992 resultados para motion adaptation


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Ninety-two strong-motion earthquake records from the California region, U.S.A., have been statistically studied using principal component analysis in terms of twelve important standardized strong-motion characteristics. The first two principal components account for about 57 per cent of the total variance. Based on these two components the earthquake records are classified into nine groups in a two-dimensional principal component plane. Also a unidimensional engineering rating scale is proposed. The procedure can be used as an objective approach for classifying and rating future earthquakes.

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In this paper we have used the method of characteristics developed for two dimensional unsteady flow problems to study a simplified axial turbine problem. The system consists of two sets of blades —the guiding vanes which are fixed and the rotor blades which move perpendicular to these vanes. The initial undisturbed constant flow in the system is perturbed by introducing a small velocity normal to the rotor blades to simulate a slight constant inclination. The resulting perturbed flow is periodic after the first three cycles. We have studied the perturbed density distribution throughout the system during a period.

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Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset

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In this paper, we tackle the problem of unsupervised domain adaptation for classification. In the unsupervised scenario where no labeled samples from the target domain are provided, a popular approach consists in transforming the data such that the source and target distributions be- come similar. To compare the two distributions, existing approaches make use of the Maximum Mean Discrepancy (MMD). However, this does not exploit the fact that prob- ability distributions lie on a Riemannian manifold. Here, we propose to make better use of the structure of this man- ifold and rely on the distance on the manifold to compare the source and target distributions. In this framework, we introduce a sample selection method and a subspace-based method for unsupervised domain adaptation, and show that both these manifold-based techniques outperform the cor- responding approaches based on the MMD. Furthermore, we show that our subspace-based approach yields state-of- the-art results on a standard object recognition benchmark.

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Root system characteristics are of fundamental importance to soil exploration and below-ground resource acquisition. Root architectural traits determine the in situ space-filling properties of a root system or root architecture. The growth angle of root axes is a principal component of root system architecture that has been strongly associated with acquisition efficiency in many crop species. The aims of this study were to examine the extent of genotypic variability for the growth angle and number of seminal roots in 27 current Australian and 3 CIMMYT wheat (Triticum aestivum L.) genotypes, and to quantify using fractal analysis the root system architecture of a subset of wheat genotypes contrasting in drought tolerance and seminal root characteristics. The growth angle and number of seminal roots showed significant genotypic variation among the wheat genotypes with values ranging from 36 to 56 (degrees) and 3 to 5 (plant-1), respectively. Cluster analysis of wheat genotypes based on similarity in their seminal root characteristics resulted in four groups. The group composition reflected to some extent the genetic background and environmental adaptation of genotypes. Wheat cultivars grown widely in the Mediterranean environments of southern and western Australia generally had wider growth angle and lower number of seminal axes. In contrast, cultivars with superior performance on deep clay soils in the northern cropping region, such as SeriM82, Baxter, Babax, and Dharwar Dry exhibited a narrower angle of seminal axes. The wheat genotypes also showed significant variation in fractal dimension (D). The D values calculated for the individual segments of each root system suggested that, compared to the standard cultivar Hartog, the drought-tolerant genotypes adapted to the northern region tended to distribute relatively more roots in the soil volume directly underneath the plant. These findings suggest that wheat root system architecture is closely linked to the angle of seminal root axes at the seedling stage. The implications of genotypic variation in the seminal root characteristics and fractal dimension for specific adaptation to drought environment types are discussed with emphasis on the possible exploitation of root architectural traits in breeding for improved wheat cultivars for water-limited environments.

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For the problem of speaker adaptation in speech recognition, the performance depends on the availability of adaptation data. In this paper, we have compared several existing speaker adaptation methods, viz. maximum likelihood linear regression (MLLR), eigenvoice (EV), eigenspace-based MLLR (EMLLR), segmental eigenvoice (SEV) and hierarchical eigenvoice (HEV) based methods. We also develop a new method by modifying the existing HEV method for achieving further performance improvement in a limited available data scenario. In the sense of availability of adaptation data, the new modified HEV (MHEV) method is shown to perform better than all the existing methods throughout the range of operation except the case of MLLR at the availability of more adaptation data.

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Better understanding of root system structure and function is critical to crop improvement in water-limited environments. The aims of this study were to examine root system characteristics of two wheat genotypes contrasting in tolerance to water limitation and to assess the functional implications on adaptation to water-limited environments of any differences found. The drought tolerant barley variety, Mackay, was also included to allow inter-species comparison. Single plants were grown in large, soil-filled root-observation chambers. Root growth was monitored by digital imaging and water extraction was measured. Root architecture differed markedly among the genotypes. The drought-tolerant wheat (cv. SeriM82) had a compact root system, while roots of barley cv. Mackay occupied the largest soil volume. Relative to the standard wheat variety (Hartog), SeriM82 had a more uniform rooting pattern and greater root length at depth. Despite the more compact root architecture of SeriM82, total water extracted did not differ between wheat genotypes. To quantify the value of these adaptive traits, a simulation analysis was conducted with the cropping system model APSIM, for a wide range of environments in southern Queensland, Australia. The analysis indicated a mean relative yield benefit of 14.5% in water-deficit seasons. Each additional millimetre of water extracted during grain filling generated an extra 55 kg ha-1 of grain yield. The functional implications of root traits on temporal patterns and total amount of water capture, and their importance in crop adaptation to specific water-limited environments, are discussed.

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The critical stream power criterion may be used to describe the incipient motion of cohesionless particles of plane sediment beds. The governing equation relating ``critical stream power'' to ``shear Reynolds number'' is developed by using the present experimental data as well as the data from several other sources. Simultaneously, a resistance equation, relating the ``particle Reynolds number'' to the``shear Reynolds number'' is developed for plane sediment beds in wide channels with little or no transport. By making use of these relations, a procedure is developed to design plane sediment beds such that any two of the four design variables, including particle size, energy/friction slope, flow depth, and discharge per unit width in the channel should be known to predict the remaining two variables. Finally, a straightforward design procedure using design tables/design curves and analytical methods is presented to solve six possible design problems.

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Introduction Markerless motion capture systems are relatively new devices that can significantly speed up capturing full body motion. A precision of the assessment of the finger’s position with this type of equipment was evaluated at 17.30 ± 9.56 mm when compare to an active marker system [1]. The Microsoft Kinect was proposed to standardized and enhanced clinical evaluation of patients with hemiplegic cerebral palsy [2]. Markerless motion capture systems have the potential to be used in a clinical setting for movement analysis, as well as for large cohort research. However, the precision of such system needs to be characterized. Global objectives • To assess the precision within the recording field of the markerless motion capture system Openstage 2 (Organic Motion, NY). • To compare the markerless motion capture system with an optoelectric motion capture system with active markers. Specific objectives • To assess the noise of a static body at 13 different location within the recording field of the markerless motion capture system. • To assess the smallest oscillation detected by the markerless motion capture system. • To assess the difference between both systems regarding the body joint angle measurement. Methods Equipment • OpenStage® 2 (Organic Motion, NY) o Markerless motion capture system o 16 video cameras (acquisition rate : 60Hz) o Recording zone : 4m * 5m * 2.4m (depth * width * height) o Provide position and angle of 23 different body segments • VisualeyezTM VZ4000 (PhoeniX Technologies Incorporated, BC) o Optoelectric motion capture system with active markers o 4 trackers system (total of 12 cameras) o Accuracy : 0.5~0.7mm Protocol & Analysis • Static noise: o Motion recording of an humanoid mannequin was done in 13 different locations o RMSE was calculated for each segment in each location • Smallest oscillation detected: o Small oscillations were induced to the humanoid mannequin and motion was recorded until it stopped. o Correlation between the displacement of the head recorded by both systems was measured. A corresponding magnitude was also measured. • Body joints angle: o Body motion was recorded simultaneously with both systems (left side only). o 6 participants (3 females; 32.7 ± 9.4 years old) • Tasks: Walk, Squat, Shoulder flexion & abduction, Elbow flexion, Wrist extension, Pronation / supination (not in results), Head flexion & rotation (not in results), Leg rotation (not in results), Trunk rotation (not in results) o Several body joint angles were measured with both systems. o RMSE was calculated between signals of both systems. Results Conclusion Results show that the Organic Motion markerless system has the potential to be used for assessment of clinical motor symptoms or motor performances However, the following points should be considered: • Precision of the Openstage system varied within the recording field. • Precision is not constant between limb segments. • The error seems to be higher close to the range of motion extremities.

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Soft-leaf buffalo grass is increasing in popularity as an amenity turfgrass in Australia. This project was instigated to assess the adaptation of and establish management guidelines for its use in Australias vast array of growing environments. There is an extensive selection of soft-leaf buffalo grass cultivars throughout Australia and with the countrys changing climates from temperate in the south to tropical in the north not all cultivars are going to be adapted to all regions. The project evaluated 19 buffalo grass cultivars along with other warm-season grasses including green couch, kikuyu and sweet smother grass. The soft-leaf buffalo grasses were evaluated for their growth and adaptation in a number of regions throughout Australia including Western Australia, Victoria, ACT, NSW and Queensland. The growth habit of the individual cultivars was examined along with their level of shade tolerance, water use, herbicide tolerance, resistance to wear, response to nitrogen applications and growth potential in highly alkaline (pH) soils. The growth habit of the various cultivars currently commercially available in Australia differs considerably from the more robust type that spreads quicker and is thicker in appearance (Sir Walter, Kings Pride, Ned Kelly and Jabiru) to the dwarf types that are shorter and thinner in appearance (AusTine and AusDwarf). Soft-leaf buffalo grass types tested do not differ in water use when compared to old-style common buffalo grass. Thus, soft-leaf buffalo grasses, like other warm-season turfgrass species, are efficient in water use. These grasses also recover after periods of low water availability. Individual cultivar differences were not discernible. In high pH soils (i.e. on alkaline-side) some elements essential for plant growth (e.g. iron and manganese) may be deficient causing turfgrass to appear pale green, and visually unacceptable. When 14 soft-leaf buffalo grass genotypes were grown on a highly alkaline soil (pH 7.5-7.9), cultivars differed in leaf iron, but not in leaf manganese, concentrations. Nitrogen is critical to the production of quality turf. The methods for applying this essential element can be manipulated to minimise the maintenance inputs (mowing) during the peak growing period (summer). By applying the greatest proportion of the turfs total nitrogen requirements in early spring, peak summer growth can be reduced resulting in a corresponding reduction in mowing requirements. Soft-leaf buffalo grass cultivars are more shade and wear tolerant than other warm-season turfgrasses being used by homeowners. There are differences between the individual buffalo grass varieties however. The majority of types currently available would be classified as having moderate levels of shade tolerance and wear reasonably well with good recovery rates. The impact of wear in a shaded environment was not tested and there is a need to investigate this as this is a typical growing environment for many homeowners. The use of herbicides is required to maintain quality soft-leaf buffalo grass turf. The development of softer herbicides for other turfgrasses has seen an increase in their popularity. The buffalo grass cultivars currently available have shown varying levels of susceptibility to the chemicals tested. The majority of the cultivars evaluated have demonstrated low levels of phytotoxicity to the herbicides chlorsulfuron (Glean) and fluroxypyr (Starane and Comet). In general, soft leaf buffalo grasses are varied in their makeup and have demonstrated varying levels of tolerance/susceptibility/adaptation to the conditions they are grown under. Consequently, there is a need to choose the cultivar most suited to the environment it is expected to perform in and the management style it will be exposed to. Future work is required to assess how the structure of the different cultivars impacts on their capacity to tolerate wear, varying shade levels, water use and herbicide tolerance. The development of a growth model may provide the solution.

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Red blood cells (RBCs) are the most common type of blood cells in the blood and 99% of the blood cells are RBCs. During the circulation of blood in the cardiovascular network, RBCs squeeze through the tiny blood vessels (capillaries). They exhibit various types of motions and deformed shapes, when flowing through these capillaries with diameters varying between 5 10 µm. RBCs occupy about 45 % of the whole blood volume and the interaction between the RBCs directly influences on the motion and the deformation of the RBCs. However, most of the previous numerical studies have explored the motion and deformation of a single RBC when the interaction between RBCs has been neglected. In this study, motion and deformation of two 2D (two-dimensional) RBCs in capillaries are comprehensively explored using a coupled smoothed particle hydrodynamics (SPH) and discrete element method (DEM) model. In order to clearly model the interactions between RBCs, only two RBCs are considered in this study even though blood with RBCs is continuously flowing through the blood vessels. A spring network based on the DEM is employed to model the viscoelastic membrane of the RBC while the inside and outside fluid of RBC is modelled by SPH. The effect of the initial distance between two RBCs, membrane bending stiffness (Kb) of one RBC and undeformed diameter of one RBC on the motion and deformation of both RBCs in a uniform capillary is studied. Finally, the deformation behavior of two RBCs in a stenosed capillary is also examined. Simulation results reveal that the interaction between RBCs has significant influence on their motion and deformation.

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In this paper we have discussed the motion of a viscous fluid with suspended particles through a curved tube of small curvature ratio. The system is treated as two separate interacting continua. Solutions for axial and secondary velocities are obtained in the form of asymptotic expansions in powers of Dean Number. The streamline pattern for the particulate phase reveals many interesting features. The influence of the particulate continium on the fluid is described by the parameter τ which depends on the density ratio of the two continua. The concentration distribution of the particles in a given cross section is determined. It is noticed that the particles move closer to the wall for certain values of the concentration and the density ratio.

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The report summarises data from a large number of trials of species with potential for use by the plantation forest industry in north-eastern Australia and provides information aimed at improving the understanding of growth rates, pest and disease risks and carbon sequestration. Data is summarised and presented at a regional level as opposed to individual trial or plot level. As well, nutritional impediments to tree growth and impacts on forest health are also reported. This report is intended to contribute to policy deliberations about developing forestry opportunities that can that can be integrated into the landscape, with particular consideration given to lower rainfall regions. There are several examples in north-eastern Australia where production forests have developed sub-optimally; this has often been due to poor selection of tree species as little information has been available. This report helps address this deficiency.

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The project uses participatory methods to engage primary producers and advisers in central Queensland, southern Queensland, and north east New South Wales on-farm trials and demonstrations to adapt mixed farming systems to changed climate conditions. The focus is adaptation to climate change but will support abatement of greenhouse gas emissions by building soil carbon, better managing soil nitrogen and soil organic carbon. Data will be collected and integrated with data from Round 1 of the Climate Change Research Program to extend industry understanding beyond a general awareness of ‘climate change’. Nitrous oxide and soil carbon data will help farmers/advisers understand the implications of climate change and develop adaptation strategies for a more sustainable, climate sensitive future.

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Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.