Steady state and transient dynamometer vehicle emission measurements using a DiSC

Analysis of the particulate size and number concentration emissions from a fleet of inner city medium duty CNG buses was conducted using the newly available Diffusion Size Classifier in comparison with more traditional SMPS's and CPC's. Studies were conducted at both steady state and transient driving modes on a vehicle dynamometer utilising a CVS dilution system. Comparative analysis of the results showed that the DiSC provided equivalent information during steady state conditions and was able to provide additional information during transient conditions, namely, the modal diameter of the particle size distribution.

SWCNT networks on nanoporous silica catalyst support : morphological and connectivity control for nanoelectronic, gas-sensing, and biosensing devices

Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions

The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

Charge transport study of high mobility polymer thin-film transistors based on thiophene substituted diketopyrrolopyrrole copolymers

In this paper, we report on the device physics and charge transport characteristics of high-mobility dual-gated polymer thin-film transistors with active semiconductor layers consisting of thiophene flanked DPP with thienylene-vinylene-thienylene (PDPP-TVT) alternating copolymers. Room temperature mobilities in these devices are high and can exceed 2 cm2 V-1 s-1. Steady-state and non-quasi-static measurements have been performed to extract key transport parameters and velocity distributions of charge carriers in this copolymer. Charge transport in this polymer semiconductor can be explained using a Multiple-Trap-and-Release or Monroe-type model. We also compare the activation energy vs. field-effect mobility in a few important polymer semiconductors to gain a better understanding of transport of DPP systems and make appropriate comparisons.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Efficiently capturing large, complex cultural heritage sites with a handheld mobile 3D laser mapping system

Accurate three-dimensional representations of cultural heritage sites are highly valuable for scientific study, conservation, and educational purposes. In addition to their use for archival purposes, 3D models enable efficient and precise measurement of relevant natural and architectural features. Many cultural heritage sites are large and complex, consisting of multiple structures spatially distributed over tens of thousands of square metres. The process of effectively digitising such geometrically complex locations requires measurements to be acquired from a variety of viewpoints. While several technologies exist for capturing the 3D structure of objects and environments, none are ideally suited to complex, large-scale sites, mainly due to their limited coverage or acquisition efficiency. We explore the use of a recently developed handheld mobile mapping system called Zebedee in cultural heritage applications. The Zebedee system is capable of efficiently mapping an environment in three dimensions by continually acquiring data as an operator holding the device traverses through the site. The system was deployed at the former Peel Island Lazaret, a culturally significant site in Queensland, Australia, consisting of dozens of buildings of various sizes spread across an area of approximately 400 × 250 m. With the Zebedee system, the site was scanned in half a day, and a detailed 3D point cloud model (with over 520 million points) was generated from the 3.6 hours of acquired data in 2.6 hours. We present results demonstrating that Zebedee was able to accurately capture both site context and building detail comparable in accuracy to manual measurement techniques, and at a greatly increased level of efficiency and scope. The scan allowed us to record derelict buildings that previously could not be measured because of the scale and complexity of the site. The resulting 3D model captures both interior and exterior features of buildings, including structure, materials, and the contents of rooms.

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

The topography of multiple drug use among adolescent Australians : findings from the National Drug Strategy Household Survey

Introduction and aims: Despite evidence that many Australian adolescents have considerable experience with various drug types, little is known about the extent to which adolescents use multiple substances. The aim of this study was to examine the degree of clustering of drug types within individuals, and the extent to which demographic and psychosocial predictors are related to cluster membership. Design and method: A sample of 1402 adolescents aged 12-17. years were extracted from the Australian 2007 National Drug Strategy Household Survey. Extracted data included lifetime use of 10 substances, gender, psychological distress, physical health, perceived peer substance use, socioeconomic disadvantage, and regionality. Latent class analysis was used to determine clusters, and multinomial logistic regression employed to examine predictors of cluster membership. Result: There were 3 latent classes. The great majority (79.6%) of adolescents used alcohol only, 18.3% were limited range multidrug users (encompassing alcohol, tobacco, and marijuana), and 2% were extended range multidrug users. Perceived peer drug use and psychological distress predicted limited and extended multiple drug use. Psychological distress was a more significant predictor of extended multidrug use compared to limited multidrug use. Discussion and conclusion: In the Australian school-based prevention setting, a very strong focus on alcohol use and the linkages between alcohol, tobacco and marijuana are warranted. Psychological distress may be an important target for screening and early intervention for adolescents who use multiple drugs.

Multiple criteria-based real-time decision making by autonomous city vehicles

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

Theorizing the use of multiple conceptual models in combination

Conceptual modelling continues to be an important means for graphically capturing the requirements of an information system. Observations of modelling practice suggest that modellers often use multiple conceptual models in combination, because they articulate different aspects of real-world domains. Yet, the available empirical as well as theoretical research in this area has largely studied the use of single models, or single modelling grammars. We develop a Theory of Combined Ontological Coverage by extending an existing theory of ontological expressiveness of conceptual modelling grammars. Our new theory posits that multiple conceptual models are used to increase the maximum coverage of the real-world domain being modelled, whilst trying to minimize the ontological overlap between the models. We illustrate how the theory can be applied to analyse sets of conceptual models. We develop three propositions of the theory about evaluations of model combinations in terms of users’ selection, understandability and usefulness of conceptual models.

Population variation in biomonitoring data for persistent organic pollutants (POPs) : an examination of multiple population-based datasets for application to Australian pooled biomonitoring data

Background Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. Methods Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2′,4,4′ tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Results Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. Conclusions Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

Efficient multiple relay selection for cooperative communication using alamouti-coded virtual transmit antenna systems

An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.