Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

3D reconstruction of magnetization from dichroic soft X-ray transmission tomography

The development of magnetic nanostructures for applications in spintronics requires methods capable of visualizing their magnetization. Soft X‐ray magnetic imaging combined with circular magnetic dichroism allows nanostructures up to 100–300 nm in thickness to be probed with resolutions of 20–40 nm. Here a new iterative tomographic reconstruction method to extract the three‐dimensional magnetization configuration from tomographic projections is presented. The vector field is reconstructed by using a modified algebraic reconstruction approach based on solving a set of linear equations in an iterative manner. The application of this method is illustrated with two examples (magnetic nano‐disc and micro‐square heterostructure) along with comparison of error in reconstructions, and convergence of the algorithm

Design and construction of a configurable full-field range imaging system for mobile robotic applications

Mobile robotic devices rely critically on extrospection sensors to determine the range to objects in the robot’s operating environment. This provides the robot with the ability both to navigate safely around obstacles and to map its environment and hence facilitate path planning and navigation. There is a requirement for a full-field range imaging system that can determine the range to any obstacle in a camera lens’ field of view accurately and in real-time. This paper details the development of a portable full-field ranging system whose bench-top version has demonstrated sub-millimetre precision. However, this precision required non-real-time acquisition rates and expensive hardware. By iterative replacement of components, a portable, modular and inexpensive version of this full-field ranger has been constructed, capable of real-time operation with some (user-defined) trade-off with precision

Fast iterative solution of reaction-diffusion control problems arising from chemical processes

PDE-constrained optimization problems, and the development of preconditioned iterative methods for the efficient solution of the arising matrix system, is a field of numerical analysis that has recently been attracting much attention. In this paper, we analyze and develop preconditioners for matrix systems that arise from the optimal control of reaction-diffusion equations, which themselves result from chemical processes. Important aspects in our solvers are saddle point theory, mass matrix representation and effective Schur complement approximation, as well as the outer (Newton) iteration to take account of the nonlinearity of the underlying PDEs

Detection of low energy single ion impacts in micron scale transistors at room temperature

We report the detection of single ion impacts through monitoring of changes in the source-drain currents of field effect transistors (FET) at room temperature. Implant apertures are formed in the interlayer dielectrics and gate electrodes of planar, micro-scale FETs by electron beam assisted etching. FET currents increase due to the generation of positively charged defects in gate oxides when ions (121Sb12+, 14+, Xe6+; 50 to 70 keV) impinge into channel regions. Implant damage is repaired by rapid thermal annealing, enabling iterative cycles of device doping and electrical characterization for development of single atom devices and studies of dopant fluctuation effects

Developing Feasible and Effective School-Based Interventions for Children With ASD: A Case Study of the Iterative Development Process

Despite an emphasis on identifying evidence-based practices among researchers and using evidence-based practices among professionals in the field of education, there are still problems with uptake and implementation in real-world settings. This lack of diffusion of practices is evident in educational programming for children with autism spectrum disorder (ASD). One solution is to use an iterative process to develop interventions in which researchers work in collaboration with the end users to test and refine interventions. However, there are very few guidelines for developing feasible and effective interventions through these iterative processes. This article provides a description of the iterative process used to develop the Advancing Social-Communication and Play (ASAP) intervention, a supplemental program designed for public preschool classrooms serving students with ASD, and examples of how data from the sequence of iterative design studies shaped the intervention development. The research team offers guidelines for other researchers looking to engage in intervention development using an iterative process in the context of partnerships with end users, including suggestions for planning and executing an intervention development grant

Computational morphodynamics of plants: integrating development over space and time

The emerging field of computational morphodynamics aims to understand the changes that occur in space and time during development by combining three technical strategies: live imaging to observe development as it happens; image processing and analysis to extract quantitative information; and computational modelling to express and test time-dependent hypotheses. The strength of the field comes from the iterative and combined use of these techniques, which has provided important insights into plant development

Developing a Second Life virtual field trip for university students: an action research approach

Background: Integrating 3D virtual world technologies into educational subjects continues to draw the attention of educators and researchers alike. The focus of this study is the use of a virtual world, Second Life, in higher education teaching. In particular, it explores the potential of using a virtual world experience as a learning component situated within a curriculum delivered predominantly through face-to-face teaching methods. Purpose: This paper reports on a research study into the development of a virtual world learning experience designed for marketing students taking a Digital Promotions course. The experience was a field trip into Second Life to allow students to investigate how business branding practices were used for product promotion in this virtual world environment. The paper discusses the issues involved in developing and refining the virtual course component over four semesters. Methods: The study used a pedagogical action research approach, with iterative cycles of development, intervention and evaluation over four semesters. The data analysed were quantitative and qualitative student feedback collected after each field trip as well as lecturer reflections on each cycle. Sample: Small-scale convenience samples of second- and third-year students studying in a Bachelor of Business degree, majoring in marketing, taking the Digital Promotions subject at a metropolitan university in Queensland, Australia participated in the study. The samples included students who had and had not experienced the field trip. The numbers of students taking part in the field trip ranged from 22 to 48 across the four semesters. Findings and Implications: The findings from the four iterations of the action research plan helped identify key considerations for incorporating technologies into learning environments. Feedback and reflections from the students and lecturer suggested that an innovative learning opportunity had been developed. However, pedagogical potential was limited, in part, by technological difficulties and by student perceptions of relevance