A late Holocene onset of Aboriginal burning in southeastern Australia

The extent to which Aboriginal Australians used fire to modify their environment has been debated for decades and is generally based on charcoal and pollen records rather than landscape responses to land-use change. Here we investigate the sensitivity of in-situ–produced 10Be, an isotope commonly used in geomorphological contexts, to anthropogenic perturbations in the southeastern Australian Tablelands. Comparing 10Be-derived erosion rates from fluvial sediment (8.7 ± 0.9 mm k.y.–1; 1 standard error, SE; n = 11) and rock outcrops (5.3 ± 1.4 mm k.y.–1; 1 SE; n = 6) confirms that landscape lowering rates integrating over 104–105 yr are consistent with rates previously derived from studies integrating over 104 to >107 yr. We then model an expected 10Be inventory in fluvial sediment if background erosion rates were perturbed by a low-intensity, high-frequency Aboriginal burning regime. When we run the model using the average erosion rate derived from 10Be in fluvial sediment (8.7 mm k.y.–1), measured and modeled 10Be concentrations overlap between ca. 3 ka and 1 ka. Our modeling is consistent with intensified Aboriginal use of fire in the late Holocene, a time when Aboriginal population growth is widely recognized

Automatic Induction of Neural Network Decision Tree Algorithms

This work presents an approach to automatically induction for non-greedy decision trees constructed from neural network architecture. This construction can be used to transfer weights when growing or pruning a decision tree, allowing non-greedy decision tree algorithms to automatically learn and adapt to the ideal architecture. In this work, we examine the underpinning ideas within ensemble modelling and Bayesian model averaging which allow our neural network to asymptotically approach the ideal architecture through weights transfer. Experimental results demonstrate that this approach improves models over fixed set of hyperparameters for decision tree models and decision forest models.Comment: This is a pre-print of a contribution "Chapman Siu, Automatic Induction of Neural Network Decision Tree Algorithms." To appear in Computing Conference 2019 Proceedings. Advances in Intelligent Systems and Computing. Implementation: https://github.com/chappers/automatic-induction-neural-decision-tre

Hydrogeological modelling of the Atlantis aquifer for management support to the Atlantis Water Supply Scheme

The Atlantis Water Supply Scheme (AWSS, Western Cape, South Africa) has been in operation for about 40 years as a means to supply and augment drinking water to the town of Atlantis via managed aquifer recharge (MAR). In this study, the numerical model MODFLOW for groundwater flow and contaminant transport was used in support of the management of the AWSS. The aims were: (i) to calibrate the MODFLOW model for the MAR site at Atlantis; (ii) to run realistic scenarios that cannot be replicated through experiments; and (iii) to make recommendations in support of efficient and sustainable management of the aquifer. MODFLOW was calibrated through comparison of observed and simulated groundwater levels (R2 between 0.663 and 0.995). Scenario simulations indicated possible drawdowns between < 5 m (low groundwater abstraction and low artificial recharge of groundwater through infiltration basins) and > 20 m (high abstraction and high artificial recharge) at localized areas of the Witzand wellfield. At Silwerstroom, large drawdown levels were not predicted to occur, so this wellfield could be exploited more without affecting the sustainability of the groundwater resource. Groundwater moves from the infiltration basins towards the Witzand wellfield at a rate of 120–150 m·a-1. The modelling results supported recommendations for balancing groundwater abstraction and artificial recharge volumes, monitoring the water balance components of the system, the potential risks of groundwater contamination and the delineation of groundwater protection zones.Keywords: Groundwater abstraction; managed aquifer recharge; MODFLOW; particle tracking; scenario modellin

Improving the minimum description length inference of phrase-based translation models

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19390-8_25We study the application of minimum description length (MDL) inference to estimate pattern recognition models for machine translation. MDL is a theoretically-sound approach whose empirical results are however below those of the state-of-the-art pipeline of training heuristics. We identify potential limitations of current MDL procedures and provide a practical approach to overcome them. Empirical results support the soundness of the proposed approach.Work supported by the EU 7th Framework Programme (FP7/2007–2013) under the CasMaCat project (grant agreement no 287576), by Spanish MICINN under grant TIN2012-31723, and by the Generalitat Valenciana under grant ALMPR (Prometeo/2009/014).Gonzalez Rubio, J.; Casacuberta Nolla, F. (2015). Improving the minimum description length inference of phrase-based translation models. En Pattern Recognition and Image Analysis: 7th Iberian Conference, IbPRIA 2015, Santiago de Compostela, Spain, June 17-19, 2015, Proceedings. Springer International Publishing. 219-227. https://doi.org/10.1007/978-3-319-19390-8 25S21922

Active authentication for mobile devices utilising behaviour profiling.

With nearly 6 billion subscribers around the world, mobile devices have become an indispensable component in modern society. The majority of these devices rely upon passwords and personal identification numbers as a form of user authentication, and the weakness of these point-of-entry techniques is widely documented. Active authentication is designed to overcome this problem by utilising biometric techniques to continuously assess user identity. This paper describes a feasibility study into a behaviour profiling technique that utilises historical application usage to verify mobile users in a continuous manner. By utilising a combination of a rule-based classifier, a dynamic profiling technique and a smoothing function, the best experimental result for a users overall application usage was an equal error rate of 9.8 %. Based upon this result, the paper proceeds to propose a novel behaviour profiling framework that enables a user’s identity to be verified through their application usage in a continuous and transparent manner. In order to balance the trade-off between security and usability, the framework is designed in a modular way that will not reject user access based upon a single application activity but a number of consecutive abnormal application usages. The proposed framework is then evaluated through simulation with results of 11.45 and 4.17 % for the false rejection rate and false acceptance rate, respectively. In comparison with point-of-entry-based approaches, behaviour profiling provides a significant improvement in both the security afforded to the device and user convenience

Are autistic traits in the general population stable across development?

There is accumulating evidence that autistic traits (AT) are on a continuum in the general population, with clinical autism representing the extreme end of a quantitative distribution. While the nature and severity of symptoms in clinical autism are known to persist over time, no study has examined the long-term stability of AT among typically developing toddlers. The current investigation measured AT in 360 males and 400 males from the general population close to two decades apart, using the Pervasive Developmental Disorder subscale of the Child Behavior Checklist in early childhood (M = 2.14 years; SD = 0.15), and the Autism-Spectrum Quotient in early adulthood (M = 19.50 years; SD = 0.70). Items from each scale were further divided into social (difficulties with social interaction and communication) and non-social (restricted and repetitive behaviours and interests) AT. The association between child and adult measurements of AT as well the influence of potentially confounding sociodemographic, antenatal and obstetric variables were assessed using Pearson's correlations and linear regression. For males, Total AT in early childhood were positively correlated with total AT (r = .16, p = .002) and social AT (r = .16, p = .002) in adulthood. There was also a positive correlation for males between social AT measured in early childhood and Total (r = .17, p = .001) and social AT (r = .16, p = .002) measured in adulthood. Correlations for non-social AT did not achieve significance in males. Furthermore, there was no significant longitudinal association in AT observed for males or females. Despite the constraints of using different measures and different raters at the two ages, this study found modest developmental stability of social AT from early childhood to adulthood in boys

Characterization of digital medical images utilizing support vector machines

BACKGROUND: In this paper we discuss an efficient methodology for the image analysis and characterization of digital images containing skin lesions using Support Vector Machines and present the results of a preliminary study. METHODS: The methodology is based on the support vector machines algorithm for data classification and it has been applied to the problem of the recognition of malignant melanoma versus dysplastic naevus. Border and colour based features were extracted from digital images of skin lesions acquired under reproducible conditions, using basic image processing techniques. Two alternative classification methods, the statistical discriminant analysis and the application of neural networks were also applied to the same problem and the results are compared. RESULTS: The SVM (Support Vector Machines) algorithm performed quite well achieving 94.1% correct classification, which is better than the performance of the other two classification methodologies. The method of discriminant analysis classified correctly 88% of cases (71% of Malignant Melanoma and 100% of Dysplastic Naevi), while the neural networks performed approximately the same. CONCLUSION: The use of a computer-based system, like the one described in this paper, is intended to avoid human subjectivity and to perform specific tasks according to a number of criteria. However the presence of an expert dermatologist is considered necessary for the overall visual assessment of the skin lesion and the final diagnosis

Neural Network Parameterizations of Electromagnetic Nucleon Form Factors

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks. As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties. The Bayesian approach for the neural networks is adapted for chi2 error-like function and applied to the data analysis. The sequence of the feed forward neural networks with one hidden layer of units is considered. The given neural network represents a particular form-factor parametrization. The so-called evidence (the measure of how much the data favor given statistical model) is computed with the Bayesian framework and it is used to determine the best form factor parametrization.Comment: The revised version is divided into 4 sections. The discussion of the prior assumptions is added. The manuscript contains 4 new figures and 2 new tables (32 pages, 15 figures, 2 tables

Age-Related Attenuation of Dominant Hand Superiority

The decline of motor performance of the human hand-arm system with age is well-documented. While dominant hand performance is superior to that of the non-dominant hand in young individuals, little is known of possible age-related changes in hand dominance. We investigated age-related alterations of hand dominance in 20 to 90 year old subjects. All subjects were unambiguously right-handed according to the Edinburgh Handedness Inventory. In Experiment 1, motor performance for aiming, postural tremor, precision of arm-hand movement, speed of arm-hand movement, and wrist-finger speed tasks were tested. In Experiment 2, accelerometer-sensors were used to obtain objective records of hand use in everyday activities

The Relation Between Cognitive Development and Anxiety Phenomena in Children

We examined the relation between cognitive development and fear, anxiety, and behavioral inhibition in a non-clinical sample of 226 Dutch children aged 4–9 years. To assess cognitive development, children were tested with Piagetian conservation tasks and a Theory-of-Mind (TOM) test. Fears were measured by means of a self-report scale completed by the children, while anxiety symptoms and behavioral inhibition were indexed by rating scales that were filled out by parents. Significant age trends were observed for some anxiety phenomena. For example, younger children displayed higher fear scores, whereas older children exhibited higher levels of generalized anxiety. Most importantly, results of regression analyses (in which we controlled for age) indicated that cognitive development, and in particular TOM ability, made a unique and significant contribution to various domains of behavioral inhibition. In all cases, higher levels of TOM were associated with lower levels of behavioral inhibition. In general, percentages of explained variance were rather small (i.e., <6%), indicating that the role of cognitive development in various anxiety phenomena is limited