Automated weighing by sequential inference in dynamic environments

We demonstrate sequential mass inference of a suspended bag of milk powder from simulated measurements of the vertical force component at the pivot while the bag is being filled. We compare the predictions of various sequential inference methods both with and without a physics model to capture the system dynamics. We find that non-augmented and augmented-state unscented Kalman filters (UKFs) in conjunction with a physics model of a pendulum of varying mass and length provide rapid and accurate predictions of the milk powder mass as a function of time. The UKFs outperform the other method tested - a particle filter. Moreover, inference methods which incorporate a physics model outperform equivalent algorithms which do not.Comment: 5 pages, 7 figures. Copyright IEEE (2015

Navigation by Induction-Based Magnetoreception in Elasmobranch Fishes

A quantitative frequency-domain model of induction-based magnetoreception is presented for elasmobranch fishes. We show that orientation with respect to the geomagnetic field can be determined by synchronous detection of electrosensory signals at harmonics of the vestibular frequency. The sensitivity required for this compass-sense mechanism is shown to be less than that known from behavioral experiments. Recent attached-magnet experiments have called into doubt the induction-based mechanism for magnetoreception. We show that the use of attached magnets would interfere with an induction-based mechanism unless relative movement between the electrosensory system and the attached magnet is less than 100 μm. This suggests that further experiments may be required to eliminate induction as a basis for magnetoreception

The prevalence of mental disorders among children, adolescents and adults in the Western Cape, South Africa

Objective: To provide estimates of the prevalence of selected mental disorders in the Western Cape, based on the consensus achieved by a working group established for this purpose. Method: An expert working group was established to provide technical expertise for the project. Potential risk factors likely to influence local prevalence rates were identified. Annual prevalence rates for adults and for children and adolescents were derived by consensus, informed by a systematic literature review. Prevalence rates were derived for individual disorders and adjusted for comorbidity. Results: The overall prevalence was 25.0% for adults and 17.0% for children and adolescents. Conclusion: Prevalence rates of child, adolescent and adult mental disorders were derived in a short period of time and with the use of minimal resources. Although of unknown validity, they are useful for policy development and for planning service utilisation estimates, resource costing and targets for service development for local mental health needs. This in the absence of an existing methodologically sound national prevalence study. We recommend that policy and programme developers draw on the expertise of local academics and clinicians to promote research-informed planning and policy development in the public sector. South African Psychiatry Review Vol. 9(3) 2006: 157-16

A Comparison of Genetic Programming with Genetic Algorithms for Wire Antenna Design

This work compares the performance of genetic programming (GP) against traditional fixed-length genome GA approaches on the optimization of wire antenna designs. We describe the implementation of a GP electromagnetic optimization system for wire structures. The results are compared with the traditional GA approach. Although the dimensionality of the search space is much higher for GP than GA, we find that the GP approach gives better results than GA for the same computational effort. In addition, we find that a more expressive antenna structure grammar, dramatically, improves the performance of the GP approach

A Heuristic Image Search Algorithm for Active Shape Model Segmentation of the Caudate Nucleus and Hippocampus in Brain MR Images of Children with FASD

Magnetic Resonance Imaging provides a non-invasive means to study the neural correlates of Fetal Alcohol Spectrum Disorder (FASD) - the most common form of preventable mental retardation worldwide. One approach aims to detect brain abnormalities through an assessment of volume and shape of two sub-cortical structures, the caudate nucleus and hippocampus. We present a method for automatically segmenting these structures from high-resolution MR images captured as part of an ongoing study into the neural correlates of FASD. Our method incorporates an Active Shape Model, which is used to learn shape variation from manually segmented training data. A modified discrete Geometrically Deformable Model is used to generate point correspondence between training models. An ASM is then created from the landmark points. Experiments were conducted on the image search phase of ASM segmentation, in order to find the technique best suited to segmentation of the hippocampus and caudate nucleus. Various popular image search techniques were tested, including an edge detection method and a method based on grey profile Mahalanobis distance measurement. A novel heuristic image search method was also developed and tested. This heuristic method improves image segmentation by taking advantage of characteristics specific to the target data, such as a relatively homogeneous tissue colour in target structures. Results show that ASMs that use the heuristic image search technique produce the most accurate segmentations. An ASM constructed using this technique will enable researchers to quickly, reliably, and automatically segment test data for use in the FASD study