Abstract
This paper presents a numerically investigation of the performance analysis of a conventional photonic crystal fiber (PCF) with a planar metamaterials structure for refractive index sensing, based on surface plasmon resonance (SPR), using the finite element method (FEM). We study the concentration metamaterials conformed by the aluminium oxide (Al2O3) and silver (Ag) and compared its performance with a single metal (Ag), assessing their impacts in the effective refractive index. Furthermore, we also use different types of mechanics to describe the effects of varying the structural parameters sensor on the evanescent field and the sensor performance.

Abstract
A better evaluation and understanding of the client's perception of the service provided by hotels is critical for hotel managers, especially in the "Travel 2.0" era, where tourists not only access but also actively review the service provided. This paper analyses data automatically collected from TripAdvisor reviews regarding 2 star and 5 star hotels in Porto. TripAdvisor user generated content is explored through text mining techniques with the purpose of creating word clouds, synthesizing and prioritizing the aspects of the service raised by customers. Furthermore, this content is analyzed using the SERVQUAL model to identify the service quality dimensions most valued by guests of the two types of hotels. The results of the preliminary study demonstrate that the methodology proposed allows us to identify service perceptions with reasonable effectiveness, highlighting the potential of the procedure to become a complementary tool for hotel management.

Abstract
This paper describes the mapping and the acceleration of an object detection algorithm on a multiprocessor system based on an FPGA. We use HOG ( Histogram of Oriented Gradients), one of the most popular algorithms for detection of different classes of objects and currently being used in smart embedded systems. The use of HOG on such systems requires efficient implementations in order to provide high performance possibly with low energy/power consumption budgets. Also, as variations and adaptations of this algorithm are needed to deal with different scenarios and classes of objects, programmability is required to allow greater development flexibility. In this paper we show our approach towards implementing the HOG algorithm into a multi-softcore Nios II based-system, bearing in mind high-performance and programmability issues. By applying sourceto-source transformations we obtain speedups of 19x and by using pipelined processing we reduce the algorithms execution time 49x. We also show that improving the hardware with acceleration units can result in speedups of 72.4x compared to the embedded baseline application.

Abstract
The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-To-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° ± 18, 50° was found, whereas the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-Time application. In conclusion, a successful automatic real-Time method for orientation of the segmented left ventricle is proposed. © 2016 SPIE.

Abstract

Abstract
Wireless Underground Networks (WUN) have many applications, such as border surveillance, agriculture monitoring, and infrastructure monitoring. Recent studies have shown that they are feasible and have deployment advantages over wired networks, but only a few WUN evaluations in multiple access scenarios have been done. This paper presents a simulation study on medium access for a WUN with 4 nodes buried, and one node aboveground. The simulations were carried out using the ns-3 simulator and they evaluate both Wi-Fi, and Lr-Wpan networks for dry and wet soils. We verified that for the same number of concurrent nodes, the use of the RTS/CTS mechanism has a much higher influence than the soil water content. Furthermore, a study about the feasibility of using Wi-Fi fingerprinting for positioning above the ground based on the buried infrastructure revealed promising results.