Simplified method for including spatial correlations in mean-field approximations

Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.

Development of a simplified design method to predict the fire rating of LSF walls

Recent fire research into the behaviour of light gauge steel frame (LSF) wall systems has devel-oped fire design rules based on Australian and European cold-formed steel design standards, AS/NZS 4600 and Eurocode 3 Part 1.3. However, these design rules are complex since the LSF wall studs are subjected to non-uniform elevated temperature distributions when the walls are exposed to fire from one side. Therefore this paper proposes an alternative design method for routine predictions of fire resistance rating of LSF walls. In this method, suitable equations are recommended first to predict the idealised stud time-temperature pro-files of eight different LSF wall configurations subject to standard fire conditions based on full scale fire test results. A new set of equations was then proposed to find the critical hot flange (failure) temperature for a giv-en load ratio for the same LSF wall configurations with varying steel grades and thickness. These equations were developed based on detailed finite element analyses that predicted the axial compression capacities and failure times of LSF wall studs subject to non-uniform temperature distributions with varying steel grades and thicknesses. This paper proposes a simple design method in which the two sets of equations developed for time-temperature profiles and critical hot flange temperatures are used to find the failure times of LSF walls. The proposed method was verified by comparing its predictions with the results from full scale fire tests and finite element analyses. This paper presents the details of this study including the finite element models of LSF wall studs, the results from relevant fire tests and finite element analyses, and the proposed equations.

Reconstructing 3D x-ray CT images of polymer gel dosimeters using the zero-scan method

In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels.

A discourse on the non-method

In spite of the activism of professional bodies and researchers, empirical evidence shows that project management still does not deliver the expected benefits and promises. Hence, many have questioned the validity of the hegemonic rationalist paradigm anchored in the Enlightenment and Natural Sciences tradition supporting project management research and practice for the last 60 years and the lack of relevance to practice of the current conceptual base of project management. In order to address these limitations many authors, taking a post-modernist stance in social sciences, build on ‘pre-modern’ philosophies such as the Aristotelian one, specially emphasizing the role of praxis (activity), and phronesis (practical wisdom, prudence). Indeed, ‘Praxis … is the central category of the philosophy which is not merely an interpretation of the world, but is also a guide to its transformation …’ (Vazquez, 1977:. 149). Therefore, praxis offers an important focus for practitioners and researchers in social sciences, one in which theory is integrated with practice at the point of intervention. Simply stated, praxis can serve as a common ground for those interested in basic and applied research by providing knowledge of the reality in which action, informed by theory, takes place. Consequently, I suggest a ‘praxeological’ style of reasoning (praxeology being defined as study or science of human actions and conduct, including praxis, practices and phronesis) and to go beyond the ‘Theory-Practice’ divide. Moreover, I argue that we need to move away from the current dichotomy between the two classes ‘scholars experts-researchers’ and ‘managers/workers-practitioners-participants’. Considering one single class of ‘PraXitioner’, becoming a phronimos, may contribute to create new perspectives and open up new ways of thinking and acting in project situations. Thus, I call for a Perestroika in researching and acting in project management situations. My intent is to suggest a balanced praxeological view of the apparent opposition between social and natural science approaches. I explore, in this chapter, three key questions, covering the ontological, epistemological and praxeological dimensions of project management in action. 1. Are the research approaches being currently used appropriate for generating contributions that matter to both theory and practice with regards to what a ‘project’ is or to what we do when we call a specific situation ‘a project’? 2. On the basis of which intellectual virtues is the knowledge generated and what is the impact for theory and practice? 3. Are the modes of action of the practitioners ‘prudent’ and are they differentiating or reconciling formal and abstract rationality from substantive rationality and situated reasoning with regards to the mode of action they adopt in particular project situations? The investigation of the above questions leads me to debate about ‘Project Management-as-Praxis’, and to suggest ‘A’ (not ‘THE’) ‘praxeological’ style of reasoning and mode of inquiry – acknowledging a non-paradigmatic, subjective and kaleidoscopic perspective – for ‘Knowing-as-Practicing’ in project management. In short, this is about making a ‘Projects Science’ that matters.

A method for predicting rain-induced instability of an individual slope

Awareness to avoid losses and casualties due to rain-induced landslide is increasing in regions that routinely experience heavy rainfall. Improvements in early warning systems against rain-induced landslide such as prediction modelling using rainfall records, is urgently needed in vulnerable regions. The existing warning systems have been applied using stability chart development and real-time displacement measurement on slope surfaces. However, there are still some drawbacks such as: ignorance of rain-induced instability mechanism, mislead prediction due to the probabilistic prediction and short time for evacuation. In this research, a real-time predictive method was proposed to alleviate the drawbacks mentioned above. A case-study soil slope in Indonesia that failed in 2010 during rainfall was used to verify the proposed predictive method. Using the results from the field and laboratory characterizations, numerical analyses can be applied to develop a model of unsaturated residual soils slope with deep cracks and subject to rainwater infiltration. Real-time rainfall measurement in the slope and the prediction of future rainfall are needed. By coupling transient seepage and stability analysis, the variation of safety factor of the slope with time were provided as a basis to develop method for the real-time prediction of the rain-induced instability of slopes. This study shows the proposed prediction method has the potential to be used in an early warning system against landslide hazard, since the FOS value and the timing of the end-result of the prediction can be provided before the actual failure of the case study slope.

A data mining driven crash risk profiling method for road asset management

This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.

Biomechanical aspects of seating comfort in vehicle seating package engineering

In this paper, problems are described which are related to the ergonomic assessment of vehicle package design in vehicle systems engineering. The traditional approach, using questionnaire techniques for a subjective assessment of comfort related to package design, is compared to a biomechanical approach. An example is given for ingress design. The biomechanical approach is based upon objective postural data. The experimental setup for the study is described and methods used for the biomechanical analysis are explained. Because the biomechanic assessment requires not only a complex experimental setup but also time consuming data processing, a systematic reduction and preparation of biomechanic data for classification with an Artificial Neural Network significantly improves the economy of the biomechanical method.

An ontology-based method for sparsity problem in tag recommendation

Tags or personal metadata for annotating web resources have been widely adopted in Web 2.0 sites. However, as tags are freely chosen by users, the vocabularies are diverse, ambiguous and sometimes only meaningful to individuals. Tag recommenders may assist users during tagging process. Its objective is to suggest relevant tags to use as well as to help consolidating vocabulary in the systems. In this paper we discuss our approach for providing personalized tag recommendation by making use of existing domain ontology generated from folksonomy. Specifically we evaluated the approach in sparse situation. The evaluation shows that the proposed ontology-based method has improved the accuracy of tag recommendation in this situation.

A combined method for mitigating sparsity problem in tag recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

Elastic buckling analysis of ideal thin-walled structures under combined loading using a finite strip method

The details of an application of the finite strip method to the elastic buckling analysis of thin-walled structures with various boundary conditions and subjected to single or combined loadings of longitudinal compression, transverse compression, bending and shear are presented. The presence of shear loading is accounted for by modifying the displacement functions which are commonly used in cases when shear is absent. A program based on the finite strip method was used to obtain the elastic buckling stress, buckling plot and buckling mode of thin-walled structures and some of these results are presented.

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.

The heterogeneous cluster ensemble method using hubness for clustering text documents

We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed meth-od outperforms state-of-the-art text clustering approaches.

A concept-based retrieval method for entity-oriented search

Entity-oriented retrieval aims to return a list of relevant entities rather than documents to provide exact answers for user queries. The nature of entity-oriented retrieval requires identifying the semantic intent of user queries, i.e., understanding the semantic role of query terms and determining the semantic categories which indicate the class of target entities. Existing methods are not able to exploit the semantic intent by capturing the semantic relationship between terms in a query and in a document that contains entity related information. To improve the understanding of the semantic intent of user queries, we propose concept-based retrieval method that not only automatically identifies the semantic intent of user queries, i.e., Intent Type and Intent Modifier but introduces concepts represented by Wikipedia articles to user queries. We evaluate our proposed method on entity profile documents annotated by concepts from Wikipedia category and list structure. Empirical analysis reveals that the proposed method outperforms several state-of-the-art approaches.

An innovative method to obtain porous PLLA scaffolds with highly spherical and interconnected pores

Scaffolding is an essential issue in tissue engineering and scaffolds should answer certain essential criteria: biocompatibility, high porosity, and important pore interconnectivity to facilitate cell migration and fluid diffusion. In this work, a modified solvent castingparticulate leaching out method is presented to produce scaffolds with spherical and interconnected pores. Sugar particles (200–300 lm and 300–500 lm) were poured through a horizontal Meker burner flame and collected below the flame. While crossing the high temperature zone, the particles melted and adopted a spherical shape. Spherical particles were compressed in plastic mold. Then, poly-L-lactic acid solution was cast in the sugar assembly. After solvent evaporation, the sugar was removed by immersing the structure into distilled water for 3 days. The obtained scaffolds presented highly spherical interconnected pores, with interconnection pathways from 10 to 100 lm. Pore interconnection was obtained without any additional step. Compression tests were carried out to evaluate the scaffold mechanical performances. Moreover, rabbit bone marrow mesenchymal stem cells were found to adhere and to proliferate in vitro in the scaffold over 21 days. This technique produced scaffold with highly spherical and interconnected pores without the use of additional organic solvents to leach out the porogen.