Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

Bioactive Gyroid Scaffolds Formed by Sacrificial Templating of Nanocellulose and Nanochitin Hydrogels as Instructive Platforms for Biomimetic Tissue Engineering

A sacrificial templating process using lithographically printed minimal surface structures allows complex de novo geometries of delicate hydrogel materials. The hydrogel scaffolds based on cellulose and chitin nanofibrils show differences in terms of attachment of human mesenchymal stem cells, and allow their differentiation into osteogenic outcomes. The approach here serves as a first example toward designer hydrogel scaffolds viable for biomimetic tissue engineering.

LC- HRMS based metabolomics in food safety and doping control – DeTECH21

Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

Lanthanide luminescent logic gate mimics in soft matter: [H(+)] and [F(-)] dual-input device in a polymer gel with potential for selective component release

The non-covalent incorporation of responsive luminescent lanthanide, Ln(iii), complexes with orthogonal outputs from Eu(iii) and Tb(iii) in a gel matrix allows for in situ logic operation with colorimetric outputs. Herein, we report an exemplar system with two inputs ([H(+)] and [F(-)]) within a p(HEMA-co-MMA) polymer organogel acting as a dual-responsive device and identify future potential for such systems.

FPGA Soft-core Processors, Compiler and Hardware Optimizations validated using HOG

There is demand for an easily programmable, high performance image processing platform based on FPGAs. In previous work, a novel, high performance processor - IPPro was developed and a Histogram of Orientated Gradients (HOG) algorithm study undertaken on a Xilinx Zynq platform. Here, we identify and explore a number of mapping strategies to improve processing efficiency for soft-cores and a number of options for creation of a division coprocessor. This is demonstrated for the revised high definition HOG implementation on a Zynq platform, resulting in a performance of 328 fps which represents a 146% speed improvement over the original realization and a tenfold reduction in energy.

Soft-core Stream Processor for Sliding Window Applications

Software-programmable `soft' processors have shown tremendous potential for efficient realisation of high performance signal processing operations on Field Programmable Gate Array (FPGA), whilst lowering the design burden by avoiding the need to design fine-grained custom circuit archi-tectures. However, the complex data access patterns, high memory bandwidth and computational requirements of sliding window applications, such as Motion Estimation (ME) and Matrix Multiplication (MM), lead to low performance, inefficient soft processor realisations. This paper resolves this issue, showing how by adding support for block data addressing and accelerators for high performance loop execution, performance and resource efficiency over four times better than current best-in-class metrics can be achieved. In addition, it demonstrates the first recorded real-time soft ME estimation realisation for H.263 systems.

Soft-core Stream Processing on FPGA: An FFT Case Study

The increasing design complexity associated with modern Field Programmable Gate Array (FPGA) has prompted the emergence of 'soft'-programmable processors which attempt to replace at least part of the custom circuit design problem with a problem of programming parallel processors. Despite substantial advances in this technology, its performance and resource efficiency for computationally complex operations remains in doubt. In this paper we present the first recorded implementation of a softcore Fast-Fourier Transform (FFT) on Xilinx Virtex FPGA technology. By employing a streaming processing architecture, we show how it is possible to achieve architectures which offer 1.1 GSamples/s throughput and up to 19 times speed-up against the Xilinx Radix-2 FFT dedicated circuit with comparable cost.

The Portuguese continental shelf soft-bottom benthic habitats

As comunidades de macrofauna bentónica são ecológica e economicamente relevantes, sendo fonte de diversos bens e serviços. A sua identificação, caracterização e mapeamento são importantes para identificar áreas marinhas protegidas e para uma melhor utilização do ambiente marinho. Este trabalho apresenta um estudo holístico da diversidade e distribuição espacial das comunidades de macrofauna bentónica ao longo da plataforma continental Portuguesa. Cerca de 145 locais posicionados ao longo da plataforma ocidental e setentrional foram amostrados com uma draga Smith-McIntyre de área 0,1 m2, a profundidades que variaram entre os 13 e 195 metros. Os sedimentos foram caracterizados em termos de granulometria, de matéria orgânica e geoquímica. São propostos seis habitats bentónicos principais para a plataforma continental Portuguesa, analisada a relação entre os dados biológicos e ambientais e discutidas questões biogeográficas relacionadas com a distribuição espacial de espécies e das comunidades. A distribuição da granulometria e assinatura geoquímica dos sedimentos da plataforma continental revelou-se bastante complexa, refletindo importantes diferenças nas fontes (naturais e antropogénicas), origem fluvial, geomorfologia da plataforma, hidrodinamismo e atividade biológica. Relativamente à macrofauna, entre os mais de 30 mil indivíduos recolhidos, foram identificados cerca de 737 taxa, dos quais quatro são novas espécies e aproximadamente 40 correspondem a primeiras ocorrências para a costa Portuguesa. As espécies mais frequentes foram a Ampharete finmarchica, Ampelisca sp. e Lumbrineris lusitanica sp. nov. enquanto as mais abundantes foram Mediomastus fragilis, Polygordius appendiculatus e Ampharete finmarchica. A abundância por local de amostragem variou entre 7 e 1.307 espécimens e a diversidade alfa atingiu um máximo de 96 taxa. Os sedimentos mais grosseiros apresentaram maior diversidade e abundância comparativamente com os sedimentos envasados. Foram identificados seis habitats bentónicos na plataforma continental Portuguesa: (a) sedimentos grosseiros com Protodorvillea kefersteini, Pisione remota, Angulus pygmaeus e várias espécies intersticiais; (b) areias finas hidrodinamicamente expostas e próximas da linha de costa com Magelona johnstoni, Urothoe pulchella e Angulus fabula; (c) comunidade de Abra alba em areia envasadas da plataforma profunda do noroeste; (d) Galathowenia oculata, Lumbrinerides amoureuxi e outros poliquetas escavadores e tubícolas em areais envasadas muito profundas na plataforma sudoeste; (e) Euchone rubrocincta, Nematonereis unicornis e várias espécies setentrionais nas areias envasadas da plataforma sul; (f) vasas com Sternaspis scutata, Heteromastus filiformis e Psammogammarus caecus. A granulometria do sedimento (particularmente teor em finos), matéria orgânica, profundidade e hidrodinamismo foram as variáveis ambientais com a maior relação com os padrões de distribuição da macrofauna. As espécies cosmopolitas e de latitudes superiores (clima Boreal ou Temperado Frio) dominaram o setor noroeste, sendo substituídas por espécies mais quentes na área de transição entre os canhões da Nazaré e S. Vicente, que dominaram por conseguinte a plataforma sul. O presente estudo evidenciou a abundância e diversidade da macrofauna bentónica ao longo da área costeira de Portugal, na qual coexistem faunas das províncias biogeográficas do norte da Europa, bem como subtropicais. Integrado com outro estudos, este poderá ser a base para uma melhor gestão da plataforma continental Portuguesa.

Electromechanical properties of engineered lead free potassium sodium niobate based materials

K0.5Na0.5NbO3 (KNN), is the most promising lead free material for substituting lead zirconate titanate (PZT) which is still the market leader used for sensors and actuators. To make KNN a real competitor, it is necessary to understand and to improve its properties. This goal is pursued in the present work via different approaches aiming to study KNN intrinsic properties and then to identify appropriate strategies like doping and texturing for designing better KNN materials for an intended application. Hence, polycrystalline KNN ceramics (undoped, non-stoichiometric; NST and doped), high-quality KNN single crystals and textured KNN based ceramics were successfully synthesized and characterized in this work. Polycrystalline undoped, non-stoichiometric (NST) and Mn doped KNN ceramics were prepared by conventional ceramic processing. Structure, microstructure and electrical properties were measured. It was observed that the window for mono-phasic compositions was very narrow for both NST ceramics and Mn doped ceramics. For NST ceramics the variation of A/B ratio influenced the polarization (P-E) hysteresis loop and better piezoelectric and dielectric responses could be found for small stoichiometry deviations (A/B = 0.97). Regarding Mn doping, as compared to undoped KNN which showed leaky polarization (P-E) hysteresis loops, B-site Mn doped ceramics showed a well saturated, less-leaky hysteresis loop and a significant properties improvement. Impedance spectroscopy was used to assess the role of Mn and a relation between charge transport – defects and ferroelectric response in K0.5Na0.5NbO3 (KNN) and Mn doped KNN ceramics could be established. At room temperature the conduction in KNN which is associated with holes transport is suppressed by Mn doping. Hence Mn addition increases the resistivity of the ceramic, which proved to be very helpful for improving the saturation of the P-E loop. At high temperatures the conduction is dominated by the motion of ionized oxygen vacancies whose concentration increases with Mn doping. Single crystals of potassium sodium niobate (KNN) were grown by a modified high temperature flux method. A boron-modified flux was used to obtain the crystals at a relatively low temperature. XRD, EDS and ICP analysis proved the chemical and crystallographic quality of the crystals. The grown KNN crystals exhibit higher dielectric permittivity (29,100) at the tetragonal-to-cubic phase transition temperature, higher remnant polarization (19.4 μC/cm2) and piezoelectric coefficient (160 pC/N) when compared with the standard KNN ceramics. KNN single crystals domain structure was characterized for the first time by piezoforce response microscopy. It could be observed that <001> - oriented potassium sodium niobate (KNN) single crystals reveal a long range ordered domain pattern of parallel 180° domains with zig-zag 90° domains. From the comparison of KNN Single crystals to ceramics, It is argued that the presence in KNN single crystal (and absence in KNN ceramics) of such a long range order specific domain pattern that is its fingerprint accounts for the improved properties of single crystals. These results have broad implications for the expanded use of KNN materials, by establishing a relation between the domain patterns and the dielectric and ferroelectric response of single crystals and ceramics and by indicating ways of achieving maximised properties in KNN materials. Polarized Raman analysis of ferroelectric potassium sodium niobate (K0.5Na0.5)NbO3 (KNN) single crystals was performed. For the first time, an evidence is provided that supports the assignment of KNN single crystals structure to the monoclinic symmetry at room temperature. Intensities of A′, A″ and mixed A′+A″ phonons have been theoretically calculated and compared with the experimental data in dependence of crystal rotation, which allowed the precise determination of the Raman tensor coefficients for (non-leaking) modes in monoclinic KNN. In relation to the previous literature, this study clarifies that assigning monoclinic phase is more suitable than the orthorhombic one. In addition, this study is the basis for non-destructive assessments of domain distribution by Raman spectroscopy in KNN-based lead-free ferroelectrics with complex structures. Searching a deeper understanding of the electrical behaviour of both KNN single crystal and polycrystalline materials for the sake of designing optimized KNN materials, a comparative study at the level of charge transport and point defects was carried out by impedance spectroscopy. KNN single crystals showed lower conductivity than polycrystals from room temperature up to 200 ºC, but above this temperature polycrystalline KNN displays lower conductivity. The low temperature (T < 200 ºC) behaviour reflects the different processing conditions of both ceramics and single crystals, which account for less defects prone to charge transport in the case of single crystals. As temperature increases (T > 200 ºC) single crystals become more conductive than polycrystalline samples, in which grain boundaries act as barriers to charge transport. For even higher temperatures the conductivity difference between both is increased due to the contribution of ionic conduction in single crystals. Indeed the values of activation energy calculated to the high temperature range (T > 300 ºC) were 1.60 and 0.97 eV, confirming the charge transport due to ionic conduction and ionized oxygen vacancies in single crystals and polycrystalline KNN, respectively. It is suggested that single crystals with low defects content and improved electromechanical properties could be a better choice for room temperature applications, though at high temperatures less conductive ceramics may be the choice, depending on the targeted use. Aiming at engineering the properties of KNN polycrystals towards the performance of single crystals, the preparation and properties study of (001) – oriented (K0.5Na0.5)0.98Li0.02NbO3 (KNNL) ceramics obtained by templated grain growth (TGG) using KNN single crystals as templates was undertaken. The choice of KNN single crystals templates is related with their better properties and to their unique domain structure which were envisaged as a tool for templating better properties in KNN ceramics too. X-ray diffraction analysis revealed for the templated ceramics a monoclinic structure at room temperature and a Lotgering factor (f) of 40% which confirmed texture development. These textured ceramics exhibit a long range ordered domain pattern consisting of 90º and 180º domains, similar to the one observed in the single crystals. Enhanced dielectric (13017 at TC), ferroelectric (2Pr = 42.8 μC/cm2) and piezoelectric (d33 = 280 pC/N) properties are observed for textured KNNL ceramics as compared to the randomly oriented ones. This behaviour is suggested to be due to the long range ordered domain patterns observed in the textured ceramics. The obtained results as compared with the data previously reported on texture KNN based ceramics confirm that superior properties were found due to ordered repeated domain pattern. This study provides an useful approach towards properties improvement of KNN-based piezoelectric ceramics. Overall, the present results bring a significant contribution to the pool of knowledge on the properties of sodium potassium niobate materials: a relation between the domain patterns and di-, ferro-, and piezo-electric response of single crystals and ceramics was demonstrated and ways of engineering maximised properties in KNN materials, for example by texturing were established. This contribution is envisaged to have broad implications for the expanded use of KNN over the alternative lead-based materials.

Soft-computing techniques applied to artificial tissue temperature estimation

Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008