287 resultados para Heterogeneous UAVs


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Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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Transport processes within heterogeneous media may exhibit non-classical diffusion or dispersion; that is, not adequately described by the classical theory of Brownian motion and Fick's law. We consider a space fractional advection-dispersion equation based on a fractional Fick's law. The equation involves the Riemann-Liouville fractional derivative which arises from assuming that particles may make large jumps. Finite difference methods for solving this equation have been proposed by Meerschaert and Tadjeran. In the variable coefficient case, the product rule is first applied, and then the Riemann-Liouville fractional derivatives are discretised using standard and shifted Grunwald formulas, depending on the fractional order. In this work, we consider a finite volume method that deals directly with the equation in conservative form. Fractionally-shifted Grunwald formulas are used to discretise the fractional derivatives at control volume faces. We compare the two methods for several case studies from the literature, highlighting the convenience of the finite volume approach.

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We study a political economy model which aims to understand the diversity in the growth and technology-adoption experiences in different economies. In this model the cost of technology adoption is endogenous and varies across heterogeneous agents. Agents in the model vote on the proportion of revenues allocated towards such expenditures. In the early stages of development, the political-economy outcome of the model ensures that a sub-optimal proportion of government revenue is used to finance adoption-cost reducing expenditures. This sub-optimality is due to the presence of inequality; agents at the lower end of the distribution favor a larger amount of revenue allocated towards redistribution in the form of lump-sum transfers. Eventually all individuals make the switch to the better technology and their incomes converge. The outcomes of the model therefore explain why public choice is more likely to be conservative in nature; it represents the majority choice given conflicting preferences among agents. Consequently, the transition path towards growth and technology adoption varies across countries depending on initial levels of inequality.

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An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs). Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV. This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management.

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We used Magnetic Resonance microimaging (μMRI) to study the compressive behaviour of synthetic elastin. Compression-induced changes in the elastin sample were quantified using longitudinal and transverse spin relaxation rates (R1 and R2, respectively). Spatially-resolved maps of each spin relaxation rate were obtained, allowing the heterogeneous texture of the sample to be observed with and without compression. Compression resulted in an increase of both the mean R1 and the mean R2, but most of this increase was due to sub-locations that exhibited relatively low R1 and R2 in the uncompressed state. This behaviour can be described by differential compression, where local domains in the hydrogel with a relatively low biopolymer content compress more than those with a relatively high biopolymer content.

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The decisions people make about medical treatments have a great impact on their lives. Health care practitioners, providers and patients often make decisions about medical treatments without complete understanding of the circumstances. The main reason for this is that medical data are available in fragmented, disparate and heterogeneous data silos. Without a centralised data warehouse structure to integrate these data silos, it is highly unlikely and impractical for the users to get all the information required on time to make a correct decision. In this research paper, a clinical data integration approach using SAS Clinical Data Integration Server tools is presented.

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One important challenge for regenerative medicine is to produce a clinically relevant number of cells with consistent tissue-forming potential. Isolation and expansion of cells from skeletal tissues results in a heterogeneous population of cells with variable regenerative potential. A more consistent tissue formation could be achieved by identification and selection of potent progenitors based on cell surface molecules. In this study, we assessed the expression of stage-specific embryonic antigen-4 (SSEA-4), a classic marker of undifferentiated stem cells, and other surface markers in human articular chondrocytes (hACs), osteoblasts, and bone marrow-derived mesenchymal stromal cells (bmMSCs) and characterized their differentiation potential. Further, we sorted SSEA-4-expressing hACs and followed their potential to proliferate and to form cartilage in vitro. Cells isolated from cartilage and bone exhibited remarkably heterogeneous SSEA-4 expression profiles in expansion cultures. SSEA-4 expression levels increased up to approximately 5 population doublings, but decreased following further expansion and differentiation cultures; levels were not related to the proliferation state of the cells. Although SSEA-4-sorted chondrocytes showed a slightly better chondrogenic potential than their SSEA-4-negative counterparts, differences were insufficient to establish a link between SSEA-4 expression and chondrogenic potential. SSEA-4 levels in bmMSCs also did not correlate to the cells' chondrogenic and osteogenic potential in vitro. SSEA-4 is clearly expressed by subpopulations of proliferating somatic cells with a MSC-like phenotype. However, the predictive value of SSEA-4 as a specific marker of superior differentiation capacity in progenitor cell populations from adult human tissue and even its usefulness as a stem cell marker appears questionable.

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The presence of insect pests in grain storages throughout the supply chain is a significant problem for farmers, grain handlers, and distributors world-wide. Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of pest populations. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 and 3 dimensions showed that insect numbers were positively correlated over short (0.5 cm) distances, and negatively correlated over longer (.10 cm) distances. At 35 C, insects were located significantly further from the grain surface than at 25 and 30 C. Dispersion metrics showed statistically significant aggregation in all cases. The observed heterogeneous spatial distribution of R. dominica may also be influenced by factors such as the site of initial infestation and disturbance during handling. To account for these additional factors, I significantly extended a simulation model that incorporates both pest growth and movement through a typical stored-grain supply chain. By incorporating the effects of abundance, initial infestation site, grain handling, and treatment on pest spatial distribution, I developed a supply chain model incorporating estimates of pest spatial distribution. This was used to examine several scenarios representative of grain movement through a supply chain, and determine the influence of infestation location and grain disturbance on the sampling intensity required to detect pest infestations at various infestation rates. This study has investigated the effects of temperature, infestation point, and grain handling on the spatial distribution and detection of R. dominica. The proportion of grain infested was found to be dependent upon abundance, initial pest location, and grain handling. Simulation modelling indicated that accounting for these factors when developing sampling strategies for stored grain has the potential to significantly reduce sampling costs while simultaneously improving detection rate, resulting in reduced storage and pest management cost while improving grain quality.

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Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.

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The price formation of financial assets is a complex process. It extends beyond the standard economic paradigm of supply and demand to the understanding of the dynamic behavior of price variability, the price impact of information, and the implications of trading behavior of market participants on prices. In this thesis, I study aggregate market and individual assets volatility, liquidity dimensions, and causes of mispricing for US equities over a recent sample period. How volatility forecasts are modeled, what determines intradaily jumps and causes changes in intradaily volatility and what drives the premium of traded equity indexes? Are they induced, for example, by the information content of lagged volatility and return parameters or by macroeconomic news, changes in liquidity and volatility? Besides satisfying our intellectual curiosity, answers to these questions are of direct importance to investors developing trading strategies, policy makers evaluating macroeconomic policies and to arbitrageurs exploiting mispricing in exchange-traded funds. Results show that the leverage effect and lagged absolute returns improve forecasts of continuous components of daily realized volatility as well as jumps. Implied volatility does not subsume the information content of lagged returns in forecasting realized volatility and its components. The reported results are linked to the heterogeneous market hypothesis and demonstrate the validity of extending the hypothesis to returns. Depth shocks, signed order flow, the number of trades, and resiliency are the most important determinants of intradaily volatility. In contrast, spread shock and resiliency are predictive of signed intradaily jumps. There are fewer macroeconomic news announcement surprises that cause extreme price movements or jumps than those that elevate intradaily volatility. Finally, the premium of exchange-traded funds is significantly associated with momentum in net asset value and a number of liquidity parameters including the spread, traded volume, and illiquidity. The mispricing of industry exchange traded funds suggest that limits to arbitrage are driven by potential illiquidity.

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This paper outlines an innovative and feasible flight control scheme for a rotary-wing unmanned aerial system (RUAS) with guaranteed safety and reliable flight quality in a gusty environment. The proposed control methodology aims to increase gust-attenuation capability of a RUAS to ensure improved flight performance when strong gusts occur. Based on the design of an effective estimator, an altitude controller is firstly constructed to synchronously compensate for fluctuations of the main rotor thrust which might lead to crashes in a gusty environment. Afterwards, a nonlinear state feedback controller is proposed to stabilize horizontal positions of the RUAS with gust-attenuation property. Performance of the proposed control framework is evaluated using parameters of a Vario XLC helicopter and high-fidelity simulations show that the proposed controllers can effectively reduce side-effect of gusts and demonstrate performance improvement when compared with the proportional-integral-derivative (PID) controllers.

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Nano-tin oxide was deposited on the surface of wollastonite using the mixed solution including stannic chloride pentahydrate precursor and wollastonite by a hydrolysis precipitation process. The antistatic properties of the wollastonite materials under different calcined conditions and composite materials (nano-SnO2/wollastonite, SW) were measured by rubber sheeter and four-point probe (FPP) sheet resistance measurement. Effects of hydrolysis temperature and time, calcination temperature and time, pH value and nano-SnO2 coating amount on the resistivity of SW powders were studied, and the optimum experimental conditions were obtained. The microstructure and surface properties of wollastonite, precipitate and SW were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray spectrometry (EDS), specific surface area analyzer (BET), thermogravimetry (TG), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and Fourier translation infrared spectroscopy (FTIR) respectively. The results showed that the nano-SnO2/wollastonite composite materials under optimum preparation conditions showed better antistatic properties, the resistivity of which was reduced from 1.068 × 104 Ω cm to 2.533 × 103 Ω cm. From TG and XRD analysis, the possible mechanism for coating of SnO2 nanoparticles on the surface of wollastonite was proposed. The infrared spectrum indicated that there were a large number of the hydroxyl groups on the surface of wollastonite. This is beneficial to the heterogeneous nucleation reaction. Through morphology, EDS and XPS analysis, the surface of wollastonite fiber was coated with a layer of 10–15 nm thickness of tin oxide grains the distribution of which was uniform.

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Students entering tertiary studies possess a diverse range of prior experiences in their academic preparation for tertiary chemistry so academics need tools to enable them to respond to issues in diversity in conceptual models possessed by entering students. Concept inventories can be used to provide formative feedback to help students identify concepts that they need to address to improve construction of subsequent understanding enabling their learning. Modular, formative learning activities that can be administered inside or outside of class in first year chemistry courses have been developed. These activities address key missing and mis-conceptions possessed by incoming student. Engagement in these learning activities by students and academics will help shift the culture of diagnostic and formative assessment within the tertiary context and address issues around the secondary/tertiary transition. This diagnostic/intervention framework is currently being trialed across five Australian tertiary institutions encompassing a large heterogeneous sample of students.

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Text categorisation is challenging, due to the complex structure with heterogeneous, changing topics in documents. The performance of text categorisation relies on the quality of samples, effectiveness of document features, and the topic coverage of categories, depending on the employing strategies; supervised or unsupervised; single labelled or multi-labelled. Attempting to deal with these reliability issues in text categorisation, we propose an unsupervised multi-labelled text categorisation approach that maps the local knowledge in documents to global knowledge in a world ontology to optimise categorisation result. The conceptual framework of the approach consists of three modules; pattern mining for feature extraction; feature-subject mapping for categorisation; concept generalisation for optimised categorisation. The approach has been promisingly evaluated by compared with typical text categorisation methods, based on the ground truth encoded by human experts.

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Temperate Australia sits between the heat engine of the tropics and the cold Southern Ocean, encompassing a range of rainfall regimes and falling under the influence of different climatic drivers. Despite this heterogeneity, broad-scale trends in climatic and environmental change are evident over the past 30 ka. During the early glacial period (∼30–22 ka) and the Last Glacial Maximum (∼22–18 ka), climate was relatively cool across the entire temperate zone and there was an expansion of grasslands and increased fluvial activity in regionally important Murray–Darling Basin. The temperate region at this time appears to be dominated by expanded sea ice in the Southern Ocean forcing a northerly shift in the position of the oceanic fronts and a concomitant influx of cold water along the southeast (including Tasmania) and southwest Australian coasts. The deglacial period (∼18–12 ka) was characterised by glacial recession and eventual disappearance resulting from an increase in temperature deduced from terrestrial records, while there is some evidence for climatic reversals (e.g. the Antarctic Cold Reversal) in high resolution marine sediment cores through this period. The high spatial density of Holocene terrestrial records reveals an overall expansion of sclerophyll woodland and rainforest taxa across the temperate region after ∼12 ka, presumably in response to increasing temperature, while hydrological records reveal spatially heterogeneous hydro-climatic trends. Patterns after ∼6 ka suggest higher frequency climatic variability that possibly reflects the onset of large scale climate variability caused by the El Niño/Southern Oscillation.