Smart technologies for peanut industry

Commercialisation and adoption of remote sensing and GIS technologies for improved production forecasting, productivity, quality and paddock- to- plate tracking within the Australian Peanut Industry.

From mundane to smart: Exploring interactions with ‘smart' design objects

In addition to functional and technological features, the role of augmented objects should also be seen in terms of how effectively they fit into the everyday practices of users and how they enhance users' experiences. In this article, the authors introduce a low-tech, internet-of-things technology called CAM (Cooperative Artefact Memory) that is used as a collaborative tool in design studio environments. CAM works as an object memory technology and allows industrial and product designers to collaboratively store relevant information onto their physical design objects, such as sketches, collages, storyboards, and physical mock-ups in the form of messages, annotations and external web links. In the context of this study, CAM serves as an important probing device to understand designers' interaction and experiences with augmented design objects, in their natural environment. The authors carried out a small-scale field trial of CAM in an academic design studio, over three student design projects. In this article, they discuss the findings of their field trial and show how CAM was used by the participants, how it was integrated into the design process and how it was appropriated for different purposes. The authors also found that CAM supported coordination and awareness within the design teams, yet its serendipitous and asynchronous nature facilitated creative and playful interactions between team members. In general, the results show how CAM transformed mundane design objects into “smart” objects that made the creative and playful side of cooperative design visible.

Grids with multiple batch systems for performance enhancement of multi-component and parameter sweep parallel applications

In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies(FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

Analysis of DNA sequence transformations on grids

Study of the evolution of species or organisms is essential for various biological applications. Evolution is typically studied at the molecular level by analyzing the mutations of DNA sequences of organisms. Techniques have been developed for building phylogenetic or evolutionary trees for a set of sequences. Though phylogenetic trees capture the overall evolutionary relationships among the sequences, they do not reveal fine-level details of the evolution. In this work, we attempt to resolve various fine-level sequence transformation details associated with a phylogenetic tree using cellular automata. In particular, our work tries to determine the cellular automata rules for neighbor-dependent mutations of segments of DNA sequences. We also determine the number of time steps needed for evolution of a progeny from an ancestor and the unknown segments of the intermediate sequences in the phylogenetic tree. Due to the existence of vast number of cellular automata rules, we have developed a grid system that performs parallel guided explorations of the rules on grid resources. We demonstrate our techniques by conducting experiments on a grid comprising machines in three countries and obtaining potentially useful statistics regarding evolutions in three HIV sequences. In particular, our work is able to verify the phenomenon of neighbor-dependent mutations and find that certain combinations of neighbor-dependent mutations, defined by a cellular automata rule, occur with greater than 90% probability. We also find the average number of time steps for mutations for some branches of phylogenetic tree over a large number of possible transformations with standard deviations less than 2.

Anion directed template synthesis of Cu(II) complexes of a N,N,O donor mono-condensed Schiff base ligand: A molecular scaffold forming highly ordered H-bonded rectangular grids

Anion directed, template syntheses of two dinuclear copper(II) complexes of mono-condensed Schiff base ligand Hdipn (4-[(3-aminopentylimino)-methyl]-benzene-1,3-diol) involving 2,4- dihydroxybenzaldehyde and 1,3-diaminopentane were realized in the presence of bridging azide and acetate anions. Both complexes, [Cu-2(dipn)(2)(N-3)(2)] (1) and [Cu-2(dip(n))(2)(OAc)(2)] (2) have been characterized by X-ray crystallography. The two mononuclear units are joined together by basal-apical, double end-on azido bridges in complex 1 and by basal-apical, double mono-atomic acetate oxygen-bridges in 2. Both complexes form rectangular grid-like supramolecular structures via H-bonds connecting the azide or acetate anion and the p-hydroxy group of 2,4- dihydroxybenzaldehyde. Variable-temperature (300-2 K) magnetic susceptibility measurements reveal that complex 1 has antiferromagnetic coupling (J = -2.10 cm (1)) through the azide bridge while 2 has intra-dimer ferromagnetic coupling through the acetate bridge and inter-dimer antiferromagnetic coupling through H-bonds (J = 2.85 cm (1), J' = -1.08 cm (1)). (C) 2009 Elsevier B. V. All rights reserved.

Why we should design smart cities for getting lost

If smart cities run on big data and algorithms that channel only 'relevant' information and opinions to us, how do we maintain the diversity of ideas and possibilities that drives truly smart cities?

KFVS (Kinetic Flux Vector Splitting) on moving grids for unsteady aerodynamics

Accurate numerical solutions to the problems in fluid-structure (aeroelasticity) interaction are becoming increasingly important in recent years. The methods based on FCD (Fixed Computational Domain) and ALE (Alternate Lagrangian Eulerian) to solve such problems suffer from numerical instability and loss of accuracy. They are not general and can not be extended to the flowsolvers on unstructured meshes. Also, global upwind schemes can not be used in ALE formulation thus leads to the development of flow solvers on moving grids. The KFVS method has been shown to be easily amenable on moving grids required in unsteady aerodynamics. The ability of KFMG (Kinetic Flux vector splitting on Moving Grid) Euler solver in capturing shocks, expansion waves with small and very large pressure ratios and contact discontinuities has been demonstrated.

Smart applications for energy harvested WSNs

A Wireless Sensor Network (WSN) powered using harvested energies is limited in its operation by instantaneous power. Since energy availability can be different across nodes in the network, network setup and collaboration is a non trivial task. At the same time, in the event of excess energy, exciting node collaboration possibilities exist; often not feasible with battery driven sensor networks. Operations such as sensing, computation, storage and communication are required to achieve the common goal for any sensor network. In this paper, we design and implement a smart application that uses a Decision Engine, and morphs itself into an energy matched application. The results are based on measurements using IRIS motes running on solar energy. We have done away with batteries; instead used low leakage super capacitors to store harvested energy. The Decision Engine utilizes two pieces of data to provide its recommendations. Firstly, a history based energy prediction model assists the engine with information about in-coming energy. The second input is the energy cost database for operations. The energy driven Decision Engine calculates the energy budgets and recommends the best possible set of operations. Under excess energy condition, the Decision Engine, promiscuously sniffs the neighborhood looking for all possible data from neighbors. This data includes neighbor's energy level and sensor data. Equipped with this data, nodes establish detailed data correlation and thus enhance collaboration such as filling up data gaps on behalf of nodes hibernating under low energy conditions. The results are encouraging. Node and network life time of the sensor nodes running the smart application is found to be significantly higher compared to the base application.

Evaluation of bearing capacity improvement using composite grids

Recently, composite reinforcements in which combinations of materials and material forms such as strips, grids, and strips and anchors, depending on requirements have proven to be effective in various ground improvement applications. Composite geogrids studied in this paper belong to the category of composite reinforcements and are useful for bearing capacity improvement. The paper presents evaluation of results of bearing capacity tests conducted oil a composite geogrid, made of composite reinforcement consisting of steel and cement mortar. The study shows that the behavior of composite reinforcements follows the general trends observed in the case of conventional geogrids, with reference to the depth of first layer below the footing, number of layers of reinforcement, and vertical spacing of the reinforcement. Results show that the performance is comparable to that of a conventional polymer geogrid.

Strategies for Rescheduling Tightly-Coupled Parallel Applications in Multi-Cluster Grids

As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

Executing Long-running Multi-component Applications on Batch Grids

Computational grids are increasingly being used for executing large multi-component scientific applications. The most widely reported advantages of application execution on grids are the performance benefits, in terms of speeds, problem sizes or quality of solutions, due to increased number of processors. We explore the possibility of improved performance on grids without increasing the application’s processor space. For this, we consider grids with multiple batch systems. We explore the challenges involved in and the advantages of executing long-running multi-component applications on multiple batch sites with a popular multi-component climate simulation application, CCSM, as the motivation.We have performed extensive simulation studies to estimate the single and multi-site execution rates of the applications for different system characteristics.Our experiments show that in many cases, multiple batch executions can have better execution rates than a single site execution.