Improved 2-D vector field reconstruction using virtual sensors and the Radon transform

This paper describes a method that allows one to recover both components of a 2-D vector field based on boundary information only, by solving a system of linear equations. The analysis is carried out in the digital domain and takes advantage of the redundancy in the boundary data, since these may be viewed as weighted sums of the local vector field’s Cartesian components. Furthermore, a sampling of lines is used in order to combine the available measurements along continuous tracing lines with the digitised 2-D space where the solution is sought. A significant enhancement in the performance of the proposed algorithm is achieved by using, apart from real data, also boundary data obtained at virtual sensors. The potential of the proposed method is demonstrated by presenting an example of vector field reconstruction

Virtual sensors for 2D vector field tomography

We consider the application of tomography to the reconstruction of 2-D vector fields. The most convenient sensor configuration in such problems is the regular positioning along the domain boundary. However, the most accurate reconstructions are obtained by sampling uniformly the Radon parameter domain rather than the border of the reconstruction domain. This dictates a prohibitively large number of sensors and impractical sensor positioning. In this paper, we propose uniform placement of the sensors along the boundary of the reconstruction domain and interpolation of the measurements for the positions that correspond to uniform sampling in the Radon domain. We demonstrate that when the cubic spline interpolation method is used, a 60 times reduction in the number of sensors may be achieved with only about 10% increase in the error with which the vector field is estimated. The reconstruction error by using the same sensors and ignoring the necessity of uniform sampling in the Radon domain is in fact higher by about 30%. The effects of noise are also examined

Design and evaluation of parallel hashing over large-scale data

High-performance analytical data processing systems often run on servers with large amounts of memory. A common data structure used in such environment is the hash tables. This paper focuses on investigating efficient parallel hash algorithms for processing large-scale data. Currently, hash tables on distributed architectures are accessed one key at a time by local or remote threads while shared-memory approaches focus on accessing a single table with multiple threads. A relatively straightforward “bulk-operation” approach seems to have been neglected by researchers. In this work, using such a method, we propose a high-level parallel hashing framework, Structured Parallel Hashing, targeting efficiently processing massive data on distributed memory. We present a theoretical analysis of the proposed method and describe the design of our hashing implementations. The evaluation reveals a very interesting result - the proposed straightforward method can vastly outperform distributed hashing methods and can even offer performance comparable with approaches based on shared memory supercomputers which use specialized hardware predicates. Moreover, we characterize the performance of our hash implementations through extensive experiments, thereby allowing system developers to make a more informed choice for their high-performance applications

Efficiently Handling Skew in Outer Joins on Distributed Systems

Outer joins are ubiquitous in databases and big data systems. The question of how best to execute outer joins in large parallel systems is particularly challenging as real world datasets are characterized by data skew leading to performance issues. Although skew handling techniques have been extensively studied for inner joins, there is little published work solving the corresponding problem for parallel outer joins. Conventional approaches to this problem such as ones based on hash redistribution often lead to load balancing problems while duplication-based approaches incurs significant overhead in terms of network communication. In this paper, we propose a new algorithm, query with counters (QC), for directly handling skew in outer joins on distributed architectures. We present an efficient implementation of our approach based on the asynchronous partitioned global address space (APGAS) parallel programming model. We evaluate the performance of our approach on a cluster of 192 cores (16 nodes) and datasets of 1 billion tuples with different skew. Experimental results show that our method is scalable and, in cases of high skew, faster than the state-of-the-art

Mobile Cloud Support for Semantic-Enriched Speech Recognition in Social Care

Nowadays, most users carry high computing power mobile devices where speech recognition is certainly one of the main technologies available in every modern smartphone, although battery draining and application performance (resource shortage) have a big impact on the experienced quality. Shifting applications and services to the cloud may help to improve mobile user satisfaction as demonstrated by several ongoing efforts in the mobile cloud area. However, the quality of speech recognition is still not sufficient in many complex cases to replace the common hand written text, especially when prompt reaction to short-term provisioning requests is required. To address the new scenario, this paper proposes a mobile cloud infrastructure to support the extraction of semantics information from speech recognition in the Social Care domain, where carers have to speak about their patients conditions in order to have reliable notes used afterward to plan the best support. We present not only an architecture proposal, but also a real prototype that we have deployed and thoroughly assessed with different queries, accents, and in presence of load peaks, in our experimental mobile cloud Platform as a Service (PaaS) testbed based on Cloud Foundry

NREM Sleep Parasomnias Commencing in Childhood:Trauma and Atopy as Perpetuating Factors

Objective/Background: Phenotyping of non-rapid-eye-movement (NREM) parasomnias is currently poorly undertaken. This study aimed to determine whether there are differences phenotypically among childhood-, adolescent-, and adult-onset NREM parasomnias continuing into and presenting in adulthood. Patients/Methods: A retrospective, cohort study of patients presenting with NREM parasomnia between 2008 and 2019 (n = 307) was conducted. Disorders included sleepwalking (n = 231), night terrors (n = 150), sexualised behaviour in sleep (n = 50), and sleep-related eating disorder (n = 28). Results: Compared to the adult-onset NREM behaviours group, the childhood- and adolescent-onset groups were more likely to have a family history of NREM behaviours (p < 0.001), experience a greater spectrum of NREM disorders (p = 0.001), and report a history of sleep-talking significantly more frequently (p = 0.014). Atopy was most prevalent in the childhood-onset group (p = 0.001). Those with childhood-onset NREM parasomnias were significantly more likely to arouse from N3 sleep on video polysomnography (p = 0.0003). Psychiatric disorders were more likely to be comorbid in the adult-onset group (p = 0.012). A history of trauma coinciding with onset of NREM behaviours was significantly more common in the childhood- and adolescent-onset groups (p < 0.001). Conclusions: Significant differences exist across childhood-, adolescent-, and adult-onset NREM parasomnia presenting in adulthood. This study suggests that adult-onset slow-wave sleep disorders may be confounded by psychiatric disorders resulting in nocturnal sleep disruption and that unresolved traumatic life experiences perpetuate NREM disorders arising in childhood and comprise one of the strongest external risk factors for triggering and perpetuating these disorders in adolescence

A genetic linkage map of the hermaphrodite teleost fish Sparus aurata L.

The gilthead sea bream (Sparus aurata L.) is a marine fish of great importance for fisheries and aquaculture. It has also a peculiar sex-determination system, being a protandrous hermaphrodite. Here we report the construction of a first-generation genetic linkage map for S. aurata, based on 204 microsatellite markers. Twenty-six linkage groups (LG) were found. The total map length was 1241.9 cM. The ratio between sex-specific map lengths was 1:1.2 (male:female). Comparison with a preliminary radiation hybrid (RH) map reveals a good concordance, as all markers located in a single LG are located in a single RH group, except for Ad-25 and CId-31. Comparison with the Tetraodon nigroviridis genome revealed a considerable number of evolutionary conserved regions (ECRs) between the two species. The mean size of ECRs was 182 bp (sequence identity 60–90%). Forty-one ECRs have a known chromosomal location in the pufferfish genome. Despite the limited number of anchoring points, significant syntenic relationships were found. The linkage map presented here provides a robust comparative framework for QTL analysis in S. aurata and is a step toward the identification of genetic loci involved both in the determination of economically important traits and in the individual timing of sex reversal

A hybrid framework for nonlinear dynamic simulations including full-field optical measurements and image decomposition algorithms

Innovative designs of transport vehicles need to be validated in order to demonstrate reliability and provide confidence. It is normal practice to study the mechanical response of the structural elements by comparing numerical results obtained from finite element simulation models with results obtained from experiment. In this frame, the use of wholefield optical techniques has been proven successful in the validation of deformation, strain, or vibration modes. The strength of full-field optical techniques is that the entire displacement field can be acquired. The objective of this article is to integrate full-field optical measurement methodologies with state-of-the-art computational simulation techniques for nonlinear transient dynamic events. In this frame, composite car bonnet frame structures of dimensions about 1.8 m 30.8 m are considered. They have been tested in low-velocity mass-drop impact loading with impact energies ranging from 20 to 200 J. In parallel, simulation models of the car bonnet frame have been developed using layered shell elements. The Zernike shape descriptor approach was used to decompose numerical and experimental data into moments for comparison purposes. A very good agreement between numerical and experimental results was observed. Therefore, integration of numerical analysis with full-field optical measurements along with sophisticated comparison techniques can increase design reliability