Design Methodology for Offloading Software Executions to FPGA

Field programmable gate array (FPGA) is a flexible solution for offloading part of the computations from a processor. In particular, it can be used to accelerate an execution of a computationally heavy part of the software application, e.g., in DSP, where small kernels are repeated often. Since an application code for a processor is a software, a design methodology is needed to convert the code into a hardware implementation, applicable to the FPGA. In this paper, we propose a design method, which uses the Transport Triggered Architecture (TTA) processor template and the TTA-based Co-design Environment toolset to automate the design process. With software as a starting point, we generate a RTL implementation of an application-specific TTA processor together with the hardware/software interfaces required to offload computations from the system main processor. To exemplify how the integration of the customized TTA with a new platform could look like, we describe a process of developing required interfaces from a scratch. Finally, we present how to take advantage of the scalability of the TTA processor to target platform and application-specific requirements.     

On Discriminative Bayesian Network Classifiers and Logistic Regression

Discriminative learning of the parameters in the naive Bayes model is known to be equivalent to a logistic regression problem. Here we show that the same fact holds for much more general Bayesian network models, as long as the corresponding network structure satisfies a certain graph-theoretic property. The property holds for naive Bayes but also for more complex structures such as tree-augmented naive Bayes (TAN) as well as for mixed diagnostic-discriminative structures. Our results imply that for networks satisfying our property, the conditional likelihood cannot have local maxima so that the global maximum can be found by simple local optimization methods. We also show that if this property does not hold, then in general the conditional likelihood can have local, non-global maxima. We illustrate our theoretical results by empirical experiments with local optimization in a conditional naive Bayes model. Furthermore, we provide a heuristic strategy for pruning the number of parameters and relevant features in such models. For many data sets, we obtain good results with heavily pruned submodels containing many fewer parameters than the original naive Bayes model.Editors: Pedro Larrañaga, Jose A. Lozano, Jose M. Peña and Iñaki Inza     

An 8-hour system for Salmonella detection with immunomagnetic separation and homogeneous time-resolved fluorescence PCR

We describe a system consisting of rapid sample enrichment and homogeneous end-point PCR analysis that enables the detection of Salmonella in various food matrices in 8 h. Sample preparation starts with 6 h enrichment step in supplemented broth, after which Salmonella cells are collected with immunomagnetic particles. The particles are washed and dispensed to ready-to-use PCR reaction vessels, which contain dried assay-specific reagents and an internal amplification control. PCR is performed with a novel instrument platform utilising the sensitive label technology of time-resolved fluorometry. Qualitative assay results are automatically interpreted and available in 45 min after sample addition. The overall accuracy, sensitivity and specificity of the Magda CA Salmonella system were 99.1%, 98.4% and 100.0%, respectively, based on the evaluation of 107 samples (beef, pork, poultry and ready-to-eat meals) artificially contaminated with sub-lethally injured Salmonella cells.     

Understanding maintenance work in safety-critical organisations – managing the performance variability

Human and organisational performance variability has been identified as a cause of many latent and active failures in maintenance. Seldom has the variability been considered as an integral and inherent part of the maintenance activity to be managed by organisational means. The article deals with the challenge of understanding maintenance work in safety-critical organisations. The aim is to review the current literature on maintenance work and illustrate the organisational research challenges of managing performance variability in maintenance. This article presents six major research challenges in managing performance variability in maintenance. The article concludes by noting that a holistic theory on maintenance work is needed to manage the variability and turn it into a positive force. Maintenance has the potential to produce positive performance variability and guard against negative instability in complex sociotechnical systems.     

Experimental Study on the Influence of Selected Process Variables on the Separation of a Fine Particle Suspension with a Pilot Scale Decanter Centrifuge

Decanter centrifuges are used widely in the chemical and process industries for dewatering and classification of solid-liquid suspensions. The most important applications of this class of centrifuges are found in wastewater sludge treatment and in pigment production. The objective of this study was to investigate the operation of a pilot scale decanter centrifuge in a challenging dewatering application. Dewatering tests were performed using fine-particle slurries consisting of water and various concentrations of kaolin. In addition to the solid concentration of the feed, the feed rate of the suspension and the differential speed between the bowl and the conveyer screw were also chosen as variables. The experimental conditions were selected according to a factorial test design and the responses monitored included the production capacity (productivity) of the decanter, the solid contents of the cake and the centrate, as well as the time that was required for the stabilization of the test unit. The results obtained clearly showed that the studied variables have a significant influence on the performance of the dewatering process. The variables were also able to explain the dewatering results at a high level of statistical significance. The repeatability of the experiments was, in most cases, good: On average, the relative standard deviations for the productivity and the solid contents of the cake were 6.0% and 0.5%. It was also apparent that random variations in the feed conditions may have a remarkable and long-lasting impact on the operation of the centrifuge.     

A Test of Two Methods for Waste Rock Drainage Quality Prediction: Aqua Regia Extraction and Single-addition Net-acid Generation Test Leachate Analysis

Mine Water and the Environment - The mobility of contaminants from mine waste can be assessed using different extraction methods. Aqua regia (AR) extraction is the most commonly used method in...     

Statistical analysis of control parameters in evolutionary map L-systems-based topology optimization

Map L-systems-based parametrization, also referred to as the cellular division method, is a generative encoding, suitable for topology optimization. The parametrization is compact due to its ability to reuse its elements, and therefore capable of covering a large design space with relatively few design variables. Map L-systems are often evolved using genetic algorithms (GAs). A key implementation detail of such procedures, as with most GA-based geometry searches, is the choice of parameters controlling the operation of the evolutionary process. The optimal choice of these in conventional optimization formulations is highly problem-specific—far less so, however, when the GA evolves an L-systems encoding and does not act directly on the geometry. This is because the L-system encoding is, itself, independent of the geometry. We study the effects of different control parameters by conducting a statistical test of over 400 parameter combinations on five test cases, for which the global optima are known. The best-performing parameter combinations are reported as a Pareto front of the average number of objective function evaluations and ranking based on the average of optimized fitnesses. Finally, three Pareto-optimal parameter combinations are selected and applied to an optimization problem of maximizing the fundamental natural frequency of an integrally stiffened aluminum panel. The best of the resulting designs has a higher fundamental natural frequency than the baseline design by a margin of 11.2%.     

Breakdown of Zero-Energy Quantum Hall State in Graphene in the Light of Current Fluctuations and Shot Noise

We have investigated the cross-over from Zener tunneling of single charge carriers to avalanche type of bunched electron transport in a suspended graphene Corbino disk in the zeroth Landau level. At low bias, we find a tunneling current that follows the gyrotropic Zener tunneling behavior. At larger bias, we find an avalanche type of transport that sets in at a smaller current the larger the magnetic field is. The low-frequency noise indicates strong bunching of the electrons in the avalanches. On the basis of the measured low-frequency switching noise power, we deduce the characteristic switching rates of the avalanche sequence. The simultaneous microwave shot noise measurement also reveals intrinsic correlations within the avalanche pulses and indicate a decrease in correlations with increasing bias.     

MRI quality assurance based on 3D FLAIR brain images

Objective

Quality assurance (QA) of magnetic resonance imaging (MRI) often relies on imaging phantoms with suitable structures and uniform regions. However, the connection between phantom measurements and actual clinical image quality is ambiguous. Thus, it is desirable to measure objective image quality directly from clinical images.

Materials and methods

In this work, four measurements suitable for clinical image QA were presented: image resolution, contrast-to-noise ratio, quality index and bias index. The methods were applied to a large cohort of clinical 3D FLAIR volumes over a test period of 9.5 months. The results were compared with phantom QA. Additionally, the effect of patient movement on the presented measures was studied.

Results

A connection between the presented clinical QA methods and scanner performance was observed: the values reacted to MRI equipment breakdowns that occurred during the study period. No apparent correlation with phantom QA results was found. The patient movement was found to have a significant effect on the resolution and contrast-to-noise ratio values.

Discussion

QA based on clinical images provides a direct method for following MRI scanner performance. The methods could be used to detect problems, and potentially reduce scanner downtime. Furthermore, with the presented methodologies comparisons could be made between different sequences and imaging settings. In the future, an online QA system could recognize insufficient image quality and suggest an immediate re-scan.