Delving deeper into the whorl of flower segmentation

We describe an algorithm for automatically segmenting flowers in colour photographs. This is a challenging problem because of the sheer variety of flower classes, the variability within a class and within a particular flower, and the variability of the imaging conditions – lighting, pose, foreshortening, etc.     

Attentional orienting within visual field in a lexical decision task.

The influence of spatial attention on lexical decisions to lateralized target letter-strings appearing either along with a distractor (Experiment 1) or in an otherwise empty field (Experiments 2–6) was examined. Attentional orienting was controlled by peripheral (Experiments 1, 2, 3, and 6) and central (Experiments 4–5) cuing methods. Manipulations of spatial attention, including cue validity and cue–target stimulus onset asynchrony, were combined with manipulations of word frequency in Experiments 3-6. All the attentional manipulations were effective, but they did not modify the right visual field advantage in word performance, In addition, the attentional effects did not interact with either the presence or absence of distractors or with stimulus familiarity. Implications of these results regarding the influence of spatial attention (the posterior attention system) on word processing are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Stable superhydrophobic surfaces induced by dual-scale topography on SU-8

SU-8 is a photosensitive resist widely used for the fabrication of MEMS and lab-on-a-chip devices, as well as of model structures for testing wetting theories. In this work, superhydrophobic surfaces are fabricated on SU-8 by combining micro- and nano-sized structures formed by means of lithography and plasma etching, respectively. It is found that nanotexturing of the micropatterned SU-8 surfaces is essential in enhancing surface hydrophobicity and rendering the surfaces water repellent (i.e. minimizing contact angle hysteresis). The proposed method will be shown to be of paramount importance for the fabrication of mechanically stable and robust superhydrophobic SU-8 surfaces with low aspect ratio microstructuring.     

Software-programmable digital pre-distortion on new generation FPGAs

In this paper we present a software programmable design flow that facilitates the implementation and integration of efficient digital pre-distortion (DPD) solutions on the leading-edge field programmable gate arrays, combining industry-standard embedded processors and programmable logic fabric into one chip. In addition to software programmability, another key contribution of this design flow is the flexible partitioning of functionality among the hardware and software components, depending on the complexity of the DPD parameter estimation algorithm in use. We have applied processor-specific optimizations to the software implementation and used Vivado high-level synthesis (HLS) tool as the design tool for the programmable logic. Furthermore, we have compared two different techniques for the integration of hardware and software components, where we have chosen the one with better area/latency trade-off. We present a comprehensive study reporting the DPD parameter update times when exploring the partitioning of the functionality among hardware and software. For low-complexity algorithms, we show that a software-only solution is applicable after carrying out the processor-specific software optimizations. For higher-complexity algorithms, we use Vivado HLS to accelerate the time-consuming blocks in the programmable logic, leading to a speed-up factor of up to 7× in the overall algorithm execution time. We present the performance results for two target devices. We also show that our accelerators use only a small portion of the programmable logic fabric on these devices and that a significant reduction of the system’s energy consumption can be obtained by leveraging the FPGA fabric.     

System-level power-performance tradeoffs for reconfigurable computing

In this paper, we propose a configuration-aware data-partitioning approach for reconfigurable computing. We show how the reconfiguration overhead impacts the data-partitioning process. Moreover, we explore the system-level power-performance tradeoffs available when implementing streaming embedded applications on fine-grained reconfigurable architectures. For a certain group of streaming applications, we show that an efficient hardware/software partitioning algorithm is required when targeting low power. However, if the application objective is performance, then we propose the use of dynamically reconfigurable architectures. We propose a design methodology that adapts the architecture and algorithms to the application requirements. The methodology has been proven to work on a real research platform based on Xilinx devices. Finally, we have applied our methodology and algorithms to the case study of image sharpening, which is required nowadays in digital cameras and mobile phones.     

Surface Reconstruction from Unstructured 3D Data

Building 3 0 models from unstructured data is a problem that arises increasingly as new 30 scanning technology is able to produce large and complex databases of full 3 0 information. Huge efforts put into segmenting entire sets of 20 images demand robust tools that are then able to reconstruct any arbitrary 30 surface segmented from the images. In this paper we propose an algorithmic methodology that automatically produces a surface from a set of points in ?³ about which we have no topological knowledge. Our method uses a spatial decomposition and a surface tracking algorithm to produce a rough approximation S' of the unknown manifold S. The produced surface S' serves as a robust initialisation for a physically based modeling technique that yields the fine details of S and so improves the quality of the reconstruction.     

Mercury content of some marine fish from the southern Caribbean Sea

The mercury concentration in muscle and liver of 63 specimens, comprising 17 species of edible fish from coastal waters of the Caribbean Sea near Cumaná, was determined by cold vapour atomic absorption spectrophotometry. The Hg content of edible muscle tissue, expressed on a fresh weight basis, varied from 0.048 microgram g-1 in lisa (Mugil curema) to 0.190 microgram g-1 in tajali (Trichiurus lepturus), with an average value of 0.096 +/- 0.042 microgram g-1. The corresponding values for liver varied from 0.135 microgram g-1 in lebranche (Mugil brasiliensis) to 0.361 micrograms g-1 in tajali (Trichiurus lepturus), with an average value of 0.269 +/- 0.059 microgram g-1. Of the 17 species analysed, seven had a mercury concentration greater than 0.10 microgram g-1 and the remainder contained less than 0.08 microgram g-1 in edible muscle tissue.