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Publications

2024

A New Equipment for Automatic Calibration of the Semmes-Weinstein Monofilament

Authors
Castro-Martins, P; Pinto-Coelho, L;

Publication
FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING: ESTABLISHING BRIDGES FOR MORE SUSTAINABLE MANUFACTURING SYSTEMS, FAIM 2023, VOL 1

Abstract
Diabetic foot is a complication that carries a considerable risk in diabetic patients. The consequent loss of protective sensitivity in the lower limbs requires an early diagnosis due to the imminent possibility of ulceration or amputation of the affected limb. To assess the loss of protective sensitivity, the 10 gf Semmes-Weinstein (SW) monofilament is the most used first-line procedure. However, the used device is most often non-calibrated and its feedback can lead to decision errors. In this paper we present an equipment that is able to automatically conduct a metrological verification and evaluation of the 10 gf SW monofilament in the assessment of the loss of protective sensitivity. Additionally, the proposed equipment is able to simulate the practicioner's procedure, or can be used for training purposes, providing force-feedback information. After calibration, displacement vs. buckling force contours were plotted for three distinct monofilaments, confirming then ability of the equipment to provide fast, detailed and precise information.

2024

Immigrant groups in the Luxembourgish labour market: A Symbolic Data Analysis approach

Authors
Silva, CC; Brito, P; Campos, P;

Publication
Statistical Journal of the IAOS

Abstract
Luxembourg, known for its immigration history, attracts immigrants to work. This study analyses different immigrant groups in the labour market from 2014 to 2022 by using Labor Force Survey (LFS) data, Symbolic Data Analysis (SDA), and the Monitoring the Evolution of Clusters (MEC) framework. Based on the birthplace and length of residence in Luxembourg, in each year, microdata were aggregated into 21 symbolic objects. They were primarily described by 16 modal variables which are multi-valued variables with a frequency attached to each category. Moreover, clustering using complete linkage and the Chernoff’s distance was applied. The Heuristic Identification of Noisy Variables (HINoV) suggested that with just six variables, objects may be grouped homogeneously. The MEC framework traced temporal relations and transitions between the clusters, revealing some movements across the different years. Results indicate that people from the European Union (EU) and Neighbouring countries have similar profiles while the Portuguese have opposite characteristics. The Luxembourgers are somewhere in between. Profiling people from non-EU countries was challenging. The data and methodology used make it easy to replicate the work in other nations, enabling comparison of results and monitoring to continue in the future.

2024

Weather and Meteorological Optical Range Classification for Autonomous Driving

Authors
Pereira, C; Cruz, RPM; Fernandes, JND; Pinto, JR; Cardoso, JS;

Publication
IEEE Transactions on Intelligent Vehicles

Abstract

2024

On the Relational Basis of Early R/G Work

Authors
Oliveira, N;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
The R/G approach to the development of interfering programs was initiated by the pioneering work of Cliff Jones (1981) on a relational basis. R/G has been the subject of much research since then, most of it deviating from the original relational set-up. This paper looks at such early work from a historical perspective and shows how it can be approached and extended using state-of-the-art relational algebra. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

2024

Application of active contours in feature extraction in LANDSAT 8 and CBERS 4 images

Authors
Reiz, C; Filgueiras, JLD; Evaristo, JW; Zanin, RB; Martins, EFdO;

Publication
Caderno Pedagógico

Abstract
Digital images from orbital platforms are the main source of information for mapping and decision-making. Their use has become increasingly popular over the years and has expanded into various areas. Feature extraction in digital images has been widely researched in Image Analysis, Photogrammetry, and Computer Vision. Works related to feature extraction for the generation and updating of GISs are generally divided into anthropic features such as buildings and/or highways and natural features such as vegetation areas or bodies of water. One attractive methodology for feature extraction, especially for rivers and bodies of water, is based on active contours, formulated based on the evolution of curves, which can have parametric models (Snakes) or geometric models (Level set). In this context, this work intends to identify and compare some characteristics of parametric and geometric active contour methods and apply them to orbital images from the OLI and PAN sensors of the LANDSAT 8 and CBERS 4 satellites for feature extraction, correlating these characteristics with the parameters required in the mathematical models of active contours. The present work makes use of Digital Image Processing (DIP) methods, with the first processing stage known as pre-processing, consisting of interconnected tasks that can be used to extract some information about the objects present in the scene. Subsequently, in the processing stage, the features of interest are extracted with the help of the Fiji and Icy software using Level Set and Snake, respectively. Regardless of the method used, the results presented in this work show an extraction time compatible with application needs, as they are developed semi-automatically.

2024

Optimal planning of a green hydrogen fueling station

Authors
Coelho, A; Soares, FJ; Iria, JP;

Publication
IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2024, Dubrovnik, Croatia, October 14-17, 2024

Abstract
As the global community transitions towards decarbonization and sustainable energy, green hydrogen is emerging as a key clean energy carrier. This paper addresses the role of hydrogen in transportation, emphasizing the European Union's additionality principle for renewable energy sources in green hydrogen production. It introduces a model for optimally designing hydrogen fueling stations, considering electrolyzers, hydrogen storage, fuel cells, PV systems, and batteries. This model also considers the participation in electricity (energy and secondary reserve), hydrogen, and oxygen markets, and it is evaluated under different additionality policy scenarios. Results indicate that stricter additionality policies reduce the internal rate of return. However, participation in secondary reserve markets significantly boosts operational revenues and compensates for higher investment costs. © 2024 IEEE.

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