2024
Authors
Silva, C; Trigo, L;
Publication
Proceedings of the 16th International Conference on Computational Processing of Portuguese, PROPOR 2024, Santiago de Compostela, Galicia/Spain, 12-15 March, 2024
Abstract
2024
Authors
Elsaid, M; Pessoa, LM;
Publication
2024 18TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION, EUCAP
Abstract
Reconfigurable Intelligent Surfaces (RISs) are in significant focus within 6G research. However, RISs face a power consumption challenge in the reconfigurable elements which may restrict its future scale-up to large areas. We address this issue by proposing a unit cell based on a non-volatile memristor-based switching mechanism. A 1-bit memristor-based reconfigurable RIS unit cell was designed in the Ka-band, and validated using CST and HFSS simulation platforms. The required control circuit to enable the digital control of the memristor has also been proposed. The proposed unit cell achieves losses of less than 1 dB over a frequency band of 25 - 28.3 GHz and a phase difference of 180 degrees +/- 20 degrees at a central frequency of 26.7 GHz, with an operational bandwidth of approximately 1 GHz. Furthermore, an exemplary 16x16 RIS was designed and simulated based on the proposed unit cell to demonstrate its capability to achieve beam steering.
2024
Authors
Chaichana, T; Reeve, G; Drury, B; Chakrabandhu, Y; Wangtueai, S; Yoowattana, S; Sookpotharom, S; Boonnam, N; Brennan, CS; Muangprathub, J;
Publication
ECOLOGICAL INDICATORS
Abstract
Climate change has driven agriculture to alter farming methods for food production. This paper presents a new concept for monitoring, acquisition, management, analysis, and synthesis of ecological data, which captures the environmental determinants and direct gradients suited to a particular requirement for specific plant cultivation and sustainable agriculture. The purpose of this study is to investigate a smart seablite cultivation system. A novel digital agricultural method was developed and applied to digitised seablite cultivation. Machine learning was used to predict the future growth conditions of plants (seablites). The study identified the illustrative maps of seablite origins, a conceptual seablite smart farming model, essential factors for growing seablite, a digital circuit for cultivating seablite, and digital data of seablite growth phases comprised the digital data. The findings indicate that: (1) An indicator of soil salinity is a quantity of sodium chloride extracted from a seablite sample indicating its origin of environmental determinants. (2) Saline soil, saline water, pH, moisture, temperature, and sunlight are essential factors for seablite development. These factors are dependent on climate change and were measured using a smart seablite cultivation system. (3) Digital circuits of seablite cultivation provide a better understanding of the relationship between the essential factors for seablite growth and seablite growth phases. (4) Deep neural networks outperformed vector machines, with 86% accuracy at predicting future growth of seablites. Therefore, this finding showed that the essential seablite development factors can be manipulated as key controllers for agriculture in response to climate change and agriculture can be planned. Basic digitisation of specific plants aids plant migration. Digital agriculture is an important practice for agroecosystems.
2024
Authors
Tinoco, D; Madeira, A; Martins, MA; Proença, J;
Publication
Formal Aspects of Component Software - 20th International Conference, FACS 2024, Milan, Italy, September 9-10, 2024, Proceedings
Abstract
2024
Authors
Sousa, RB; Rocha, CD; Martins, JG; Costa, JP; Padrao, JT; Sarmento, JM; Carvalho, JP; Lopes, MS; Costa, PG; Moreira, AP;
Publication
2024 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC
Abstract
Robotic competitions stand as platforms to propel the forefront of robotics research while nurturing STEM education, serving as hubs of both applied research and scientific innovation. In Portugal, the Portuguese Robotics Open (FNR) is an event with several robotic competitions, including the Robot@Factory 4.0 competition. This competition presents an example of deploying autonomous robots on a factory shop floor. Although the literature has works proposing frameworks for the original version of the Robot@Factory competition, none of them proposes a system framework for the Robot@Factory 4.0 version that presents the hardware, firmware, and software to complete the competition and achieve autonomous navigation. This paper proposes a complete robotic framework for the Robot@Factory 4.0 competition that is modular and open-access, enabling future participants to use and improve it in future editions. This work is the culmination of all the knowledge acquired by winning the 2022 and 2023 editions of the competition.
2024
Authors
Carvalho J.; de Sousa J.P.; Macário R.;
Publication
Transportation Research Procedia
Abstract
Participatory processes are an essential aspect of collaborative planning and decision-making processes, but designing such processes effectively can be quite challenging. This work departs from the assumptions that in sustainable urban mobility planning, the functional urban area needs to be considered, and that citizen engagement is often enacted at the neighborhood level. Under these assumptions, we have examined the experiences of 6 metropolitan cases (Bologna, Nantes, Manchester, Montreal, Christchurch, and Santiago de Chile) and draw insights from their experiences. We conclude this work with some general reflections on the importance of systemic approaches to effectively plan for sustainable transitions in urban mobility.
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