Abstract
We present a real-time percussive beat tracking algorithm for synchronisation within live music. A percussive detection function that represents the percussive component of the audio input is created by an efficient method for median filtering. Dynamic programming techniques are used to predict the beat locations and update a cumulative beat function. It is possible to use the percussive component of the spectrogram to create functions which correlate with kick and snare events, thereby generating a prediction of drum pattern events.

Abstract
In this paper we present a system, AutoMashUpper, for making multi-song music mashups. Central to our system is a measure of "mashability" calculated between phrase sections of an input song and songs in a music collection. We define mashability in terms of harmonic and rhythmic similarity and a measure of spectral balance. The principal novelty in our approach centres on the determination of how elements of songs can be made fit together using key transposition and tempo modification, rather than based on their unaltered properties. In this way, the properties of two songs used to model their mashability can be altered with respect to transformations performed to maximize their perceptual compatibility. AutoMashUpper has a user interface to allow users to control the parameterization of the mashability estimation. It allows users to define ranges for key shifts and tempo as well as adding, changing or removing elements from the created mashups. We evaluate AutoMashUpper by its ability to reliably segment music signals into phrase sections, and also via a listening test to examine the relationship between estimated mashability and user enjoyment.

Abstract
A recent trend in the field of beat tracking for musical audio signals has been to explore techniques for measuring the level of agreement and disagreement between a committee of beat tracking algorithms. By using beat tracking evaluation methods to compare all pairwise combinations of beat tracker outputs, it has been shown that selecting the beat tracker which most agrees with the remainder of the committee, on a song-by-song basis, leads to improved performance which surpasses the accuracy of any individual beat tracker used on its own. In this paper we extend this idea towards presenting a single, standalone beat tracking solution which can exploit the benefit of mutual agreement without the need to run multiple separate beat tracking algorithms. In contrast to existing work, we re-cast the problem as one of selecting between the beat outputs resulting from a single beat tracking model with multiple, diverse input features. Through extended evaluation on a large annotated database, we show that our multi-feature beat tracker can outperform the state of the art, and thereby demonstrate that there is sufficient diversity in input features for beat tracking, without the need for multiple tracking models.

Abstract
The integrate-and-fire model of a biological neuron is an amplitude to time encoding in the spacing between action potentials (spikes). In principle, this encoding can be used to modulate signals in an Impulse Radio Ultra Wide-Band (IRUWB) transmitter suitable for Wireless Sensor Networks (WSN). This paper presents a system level study on power efficiency using MATLAB/ Simulink to evaluate the required energy for an IR-UWB Transmitter using integrate-and-fire encoding technique. Also, a simple but clear comparison with common systems utilizing Nyquist rate Analog-to-Digital Converters (ADC) is presented. This study has been carried out on a band-limited random Gaussian signal and the results show that IR-IF transmitter consumes roughly seven times less energy than a digital UWB transmitter; moreover, in the proposed architecture the need for power hungry ADC is relaxed.

Abstract
Alzheimer's disease is a major cause of disability in older people and because of its nature and symptoms it is a huge weight on the caregivers and health system. The aim of this project, developed at Fraunhofer Portugal, is to create a remote monitoring system for patients suffering from Alzheimer's disease. This system comprises a device able to monitor the environment temperature and humidity, the patients location, using GPS, as well as the patient's movements, including falls. The device sends this information to the caregiver via SMS, and also to a server, where it is stored in a database developed in this work, and which the caregiver can access via a smartphone, using an application also developed in this project. This system therefore affords a close surveillance of the patient's status as well as access to historical data of the patient's information.

Abstract
Plant diseases, such as the pinewood disease, PWD, have become a problem of economical and forestall huge proportions. These diseases, that are asymptomatic and characterized by a fast spread, have no cure developed to date. Besides, there are no technical means to diagnose the disease in situ, without causing tree damage, and help to assist the forest management. Herein is proposed a portable and non-damage system, based on electrical impedance spectroscopy, EIS, for biological applications. In fact, EIS has been proving efficacy and utility in wide range of areas. However, although commercial equipment is available, it is expensive and unfeasible for in vivo and in field applications. The developed EIS system is able to perform AC current or voltage scans, within a selectable frequency range, and its effectiveness in assessing pine decay was proven. The procedure and the results obtained for a population of 24 young pine trees (Pinus pinaster Aiton) are presented. Pine trees were kept in a controlled environment and were inoculated with the nematode (Bursaphelenchus xylophilus Nickle), that causes the PWD, and also with bark beetles (Tomicus destruens Wollaston). The obtained results may constitute a first innovative approach to the diagnosis of such types of diseases.