827 resultados para Multiple-scale processing
Resumo:
In this paper, we propose a novel linear transmit precoding strategy for multiple-input, multiple-output (MIMO) systems employing improper signal constellations. In particular, improved zero-forcing (ZF) and minimum mean square error (MMSE) precoders are derived based on modified cost functions, and are shown to achieve a superior performance without loss of spectrum efficiency compared to the conventional linear and nonlinear precoders. The superiority of the proposed precoders over the conventional solutions are verified by both simulation and analytical results. The novel approach to precoding design is also applied to the case of an imperfect channel estimate with a known error covariance as well as to the multi-user scenario where precoding based on the nullspace of channel transmission matrix is employed to decouple multi-user channels. In both cases, the improved precoding schemes yield significant performance gain compared to the conventional counterparts.
Resumo:
BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.
Resumo:
This paper provides an overview of research on modelling of the structure–property interactions of polymer nanocomposites in manufacturing processes (stretch blow moulding and thermoforming) involving large-strain biaxial stretching of relatively thin sheets, aimed at developing computer modelling tools to help producers of materials, product designers and manufacturers exploit these materials to the full, much more quickly than could be done by experimental methods alone. The exemplar systems studied are polypropylene and polyester terephalate, with nanoclays. These were compounded and extruded into 2mm thick sheet which was then biaxially stretched at 155°C for the PP and 90 to 100°C for the PET. Mechanical properties were determined for the unstretched and stretched materials, together with TEM and XRD studies of structure. Multi-scale modelling, using representative volume elements is used to model the properties of these products.
Resumo:
UVES interstellar observations from the Paranal Observatory Project are presented for early-type stars located in the line of sight to the nearby open clusters IC 2391 (Omni Vel) and NGC 6475 (M7), with spectroscopic resolution R similar to 80 000 and signal-to-noise ratios in the Ti II (3383 angstrom), Ca II K, CH+ (4232 angstrom), Na I D and K I (7698 angstrom) lines of several hundred. The sightlines are a mixture of cluster and non-cluster objects. A total of 22 early-type stars (A and B type) are present in our sample towards IC 2391, with 21 towards NGC 6475/M7, and enable us to probe for differences in column density on scales from similar to 0.07 to 7.3 and similar to 0.05 to 4.9 pc in the respective clusters. Additionally, towards Praesepe the Na I D interstellar variation only is probed towards 13 sightlines and transverse scales of similar to 0.16-10.7 pc at R = 70 000. Towards IC 2391 variations are found in Ti II, Ca II K and Na I D column density in different sightlines of up to 0.7, 1.0 and 1.8 dex (excluding one star), respectively. This kind of variability correlates well with the Hipparcos parallax of the objects, and probes structure within the Local Bubble. For cluster-only objects the variations are 0.3, 0.3 and 0.5 dex, respectively. For the field of view towards NGC6475 the corresponding maximum variations are somewhat smaller, being 0.5, 0.3, 0.8 and 1.0 dex for Ti II, Ca II K, Na I and K I, respectively, for all objects and 0.4, 0.2, 0.6 and 0.7 dex for the cluster-only objects. These are uncorrelated with parallax, and again demonstrate that Ca II K tends to be more smoothly distributed than Na I D. A few likely cluster sightlines show evidence for CH+ and variations in this molecular species of a factor of 10 in equivalent width over sub-pc scales. Towards Praesepe variation in interstellar Na I D is small, being a maximum of only similar to 0.4 dex (including measurement errors), but with fewer sightlines studied. Overall, the scatter in the data is similar for the singly ionized species Ti II and Ca II, lending more support to the hypothesis that these two species sample similar parts of the interstellar medium (ISM). This also appears to be the case for the neutral species Na I D and K I in the one cluster studied. Finally, multiple-epoch observations from a variety of archive sources are used to search for astronomical unit (au) scale structure in the ISM towards 46 sightlines. There are tentative indications of structure on scales of tens to thousands of au for three sightlines. Future observations will confirm the veracity or otherwise of the time-variable components and others presented.
Resumo:
The Cell Broadband Engine (BE) Architecture is a new heterogeneous multi-core architecture targeted at compute-intensive workloads. The architecture of the Cell BE has several features that are unique in high-performance general-purpose processors, most notably the extensive support for vectorization, scratch pad memories and explicit programming of direct memory accesses (DMAs) and mailbox communication. While these features strongly increase programming complexity, it is generally claimed that significant speedups can be obtained by using Cell BE processors. This paper presents our experiences with using the Cell BE architecture to accelerate Clustal W, a bio-informatics program for multiple sequence alignment. We report on how we apply the unique features of the Cell BE to Clustal W and how important each is in obtaining high performance. By making extensive use of vectorization and by parallelizing the application across all cores, we demonstrate a speedup of 24.4 times when using 16 synergistic processor units on a QS21 Cell Blade compared to single-thread execution on the power processing unit. As the Cell BE exploits a large number of slim cores, our highly optimized implementation is just 3.8 times faster than a 3-thread version running on an Intel Core2 Duo, as the latter processor exploits a small number of fat cores.
Resumo:
The increasing demand for fast air transportation around the clock
has increased the number of night flights in civil aviation over
the past few decades. In night aviation, to land an aircraft, a
pilot needs to be able to identify an airport. The approach
lighting system (ALS) at an airport is used to provide
identification and guidance to pilots from a distance. ALS
consists of more than $100$ luminaires which are installed in a
defined pattern following strict guidelines by the International
Civil Aviation Organization (ICAO). ICAO also has strict
regulations for maintaining the performance level of the
luminaires. However, once installed, to date there is no automated
technique by which to monitor the performance of the lighting. We
suggest using images of the lighting pattern captured using a camera
placed inside an aircraft. Based on the information contained
within these images, the performance of the luminaires has to be
evaluated which requires identification of over $100$ luminaires
within the pattern of ALS image. This research proposes analysis
of the pattern using morphology filters which use a variable
length structuring element (VLSE). The dimension of the VLSE changes
continuously within an image and varies for different images.
A novel
technique for automatic determination of the VLSE is proposed and
it allows successful identification of the luminaires from the
image data as verified through the use of simulated and real data.
Resumo:
Sphere Decoding (SD) is a highly effective detection technique for Multiple-Input Multiple-Output (MIMO) wireless communications receivers, offering quasi-optimal accuracy with relatively low computational complexity as compared to the ideal ML detector. Despite this, the computational demands of even low-complexity SD variants, such as Fixed Complexity SD (FSD), remains such that implementation on modern software-defined network equipment is a highly challenging process, and indeed real-time solutions for MIMO systems such as 4 4 16-QAM 802.11n are unreported. This paper overcomes this barrier. By exploiting large-scale networks of fine-grained softwareprogrammable processors on Field Programmable Gate Array (FPGA), a series of unique SD implementations are presented, culminating in the only single-chip, real-time quasi-optimal SD for 44 16-QAM 802.11n MIMO. Furthermore, it demonstrates that the high performance software-defined architectures which enable these implementations exhibit cost comparable to dedicated circuit architectures.
Resumo:
To enable reliable data transfer in next generation Multiple-Input Multiple-Output (MIMO) communication systems, terminals must be able to react to fluctuating channel conditions by having flexible modulation schemes and antenna configurations. This creates a challenging real-time implementation problem: to provide the high performance required of cutting edge MIMO standards, such as 802.11n, with the flexibility for this behavioural variability. FPGA softcore processors offer a solution to this problem, and in this paper we show how heterogeneous SISD/SIMD/MIMD architectures can enable programmable multicore architectures on FPGA with similar performance and cost as traditional dedicated circuit-based architectures. When applied to a 4×4 16-QAM Fixed-Complexity Sphere Decoder (FSD) detector we present the first soft-processor based solution for real-time 802.11n MIMO.
Resumo:
Real time digital signal processing requires the development of high performance arithmetic algorithms suitable for VLSI design. In this paper, a new online, circular coordinate system CORDIC algorithm is described, which has a constant scale factor. This algorithm was developed using a new Angular Representation (AR) model A radix 2 version of the CORDIC algorithm is presented, along with an architecture suitable for VLSI implementation.
Resumo:
The effect of superficial air velocity on lovastatin production by Aspergillus terreus PL10 using wheat bran and wheat straw was investigated in a 7 l and a 1200 l packed bed reactor. Mass transfer and reaction limitations on bioconversion in the 1200 l reactor was studied based on a central composite design of experiments constructed using the superficial air velocity and solid substrate composition as variables and lovastatin production as response.
The surface response prediction showed a maximum lovastatin production of 1.86 mg g-1 dry substrate on day 5 of the bioconversion process when the reactor was operated using 0.19 vvm airflow rate (23.37 cm min-1 superficial air velocity) and 54% substrate composition (wC). Lovastatin production did not increase significantly with superficial air velocity in the 7 l reactor. Variation in temperature and exit CO2 composition was recorded, and the Damköhler number was calculated for lovastatin production at these two scales. The results showed that in larger reactors mass transfer limitation controlled bioconversion while in smaller reactors bioconversion was controlled by reaction rate limitations. In addition, mass transfer limitations in larger reactors reduced the rate of metabolic heat removal, resulting in hot spots within the substrate bed.
Resumo:
Accurate conceptual models of groundwater systems are essential for correct interpretation of monitoring data in catchment studies. In surface-water dominated hard rock regions, modern ground and surface water monitoring programmes often have very high resolution chemical, meteorological and hydrological observations but lack an equivalent emphasis on the subsurface environment, the properties of which exert a strong control on flow pathways and interactions with surface waters. The reasons for this disparity are the complexity of the system and the difficulty in accurately characterising the subsurface, except locally at outcrops or in boreholes. This is particularly the case in maritime north-western Europe, where a legacy of glacial activity, combined with large areas underlain by heterogeneous igneous and metamorphic bedrock, make the structure and weathering of bedrock difficult to map or model. Traditional approaches which seek to extrapolate information from borehole to field-scale are of limited application in these environments due to the high degree of spatial heterogeneity. Here we apply an integrative and multi-scale approach, optimising and combining standard geophysical techniques to generate a three-dimensional geological conceptual model of the subsurface in a catchment in NE Ireland. Available airborne LiDAR, electromagnetic and magnetic data sets were analysed for the region. At field-scale surface geophysical methods, including electrical resistivity tomography, seismic refraction, ground penetrating radar and magnetic surveys, were used and combined with field mapping of outcrops and borehole testing. The study demonstrates how combined interpretation of multiple methods at a range of scales produces robust three-dimensional conceptual models and a stronger basis for interpreting groundwater and surface water monitoring data.