Abstract
The Extended Kalman Filter (EKF) computation is a core task for the simultaneous localization and mapping (SLAM) problem in autonomous mobile robots. The SLAM problem involves operations over high dimension data sets, requiring high throughput and performance, given the real-time nature of the robotics, control-decision algorithm this task is a part of. The lightweight and power restricted computing environments in mobile robotics requires customized processing systems such as Field-Programmable Gate Arrays (FPGAs). This work presents an arithmetic precision analysis and a Faddeev algorithm to calculate the Schur’s Complement hardware architecture implementation for the EKF-SLAM using a Systolic Array (SA). While it is widely believed that fixed-point implementations of arithmetic operations lead to area and performance benefits on FPGAs, the results in this article reveal that each Processing Element (PE) in the SA consumes 25% more logic and about 30% more register resources for the fixed-point 13.23 representation than if using the IEEE-754 single precision floating-point format. In addition, for FPGA devices with hardware support for key components of floating-point computations, a single PE floating-point implementation can achieve a maximum frequency up to 50% higher than a corresponding fixed-point implementation for the same relative numeric errors. © 2017, Springer Science+Business Media New York.

Abstract
The economic and social challenges felt in recent years because of the financial crisis impact wave were somehow attenuated by the silent work provided by the third sector institutions. Therefore, the incessant instability of the markets, as well as the population life-expectancy increasing and the implications thereof require new approaches towards pointing strategies to mitigate these problematic situations. For that reason, the development of technological solutions and applications for the private social solidarity institutions is an utmost challenge towards guaranteeing their sustainability and efficiency over time. The adoption of such solutions should be properly conceived to enhance their efficiency of the daily routines and to fulfill and inclusion of all users, while trying to reduce the technological literacy. The development of a technological framework to support the adoption of the practices, selection of technical requirements, and functionalities is seen as a great contribution for setting the roadmap that should be followed. This chapter explores the development of a framework for technological embedding in private social solidarity institutions. © 2018, IGI Global.

Abstract
This paper studies how to optimally capture side information to aid in the reconstruction of high-dimensional signals from low-dimensional random linear and noisy measurements, by assuming that both the signal of interest and the side information signal are drawn from a joint Gaussian mixture model. In particular, we derive sufficient and (occasionally) necessary conditions on the number of linear measurements for the signal reconstruction minimum mean squared error (MMSE) to approach zero in the low-noise regime; moreover, we also derive closed-form linear side information measurement designs for the reconstruction MMSE to approach zero in the low-noise regime. Our designs suggest that a linear projection kernel that optimally captures side information is such that it measures the attributes of side information that are maximally correlated with the signal of interest. A number of experiments both with synthetic and real data confirm that our theoretical results are well aligned with numerical ones. Finally, we offer a case study associated with a panchromatic sharpening (pan sharpening) application in the presence of compressive hyperspectral data that demonstrates that our proposed linear side information measurement designs can lead to reconstruction peak signal-to-noise ratio (PSNR) gains in excess of 2 dB over other approaches in this practical application.

Abstract
This paper addresses the problem of finding the best Brain Emotional Learning (BEL) controller parameters in order to improve the response of a single degree-of-freedom (SDOF) structural system under an earthquake excitation. The control paradigm considered is based on a semi-active system to control the dynamics of a lumped mass-damper-spring model, being carried out by changing the damping force of a magneto-rheological (MR) damper. A typical BEL based controller requires the definition of several parameters which can be proved difficult and non-intuitive to obtain. For this reason, an evolutionary based search technique has been added to the current problem framework in order to automate the controller design. In particular, the particle swarm optimization (PSO) method was chosen as the evolutionary based technique to be integrated within the current control paradigm. The obtained results suggest that, indeed, it is possible to parametrize a BEL controller using an evolutionary based algorithm. Moreover, simulation shows that the obtained results can outperform the ones obtained by manual tuning each controller parameter individually.

Abstract
Vascular access dysfunction is a serious problem in dialysis units. Some patients have complex dysfunctions that are difficult to resolve. In this article, we report the case a of two patients with radiocephalic arteriovenous fistulae (RC-AVF) who had stenosis/occlusion of the forearm median vein and where we used the basilic vein of the forearm as a solution. We reviewed the use of this surgical solution in RC-AVF. Two male patients on hemodialysis exhibited stenosis/occlusion of the forearm median vein. The forearm basilic vein was isolated and rotated toward the forearm median vein in order to solve RC-AVF problems. One patient had fistula thrombosis 5 months after the procedure, while for the other patient, the fistula continues to work without problems. Literature describes only a few cases using the forearm basilic vein or the brachial vein for fistula recovery. This procedure increased the patency of fistulas. This approach has been proven to be a good solution for solving outflow problems using the superficial or deep veins, increasing fistula patency and avoiding the need to place a central venous catheter and all the related complications.

Abstract
Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a "conditioned" and a real world setup, where the system performed worse compared to the "conditioned" setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.