Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

The essential parameters of a resource-based carrying capacity assessment model : an Australian case study

Carrying capacity assessments model a population’s potential self-sufficiency. A crucial first step in the development of such modelling is to examine the basic resource-based parameters defining the population’s production and consumption habits. These parameters include basic human needs such as food, water, shelter and energy together with climatic, environmental and behavioural characteristics. Each of these parameters imparts land-usage requirements in different ways and varied degrees so their incorporation into carrying capacity modelling also differs. Given that the availability and values of production parameters may differ between locations, no two carrying capacity models are likely to be exactly alike. However, the essential parameters themselves can remain consistent so one example, the Carrying Capacity Dashboard, is offered as a case study to highlight one way in which these parameters are utilised. While examples exist of findings made from carrying capacity assessment modelling, to date, guidelines for replication of such studies in other regions and scales have largely been overlooked. This paper addresses such shortcomings by describing a process for the inclusion and calibration of the most important resource-based parameters in a way that could be repeated elsewhere.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

Facile mutant identification via a single parental backcross method and application of whole genome sequencing based mapping pipelines

Forward genetic screens have identified numerous genes involved in development and metabolism, and remain a cornerstone of biological research. However, to locate a causal mutation, the practice of crossing to a polymorphic background to generate a mapping population can be problematic if the mutant phenotype is difficult to recognize in the hybrid F2 progeny, or dependent on parental specific traits. Here in a screen for leaf hyponasty mutants, we have performed a single backcross of an Ethane Methyl Sulphonate (EMS) generated hyponastic mutant to its parent. Whole genome deep sequencing of a bulked homozygous F2 population and analysis via the Next Generation EMS mutation mapping pipeline (NGM) unambiguously determined the causal mutation to be a single nucleotide polymorphisim (SNP) residing in HASTY, a previously characterized gene involved in microRNA biogenesis. We have evaluated the feasibility of this backcross approach using three additional SNP mapping pipelines; SHOREmap, the GATK pipeline, and the samtools pipeline. Although there was variance in the identification of EMS SNPs, all returned the same outcome in clearly identifying the causal mutation in HASTY. The simplicity of performing a single parental backcross and genome sequencing a small pool of segregating mutants has great promise for identifying mutations that may be difficult to map using conventional approaches.

Description of plant tRNA-derived RNA fragments (tRFs) associated with argonaute and identification of their putative targets

tRNA-derived RNA fragments (tRFs) are 19mer small RNAs that associate with Argonaute (AGO) proteins in humans. However, in plants, it is unknown if tRFs bind with AGO proteins. Here, using public deep sequencing libraries of immunoprecipitated Argonaute proteins (AGO-IP) and bioinformatics approaches, we identified the Arabidopsis thaliana AGO-IP tRFs. Moreover, using three degradome deep sequencing libraries, we identified four putative tRF targets. The expression pattern of tRFs, based on deep sequencing data, was also analyzed under abiotic and biotic stresses. The results obtained here represent a useful starting point for future studies on tRFs in plants. © 2013 Loss-Morais et al.; licensee BioMed Central Ltd.

Identification and occupational stress : a stress-buffering perspective

Occupational stress research has consistently demonstrated many negative effects of work stressors on employee adjustment (i.e., job-related attitudes and health). Considerable literature also describes potential moderators of this relationship. While research has revealed that different workplace identifications can have significant positive effects on employee adjustment, it has neglected to investigate their potential stress-buffering effects. Based on identity theories, it was predicted that stress-buffering effects of different types of identifications (distal versus proximal) would be revealed when the identification type and employee adjustment outcome type (distal versus proximal) were congruent. Predictions were tested with an employee sample from five human service nonprofit organizations (N = 337). Hierarchical multiple regression analyses revealed that main and moderated effects relating to identification supported the notion that occupational stress would be reduced when there was congruence of distal and proximal identifications and distal and proximal outcome types. However, stress-buffering effects were also found for high identifiers and low identifiers that were not in line with hypotheses posing questions for the definitions of distal and proximal identifications. Findings are discussed in terms of theoretical and practical implications.

Identification and elimination of a matrix-induced systematic error in LA–ICP–MS 206Pb/238U dating of zircon

Black et al. (2004) identified a systematic difference between LA–ICP–MS and TIMS measurements of 206Pb/238U in zircons, which they correlated with the incompatible trace element content of the zircon. We show that the offset between the LA–ICP–MS and TIMS measured 206Pb/238U correlates more strongly with the total radiogenic Pb than with any incompatible trace element. This suggests that the cause of the 206Pb/238U offset is related to differences in the radiation damage (alpha dose) between the reference and unknowns. We test this hypothesis in two ways. First, we show that there is a strong correlation between the difference in the LA–ICP–MS and TIMS measured 206Pb/238U and the difference in the alpha dose received by unknown and reference zircons. The LA–ICP–MS ages for the zircons we have dated can be as much as 5.1% younger than their TIMS age to 2.1% older, depending on whether the unknown or reference received the higher alpha dose. Second, we show that by annealing both reference and unknown zircons at 850 °C for 48 h in air we can eliminate the alpha-dose-induced differences in measured 206Pb/238U. This was achieved by analyzing six reference zircons a minimum of 16 times in two round robin experiments: the first consisting of unannealed zircons and the second of annealed grains. The maximum offset between the LA–ICP–MS and TIMS measured 206Pb/238U for the unannealed zircons was 2.3%, which reduced to 0.5% for the annealed grains, as predicted by within-session precision based on counting statistics. Annealing unknown zircons and references to the same state prior to analysis holds the promise of reducing the 3% external error for the measurement of 206Pb/238U of zircon by LA–ICP–MS, indicated by Klötzli et al. (2009), to better than 1%, but more analyses of annealed zircons by other laboratories are required to evaluate the true potential of the annealing method.

Putative full-length clones of the genomic DNA segments of subterranean clover stunt virus and identification of the segment coding for the viral coat protein

Subterranean clover stunt disease is an economically important aphid-borne virus disease affecting certain pasture and grain legumes in Australia. The virus associated with the disease, subterranean clover stunt virus (SCSV), was previously found to be representative of a new type of single-stranded DNA virus. Analysis of the virion DNA and restriction mapping of double-stranded cDNA synthesized from virion DNA suggested that SCSV has a segmented genome composed of 3 or 4 different species of circular ssDNA each of about 850-880 nucleotides. To further investigate the complexity of the SCSV genome, we have isolated the replicative form DNA from infected pea and from it prepared putative full-length clones representing the SCSV genome segments. Analysis of these clones by restriction mapping indicated that clones representing at least 4 distinct genomic segments were obtained. This method is thus suitable for generating an extensive genomic library of novel ssDNA viruses containing multiple genome segments such as SCSV and banana bunchy top virus. The N-terminal amino acid sequence and amino acid composition of the coat protein of SCSV were determined. Comparison of the amino acid sequence with partial DNA sequence data, and the distinctly different restriction maps obtained for the full-length clones suggested that only one of these clones contained the coat protein gene. The results confirmed that SCSV has a functionally divided genome composed of several distinct ssDNA circles each of about 1 kb.

Sequence and identification of the barley yellow dwarf virus coat protein gene

The nucleotide sequence of the coat protein gene of barley yellow dwarf virus (BYDV, PAV serotype) was determined, and the amino acid sequence was deduced. The open reading frame, encoding a protein of relative molecular mass (Mr) 22,047, was confirmed as the coat protein gene by comparison with amino acid sequences of tryptic peptides derived from dissociated virions. In addition, a fragment of this gene expressed in Escherichia coli produced a product which was recognized by antibodies prepared against purified BYDV virions. An overlapping reading frame encoding an Mr 17,147 protein is contained completely within the coat protein gene. © 1988.

How accurate is the identification of serious traffic injuries by Police? The concordance between Police and hospital reported traffic injuries

Police reported crash data are the primary source of crash information in most jurisdictions. However, the definition of serious injury within police-reported data is not consistent across jurisdictions and may not be accurate. With the Australian National Road Safety Strategy targeting the reduction of serious injuries, there is a greater need to assess the accuracy of the methods used to identify these injuries. A possible source of more accurate information relating to injury severity is hospital data. While other studies have compared police and hospital data to highlight the under-reporting in police-reported data, little attention has been given to the accuracy of the methods used by police to identify serious injuries. The current study aimed to assess how accurate the identification of serious injuries is in police-reported crash data, by comparing the profiles of transport-related injuries in the Queensland Road Crash Database with an aligned sample of data from the Queensland Hospital Admitted Patients Data Collection. Results showed that, while a similar number of traffic injuries were recorded in both data sets, the profile of these injuries was different based on gender, age, location, and road user. The results suggest that the ‘hospitalisation’ severity category used by police may not reflect true hospitalisations in all cases. Further, it highlights the wide variety of severity levels within hospitalised cases that are not captured by the current police-reported definitions. While a data linkage study is required to confirm these results, they highlight that a reliance on police-reported serious traffic injury data alone could result in inaccurate estimates of the impact and cost of crashes and lead to a misallocation of valuable resources.

A Human identification technique using images of the iris and wavelet transform

A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions.

Effects of wireless sensor network uncertainties on output-only modal-based damage identification

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

A security system based on human iris identification using wavelet transform

A security system based on the recognition of the iris of human eyes using the wavelet transform is presented. The zero-crossings of the wavelet transform are used to extract the unique features obtained from the grey-level profiles of the iris. The recognition process is performed in two stages. The first stage consists of building a one-dimensional representation of the grey-level profiles of the iris, followed by obtaining the wavelet transform zerocrossings of the resulting representation. The second stage is the matching procedure for iris recognition. The proposed approach uses only a few selected intermediate resolution levels for matching, thus making it computationally efficient as well as less sensitive to noise and quantisation errors. A normalisation process is implemented to compensate for size variations due to the possible changes in the camera-to-face distance. The technique has been tested on real images in both noise-free and noisy conditions. The technique is being investigated for real-time implementation, as a stand-alone system, for access control to high-security areas.

Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.