First-principle studies of electronic structure and C-doping effect in boron nitride nanoribbon

Structural and electronic properties have been studied for Boron Nitride nanoribbons (BNNR) with both zigzag and armchair shaped edge (Z-BNNR and A-BNNR) by first-principle spin-polarized total energy calculations. We found that the energy band gap of Z-BNNR is indirect and decreases monotonically with the increasing ribbon width, whereas direct energy band gap oscillation was observed for A-BNNRs. Additionally, C-substitution at either single boron or nitrogen atom site in BNNRs could induce spontaneous magnetization. Our results could be potentially useful to design magnetic nano-devices based on BNNRs.

Structure character in small-carbon-cluster deposition on diamond surface

Experimentally, hydrogen-free diamond-like carbon (DLC) films were assembled by means of pulsed laser deposition (PLD), where energetic small-carbon-clusters were deposited on the substrate. In this paper, the chemisorption of energetic C2 and C10 clusters on diamond (001)-( 2×1) surface was investigated by molecular dynamics simulation. The influence of cluster size and the impact energy on the structure character of the deposited clusters is mainly addressed. The impact energy was varied from a few tens eV to 100 eV. The chemisorption of C10 was found to occur only when its incident energy is above a threshold value ( E th). While, the C2 cluster was easily to adsorb on the surface even at much lower incident energy. With increasing the impact energy, the structures of the deposited C2 and C10 are different from the free clusters. Finally, the growth of films synthesized by energetic C2 and C10 clusters were simulated. The statistics indicate the C2 cluster has high probability of adsorption and films assembled of C2 present slightly higher SP3 fraction than that of C10-films, especially at higher impact energy and lower substrate temperature. Our result supports the experimental findings. Moreover, the simulation underlines the deposition mechanism at atomic scale.

Infrared and Raman spectroscopic characterization of the borate mineral colemanite – CaB3O4(OH)3·H2O – implications for the molecular structure

Colemanite CaB3O4(OH)3 H2O is a secondary borate mineral formed from borax and ulexite in evaporate deposits of alkaline lacustrine sediments. The basic structure of colemanite contains endless chains of interlocking BO2(OH) triangles and BO3(OH) tetrahedrons with the calcium, water and extra hydroxide units interspersed between these chains. The Raman spectra of colemanite is characterized by an intense band at 3605 cm-1 assigned to the stretching vibration of OH units and a series of bands at 3182, 3300, 3389 and 3534 cm-1 assigned to water stretching vibrations. Infrared bands are observed in similar positions. The BO stretching vibrations of the trigonal and tetrahedral boron are characterized by Raman bands at 876, 1065 and 1084 cm-1. The OBO bending mode is defined by the Raman band at 611 cm-1. It is important to characterize the very wide range of borate minerals including colemanite because of the very wide range of applications of boron containing minerals.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

GrabCutSFM : how 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.

Computer modeling of diffusion in biological tissues

Molecular-level computer simulations of restricted water diffusion can be used to develop models for relating diffusion tensor imaging measurements of anisotropic tissue to microstructural tissue characteristics. The diffusion tensors resulting from these simulations can then be analyzed in terms of their relationship to the structural anisotropy of the model used. As the translational motion of water molecules is essentially random, their dynamics can be effectively simulated using computers. In addition to modeling water dynamics and water-tissue interactions, the simulation software of the present study was developed to automatically generate collagen fiber networks from user-defined parameters. This flexibility provides the opportunity for further investigations of the relationship between the diffusion tensor of water and morphologically different models representing different anisotropic tissues.

Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

BWW ontology as a lens on IS design theory: Extending the design science research roadmap

The Design Science Research Roadmap (DSR-Roadmap) [1] aims to give detailed methodological guidance to novice researchers in Information Systems (IS) DSR. Focus group evaluation, one phase of the overall study, of the evolving DSR-Roadmap revealed that a key difficulty faced by both novice and expert researchers in DSR, is abstracting design theory from design. This paper explores the extension of the DSR-Roadmap by employing IS deep structure ontology (BWW [2-4]) as a lens on IS design to firstly yield generalisable design theory, specifically 'IS Design Theory' (ISDT) elements [5]. Consideration is next given to the value of BWW in the application of the design theory by practitioners. Results of mapping BWW constructs to ISDT elements suggest that the BWW is promising as a common language between design researchers and practitioners, facilitating both design theory and design implementation

Robust scale initialization for long-range stereo visual odometry

Achieving a robust, accurately scaled pose estimate in long-range stereo presents significant challenges. For large scene depths, triangulation from a single stereo pair is inadequate and noisy. Additionally, vibration and flexible rigs in airborne applications mean accurate calibrations are often compromised. This paper presents a technique for accurately initializing a long-range stereo VO algorithm at large scene depth, with accurate scale, without explicitly computing structure from rigidly fixed camera pairs. By performing a monocular pose estimate over a window of frames from a single camera, followed by adding the secondary camera frames in a modified bundle adjustment, an accurate, metrically scaled pose estimate can be found. To achieve this the scale of the stereo pair is included in the optimization as an additional parameter. Results are presented both on simulated and field gathered data from a fixed-wing UAV flying at significant altitude, where the epipolar geometry is inaccurate due to structural deformation and triangulation from a single pair is insufficient. Comparisons are made with more conventional VO techniques where the scale is not explicitly optimized, and demonstrated over repeated trials to indicate robustness.

Attribute-based functional encryption on lattices

We introduce a broad lattice manipulation technique for expressive cryptography, and use it to realize functional encryption for access structures from post-quantum hardness assumptions. Specifically, we build an efficient key-policy attribute-based encryption scheme, and prove its security in the selective sense from learning-with-errors intractability in the standard model.

Variation in leaf structure of the invasive Madeira vine (Anredera cordifolia, Basellaceae) at different light levels

Madeira vine (Anredera cordifolia (Ten.) Steenis) is a climber in the angiosperm family Basellaceae. It is native to South America and has naturalised in Australia. It is regarded as a serious environmental weed because of the structural damage it causes to native vegetation. The present study, for the first time, documents anatomical and morphological traits of the leaves of A. cordifolia and considers their implications for its ecology and physiology. Plants were grown under three different light levels, and anatomical and morphological leaf characters were compared among light levels, among cohorts, and with documented traits of the related species, Basella alba L. Stomata were present on both the adaxial and abaxial sides of the leaf, with significantly more stomata on the abaxial side and under high light. This may account for the ability of this species to fix large amounts of carbon and rapidly respond to light gaps. The leaves had very narrow veins and no sclerenchyma, suggesting a low construction cost that is associated with invasive plants. There was no significant difference in any of the traits among different cohorts, which agrees with the claim that A. cordifolia primarily propagates vegetatively. The anatomy and morphology of A. cordifolia was similar to that of B. alba.

Plant structure and systematics research at the Queensland University of Technology (QUT), Brisbane

This article provides a general overview of some of the plant research being conducted by a number of researchers at the Queensland University of Technology (QUT) Brisbane. Details about student projects and research facilities have been limited to those of relevance to plant structure and systematics. Academics, technicians and research students involved in plant research are in the Faculty of Science and Engineering, mainly in the School of Earth, Environment and Biological Sciences (EEBS), with a few exceptions. Our offices and laboratories are housed in a number of different buildings at the Gardens Point campus (e.g., P, Q, R, S, M Blocks) and we have strong collaborative links with Queensland Herbarium (BRI) and Mt Coot-tha Botanic Gardens.

Mapping semantic knowledge for unsupervised text categorisation

Text categorisation is challenging, due to the complex structure with heterogeneous, changing topics in documents. The performance of text categorisation relies on the quality of samples, effectiveness of document features, and the topic coverage of categories, depending on the employing strategies; supervised or unsupervised; single labelled or multi-labelled. Attempting to deal with these reliability issues in text categorisation, we propose an unsupervised multi-labelled text categorisation approach that maps the local knowledge in documents to global knowledge in a world ontology to optimise categorisation result. The conceptual framework of the approach consists of three modules; pattern mining for feature extraction; feature-subject mapping for categorisation; concept generalisation for optimised categorisation. The approach has been promisingly evaluated by compared with typical text categorisation methods, based on the ground truth encoded by human experts.

Liveness detection based on 3D face shape analysis

In recent years face recognition systems have been applied in various useful applications, such as surveillance, access control, criminal investigations, law enforcement, and others. However face biometric systems can be highly vulnerable to spoofing attacks where an impostor tries to bypass the face recognition system using a photo or video sequence. In this paper a novel liveness detection method, based on the 3D structure of the face, is proposed. Processing the 3D curvature of the acquired data, the proposed approach allows a biometric system to distinguish a real face from a photo, increasing the overall performance of the system and reducing its vulnerability. In order to test the real capability of the methodology a 3D face database has been collected simulating spoofing attacks, therefore using photographs instead of real faces. The experimental results show the effectiveness of the proposed approach.

Count-min sketches for estimating password frequency within Hamming distance two

The count-min sketch is a useful data structure for recording and estimating the frequency of string occurrences, such as passwords, in sub-linear space with high accuracy. However, it cannot be used to draw conclusions on groups of strings that are similar, for example close in Hamming distance. This paper introduces a variant of the count-min sketch which allows for estimating counts within a specified Hamming distance of the queried string. This variant can be used to prevent users from choosing popular passwords, like the original sketch, but it also allows for a more efficient method of analysing password statistics.