Variable density approach for rotating shallow shell of variable thickness

A new approach based on variable density in conjunction with shallow shell theory is proposed to analyse rotating shallow shell of variable thickness. Coupled non-linear ordinary differential equations governing shallows shells of variable thickness are first derived before applying the variable density approach. Results obtained from the new approach compare well with FEM calculation for a wide range of profiles considered in this paper.

Synthesis of Epitaxial Metal Oxide Nanocrystals via a Phase Separation Approach

Perovskite phase instability of BiMnO3 has been exploited to synthesize epitaxial metal oxide magnetic nanocrystals. Thin film processing conditions are tuned to promote the breakdown of the perovskite precursor into Bi2O3 matrix and magnetic manganese oxide islands. Subsequent cooling in vacuum ensures complete volatization of the Bi2O3, thus leaving behind an array of self-assembled magnetic Mn3O4 nanostructures. Both shape and size can be systematically controlled by the ambient oxygen environments and deposition time.As such, this approach can be extended to any other Bi-based complex ternary oxide system as it primarily hinges on the breakdown of parent Bi-based precursor and subsequent Bi2O3 volatization.

A Far-field Pattern Separation Approach for the Synthesis of Directional Modulation Transmitter Arrays (Invited)

In this paper a far-field power pattern separation approach is proposed for the synthesis of directional modulation (DM) transmitter arrays. Separation into information pattern and interference patterns is enabled by far-field pattern null steering. Compared with other DM synthesis methods, e.g., BER-driven DM optimization and orthogonal vector injection, this approach facilitates manipulation of artificial interference spatial distributions. With such capability more interference power can be projected into those most vulnerable to eavesdropping spatial directions in free space, i.e., the information sidelobes. In such a fashion information leaked through radiation sidelobes can be effectively mitigated in a transmitter power efficient manner. The proposed synthesis approach is further validated via bit error rate (BER) simulations.

Evaluating relative impact of virtual reality system variables on architectural design comprehension and presence - A variable-centered approach using fractional factorial experiment

The relative contributions of five variables (Stereoscopy, screen size, field of view, level of realism and level of detail) of virtual reality systems on spatial comprehension and presence are evaluated here. Using a variable-centered approach instead of an object-centric view as its theoretical basis, the contributions of these five variables and their two-way interactions are estimated through a 25-1 fractional factorial experiment (screening design) of resolution V with 84 subjects. The experiment design, procedure, measures used, creation of scales and indices, results of statistical analysis, their meaning and agenda for future research are elaborated.

Modelling of urban sensible heat flux at multiple spatial scales : a demonstration using airborne hyperspectral imagery of Shanghai and a temperature–emissivity separation approach

Urbanization related alterations to the surface energy balance impact urban warming (‘heat islands’), the growth of the boundary layer, and many other biophysical processes. Traditionally, in situ heat flux measures have been used to quantify such processes, but these typically represent only a small local-scale area within the heterogeneous urban environment. For this reason, remote sensing approaches are very attractive for elucidating more spatially representative information. Here we use hyperspectral imagery from a new airborne sensor, the Operative Modular Imaging Spectrometer (OMIS), along with a survey map and meteorological data, to derive the land cover information and surface parameters required to map spatial variations in turbulent sensible heat flux (QH). The results from two spatially-explicit flux retrieval methods which use contrasting approaches and, to a large degree, different input data are compared for a central urban area of Shanghai, China: (1) the Local-scale Urban Meteorological Parameterization Scheme (LUMPS) and (2) an Aerodynamic Resistance Method (ARM). Sensible heat fluxes are determined at the full 6 m spatial resolution of the OMIS sensor, and at lower resolutions via pixel aggregation and spatial averaging. At the 6 m spatial resolution, the sensible heat flux of rooftop dominated pixels exceeds that of roads, water and vegetated areas, with values peaking at ∼ 350 W m− 2, whilst the storage heat flux is greatest for road dominated pixels (peaking at around 420 W m− 2). We investigate the use of both OMIS-derived land surface temperatures made using a Temperature–Emissivity Separation (TES) approach, and land surface temperatures estimated from air temperature measures. Sensible heat flux differences from the two approaches over the entire 2 × 2 km study area are less than 30 W m− 2, suggesting that methods employing either strategy maybe practica1 when operated using low spatial resolution (e.g. 1 km) data. Due to the differing methodologies, direct comparisons between results obtained with the LUMPS and ARM methods are most sensibly made at reduced spatial scales. At 30 m spatial resolution, both approaches produce similar results, with the smallest difference being less than 15 W m− 2 in mean QH averaged over the entire study area. This is encouraging given the differing architecture and data requirements of the LUMPS and ARM methods. Furthermore, in terms of mean study QH, the results obtained by averaging the original 6 m spatial resolution LUMPS-derived QH values to 30 and 90 m spatial resolution are within ∼ 5 W m− 2 of those derived from averaging the original surface parameter maps prior to input into LUMPS, suggesting that that use of much lower spatial resolution spaceborne imagery data, for example from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is likely to be a practical solution for heat flux determination in urban areas.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

Precise pose recovery of distal locking holes from single calibrated fluoroscopic image via a novel variable decomposition approach

This paper presents a novel variable decomposition approach for pose recovery of the distal locking holes using single calibrated fluoroscopic image. The problem is formulated as a model-based optimal fitting process, where the control variables are decomposed into two sets: (a) the angle between the nail axis and its projection on the imaging plane, and (b) the translation and rotation of the geometrical model of the distal locking hole around the nail axis. By using an iterative algorithm to find the optimal values of the latter set of variables for any given value of the former variable, we reduce the multiple-dimensional model-based optimal fitting problem to a one-dimensional search along a finite interval. We report the results of our in vitro experiments, which demonstrate that the accuracy of our approach is adequate for successful distal locking of intramedullary nails.

New doubly periodic waves of the (2+1)-dimensional double sine-Gordon equation

New exact solutions of the (2 + 1)-dimensional double sine-Gordon equation are studied by introducing the modified mapping relations between the cubic nonlinear Klein-Gordon system and double sine-Gordon equation. Two arbitrary functions are included into the Jacobi elliptic function solutions. New doubly periodic wave solutions are obtained and displayed graphically by proper selections of the arbitrary functions.

CLOSE—A Data-Driven Approach to Speech Separation

This paper studies single-channel speech separation, assuming unknown, arbitrary temporal dynamics for the speech signals to be separated. A data-driven approach is described, which matches each mixed speech segment against a composite training segment to separate the underlying clean speech segments. To advance the separation accuracy, the new approach seeks and separates the longest mixed speech segments with matching composite training segments. Lengthening the mixed speech segments to match reduces the uncertainty of the constituent training segments, and hence the error of separation. For convenience, we call the new approach Composition of Longest Segments, or CLOSE. The CLOSE method includes a data-driven approach to model long-range temporal dynamics of speech signals, and a statistical approach to identify the longest mixed speech segments with matching composite training segments. Experiments are conducted on the Wall Street Journal database, for separating mixtures of two simultaneous large-vocabulary speech utterances spoken by two different speakers. The results are evaluated using various objective and subjective measures, including the challenge of large-vocabulary continuous speech recognition. It is shown that the new separation approach leads to significant improvement in all these measures.

Directional Modulation Far-field Pattern Separation Synthesis Approach

In this study, a far-field power pattern separation approach is proposed for the synthesis of directional modulation (DM) transmitter arrays. Separation into information patterns and interference patterns is enabled by far-field pattern null steering. Compared with other DM synthesis methods, for example, bit error rate-driven DM optimisation and orthogonal vector injection, the approach developed in this study facilitates manipulation of artificial interference spatial distributions. With such capability more interference power can be projected into those spatial directions most vulnerable to eavesdropping, that is, the information side lobes. In such a fashion, information leaked through radiation side lobes can be effectively mitigated in a transmitter power efficient manner. Furthermore, for the first time, the authors demonstrate how multi-beam DM transmitters can be synthesised via this approach.

Time-frequency approach to underdetermined blind source separation

This paper presents a new time-frequency (TF) underdetermined blind source separation approach based on Wigner-Ville distribution (WVD) and Khatri-Rao product to separate N non-stationary sources from M(M <; N) mixtures. First, an improved method is proposed for estimating the mixing matrix, where the negative value of the auto WVD of the sources is fully considered. Then after extracting all the auto-term TF points, the auto WVD value of the sources at every auto-term TF point can be found out exactly with the proposed approach no matter how many active sources there are as long as N ≤ 2M-1. Further discussion about the extraction of auto-term TF points is made and finally the numerical simulation results are presented to show the superiority of the proposed algorithm by comparing it with the existing ones.

A methodological exploration to determine transportation disadvantage variables: the partial least square approach

Determining the key variables of transportation disadvantage remains a great challenge as the variables are commonly selected using ad-hoc techniques. In order to identify the variables, this research develops a transportation disadvantage framework by manipulating the capability approach. Developed framework is statistically analysed using partial least square-based software to determine the framework fitness. The statistical analysis identifies mobility and socioeconomic variables that significantly influence transportation disadvantage. The research reveals the key socioeconomic variables for transportation disadvantage in the case of Brisbane, Australia as household structure, presence of dependent family member, vehicle ownership, and driving licence possession.

Maximising capture efficiency and specificity of magnetic separation for Mycobacterium avium subsp. paratuberculosis cells

In order to introduce specificity for Mycobacterium avium subsp. paratuberculosis prior to a phage amplification assay, various magnetic-separation approaches, involving either antibodies or peptides, were evaluated in terms of the efficiency of capture (expressed as a percentage) of M. avium subsp. paratuberculosis cells and the percentage of nonspecific binding by other Mycobacterium spp. A 50:50 mixture of MyOne Tosylactivated Dynabeads coated with the chemically synthesized M. avium subsp. paratuberculosis-specific peptides biotinylated aMp3 and biotinylated aMptD (i.e., peptide-mediated magnetic separation [PMS]) proved to be the best magnetic-separation approach for achieving 85 to 100% capture of M. avium subsp. paratuberculosis and minimal (<1%) nonspecific recovery of other Mycobacterium spp. (particularly if beads were blocked with 1% skim milk before use) from broth samples containing 103 to 104 CFU/ml. When PMS was coupled with a recently optimized phage amplification assay and used to detect M. avium subsp. paratuberculosis in 50-ml volumes of spiked milk, the mean 50% limit of detection (LOD50) was 14.4 PFU/50 ml of milk (equivalent to 0.3 PFU/ml). This PMS-phage assay represents a novel, rapid method for the detection and enumeration of viable M. avium subsp. paratuberculosis organisms in milk, and potentially other sample matrices, with results available within 48 h.

Synapsing variable-length crossover: Meaningful crossover for variable-length genomes

The synapsing variable-length crossover (SVLC algorithm provides a biologically inspired method for performing meaningful crossover between variable-length genomes. In addition to providing a rationale for variable-length crossover, it also provides a genotypic similarity metric for variable-length genomes, enabling standard niche formation techniques to be used with variable-length genomes. Unlike other variable-length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC algorithm recurrently "glues" or synapses homogenous genetic subsequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable-length test problem, the SVLC algorithm compares favorably with current variable-length crossover techniques. The variable-length approach is further advocated by demonstrating how a variable-length genetic algorithm (GA) can obtain a high fitness solution in fewer iterations than a traditional fixed-length GA in a two-dimensional vector approximation task.

Thermoelectric performance of p-type TiCoSb half-Heusler compounds - Intrinsic phase separation and charge carrier concentration optimization as key to high efficiency

The world's rising demand of energy turns the development of sustainable and more efficient technologies for energy production and storage into an inevitable task. Thermoelectric generators, composed of pairs of n-type and p-type semiconducting materials, di¬rectly transform waste heat into useful electricity. The efficiency of a thermoelectric mate¬rial depends on its electronic and lattice properties, summarized in its figure of merit ZT. Desirable are high electrical conductivity and Seebeck coefficients, and low thermal con¬ductivity. Half-Heusler materials are very promising candidates for thermoelectric applications in the medium¬ temperature range such as in industrial and automotive waste heat recovery. The advantage of Heusler compounds are excellent electronic properties and high thermal and mechanical stability, as well as their low toxicity and elemental abundance. Thus, the main obstacle to further enhance their thermoelectric performance is their relatively high thermal conductivity.rn rnIn this work, the thermoelectric properties of the p-type material (Ti/Zr/Hf)CoSb1-xSnx were optimized in a multistep process. The concept of an intrinsic phase separation has recently become a focus of research in the compatible n-type (Ti/Zr/Hf)NiSn system to achieve low thermal conductivities and boost the TE performance. This concept is successfully transferred to the TiCoSb system. The phase separation approach can form a significant alternative to the previous nanostructuring approach via ball milling and hot pressing, saving pro¬cessing time, energy consumption and increasing the thermoelectric efficiency. A fundamental concept to tune the performance of thermoelectric materials is charge carrier concentration optimization. The optimum carrier concentration is reached with a substitution level for Sn of x = 0.15, enhancing the ZT about 40% compared to previous state-of-the-art samples with x = 0.2. The TE performance can be enhanced further by a fine-tuning of the Ti-to-Hf ratio. A correlation of the microstructure and the thermoelectric properties is observed and a record figure of merit ZT = 1.2 at 710°C was reached with the composition Ti0.25Hf0.75CoSb0.85Sn0.15.rnTowards application, the long term stability of the material under actual conditions of operation are an important issue. The impact of such a heat treatment on the structural and thermoelectric properties is investigated. Particularly, the best and most reliable performance is achieved in Ti0.5Hf0.5CoSb0.85Sn0.15, which reached a maximum ZT of 1.1 at 700°C. The intrinsic phase separation and resulting microstructure is stable even after 500 heating and cooling cycles.