The application of fiber Bragg grating sensor to high precision temperature measurement [基于光纤光栅的高精度测温传感器研究]

Basing on the character that Fiber Bragg Grating (FBG) is sensitive to both temperature and strain, by using Al and Fe-Ni alloy’s bimetal structure, we successfully design and manufacture a high accuracy FBG temperature sensor for earthquake premonition. Furthermore, we analyze the accuracy of the FBG sensors with enhanced sensitivity for the first time, and get its accuracy is up to ±0.05℃ with highest resolution ever in all FBG temperature sensors (0.0014℃/pm). This work experimentally proves the feasibility of using FBG in the earthquake premonition monitoring, and builds the foundation for the application of optic technology in earthquake premonition monitoring.

Recovery and reuse of ammonium from wastewater treatment plants : an application for agriculture

In wastewater treatment plants based on anaerobic digestion, supernatant and outflows from sludge dewatering systems contain significantly high amount of ammonium. Generally, these waters are returned to the head of wastewater treatment plant (WWTP), thereby increasing the total nitrogen load of the influent flow. Ammonium from these waters can be recovered and commercially utilised using novel ion-exchange materials. Mackinnon et al. have described an approach for removal and recovery of ammonium from side stream centrate returns obtained from anaerobic digester of a typical WWTP. Most of the ammonium from side streams can potentially be removed, which significantly reduces overall inlet demand at a WWTP. However, the extent of reduction achieved depends on the level of ammonium and flow-rate in the side stream. The exchange efficiency of the ion-exchange material, MesoLite, used in the ammonium recovery process deteriorates with long-term use due to mechanical degradation and use of regenerant. To ensure that a sustainable process is utilised a range of potential applications for this “spent” MesoLite have been evaluated. The primary focus of evaluations has been use of ammonium-loaded MesoLite as a source of nitrogen and growth medium for plants. A MesoLite fertiliser has advantage over soluble fertilisers in that N is held on an insoluble matrix and is gradually released according to exchange equilibria. Many conventional N fertilisers are water-soluble and thus, instantly release all applied N into the soil solution. Loss of nutrient commonly occurs through volatilisation and/or leaching. On average, up to half of the N delivered by a typical soluble fertiliser can be lost through these processes. In this context, use of ammonium-loaded MesoLite as a fertiliser has been evaluated using standard greenhouse and field-based experiments for low fertility soils. Rye grass, a suitable test species for greenhouse trials, was grown in 1kg pots over a period of several weeks with regular irrigation. Nitrogen was applied at a range of rates using a chemical fertiliser as a control and using two MesoLite fertilisers. All other nutrients were applied in adequate amounts. All treatments were replicated three times. Plants were harvested after four weeks, and dry plant mass and N concentrations were determined. At all nitrogen application rates, ammonium-loaded MesoLite produced higher plant mass than plants fertilised by the chemical fertiliser. The lower fertiliser effectiveness of the chemical fertliser is attributed to possible loss of some N through volatilisation. The MesoLite fertilisers did not show any adverse effect on availability of macro and trace nutrients, as shown by lack of deficiency symptoms, dry matter yield and plant analyses. Nitrogen loaded on to MesoLite in the form of exchanged ammonium is readily available to plants while remaining protected from losses via leaching and volatilisation. Spent MesoLite appears to be a suitable and effective fertiliser for a wide range of soils, particularly sandy soils with poor nutrient holding capacity.

Urban agriculture : a growing field of research workshop at INTERACT 2013

Growing food presents diverse challenges and opportunities within the urban environment. As cities develop, population density rises, land prices rise, and the opportunity to use land for traditional farming and gardening diminishes. Counter to this trend there are a growing number of both community gardens, city farms, guerrilla gardening, rooftop and vertical gardens, pot plants, windowsill herbs, and other balcony or backyard gardens cropping up in different cities, all with a purpose to produce food. This workshop brings to-gether practitioners and researchers in the field of urban agriculture and Hu-man-Computer Interaction to explore and opportunities for technology design to support the different forms of growing practice and foster local food production in cities. This 1-day workshop will serve as an active forum for researchers and practi-tioners across various fields including, but not limited to, agriculture and gar-dening, education, urban planning, human-computer interaction, and communi-ty engagement. This workshop has three distinct points of focus: i) Individual and small-scale gardening and food production, and how to connect like minded people who are involved in these practices to share their knowledge ii) Com-munities involved in urban agriculture, either through community gardens, city farms, or grassroots movements, often dependant on volunteer participation, providing the challenge of managing limited resources iii) Environmental and sociocultural sustainability through urban agriculture. The participants will have an opportunity to present their own work. This will be followed by a visit to a nearby city farm, which will provide a local context for a group design exercise. Finally the workshop will conclude with panel dis-cussions to review opportunities for further research and collaborations beyond the conference. For more information, please visit the workshop website, at http://www.urbaninformatics.net/resources/interact2013cfp/

Assessment of precision timing and real-time data networks for digital substation automation

This project researched the performance of emerging digital technology for high voltage electricity substations that significantly improves safety for staff and reduces the potential impact on the environment of equipment failure. The experimental evaluation used a scale model of a substation control system that incorporated real substation control and networking equipment with real-time simulation of the power system. The outcomes confirm that it is possible to implement Ethernet networks in high voltage substations that meet the needs of utilities; however component-level testing of devices is necessary to achieve this. The assessment results have been used to further develop international standards for substation communication and precision timing.

Determining process model precision and generalization with weighted artificial negative events

Process mining encompasses the research area which is concerned with knowledge discovery from event logs. One common process mining task focuses on conformance checking, comparing discovered or designed process models with actual real-life behavior as captured in event logs in order to assess the “goodness” of the process model. This paper introduces a novel conformance checking method to measure how well a process model performs in terms of precision and generalization with respect to the actual executions of a process as recorded in an event log. Our approach differs from related work in the sense that we apply the concept of so-called weighted artificial negative events towards conformance checking, leading to more robust results, especially when dealing with less complete event logs that only contain a subset of all possible process execution behavior. In addition, our technique offers a novel way to estimate a process model’s ability to generalize. Existing literature has focused mainly on the fitness (recall) and precision (appropriateness) of process models, whereas generalization has been much more difficult to estimate. The described algorithms are implemented in a number of ProM plugins, and a Petri net conformance checking tool was developed to inspect process model conformance in a visual manner.

Pragmatism and precision : psychology in the service of civil litigation

While forensic psychology is commonly associated with the criminal and family law domains, its ambit to offer skills and knowledge at the legal interface also makes it particularly suited to the civil law domain. At this time, civil law is arguably the least represented legislative area in terms of psychological research and professional commentary. However, it is also a broad area, with its very breadth providing scope for research consideration, as urged by Greene. The purposes of this article are (1) to review the broad role of the psychologist in the conduct of civil litigation matters in Australia, (2) to assist the novice to the area by indicating a non-exhaustive list of potentially ambiguous terms and concepts common to the conduct of professional practice, and; (3) to highlight, as an example, one area of practice not only where legal direction demands professional pragmatism but also where opportunity arises for psychological research to vitally address a major social issue.

Designing a seasonality application to support urban agriculture practice

This position paper describes the work in progress towards the goal of building a technical prototype that enables users – those who have little or no knowledge and experience engaging in urban agriculture – to receive information personalised to their location and situation, and allow them to ask questions and share experiences with others. We describe the design process thus far, informed by a survey and a workshop with experts in the field, before concluding with the future direction of this work.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Multifunctional agriculture in policy and practice? A comparative analysis of Norway and Australia

Ideals of productivist agriculture in the Western world have faded as the unintended consequences of intensive agriculture and pastoralism have contributed to rural decline and environmental problems. In Norway and Australia, there has been an increasing acceptance of the equal importance of social and environmental sustainability as well as economic sustainability. Alongside this shift is a belief that primary production needs to move away from an intensive, productivist-based agriculture to one that may be defined as post-productivist. In this paper, we argue that the dualism of productivism and post-productivism as concepts on agricultural policy regimes are too simplistic and discuss whether multifunctional agriculture is a better concept for a comparison of rural primary production at two extreme points of the scale, the market-oriented, liberalistic Australian agriculture and the market-protected small-scale Norwegian agriculture. We argue that multifunctionality in Australia rates relatively weakly as an ideology or policy and even less as a discourse or practice and hence is situated toward a ‘weak’ end of a continuum of a level of multifunctional agriculture. In Norwegian agriculture, multifunctional agriculture has thrived within a protectionist setting with the support of the public, the state and agricultural actors. In this sense it is very clearly a policy, practice and discourse that aims to preserve and conserve rural spaces, the cultural landscape, the farming way of life and food safety. Norway is as such situated toward a ‘strong’ end of a continuum of a level of multifunctional agriculture.

Robotics for sustainable broad-acre agriculture

This paper describes the development of small low-cost cooperative robots for sustainable broad-acre agriculture to increase broad-acre crop production and reduce environmental impact. The current focus of the project is to use robotics to deal with resistant weeds, a critical problem for Australian farmers. To keep the overall system affordable our robot uses low-cost cameras and positioning sensors to perform a large scale coverage task while also avoiding obstacles. A multi-robot coordinator assigns parts of a given field to individual robots. The paper describes the modification of an electric vehicle for autonomy and experimental results from one real robot and twelve simulated robots working in coordination for approximately two hours on a 55 hectare field in Emerald Australia. Over this time the real robot 'sprayed' 6 hectares missing 2.6% and overlapping 9.7% within its assigned field partition, and successfully avoided three obstacles.

Novelty-based visual obstacle detection in agriculture

This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.

Modeling nitrous oxide emissions from irrigated agriculture : testing DayCent with high-frequency measurements

A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.

Nanopore processing in dielectric materials and dielectric template-assisted nanoarray synthesis : using pulsed bias to enhance process throughput and precision

An effective technique to improve the precision and throughput of energetic ion condensation through dielectric nanoporous templates and reduce nanopore clogging by using finely tuned pulsed bias is proposed. Multiscale numerical simulations of ion deposition show the possibility of controlling the dynamic charge balance on the upper template's surface to minimize ion deposition on nanopore sidewalls and to deposit ions selectively on the substrate surface in contact with the pore opening. In this way, the shapes of nanodots in template-assisted nanoarray fabrication can be effectively controlled. The results are applicable to various processes involving porous dielectric nanomaterials and dense nanoarrays.

Vision based guidance for robot navigation in agriculture

This paper describes a novel vision based texture tracking method to guide autonomous vehicles in agricultural fields where the crop rows are challenging to detect. Existing methods require sufficient visual difference between the crop and soil for segmentation, or explicit knowledge of the structure of the crop rows. This method works by extracting and tracking the direction and lateral offset of the dominant parallel texture in a simulated overhead view of the scene and hence abstracts away crop-specific details such as colour, spacing and periodicity. The results demonstrate that the method is able to track crop rows across fields with extremely varied appearance during day and night. We demonstrate this method can autonomously guide a robot along the crop rows.