Efficient Design of Pruned Convolutional Neural Networks on FPGA

Journal of Signal Processing Systems - Convolutional Neural Networks (CNNs) have improved several computer vision applications, like object detection and classification, when compared to other...     

Chitosan Microspheres as Carriers for pH‐Indicating Species in Corrosion Sensing

Chitosan microspheres containing bromocresol green, cresol red, and phenolphthalein for corrosion detection, through pH change, are synthesized in order to be used in protective coatings for aluminium alloys. Microspheres containing corrosion detection species are characterized morphologically (SEM) and physico‐chemically (FTIR, TGA). Release studies (UV–vis) are performed in corrosion‐promoting conditions (pH, NaCl), and detection studies by immersion in media associated with corrosion activity while microspheres' sensing activity is evaluated visually. Electrochemical characterization of AA2024 substrates in the presence of chitosan spheres is performed to understand material performance, and a color change is observed as a result of local pH increase in cathodic areas when corrosion takes place. These findings can be correlated with the results from release studies and seem a promising approach for corrosion sensing purposes, not only because pH increase is possible to detect due to corrosion, but also because chitosan is considered an environmentally friendly material.     

A new mobile robot control approach via fusion of control signals.

This paper proposes an alternative approach to address the problem of coordinating behaviors in mobile robot navigation: fusion of control signals. Such approach is based on a set of two decentralized information filters, which accomplish the data fusion involved. Besides these two fusion engines, control architectures designed according to this approach also embed a set of different controllers that generate reference signals for the robot linear and angular speeds. Such signals are delivered to the two decentralized information filters, which estimate suitable overall reference signals for the robot linear and angular speeds, respectively. Thus, the background for designing such control architectures is provided by the nonlinear systems theory, which makes this approach different from any other yet proposed. This background also allows checking control architectures designed according to the proposed approach for stability. Such analysis is carried out in the paper, and shows that the robot always reaches its final destination, in spite of either obstacles along its path or the environment layout. As an example, a control architecture is designed to guide a mobile robot in an experiment, whose results allows checking the good performance of the control architecture and validating the design approach proposed as well.     

The Role of Network Topologies in the Optical Core of IP-over-WDM Networks with Static Wavelength Routing

In this paper, we present a performance analysis of network topologies for the optical core of IP-over-WDM networks with static wavelength routing. The performance analysis is focused on regular degree four topologies, and, for comparison purposes, degree three topologies are also considered. It is shown that the increase of the nodal degree from three (degree three topology with smallest diameter) to four (degree four topology with smallest diameter) improves the network performance if a larger number of wavelengths per link is available. However, the influence of wavelength interchange on the nodal degree gain is small. The performance of regular degree four topologies with smallest diameter is also compared with the performance of mesh–torus topologies (which are also degree four topologies), and it is shown that the blocking probability of degree four topologies with smallest diameter is about two orders of magnitude lower than the blocking probability of mesh–torus topologies. It is also presented a performance comparison of WDM-based networks with nodal degrees ranging from two to five and it is shown that the increase of the nodal degree from two to three leads to high nodal degree gains, while de increase of the nodal degree from four to five leads to low nodal degree gains. These results show that degree three and degree four topologies are very attractive for use in the optical core of IP-over-WDM networks.     

Electronic protection and routing optimization of MANETs operating in an electronic warfare environment

Domination of the electromagnetic spectrum is a crucial component of the 21st century warfare. In the harsh electromagnetic environment of the modern battlefield, it is of the utmost importance to deny the opposing force the opportunity to attack or exploit the detection/interception of friendly communications assets through the deployment of electronic protection (EP) measures in order to attain low probability of detection (LPD), low probability of interception (LPI) and anti-jam (A/J). Given that directional antennas are a suitable means to achieve both extended range and LPD/LPI, this paper proposes mechanisms to optimize the trade-off between these capabilities, minimizing the number of hops and end-to-end delay when routing packets in a multi-hop ad-hoc network, while taking into account stealth requirements. The novel scheme is based on a variant of Fisheye State Routing, coupled with a power control algorithm to guarantee a LPD/LPI beyond the zone covered by the omni-directional radiation footprint of the network. The performance of the proposed scheme is evaluated through computer simulation.     

Approximating the problem, not the solution: An alternative view of point set matching

This work discusses the issue of approximation in point set matching. In general, one may have two classes of approximations when tackling a matching problem: (1) an algorithmic approximation which consists in using suboptimal procedures to infer the assignment, and (2), a representational approximation which involves a simplified and suboptimal model for the original data. Matching techniques have typically relied on the first approach by retaining the complete model and using suboptimal techniques to solve it. In this paper, we show how a technique based on using exact inference in simple Graphical Models, an instance of the second class, can significantly outperform instances of techniques from the first class. We experimentally compare this method with well-known Spectral and Relaxation methods, which are exemplars of the first class. We have performed experiments with synthetic and real-world data sets which reveal significant performance improvement in a wide operating range.