Image based visual servo control for fixed wing UAVs tracking linear infrastructure in wind

This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

Study of new particle formation in subtropical urban environment in Brisbane, Australia

Atmospheric ultrafine particles play an important role in affecting human health, altering climate and degrading visibility. Numerous studies have been conducted to better understand the formation process of these particles, including field measurements, laboratory chamber studies and mathematical modeling approaches. Field studies on new particle formation found that formation processes were significantly affected by atmospheric conditions, such as the availability of particle precursors and meteorological conditions. However, those studies were mainly carried out in rural areas of the northern hemisphere and information on new particle formation in urban areas, especially those in subtropical regions, is limited. In general, subtropical regions display a higher level of solar radiation, along with stronger photochemical reactivity, than those regions investigated in previous studies. However, based on the results of these studies, the mechanisms involved in the new particle formation process remain unclear, particularly in the Southern Hemisphere. Therefore, in order to fill this gap in knowledge, a new particle formation study was conducted in a subtropical urban area in the Southern Hemisphere during 2009, which measured particle size distribution in different locations in Brisbane, Australia. Characterisation of nucleation events was conducted at the campus building of the Queensland University of Technology (QUT), located in an urban area of Brisbane. Overall, the annual average number concentrations of ultrafine, Aitken and nucleation mode particles were found to be 9.3 x 103, 3.7 x 103 and 5.6 x 103 cm-3, respectively. This was comparable to levels measured in urban areas of northern Europe, but lower than those from polluted urban areas such as the Yangtze River Delta, China and Huelva and Santa Cruz de Tenerife, Spain. Average particle number concentration (PNC) in the Brisbane region did not show significant seasonal variation, however a relatively large variation was observed during the warmer season. Diurnal variation of Aitken and nucleation mode particles displayed different patterns, which suggested that direct vehicle exhaust emissions were a major contributor of Aitken mode particles, while nucleation mode particles originated from vehicle exhaust emissions in the morning and photochemical production at around noon. A total of 65 nucleation events were observed during 2009, in which 40 events were classified as nucleation growth events and the remainder were nucleation burst events. An interesting observation in this study was that all nucleation growth events were associated with vehicle exhaust emission plumes, while the nucleation burst events were associated with industrial emission plumes from an industrial area. The average particle growth rate for nucleation events was found to be 4.6 nm hr-1 (ranging from 1.79-7.78 nm hr-1), which is comparable to other urban studies conducted in the United States, while monthly particle growth rates were found to be positively related to monthly solar radiation (r = 0.76, p <0.05). The particle growth rate values reported in this work are the first of their kind to be reported for the subtropical urban area of Australia. Furthermore, the influence of nucleation events on PNC within the urban airshed was also investigated. PNC was simultaneously measured at urban (QUT), roadside (Woolloongabba) and semi-urban (Rocklea) sites in Brisbane during 2009. Total PNC at these sites was found to be significantly affected by regional nucleation events. The relative fractions of PNC to total daily PNC observed at QUT, Woolloongabba and Rocklea were found to be 12%, 9% and 14%, respectively, during regional nucleation events. These values were higher than those observed as a result of vehicle exhaust emissions during weekday mornings, which ranged from 5.1-5.5% at QUT and Woolloongabba. In addition, PNC in the semi-urban area of Rocklea increased by a factor of 15.4 when it was upwind from urban pollution sources under the influence of nucleation burst events. Finally, we investigated the influence of sulfuric acid on new particle formation in the study region. A H2SO4 proxy was calculated by using [SO2], solar radiation and particle condensation sink data to represent the new particle production strength for the urban, roadside and semi-urban areas of Brisbane during the period June-July of 2009. The temporal variations of the H2SO4 proxies and the nucleation mode particle concentration were found to be in phase during nucleation events in the urban and roadside areas. In contrast, the peak of proxy concentration occurred 1-2 hr prior to the observed peak in nucleation mode particle concentration at the downwind semi-urban area of Brisbane. A moderate to strong linear relationship was found between the proxy and the freshly formed particles, with r2 values of 0.26-0.77 during the nucleation events. In addition, the log[H2SO4 proxy] required to produce new particles was found to be ~1.0 ppb Wm-2 s and below 0.5 ppb Wm-2 s for the urban and semi-urban areas, respectively. The particle growth rates were similar during nucleation events at the three study locations, with an average value of 2.7 ± 0.5 nm hr-1. This result suggested that a similar nucleation mechanism dominated in the study region, which was strongly related to sulphuric acid concentration, however the relationship between the proxy and PNC was poor in the semi-urban area of Rocklea. This can be explained by the fact that the nucleation process was initiated upwind of the site and the resultant particles were transported via the wind to Rocklea. This explanation is also supported by the higher geometric mean diameter value observed for particles during the nucleation event and the time lag relationship between the H2SO4 proxy and PNC observed at Rocklea. In summary, particle size distribution was continuously measured in a subtropical urban area of southern hemisphere during 2009, the findings from which formed the first particle size distribution dataset in the study region. The characteristics of nucleation events in the Brisbane region were quantified and the properties of the nucleation growth and burst events are discussed in detail using a case studies approach. To further investigate the influence of nucleation events on PNC in the study region, PNC was simultaneously measured at three locations to examine the spatial variation of PNC during the regional nucleation events. In addition, the impact of upwind urban pollution on the downwind semi-urban area was quantified during these nucleation events. Sulphuric acid was found to be an important factor influencing new particle formation in the urban and roadside areas of the study region, however, a direct relationship with nucleation events at the semi-urban site was not observed. This study provided an overview of new particle formation in the Brisbane region, and its influence on PNC in the surrounding area. The findings of this work are the first of their kind for an urban area in the southern hemisphere.

First steps towards modeling a multi-scale Earth system

Recent advances in computational geodynamics are applied to explore the link between Earth’s heat, its chemistry and its mechanical behavior. Computational thermal-mechanical solutions are now allowing us to understand Earth patterns by solving the basic physics of heat transfer. This approach is currently used to solve basic convection patterns of terrestrial planets. Applying the same methodology to smaller scales delivers promising similarities between observed and predicted structures which are often the site of mineral deposits. The new approach involves a fully coupled solution to the energy, momentum and continuity equations of the system at all scales, allowing the prediction of fractures, shear zones and other typical geological patterns out of a randomly perturbed initial state. The results of this approach are linking a global geodynamic mechanical framework over regional-scale mineral deposits down to the underlying micro-scale processes. Ongoing work includes the challenge of incorporating chemistry into the formulation.

How collaborative technology supports cognitive processes in collaborative process modeling : a capabilities-gains-outcome model

We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.

Construct Redundancy in Process Modeling Grammars: Improving the Explanatory Power of Ontological Analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature.

Deposition of hydrocarbon molecules on diamond (001) surfaces : atomic scale modeling

The impact induced chemisorption of hydrocarbon molecules (CH3 and CH2) on H-terminated diamond (001)-(2x1) surface was investigated by molecular dynamics simulation using the many-body Brenner potential. The deposition dynamics of the CH3 radical at impact energies of 0.1-50 eV per molecule was studied and the energy threshold for chemisorption was calculated. The impact-induced decomposition of hydrogen atoms and the dimer opening mechanism on the surface was investigated. Furthermore, the probability for dimer opening event induced by chemisorption of CH, was simulated by randomly varying the impact position as well as the orientation of the molecule relative to the surface. Finally, the energetic hydrocarbons were modeled, slowing down one after the other to simulate the initial fabrication of diamond-like carbon (DLC) films. The structure characteristic in synthesized films with different hydrogen flux was studied. Our results indicate that CH3, CH2 and H are highly reactive and important species in diamond growth. Especially, the fraction of C-atoms in the film having sp(3) hybridization will be enhanced in the presence of H atoms, which is in good agreement with experimental observations. (C) 2002 Elsevier Science B.V. All rights reserved.

The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

Computer modeling of diffusion in biological tissues

Molecular-level computer simulations of restricted water diffusion can be used to develop models for relating diffusion tensor imaging measurements of anisotropic tissue to microstructural tissue characteristics. The diffusion tensors resulting from these simulations can then be analyzed in terms of their relationship to the structural anisotropy of the model used. As the translational motion of water molecules is essentially random, their dynamics can be effectively simulated using computers. In addition to modeling water dynamics and water-tissue interactions, the simulation software of the present study was developed to automatically generate collagen fiber networks from user-defined parameters. This flexibility provides the opportunity for further investigations of the relationship between the diffusion tensor of water and morphologically different models representing different anisotropic tissues.

Business process variability modeling : A survey

It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade leading to an array of approaches to business process variability modeling. This survey examines existing approaches in this field based on a common set of criteria and illustrates their key concepts using a running example. The analysis shows that existing approaches are characterized by the fact that they extend a conventional process mod- eling language with constructs that make it able to capture customizable process models. A customizable process model represents a family of process variants in a way that each variant can be derived by adding or deleting fragments according to configuration parameters or according to a domain model. The survey puts into evidence an abundance of customizable process modeling languages, embodying a diverse set of con- structs. In contrast, there is comparatively little tool support for analyzing and constructing customizable process models, as well as a scarcity of empirical evaluations of languages in the field.

Modeling obligations with event-calculus

Time plays an important role in norms. In this paper we start from our previously proposed classification of obligations, and point out some shortcomings of Event Calculus (EC) to represent obligations. We proposed an extension of EC that avoids such shortcomings and we show how to use it to model the various types of obligations.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

Modeling electricity price events as point processes

Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

A simple test method for profiled steel cladding systems under wind uplift

A new simple test method using small scale models has been developed for testing profiled steel cladding systems under wind uplift/suction forces. This simple method should replace the large scale test method using two-span claddings used at present. It can be used for roof or wall cladding systems fastened with screw fasteners at crests or valleys.