Lopes, S., Santos, S., Rodrigues, N., Pinho, P., Viegas, D. (2023).
Modelling sorption processes of 10-h dead Pinus pinaster branches.
International Journal of Wildland Fire, 32(6), 903-912.
https://doi.org/10.1071/WF22127
Santos, D., Santos, V. (2023).
Power Flow Optimization with Energy Storage – Sal Island Case Study.
WSEAS Transactions on Power Systems, 18, 216-231.
DOI: 10.37394/232016.2023.18.23
Zhang, Y., Bliek, L., Costa, P., Refaei Afshar, R., Reijnen, R., Catshoek, T., Vos, D., et al. (2023).
The first AI4TSP competition: Learning to solve stochastic routing problems.
Artificial Intelligence, 319, 103918.
http://dx.doi.org/10.1016/j.artint.2023.103918
Gabriel, V. M. S., Neves, M. E. D., Vieira, E., Reis, P. M. N. (2023).
Connectedness between low carbon portfolios, economy and finance: the role of pandemic crisis and Ukrainian war.
Society and Business Review, 18(3), 463-483.
http://dx.doi.org/10.1108/sbr-06-2022-0179
Neves, M. E. D., Reis, S., Reis, P., Dias, A. G. (2023).
Impact of ISO 14001 and ISO 9001 adoption on corporate performance: evidence on a bank-based system.
International Journal of Productivity and Performance Management.
http://dx.doi.org/10.1108/ijppm-08-2022-0398
Silva, J., Vaz, P., Martins, P., Ferreira, L. (2023).
Reliability Estimation Using EM Algorithm with Censored Data: A Case Study on Centrifugal Pumps in an Oil Refinery.
Applied Sciences, 13(13):7736.
https://doi.org/10.3390/app13137736
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
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.
Sampaio, C., Farinha, L., Sebastião, J. R., Fernandes, A. (2022).
Tourism industry at times of crisis: a bibliometric approach and research agenda.
Journal of Hospitality and Tourism Insights, 6(4), 1464-1484.
https://doi.org/10.1108/JHTI-08-2021-0223
