Instituto Superior Técnico

About: Instituto Superior Técnico is a based out in . It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 10085 authors who have published 30226 publications receiving 667524 citations. The organization is also known as: IST & Instituto Superior Tecnico.

Estimating the higher heating value of biomass fuels from basic analysis data

Abstract: The heating value is one of the most important properties of biomass fuels for design calculations or numerical simulations of thermal conversion systems for biomass. There are a number of formulae proposed in the literature to estimate the higher heating value (HHV) of biomass fuels from the basic analysis data, i.e. proximate, ultimate and chemical analysis composition. In the present paper, these correlations were evaluated statistically based on a larger database of biomass samples collected from the open literature. It was found that the correlations based on ultimate analysis are the most accurate. The correlations based on the proximate data have low accuracy because the proximate analysis provides only an empirical composition of the biomass. The correlations based on the bio-chemical composition are not reliable because of the variation of the components properties. The low accuracy of previous correlations is mainly due to the limitation of samples used for deriving them. To achieve a higher accuracy, new correlations were proposed to estimate the HHV from the proximate and ultimate analyses based on the current database. The new correlation between the HHV and dry ash content of biomass (in weight percent, wt%) (i.e. HHV (MJ/kg) = 19.914–0.2324 Ash) could be conveniently used to estimate the HHV from proximate analysis. The new formula, based on the composition of main elements (in wt%) C, H, and O (i.e. HHV ( MJ / kg ) = - 1.3675 + 0.3137 C + 0.7009 H + 0.0318 O * ), is the most accurate one, with more than 90% predictions in the range of ± 5 % error.

Unveiling the biometric potential of finger-based ECG signals

Abstract: The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

A Multibody Factorization Method for Independently Moving Objects

Abstract: The structure-from-motion problem has been extensively studied in the field of computer vision. Yet, the bulk of the existing work assumes that the scene contains only a single moving object. The more realistic case where an unknown number of objects move in the scene has received little attention, especially for its theoretical treatment. In this paper we present a new method for separating and recovering the motion and shape of multiple independently moving objects in a sequence of images. The method does not require prior knowledge of the number of objects, nor is dependent on any grouping of features into an object at the image level. For this purpose, we introduce a mathematical construct of object shapes, called the shape interaction matrix, which is invariant to both the object motions and the selection of coordinate systems. This invariant structure is computable solely from the observed trajectories of image features without grouping them into individual objects. Once the matrix is computed, it allows for segmenting features into objects by the process of transforming it into a canonical form, as well as recovering the shape and motion of each object. The theory works under a broad set of projection models (scaled orthography, paraperspective and affine) but they must be linear, so it excludes projective “cameras”.

Functional and smart coatings for corrosion protection: A review of recent advances

Abstract: Coatings tailored to corrosion protection of metallic substrates are of the utmost relevance to ensure reliability and long-term performance of coated parts as well as the product value of the coated materials. Presently, there is a strong emphasis on the development of advanced functional and smart coatings for corrosion protection in different technological applications. On the one hand, there is a need for more advanced coatings for conventional applications and, on the other hand, there is a need to answer the requirements of several new Hi-Tech applications. Thus, this review highlights the most recent trends in the field of functional coatings for corrosion protection of metallic materials in a wide range of technical applications. Emphasis is given to self-healing coatings and smart coatings combining multiple functionalities for increased corrosion protection. Recent developments on the introduction of functionalities based on encapsulation of corrosion inhibitors, anti-fouling agents and superhydrophobic additives or modification of organic and hybrid matrices via chemical manipulation are reviewed. Special attention is dedicated to functional coatings for corrosion protection of bioresorbable metallic implants that have an important impact in biomedical applications.