered by sensors (e.g., smartwatches and smart scales) for dynamic food plan adjustment, using machine learning and deep learning algorithms.
Principal Researcher:
João Reis
Nuno Melão
Duration: 2022 – 2023
Cised team members
Nuno Melão
Technological innovations such as robotics and artificial intelligence have enabled the development of intelligent autonomous systems in the defence sector. However, it is common for decision‐makers to have doubts about what kind of decisions should be transferred to these systems. On the other hand, international law stipulates that the responsibility for the use of weapons systems rests with humans and cannot be transferred to machines. Thus, another important challenge is to determine the degree of human‐machine interaction in intelligent autonomous systems. To help address these issues, this project aims to identify the attributes and degree of automation/humanization of intelligent autonomous systems developed by the military industry in Portugal. This project will contribute to the production of knowledge about autonomous military systems, as well as to ensure that lethal decision‐making processes are not transferred to machines, thus meeting legal and ethical concerns.
Principal Researcher: Rui Pedro Duarte
Duration: 2022 – 2024
Cised team members
Carlos Augusto da Silva Cunha
Ricardo Luís da Costa Gama
Food assumes an increasingly important role in people's lives, and adequate nutrition associated with a healthy lifestyle increases the average life expectancy. To this end, there has been an increase in the number of people whom nutritionists are following to have a food plan suited to their needs, which vary according to each person's goals: from the purely aesthetic component, through the improvement of the quality of life, for professional reasons (such as sportsmen or high competition athletes), even people with special needs, in which a correct diet impacts on the aggravation of previously diagnosed diseases. There are, however, some associated problems that can impact noncompliance with a previously defined meal plan. One of them is defining a food plan made up of foods people don't like. The other relates to real-time notification of the nutritionist of the correct fulfilment of the plan in terms of the proper intake of recommended macronutrients in each meal of the food plan.
Regarding the first, the combination of foods is a factor mainly linked to people's preferences, far beyond the rules of food combinations recommended by nutritionists. Thus, patterns for each individual may vary over time and as a function of other conditions (e.g., temperature, season). People's sensitivity to these combinations is one of the factors responsible for abandoning eating plans and not matching their food tastes. With this work, we intend to develop an Artificial Intelligence model to detect food patterns to adapt a food plan defined by a nutritionist in an evolutionary way and in real-time to allow the correct management of the plan. Thus, it becomes possible to provide a better quality of life to people who need to define food plans in various types of contexts.
Principal Researcher:
Sara Santos
Duration: 2022 – 2024
Cised team members
Luísa Augusto
Currently, more and more cities and regions differentiate themselves through the creation of a positive identity and image, developing territorial branding. The use of storytelling can also be an asset when used to promote tourist destinations. It is essential that the entities that manage the tourist image of Portuguese regions rethink their dissemination strategies and give priority to “storytelling”, emotions, and involvement with the public in building the image of the territories. Territorial marketing, and in particular the focus on tourism promotion videos, allows to demonstrate the unique characteristics of the territory and its differentiation from the others. Through the story told about the region, the audience identifies with the characters and is “transported” by the narrative.
In Portugal, the Centro region has stood out for the promotional films (with storytelling techniques) that it uses to promote the Center of Portugal. In recent years, “Turismo do Centro” has won dozens of international awards related to tourism promotion. For its part, the “Aldeias Históricas de Portugal” also won the world award for best tourism film in the world, in 2021.
Considering this worldwide recognition, this project will have the partnership of “Turismo do Centro” and “Aldeias Históricas de Portugal”, as examples of good practices in tourism promotion of regions through storytelling in promotional videos.
STORYtur's main objective is to understand the strategies for promoting tourism in Portuguese regions, especially in the Center region.
The project comprises the development of studies through interviews (to the representatives of “Turismo do Centro” and “Aldeias Históricas de Portugal”) and the application of questionnaires to the public.
