Seasonal and spatial variations in rare earth elements to identify inter-aquifer linkages and recharge processes in an Australian catchment

With the aim of elucidating the seasonal behaviour of rare earth elements (REEs), surface and groundwaters were collected under dry and wet conditions in different hydrological units of the Teviot Brook catchment (Southeast Queensland, Australia). Sampled waters showed a large degree of variability in both REE abundance and normalised patterns. Overall REE abundance ranged over nearly three orders of magnitude, and was consistently lower in the sedimentary bedrock aquifer (18ppt<∑REE<477ppt) than in the other hydrological systems studied. Abundance was greater in springs draining rhyolitic rocks (∑REE=300 and 2054ppt) than in springs draining basalt ranges (∑REE=25 and 83ppt), yet was highly variable in the shallow alluvial groundwater (16ppt<∑REE<5294ppt) and, to a lesser extent, in streamwater (85ppt<∑REE<2198ppt). Generally, waters that interacted with different rock types had different REE patterns. In order to obtain an unbiased characterisation of REE patterns, the ratios between light and middle REEs (R(M/L)) and the ratios between middle and heavy REEs (R(H/M)) were calculated for each sample. The sedimentary bedrock aquifer waters had highly evolved patterns depleted in light REEs and enriched in middle and heavy REEs (0.17processes and inter-aquifer mixing. They also underline the importance of conducting seasonal sampling campaigns to capture possible short-term variations in REE patterns and abundance, which is essential to enable a better understanding of hydrological and hydrochemical processes in complex geological settings

Characterization of alluvial formation by stochastic modelling of paleo-fluvial processes: The concept and method

Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity.

Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

Envisaging change: Supporting grassroots efforts in Colombia with agonistic design processes

Design has become increasingly engaged with bringing about social change. Shifting domains and perspectives to conflict stricken contexts yield opportunities to explore emerging forms of design that enable the expression and articulation of difference in productive ways, which can contribute positively to efforts related to civic issues and struggles in urban settings from developing countries. We explore the recently developed notion of Adversarial Design to support the integration of diverging perspectives and grassroots voices in the design process. This paper presents the findings and design insights from our study with two grassroots organisations in Bogota, Colombia. We present three themes that expose ways in which conflict motivates bringing about change, the importance of the social and physical features of the urban landscape, and the way in which social change acts as catalyst for acquiring new knowledge. To finalise, we discuss two design areas and how design could be used to integrate dissimilar worldviews.

Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes

Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

The subordinated processes controlled by a family of subordinators and corresponding Fokker-Planck type equations

In this work, we consider subordinated processes controlled by a family of subordinators which consist of a power function of a time variable and a negative power function of an α-stable random variable. The effect of parameters in the subordinators on the subordinated process is discussed. By suitable variable substitutions and the Laplace transform technique, the corresponding fractional Fokker–Planck-type equations are derived. We also compute their mean square displacements in a free force field. By choosing suitable ranges of parameters, the resulting subordinated processes may be subdiffusive, normal diffusive or superdiffusive

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

Monitoring care processes in the gynecologic oncology department

The care processes of healthcare providers are typically considered as human-centric, flexible, evolving, complex and multi-disciplinary. Consequently, acquiring an insight in the dynamics of these care processes can be an arduous task. A novel event log based approach for extracting valuable medical and organizational information on past executions of the care processes is presented in this study. Care processes are analyzed with the help of a preferential set of process mining techniques in order to discover recurring patterns, analyze and characterize process variants and identify adverse medical events.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Conceptualising recognition of prior learning processes in the age of open learning

This chapter interrogates what recognition of prior learning (RPL) can and does mean in the higher education sector—a sector in the grip of the widening participation agenda and an open access age. The chapter discusses how open learning is making inroads into recognition processes and examines two studies in open learning recognition. A case study relating to e-portfolio-style RPL for entry into a Graduate Certificate in Policy and Governance at a metropolitan university in Queensland is described. In the first instance, candidates who do not possess a relevant Bachelor degree need to demonstrate skills in governmental policy work in order to be eligible to gain entry to a Graduate Certificate (at Australian Qualifications Framework Level 8) (Australian Qualifications Framework Council, 2013, p. 53). The chapter acknowledges the benefits and limitations of recognition in open learning and those of more traditional RPL, anticipating future developments in both (or their convergence).

Doing Digital Composition on the Social Web: Knowledge Processes in Literacy Learning

The power to influence others in ever-expanding social networks in the new knowledge economy is tied to capabilities with digital media production. This chapter draws on research in elementary classrooms to examine the repertoires of cross-disciplinary knowledge that literacy learners need to produce innovative digital media via the “social web”. It focuses on the knowledge processes that occurred when elementary students engaged in multimodal text production with new digital media. It draws on Kalantzis and Cope’s (2008) heuristic for theorizing “Knowledge Processes” in the Learning by Design approach to pedagogy. Learners demonstrate eight “Knowledge Processes” across different subject domains, skills areas, and sensibilities. Drawing data from media-based lessons across several classroom and schools, this chapter examines what kinds of knowledge students utilize when they produce digital, multimodal texts in the classroom. The Learning by Design framework is used as an analytic tool to theorize how students learn when they engaged in a specific domain of learning – digital media production.

Study of the processes occurring when sputtering YBa2Cu3O7-x in pure oxygen

The sputter deposition of YBa2Cu3O7-x in a de-diode was performed in pure oxygen medium and an optical spectroscopic study of the resultant discharge revealed strong emissions from both metal atoms and oxygen ions. Emission intensities were studied in pressure range from 0.5 to 3 mbar, with substrate temperatures from 150 to 850 degrees C. Raising the substrate temperature to 850 degrees C increased the number of positive ions and excited neutral atoms. Raising the pressure decreased the emission intensities of excited neutral and ionic species. The results have been compared with those obtained from Langmuir probe measurements. The rise in emission intensities of excited neutrals and ions with temperature suggested the possibility of chemically enhanced physical sputtering of YBa2Cu3O7-x. The effect of process conditions on film composition and quality is also discussed.

Influence of friction during forming processes-a study using a numerical simulation technique

Friction has an important influence in metal forming operations, as it contributes to the success or otherwise of the process. In the present investigation, the effect of friction on metal forming was studied by simulating compression tests on cylindrical Al-Mg alloy using the finite element method (FEM) technique. Three kinds of compression tests were considered wherein a constant coefficient of friction was employed at the upper die-work-piece interface. However, the coefficient of friction between the lower die-work-piece interfaces was varied in the tests. The simulation results showed that a difference in metal flow occurs near the interfaces owing to the differences in the coefficient of friction. It was concluded that the variations in the coefficient of friction between the dies and the work-piece directly affect the stress distribution and shape of the work-piece, having implications on the microstructure of the material being processed.

Exploring collaborative modeling of business processes on large interactive touch display walls - video

Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on collaborative modeling workshops where process stakeholders verbally contribute their perspective on a process while modeling experts translate their contributions and integrate them into a model using traditional input devices. Limiting participants to verbal contributions not only affects the outcome of collaboration but also collaboration itself. We created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. We are currently in the process of conducting a study that aims at assessing the impact of CubeBPM on collaboration and modeling performance. Initial results presented in this paper indicate that the setting helped participants to become more active in collaboration.

Exploring collaborative modeling of business processes on large interactive touch display walls

Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on collaborative modeling workshops where process stakeholders verbally contribute their perspective on a process while modeling experts translate their contributions and integrate them into a model using traditional input devices. Limiting participants to verbal contributions not only affects the outcome of collaboration but also collaboration itself. We created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. We are currently in the process of conducting a study that aims at assessing the impact of CubeBPM on collaboration and modeling performance. Initial results presented in this paper indicate that the setting helped participants to become more active in collaboration.