GPU implementation of a hyperspectral coded aperture algorithm for compressive sensing

This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed implementation exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs using shared memory and coalesced accesses to memory. The proposed algorithm is evaluated not only in terms of reconstruction error but also in terms of computational performance using two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN. Experimental results using real data reveals signficant speedups up with regards to serial implementation.

Velocity estimation of moving ships using C-band SLC SAR data

A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

Energy evaporation: the new concept of indoor systems for WPT and EH embedded into the floor

This work introduces a novel idea for wireless energy transfer, proposing for the first time the unit-cell of an indoor localization and RF harvesting system embedded into the floor. The unit-cell is composed by a 5.8 GHz patch antenna surrounded by a 13.56 MHz coil. The coil locates a device and activate the patch which, connected to a power grid, radiates to wirelessly charge the localized device. The HF and RF circuits co-existence and functionality are demonstrated in this paper, the novelty of which is also in the adoption of low cost and most of all ecofriendly materials, such as wood and cork, as substrates for electronics.

Non-uniform printed antenna array for wireless communications in sports arenas

Wireless communications had a great development in the last years and nowadays they are present everywhere, public and private, being increasingly used for different applications. Their application in the business of sports events as a means to improve the experience of the fans at the games is becoming essential, such as sharing messages and multimedia material on social networks. In the stadiums, given the high density of people, the wireless networks require very large data capacity. Hence radio coverage employing many small sized sectors is unavoidable. In this paper, an antenna is designed to operate in the Wi-Fi 5GHz frequency band, with a directive radiation pattern suitable to this kind of applications. Furthermore, despite the large bandwidth and low losses, this antenna has been developed using low cost, off-the-shelf materials without sacrificing quality or performance, essential to mass production. © 2015 EurAAP.

Complementary filter design with three frequency bands: robot attitude estimation

This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.

Maintenance of fire sprinkler systems based on the dynamic assessment of its condition

Safety is one of the major concerns of process safety engineers in most industrial facilities all over the world. To this scope, some events play an important role once the effect of their consequences can be assumed as totally undesirable. One of these events refers to the occurrence of a fire. Such event can result in catastrophic consequences for life, equipment, and continuity of activities or even leading to environmental damage. A fire protection equipment with low reliability means that this equipment are often unavailable and thus the risk of a fire increases. Maintenance of fire protection equipment is very important because this kind of systems is mostly in a dormant mode, which gives uncertainty about their operability when demanded in a real situation of fire. This article outlines the importance of tests, inspection, and maintenance operations in the context of a fire sprinkler system and proposes a methodology based on international standards and supported by test/inspection reports to correct the frequency of these actions according to the level of degradation of the components and regarding safety purposes. © 2015 American Institute of Chemical Engineers.

Development of a high-throughput monitoring technique of bacteria photodynamic inactivation

Summary form only given. Bacterial infections and the fight against them have been one of the major concerns of mankind since the dawn of time. During the `golden years' of antibiotic discovery, during the 1940-90s, it was thought that the war against infectious diseases had been won. However currently, due to the drug resistance increase, associated with the inefficiency of discovering new antibiotic classes, infectious diseases are again a major public health concern. A potential alternative to antibiotic treatments may be the antimicrobial photodynamic inactivation (PDI) therapy. To date no indication of antimicrobial PDI resistance development has been reported. However the PDI protocol depends on the bacteria species [1], and in some cases on the bacteria strains, for instance Staphylococcus aureus [2]. Therefore the development of PDI monitoring techniques for diverse bacteria strains is critical in pursuing further understanding of such promising alternative therapy. The present works aims to evaluate Fourier-Transformed-Infra-Red (FT-IR) spectroscopy to monitor the PDI of two model bacteria, a gram-negative (Escherichia coli) and a gram-positive (S. aureus) bacteria. For that a high-throughput FTIR spectroscopic method was implemented as generally described in Scholz et al. [3], using short incubation periods and microliter quantities of the incubation mixture containing the bacteria and the PDI-drug model the known bactericidal tetracationic porphyrin 5,10,15,20-tetrakis (4-N, N, Ntrimethylammoniumphenyl)-porphyrin p-tosylate (TTAP4+). In both bacteria models it was possible to detect, by FTIR-spectroscopy, the drugs effect on the cellular composition either directly on the spectra or on score plots of principal component analysis. Furthermore the technique enabled to infer the effect of PDI on the major cellular biomolecules and metabolic status, for example the turn-over metabolism. In summary bacteria PDI was monitored in an economic, rapid (in minutes- , high-throughput (using microplates with 96 wells) and highly sensitive mode resourcing to FTIR spectroscopy, which could serve has a technological basis for the evaluation of antimicrobial PDI therapies efficiency.

Molecular fingerprint of human gastric cell line infected by Helicobacter pylori

Helicobacter pylori infection represents a serious health problem, given its association with serious gastric diseases as gastric ulcers, cancer and MALT lymphoma. Currently no vaccine exists and antibiotic-based eradication therapy is already failing in more than 20% of cases. To increase the knowledge on the infection process diverse gastric cell lines, e.g. the adenocarcinona gastric (AGS) cell line, are routinely used has in vitro models of gastric epithelia. In the present work the molecular fingerprint of infected and non-infected AGS cell lines, by diverse H. pylori strains, was acquired using vibrational infrared spectroscopy. These molecular fingerprints enabled to discriminate infected from non-infected AGS cells, and infection due to different strains, by performing Principal Component Analysis. It was also possible to estimate, from the AGS cells molecular fingerprint, the effect of the infection on diverse biochemical and metabolic cellular status. In resume infra-red spectroscopy enabled the acquisition of infected AGS cells molecular fingerprint with minimal sample preparation, in a rapid, high-throughput, economic process yielding highly sensitive and informative data, most useful for promoting critical knowledge on the H. pylori infection process. © 2015 IEEE.

Geomorphic dam-break flows. Part II: numerical simulation

Proceedings of the Institution of Civil Engineers - Water Management 163 Issue WM6

Comparative analysis of near and mid-infrared spectroscopy to monitor recombinant cyprosin production

Infrared spectroscopy, either in the near and mid (NIR/MIR) region of the spectra, has gained great acceptance in the industry for bioprocess monitoring according to Process Analytical Technology, due to its rapid, economic, high sensitivity mode of application and versatility. Due to the relevance of cyprosin (mostly for dairy industry), and as NIR and MIR spectroscopy presents specific characteristics that ultimately may complement each other, in the present work these techniques were compared to monitor and characterize by in situ and by at-line high-throughput analysis, respectively, recombinant cyprosin production by Saccharomyces cerevisiae. Partial least-square regression models, relating NIR and MIR-spectral features with biomass, cyprosin activity, specific activity, glucose, galactose, ethanol and acetate concentration were developed, all presenting, in general, high regression coefficients and low prediction errors. In the case of biomass and glucose slight better models were achieved by in situ NIR spectroscopic analysis, while for cyprosin activity and specific activity slight better models were achieved by at-line MIR spectroscopic analysis. Therefore both techniques enabled to monitor the highly dynamic cyprosin production bioprocess, promoting by this way more efficient platforms for the bioprocess optimization and control.

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Fast unsupervised technique for extraction of endmembers spectra from hyperspectral data

One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.

Parallel hyperspectral coded aperture for compressive sensing on GPUs

The application of compressive sensing (CS) to hyperspectral images is an active area of research over the past few years, both in terms of the hardware and the signal processing algorithms. However, CS algorithms can be computationally very expensive due to the extremely large volumes of data collected by imaging spectrometers, a fact that compromises their use in applications under real-time constraints. This paper proposes four efficient implementations of hyperspectral coded aperture (HYCA) for CS, two of them termed P-HYCA and P-HYCA-FAST and two additional implementations for its constrained version (CHYCA), termed P-CHYCA and P-CHYCA-FAST on commodity graphics processing units (GPUs). HYCA algorithm exploits the high correlation existing among the spectral bands of the hyperspectral data sets and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. The proposed P-HYCA and P-CHYCA implementations have been developed using the compute unified device architecture (CUDA) and the cuFFT library. Moreover, this library has been replaced by a fast iterative method in the P-HYCA-FAST and P-CHYCA-FAST implementations that leads to very significant speedup factors in order to achieve real-time requirements. The proposed algorithms are evaluated not only in terms of reconstruction error for different compressions ratios but also in terms of computational performance using two different GPU architectures by NVIDIA: 1) GeForce GTX 590; and 2) GeForce GTX TITAN. Experiments are conducted using both simulated and real data revealing considerable acceleration factors and obtaining good results in the task of compressing remotely sensed hyperspectral data sets.

Desenvolvimento de um Controlador de Boundary Scan (Ieee 1149.1)

Mestrado em Engenharia Electrotécnica e de Computadores - Área de Especialização em Automação e Sistemas