Abstract
Demands for underwater communication systems are increasing due to the ongoing expansion of human activities in underwater environments such as environmental monitoring, underwater exploration, offshore oil field exploration and monitoring, port security, and tactical surveillance. As such, there is a serious requirement to improve the performance of underwater communication systems in order to effectively use the equipment and the resources. The high cost, lack of flexibility, and operational disadvantages of wireline (particularly optical fiber) systems to provide real-time communication in underwater applications become restrictive for many cases. This triggers the growing demand for underwater wireless links. Acoustic communications suffer from a very small available bandwidth, very low celerity, and large latencies due to the low propagation speed. Underwater wireless optical communications (UWOC) which are able to achieve data rates of hundreds of Mbps (even up to Gbps) for short ranges, typically several tens of meters, appear as an attractive alternative or complementary solution to long-range acoustic communications. In fact, water is relatively transparent to light in the visible band of the spectrum and absorption takes its minimum value in the blue-green spectral range (450 nm-550 nm) [1,2]. Thanks to the ability of providing unprecedentedly high-rate data transmission, the UWOC technology enables the establishment of high-speed and reliable links for underwater missions employing robotics or autonomous underwater vehicles (AUVs), for instance. In addition, it is highly energy efficient, compared to the traditional technique of acoustic communication, and also has much less impact on marine animal life (see Figure 11.1) [3,4]. In particular, it is harmless to the cetaceans and coral. © 2017 by Taylor & Francis Group, LLC.

Abstract

Abstract
In this paper we present the INESC Key Detection (IKD) system which incorporates a novel method for dynamically biasing key mode estimation using the spatial displacement of beat-synchronous Tonal Interval Vectors (TIVs). We evaluate the performance of the IKD system at finding the global key on three annotated audio datasets and using three key-defining profiles. Results demonstrate the effectiveness of the mode bias in favoring either the major or minor mode, thus allowing users to fine tune this variable to improve correct key estimates on style-specific music datasets or to balance predictions across key modes on unknown input sources.

Abstract
We present a hierarchical harmonic mixing method for assisting users in the process of music mashup creation. Our main contributions are metrics for computing the harmonic compatibility between musical audio tracks at small- and large-scale structural levels, which combine and reassess existing perceptual relatedness (i.e., chroma vector similarity and key affinity) and dissonance-based approaches. Underpinning our harmonic compatibility metrics are harmonic indicators from the perceptually-motivated Tonal Interval Space, which we adapt to describe musical audio. An interactive visualization shows hierarchical harmonic compatibility viewpoints across all tracks in a large musical audio collection. An evaluation of our harmonic mixing method shows our adaption of the Tonal Interval Space robustly describes harmonic attributes of musical instrument sounds irrespective of timbral differences and demonstrates that the harmonic compatibility metrics comply with the principles embodied in Western tonal harmony to a greater extent than previous approaches.

Abstract
Automatic segmentation of breast is an important step in the context of providing a planning tool for breast cancer conservative treatment, being important to segment completely the breast region in an objective way; however, current methodologies need user interaction or detect breast contour partially. In this paper, we propose a methodology to detect the complete breast contour, including the pectoral muscle, using multi-modality data. Exterior contour is obtained from 3D reconstructed data acquired from low-cost RGB-D sensors, and the interior contour (pectoral muscle) is obtained from Magnetic Resonance Imaging (MRI) data. Quantitative evaluation indicates that the proposed methodology performs an acceptable detection of breast contour, which is also confirmed by visual evaluation.

Abstract
The segmentation of the anterior fascia of the rectus abdominis muscle is an important step towards the analysis of abdominal vasculature. It may advance Computer Aided Detection tools that support the activity of clinicians who study vessels for breast reconstruction using the Deep Inferior Epigastric Perforator flap. In this paper, we propose a two-fold methodology to detect the anterior fascia in Computerized Tomographic Angiography volumes. First, a slice-wise thresholding is applied and followed by a post-processing phase. Finally, an interpolation framework is used to obtain a final smooth fascia detection. We evaluated our method in 20 different volumes, by calculating the mean Euclidean distance to manual annotations, achieving subvoxel error.