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Ana de Almeida

Researcher at ISCTE – University Institute of Lisbon

Publications -  60
Citations -  1007

Ana de Almeida is an academic researcher from ISCTE – University Institute of Lisbon. The author has contributed to research in topics: Computer science & Signal. The author has an hindex of 15, co-authored 54 publications receiving 762 citations. Previous affiliations of Ana de Almeida include University of Coimbra.

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Journal ArticleDOI

Home electrical signal disaggregation for non-intrusive load monitoring (NILM) systems

TL;DR: This paper develops an algorithm capable of determining the step-changes in signals that occur whenever a device is turned on or off, and which allows for the definition of a unique signature (ID) for each device.
Journal ArticleDOI

Electrical Signal Source Separation Via Nonnegative Tensor Factorization Using On Site Measurements in a Smart Home

TL;DR: A novel way to look into the issue of energy disaggregation is to interpret it as a single-channel source separation problem, and the performance of source modeling based on multiway arrays and the corresponding decomposition or tensor factorization is analyzed.
Book ChapterDOI

An experimental study on electrical signature identification of non-intrusive load monitoring (NILM) systems

TL;DR: This work presents the development of an algorithm for electrical feature extraction and pattern recognition, capable of determining the individual consumption of each device from the aggregate electric signal of the home.
Journal ArticleDOI

Prediction of Road Accident Severity Using the Ordered Probit Model

TL;DR: In this article, the authors used the ordered probit model to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents, and found that occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy vehicles, at oneway roads and on wet road surfaces.
Journal ArticleDOI

Big Data in Hotel Revenue Management: Exploring Cancellation Drivers to Gain Insights Into Booking Cancellation Behavior:

TL;DR: In the hospitality industry, demand forecast accuracy is highly impacted by booking cancellations, which makes demand management decisions difficult and risky as discussed by the authors, which makes it difficult to make demand forecasting decisions.