Charting the system : the integrated master schedule as a multi-level and poly-temporal boundary object in complex projects

This paper investigates the use of visual artifacts to represent a complex adaptive system (CAS). The integrated master schedule (IMS) is one of those visuals widely used in complex projects for scheduling, budgeting, and project management. In this paper, we discuss how the IMS outperforms the traditional timelines and acts as a ‘multi-level and poly-temporal boundary object’ that visually represents the CAS. We report the findings of a case study project on the way the IMS mapped interactions, interdependencies, constraints and fractal patterns in a complex project. Finally, we discuss how the IMS was utilised as a complex boundary object by eliciting commitment and development of shared mental models, and facilitating negotiation through the layers of multiple interpretations from stakeholders.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Serious fears across cultures about the collapse of the world order

This chapter approaches resilience from an evolutionary psychology (socio-biological) perspective. It argues that the internal constitution and mental toughness of the individual will provide a core protection for life’s inevitable tests in the innumerable micro and macro environments humans find themselves. The many descriptors of the construct of resilience used in various studies are explored. Finally, the difference psychologists can make in the therapy of clients whose resilience is being tested, is examined by means of case examples.

Professional identity of management accountants : leadership in changing environments

The professional identity of management accountants (MAs) is evolving. According to 8,727 descriptors expressed by 1,158 participants, a range of characteristics of MAs are competing in shaping the identity of future MAs. Respondents strongly valued qualities such as professional principles, hard work, intelligence, analytical and forward thinking in MAs. Further, more innovative, dynamic and people-oriented qualities were strongly suggested for future MAs, with roles relating to multi-skilled business integrator, business partner/advisor, leader, change agent, and decision enabler/maker. Cultivating leadership qualities in the management accounting profession is critical according to participants. Projecting a positive image of the profession and CIMA, and innovative training in management and leadership skills can further support MAs to meet future challenges. Most of all, understanding business and continued personal development by individual MAs is highly valued in shaping the future leadership identity of MAs. Our quantitative data show positive relationships between the professional identification, image and reputation, and leadership qualities of MAs. This suggests that the more one identifies with the profession, the more one is likely to report higher levels of leadership qualities that support members to internalise the desired meaning of their profession and to create a positive image and reputation. After the financial crisis of 2008–2009, the image of financial professions has been tarnished and unpredictable markets and unstable employment opportunities have challenged the profession across all sectors. Many respondents, especially CIMA members, suggested that the turmoil of the financial crisis did not impact negatively but rather elevated the pivotal role of MAs in contributing to cost efficiency and value creation.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.

A survey to evaluate the implementation of a national clinical assessment form

Purpose: The Australian Universities Radiation Therapy Student Clinical Assessment Form (AURTSCAF) was designed to assess the clinical skills of radiation therapy (RT) students from the six universities that offer entry level RT programs. Given the AURTSCAF has now been in use for over two years, the Radiation Therapy Program Coordinators (RTPC) group initiated a post implementation evaluation survey. This formed the final phase of the AURTSCAF project and was funded by the Radiation Oncology Division of the Department of Health and Ageing. Methods: A cross-sectional designed survey using purposive sampling was distributed via email to all RT clinical sites. The survey asked questions about the requirements of a pass grade for students at different stages of their program, and the addition of a new category of assessment related to fitness to practise. Response types included both forced choice closed ended responses and open ended responses. There was also a section for open comments about the AURTSCAF. Results: There were 100 responses (55%) from clinicians who had utilised the assessment form over the previous 12 month period. Responses highlighted several positives with regard to the utility and implementation of the form. Comments regarding areas for improvement with the standardisation of the grading of students and consensus for the addition of a new domain in fitness for practise have informed the recommended changes proposed for 2012. Conclusion: This evaluation has provided a representative sample of the views of clinicians involved in assessing students on clinical placement. Recommendations include the addition of the sixth domain of assessment: Fitness for practise, the addition of descriptors and prompts for this domain in the user guide, the addition of a consensus statement about the use of the rating scale and dissemination of the proposed changes nationally.

Can you describe him for me? A technique for semantic person search in video

From a law enforcement standpoint, the ability to search for a person matching a semantic description (i.e. 1.8m tall, red shirt, jeans) is highly desirable. While a significant research effort has focused on person re-detection (the task of identifying a previously observed individual in surveillance video), these techniques require descriptors to be built from existing image or video observations. As such, person re-detection techniques are not suited to situations where footage of the person of interest is not readily available, such as a witness reporting a recent crime. In this paper, we present a novel framework that is able to search for a person based on a semantic description. The proposed approach uses size and colour cues, and does not require a person detection routine to locate people in the scene, improving utility in crowded conditions. The proposed approach is demonstrated with a new database that will be made available to the research community, and we show that the proposed technique is able to correctly localise a person in a video based on a simple semantic description.

Restructuring of carbonaceous particles upon exposure to organic vapours

Recent research has described the restructuring of particles upon exposure to organic vapours; however, as yet hypotheses able to explain this phenomenon are limited. In this study, a range of experiments were performed to explore different hypotheses related to carbonaceous particle restructuring upon exposure to organic and water vapours, such as: the effect of surface tension, the role of organics in flocculating primary particles, as well as the ability of vapours to “wet” the particle surface. The change in mobility diameter (dm) was investigated for a range carbonaceous particle types (diesel exhaust, petrol exhaust, cigarette smoke, candle smoke, particles generated in a heptane/toluene flame, and wood smoke particles) exposed to different organic (heptane, ethanol, and dimethyl sulfoxide/water (1:1 vol%) mixture) and water vapours. Particles were first size-selected and then bubbled through an impinger (bubbler) containing either an organic solvent or water, where particles trapped inside rising bubbles were exposed to saturated vapours of the solvent in the impinger. The size distribution of particles was simultaneously measured upstream and downstream from the impinger. A size-dependent reduction in dm was observed when bubbling diesel exhaust, particles generated in a heptane/toluene flame, and candle smoke particles through heptane, ethanol and a dimethyl sulfoxide/water (1:1 vol %) mixture. In addition, the size distributions of particles bubbled through an impinger were broader. Moreover, an increase of the geometric standard deviation (σ) of the size distributions of particles bubbled through an impinger was also found to be size-dependent. Size-dependent reduction in dm and an increase of σ indicate that particles undergo restructuring to a more compact form, which was confirmed by TEM analysis. However, bubbling of these particles through water did not result in a size-dependent reduction in dm, nor in an increase of σ. Cigarette smoke, petrol exhaust, and wood smoke particles did not result in any substantial change in dm, or σ, when bubbled through organic solvents or water. Therefore, size-dependent reduction in the dm upon bubbling through organic solvents was observed only for particles that had a fractal-like structure, whilst particles that were liquid or were assumed to be spherical did not exhibit any reduction in dm. Compaction of fractal-like particles was attributed to the ability of condensing vapours to efficiently wet the particles. Our results also show that the presence of an organic layer on the surface of fractal-like particles, or the surface tension of the condensed liquid do not influence the extent of compaction.

Temporal boundary objects in megaprojects : mapping the system with the integrated master schedule

Recently, a stream of project management research has recognized the critical role of boundary objects in the organization of projects. In this paper, we investigate how one advanced scheduling tool, the Integrated Master Schedule (IMS), is used as a temporal boundary object at various stages of complex projects. The IMS is critical to megaprojects which typically span long periods of time and face a high degree of complexity and uncertainty. In this paper, we conceptualize projects of this type as complex adaptive systems (CAS). We report the findings of four case projects on how the IMS mapped interactions, interdependencies, constraints, and fractal patterns of these emerging projects, and how the process of IMS visualization enabled communication and negotiation of project realities. This paper highlights that this advanced timeline tool acts as a boundary object and elicits shared understanding of complex projects from their stakeholders.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

An integrated educational model for continuing nurse education

Aim This paper reports on the development and evaluation of an integrated clinical learning model to inform ongoing education for surgical nurses. The research aim was to evaluate the effectiveness of implementing a Respiratory Skills Update (ReSKU) education program, in the context of organisational utility, on improving surgical nurses' practice in the area of respiratory assessment. Background Continuous development and integration of technological innovations and research in the healthcare environment mandate the need for continuing education for nurses. Despite an increased worldwide emphasis on this, there is scant empirical evidence of program effectiveness. Methods A quasi experimental pre test, post test non–equivalent control group design evaluated the impact of the ReSKU program on surgical nurses' clinical practice. The 2008 study was conducted in a 400 bed regional referral public hospital and was consistent with contemporary educational approaches using multi-modal, interactive teaching strategies. Findings The study demonstrated statistically significant differences between groups regarding reported use of respiratory skills, three months after ReSKU program attendance. Between group data analysis indicated that the intervention group's reported beliefs and attitudes pertaining to subscale descriptors showed statistically significant differences in three of the six subscales. Conclusion The construct of critical thinking in the clinical context, combined with clinical reasoning and purposeful reflection, was a powerful educational strategy to enhance competency and capability in clinicians.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Pore structure characterization of North American shale gas reservoirs using USANS/SANS, gas adsorption, and mercury intrusion

Small-angle and ultra-small-angle neutron scattering (SANS and USANS), low-pressure adsorption (N2 and CO2), and high-pressure mercury intrusion measurements were performed on a suite of North American shale reservoir samples providing the first ever comparison of all these techniques for characterizing the complex pore structure of shales. The techniques were used to gain insight into the nature of the pore structure including pore geometry, pore size distribution and accessible versus inaccessible porosity. Reservoir samples for analysis were taken from currently-active shale gas plays including the Barnett, Marcellus, Haynesville, Eagle Ford, Woodford, Muskwa, and Duvernay shales. Low-pressure adsorption revealed strong differences in BET surface area and pore volumes for the sample suite, consistent with variability in composition of the samples. The combination of CO2 and N2 adsorption data allowed pore size distributions to be created for micro–meso–macroporosity up to a limit of �1000 Å. Pore size distributions are either uni- or multi-modal. The adsorption-derived pore size distributions for some samples are inconsistent with mercury intrusion data, likely owing to a combination of grain compression during high-pressure intrusion, and the fact that mercury intrusion yields information about pore throat rather than pore body distributions. SANS/USANS scattering data indicate a fractal geometry (power-law scattering) for a wide range of pore sizes and provide evidence that nanometer-scale spatial ordering occurs in lower mesopore–micropore range for some samples, which may be associated with inter-layer spacing in clay minerals. SANS/USANS pore radius distributions were converted to pore volume distributions for direct comparison with adsorption data. For the overlap region between the two methods, the agreement is quite good. Accessible porosity in the pore size (radius) range 5 nm–10 lm was determined for a Barnett shale sample using the contrast matching method with pressurized deuterated methane fluid. The results demonstrate that accessible porosity is pore-size dependent.

Scaffold percolative efficiency : in vitro evaluation of the structural criterion for electrospun mats

Fibrous scaffolds of engineered structures can be chosen as promising porous environments when an approved criterion validates their applicability for a specific medical purpose. For such biomaterials, this paper sought to investigate various structural characteristics in order to determine whether they are appropriate descriptors. A number of poly(3-hydroxybutyrate) scaffolds were electrospun; each of which possessed a distinguished architecture when their material and processing conditions were altered. Subsequent culture of mouse fibroblast cells (L929) was carried out to evaluate the cells viability on each scaffold after their attachment for 24 h and proliferation for 48 and 72 h. The scaffolds’ porosity, pores number, pores size and distribution were quantified and none could establish a relationship with the viability results. Virtual reconstruction of the mats introduced an authentic criterion, “Scaffold Percolative Efficiency” (SPE), with which the above descriptors were addressed collectively. It was hypothesized to be able to quantify the efficacy of fibrous scaffolds by considering the integration of porosity and interconnectivity of the pores. There was a correlation of 80% as a good agreement between the SPE values and the spectrophotometer absorbance of viable cells; a viability of more than 350% in comparison to that of the controls.