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Surface wavepackets subject to an abrupt depth change. Part II: experimental analysis
No full textSurface gravity wavepackets in intermediate water depth experiencing an abrupt depthdecrease are investigated experimentally. The experiments provide validation for thesecond-order (in steepness) theory for narrow-banded surface gravity wavepackets experiencinga sudden depth transition derived in a companion paper (Li et al. 2020).We observe the generation of free second-order sub- and super-harmonic wavepacketsdue to the sudden depth transition, in addition to changes to the main (rst-order)wavepacket and its second-order bound waves. Locally, just after the step, this leadsto the superposition of dierent wavepacket components. Thereafter, separation occursbecause of the dierent group speeds of the free second-order sub- and super-harmonicwavepackets compared to the main packet. Experiments show that the local superpositionof waves can lead to signicant amplication of wave crests near the top of a step, aspredicted by theory. In addition to a step, we also experimentally examine more gradualdepth changes in the form of 1:1 and 1:3 slopes to explore the limits of the theory'svalidity. Although we nd small dierences in amplitude and phase comparing thesesteep slopes to a step, these experiments suggest that the theoretical model derived inLi et al. (2020) for wavepackets travelling over a step is applicable to slopes steeper than1:3
Towards Developing a Virtual Guitar Instructor through Biometrics Informed Human-Computer Interaction
No full textWithin the last few years, wearable sensor technologies have allowed us to access novel biometrics that give us the ability to connect musical gesture to computing systems. Doing this affords us to study how we perform musically and understand the process at data level. However, biometric information is complex and cannot be directly mapped to digital systems. In this work, we study how guitar performance techniques can be captured/analysed towards developing an AI which can provide real-time feedback to guitar students.We do this by performing musical exercises on the guitar whilst acquiring and processing biometric (plus audiovisual) information during their performance. Our results show: there are notable differences within biometrics when playing a guitar scale in two different ways (legato and staccato) and this outcome can be used to motivate our intention to build an AI guitar tutor.CCS Concepts: • Human-centered computing → Gestural input.Additional Key Words and Phrases: Deep learning, Biometrics, Musical performance, Guitar, Multimodal data, Game engines, EMG, HC
Genotype-phenotype associations in a large PTEN Hamartoma Tumor Syndrome (PHTS) patient cohort
No full textCases of Oral Pathologies from the First Archaeological Survey of Nubia
No full textThis study investigates three cases of oral pathology identified in skeletal and mummified remains originally excavated during the First Archaeological Survey of Nubia (1907-1911). While the Survey Team conducted an extensive analysis and published their initial findings in the first year of the Project, subsequent results were minimally documented. These remains have now been re–examined, as part of the GRAFTON ELLIOT SMITH PROJECT. The first of the cases involves a significant pathological bony cavity in the maxilla attributed to an odontogenic infection that caused perforation of the maxillary sinus. Evidence of chronic sinusitis on the innersinus wall suggests the infection persisted during the individual’s life. The second one presents features consistent with leprosy, including the distinctive rhinomaxillary syndrome, characterised by perforation of the hard palate and resorption of the alveolar bone supporting the maxillary anterior teeth. The final case focuses on a bilateral cleft palate found in an adult skull and considers the implications of survival into adulthood with this condition in an ancient societal context. These pathologies have been reassessed in the framework of recent research and discoveries made over the past century
An examination of the Spanish translation of the 50-item IPIP Big-five inventory in a Spanish speaking Peruvian sample
No full textThe International Personality Item Pool (IPIP) five-factor model inventories are widely used for personality research and have been translated into multiple languages. However, the extent of the psychometric assessment of translated scales is variable, often minimal. Here we present a structural analysis of one Spanish translation of the 50-item IPIP five-factor inventory in a sample of Peruvian non-university educated working adults (n=778). A global confirmatory factor analytic (CFA) model of the a priori five factors failed to fit. So too did single factor models for four of the five factors, the exception being Neuroticism. Fit was improved via use of an exploratory structural equation measurement model, but the resultant solution showed very poor theoretical coherence. The pattern of factor loadings suggested that the lack of coherence might be due to the effects of the valence of item wording. CFA models including five substantive factors and a series of method factors modelling shared covariance based on item wording, improved fit and coherence. This investigation suggests that unless method factors are explicitly modelled the tested Spanish translation may not be suitable for use in certain Spanish-speaking countries or samples composed of non-university educated participants
Geological Process Simulation in 3-D Lithofacies Modeling: Application in a Basin Floor Fan Setting
No full textThis work examines the impact of forward stratigraphic modeling on lithofacies representation in a 3-D volume by integrating data from geological process simulations and real well logs. The complex depositional architecture, and property variation in basin floor fan systems highlights the need for modeling techniques that capture heterogeneity to improve subsurface property prediction away from known data. Geological process simulation enhances our understanding of sediment distribution in a defined 3-D geological system. The workflow involves: (1) replication of depositional patterns in a basinal fan setting using the Geological Process Modeling (GPMTM) software, (2) lithofacies classification from sediment grain distribution, and turbid water velocity in the geological process model, and (3) generation of lithofacies proportion maps and vertical trends from simulated geobodies; to serve as an additional conditioning parameter in facies modeling. The simulation produced sediment distribution patterns, lobe switching and stacking features that are characteristic in turbidites settings. The impact on lithofacies representation was assessed using a Net-to-Gross analysis of actual and process-based sedimentological logs, with a good match found between process-based, and actual-data facies model in several well locations. These results lead us to suggest that; the geological process simulation approach can improve inter-well facies property prediction in a basin floor fan setting
3D XCT Imaging of Electrical Tree Growth in Epoxy Resin
No full textThis paper reports observations of electrical tree growth by X-ray computed tomography (XCT) in multiple steps. Growth between times of observation has been obtained by subtraction of an image from the subsequent one. Partial discharge (PD) signals were also recorded during tree growth. It is determined that not all PDs support tree extension. By comparing the energy released by PD and the vaporization energy of newly grown tree channels, it is found that only the PDs that reach the tree tips can contribute to the growth of tree length. In such cases, the efficiency of energy conversion was very high, whereas PD resulting in increases in tree channel diameter had a much lower conversion efficiency. Nano XCT images reveal many finer branches along the trunk of the main tree and in the front of the main channel tree tips. It seems that those finer branches led to tree growth, but were not directly associated with local PD. The new imaging techniques have shown great value in resolving the relationship between partial discharge activity and electrical tree growth, providing a platform for deeper understanding of the tree growth process, and interpretation of partial discharge measurements
A discrete chemo-dynamical model of M87’s globular clusters: Kinematics extending to ∼ 400 kpc
No full textWe study the mass distribution and kinematics of the giant elliptical galaxy M87 (NGC4486) using discrete chemo-dynamical, axisymmetric Jeans equation modelling. Our catalogue comprises 894 globular clusters (GCs) extending to a projected radius of ∼ 430 kpc with line-of-sight velocities and colours, and Multi Unit Spectroscopic Explorer (MUSE) integral field unit data within the central 2.4 kpc of the main galaxy. The gravitational potential for our models is a combination of a luminous matter potential with a varying mass-to-light ratio for the main galaxy, a supermassive black hole and a dark matter (DM) potential with a cusped or cored DM halo. The best-fitting models with either a cusped or a cored DM halo show no significant differences and both are acceptable. We obtain a total mass of (2.16 ± 0.38) × 10 13 M within ∼ 400 kpc. By including the stellar mass-to-light ratio gradient, the DM fraction increases maj from ∼ 26 percent (with no gradient) to ∼ 73 percent within 1 R e (major axis of half-light maj isophote, 14.2 kpc), and from ∼ 84 percent to ∼ 94 percent within 5 R e (71.2 kpc). Red GCs have moderate rotation with V max /σ ∼ 0.4, and blue GCs have weak rotation with V max /σ ∼ 0.1. Red GCs have tangential velocity dispersion anisotropy, while blue GCs are consistentwith being nearly isotropic. Our results suggest that red GCs are more likely to be born in-situ, while blue GCs are more likely to be accreted
An Interpretable Deep Architecture for Similarity Learning Built Upon Hierarchical Concepts
No full textIn general, development of adequately complex mathematical models, such as deep neural networks, can be an effective way to improve the accuracy of learning models. However, this is achieved at the cost of reduced post-hoc model interpretability, because what is learned by the model can become less intelligible and tractable to humans as the model complexity increases. In this paper, we target a similarity learning task in the context of image retrieval, with a focus on the model interpretability issue. An effective similarity neural network (SNN) is proposed to offer not only to seek robust retrieval performance but also to achieve satisfactory post-hoc interpretability. The network is designed by linking the neuron architecture with the organization of a concept tree and by formulating neuron operations to pass similarity information between concepts. Various ways of understanding and visualizing what is learned by the SNN neurons are proposed. We also exhaustively evaluate the proposed approach using a number of relevant datasets against a number of state-of-the-art approaches to demonstrate the effectiveness of the proposed network. Our results show that the proposed approach can offer superior performance when compared against state-of-the-art approaches. Neuron visualization results are demonstrated to support the understanding of the trained neurons
Formal Non-fragile Verification of Step Response Requirements for Digital State-Feedback Control Systems
No full textWe describe and evaluate a novel approach to formally verify whether a digital control system meets specifications related to step-response parameters. In particular, we obtain a state feedback controller designed for a system represented by a state-space model. Then we analyze whether its required specifications regarding settling time and maximum overshoot are met, using both open- and closed-loop forms and considering finite word-length (FWL) effects for the latter. We developed our verification approaches inside DSVerifier, which is a verification tool that employs bounded (and unbounded) model checking based on satisfiability modulo theories. Thus, DSVerifier checks performance requirements of digital control systems considering fragility, such as round-off and numerical quantization errors. Our approaches were also evaluated over a set of standard control-system benchmarks extracted from the control literature. Experimental results show that DSVerifier can check settling-time and overshoot in control systems suffering from FWL effects, while other existing approaches routinely ignore those issues.<br/