Role of 3D visual conceptualisation of groundwater system models as a management support tool

After the recent prolonged drought conditions in many parts of Australia it is increasingly recognised that many groundwater systems are under stress. Although this is obvious for systems that are utilised for intensive irrigation many other groundwater systems are also impacted.Management strategies are highly variable to non-existent. Policy and regulation are also often inadequate, and are reactive or politically driven. In addition, there is a wide range of opinion by water users and other stakeholders as to what is “reasonable”management practice. These differences are often related to the “value”that is put on the groundwater resource. Opinions vary from “our right to free water”to an awareness that without effective management the resource will be degraded. There is also often misunderstanding of surface water-groundwater linkages, recharge processes, and baseflow to drainage systems.

Paper-based mixed reality sketch augmentation as a conceptual design support tool

This undergraduate student paper explores usage of mixed reality techniques as support tools for conceptual design. A proof-of-concept was developed to illustrate this principle. Using this as an example, a small group of designers was interviewed to determine their views on the use of this technology. These interviews are the main contribution of this paper. Several interesting applications were determined, suggesting possible usage in a wide range of domains. Paper-based sketching, mixed reality and sketch augmentation techniques complement each other, and the combination results in a highly intuitive interface.

Exploring the Potential Impacts of Climate Variability on Spring Wheat Yield with the APSIM Decision Support Tool

Assessing the impacts of climate variability on agricultural productivity at regional, national or global scale is essential for defining adaptation and mitigation strategies. We explore in this study the potential changes in spring wheat yields at Swift Current and Melfort, Canada, for different sowing windows under projected climate scenarios (i.e., the representative concentration pathways, RCP4.5 and RCP8.5). First, the APSIM model was calibrated and evaluated at the study sites using data from long term experimental field plots. Then, the impacts of change in sowing dates on final yield were assessed over the 2030-2099 period with a 1990-2009 baseline period of observed yield data, assuming that other crop management practices remained unchanged. Results showed that the performance of APSIM was quite satisfactory with an index of agreement of 0.80, R2 of 0.54, and mean absolute error (MAE) and root mean square error (RMSE) of 529 kg/ha and 1023 kg/ha, respectively (MAE = 476 kg/ha and RMSE = 684 kg/ha in calibration phase). Under the projected climate conditions, a general trend in yield loss was observed regardless of the sowing window, with a range from -24 to -94 depending on the site and the RCP, and noticeable losses during the 2060s and beyond (increasing CO2 effects being excluded). Smallest yield losses obtained through earlier possible sowing date (i.e., mid-April) under the projected future climate suggested that this option might be explored for mitigating possible adverse impacts of climate variability. Our findings could therefore serve as a basis for using APSIM as a decision support tool for adaptation/mitigation options under potential climate variability within Western Canada.

Environmental and aesthetic impacts of small docks and piers, workshop report: Developing a science-based decision support tool for small dock management, phase 1: Status of the science

Few issues confronting coastal resource managers are as divisive or difficult to manage as regulating the construction of private recreational docks and piers associated with residential development. State resource managers face a growing population intent on living on or near the coast, coupled with an increasing desire to have immediate access to the water by private docks or piers. (PDF contains 69 pages)

STARTEC: Novel processing technologies in the development of a decision support tool to ensure safe and nutritious Ready-To-Eat foods

Ready-to-eat (RTE) foods can be readily consumed with minimum or without any further preparation; their processing is complex—involving thorough decontamination processes— due to their composition of mixed ingredients. Compared with conventional preservation technologies, novel processing technologies can enhance the safety and quality of these complex products by reducing the risk of pathogens and/ or by preserving related health-promoting compounds. These novel technologies can be divided into two categories: thermal and non-thermal. As a non-thermal treatment, High Pressure Processing is a very promising novel methodology that can be used even in the already packaged RTE foods. A new “volumetric” microwave heating technology is an interesting cooking and decontamination method directly applied to foods. Cold Plasma technology is a potential substitute of chlorine washing in fresh vegetable decontamination. Ohmic heating is a heating method applicable to viscous products but also to meat products. Producers of RTE foods have to deal with challenging decisions starting from the ingredients suppliers to the distribution chain. They have to take into account not only the cost factor but also the benefits and food products’ safety and quality. Novel processing technologies can be a valuable yet large investment for several SME food manufacturers, but they need support data to be able to make adequate decisions. Within the FP7 Cooperation funded by the European Commission, the STARTEC project aims to develop an IT decision supporting tool to help food business operators in their risk assessment and future decision making when producing RTE foods with or without novel preservation technologies.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

A teaching/learning support tool for introductory programming courses

In This work we present a Web-based tool developed with the aim of reinforcing teaching and learning of introductory programming courses. This tool provides support for teaching and learning. From the teacher's perspective the system introduces important gains with respect to the classical teaching methodology. It reinforces lecture and laboratory sessions, makes it possible to give personalized attention to the student, assesses the degree of participation of the students and most importantly, performs a continuous assessment of the student's progress. From the student's perspective it provides a learning framework, consisting in a help environment and a correction environment, which facilitates their personal work. With this tool students are more motivated to do programming

An economic decision support tool for simulating paratuberculosis control strategies in a UK suckler beef herd

A dynamic, deterministic, economic simulation model was developed to estimate the costs and benefits of controlling Mycobacterium avium subsp. paratuberculosis (Johne's disease) in a suckler beef herd. The model is intended as a demonstration tool for veterinarians to use with farmers. The model design process involved user consultation and participation and the model is freely accessible on a dedicated website. The 'user-friendly' model interface allows the input of key assumptions and farm specific parameters enabling model simulations to be tailored to individual farm circumstances. The model simulates the effect of Johne's disease and various measures for its control in terms of herd prevalence and the shedding states of animals within the herd, the financial costs of the disease and of any control measures and the likely benefits of control of Johne's disease for the beef suckler herd over a 10-year period. The model thus helps to make more transparent the 'hidden costs' of Johne's in a herd and the likely benefits to be gained from controlling the disease. The control strategies considered within the model are 'no control', 'testing and culling of diagnosed animals', 'improving management measures' or a dual strategy of 'testing and culling in association with improving management measures'. An example 'run' of the model shows that the strategy 'improving management measures', which reduces infection routes during the early stages, results in a marked fall in herd prevalence and total costs. Testing and culling does little to reduce prevalence and does not reduce total costs over the 10-year period.