Increasing stochastic perturbations enhances acquisition and learning of complex sport movements

Traditionally, the aquisition of skills and sport movement has been characterised by numerous repetitions of presumed model movement pattern to be acquired by learners. This approach has been questioned by research identifying the presence of individualised movement patterns and the low probability of occurrence of two identical movements within and between individuals. In contrast, the differential learning approach claims advantage for incurring variability in the learning process by adding stochastic perturbations during practice. These ideas are exemplified by data from a high jump experiment which compared the effectiveness of classical and a differential training approach with pre-post test design. Results showed clear advantages for the group with additional stochastic perturbation during the aquisition phase in comparison to classically trained athletes. Analogies to similar phenomenological effects in the neurobiological literature are discussed.

Remediating vernacular creativity : photography and cultural citizenship in the Flickr photosharing network

Read through a focus on the remediation of personal photography in the Flickr photosharing website, in this essay I treat vernacular creativity as a field of cultural practice; one that that does not operate inside the institutions or cultural value systems of high culture or the commercial popular media, and yet draws on and is periodically appropriated by these other systems in dynamic and productive ways. Because of its porosity to commercial culture and art practice, this conceptual model of ‘vernacular creativity’ implies a historicised account of ‘ordinary’ or everyday creative practice that accounts for both continuity and change and avoids creating a nostalgic desire for the recuperation of an authentic folk culture. Moving beyond individual creative practice, the essay concludes by considering the unintended consequences of vernacular creativity practiced in online social networks: in particular, the idea of cultural citizenship.

White possession : the legacy of Cook's choice

Book Synopsis: From Terra Nullius to Land of Opportunities and Last Frontier, the European dream has constructed and deconstructed Australia to feed its imagination of new societies. At the same time Australia has over the last two centuries forged and re-invented its own liaisons with Europe arguably to carve out its identity. From the arts to social sciences, to society itself, a complex dynamic has grown between the two continents in ways that invite study and discussion. A transnational research group has begun its collective investigation project of which this first volume is the outcome. The book is a substantial multidisciplinary collection of current research and offers critical perspectives on culture, literature and history around themes at the heart of the Imagined Australia project. The essays instigate reflection, discovery and discussion of how reciprocal imagining between Australia and Europe has articulated itself and ways and dimensions in which a relationship between communities, imagined and not, has unfolded.

The problem of measurement indeterminacy in complex neurobiological movement systems

In the study of complex neurobiological movement systems, measurement indeterminacy has typically been overcome by imposing artificial modelling constraints to reduce the number of unknowns (e.g., reducing all muscle, bone and ligament forces crossing a joint to a single vector). However, this approach prevents human movement scientists from investigating more fully the role, functionality and ubiquity of coordinative structures or functional motor synergies. Advancements in measurement methods and analysis techniques are required if the contribution of individual component parts or degrees of freedom of these task-specific structural units is to be established, thereby effectively solving the indeterminacy problem by reducing the number of unknowns. A further benefit of establishing more of the unknowns is that human movement scientists will be able to gain greater insight into ubiquitous processes of physical self-organising that underpin the formation of coordinative structures and the confluence of organismic, environmental and task constraints that determine the exact morphology of these special-purpose devices.

External pressure in the hardening of phosphate in tribofilm on iron surfaces

Purpose: In the present work we consider our (in progress) spectroscopy study of zinc and iron phosphates under the influence external high pressure to determine zinc ion change coordination from tetrahedral to octahedral (or hexahedral) structure.----- Design/methodology/approach: The standard equipment is the optical high pressure cell with diamond (DAC). The DAC is assembled and then vibrational or electronic spectra are collected by mounting the cell in an infrared, Raman, EXAFS or UV-visible spectrometer.----- Findings: Mechanism by which zinc and iron methaphosphate material is transformed to glassy meta-phosphate is enhancing mechanical properties of tribofilm. The two decades of intensive study demonstrates that Zn (II) and Fe (III) ions participate to cross-link network under friction, hardening the phosphate.----- Research limitations/implications: Transition metal atoms with d orbital have flexible coordination numbers, for example zinc acts as a cross-linking agent increasing hardness, by changing coordination from tetrahedral to octahedral. Perhaps the external pressure effect on the [Zn–(O-P-)4 ] complex causes a transformation to an [Zn –(O-P-)6] grouping.----- Originality/value: This paper analyses high-pressure spectroscopy which has been applied for the investigation of 3D transition metal ions in solids. When studying pressure effects on coordination compounds structure, we can expect changes in ground electronic state (spin-crossovers), electronic spectra due to structural distortions (piezochromism), and changes in the ligand field causing shifts in the electronic transitions.

Trends in online journalism : a case study approach based on euaustralia online

This paper takes stock of current changes affecting journalism, and as a case study brings up to date the record of progress made with an online publishing enterprise, EUAustralia Online, first reported on in 2007. It perceives the development of news publishing on line as being in two sectors: media corporations moving to occupy the online publishing field, through complex business stratagems and product-making, and small publications enjoying low production costs and the ability to strike up relationships with numerous users, even on a mass scale. Recent developments in both major publishing and niche publishing are appraised in a literature review, considering both broad-scale industry trends; and pressure from fresh advances in information and communication technology to produce ever-more sophisticated media artefacts, like multi-platform news coverage. The paper also recounts the pattern of work on EUAustralia Online, showing how such publications, ubiquitous ‘blogs’ or newsletters, may be placed in a prospective online order, where large and small operations might co-exist.

A model of project complexity : distinguishing dimensions of complexity from severity

There is increasing agreement that understanding complexity is important for project management because of difficulties associated with decision-making and goal attainment which appear to stem from complexity. However the current operational definitions of complex projects, based upon size and budget, have been challenged and questions have been raised about how complexity can be measured in a robust manner that takes account of structural, dynamic and interaction elements. Thematic analysis of data from 25 in-depth interviews of project managers involved with complex projects, together with an exploration of the literature reveals a wide range of factors that may contribute to project complexity. We argue that these factors contributing to project complexity may define in terms of dimensions, or source characteristics, which are in turn subject to a range of severity factors. In addition to investigating definitions and models of complexity from the literature and in the field, this study also explores the problematic issues of ‘measuring’ or assessing complexity. A research agenda is proposed to further the investigation of phenomena reported in this initial study.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

Decision support system for contractor pre-qualification : artificial neural network model

The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

Reflective learning through social network sites in design education

Reflective learning is vital for successful practice-led education such as animation, multimedia design and graphic design, and social network sites can accommodate various learning styles for effective reflective learning. In this paper, the researcher studies reflective learning through social network sites with two animation units. These units aim to provide students with an understanding of the tasks and workflows involved in the production of style sheets, character sheets and motion graphics for use in 3D productions for film and television and game design. In particular, an assessment in these units requires students to complete their online reflective journals throughout the semester. The reflective learning has been integrated within the unit design and students are encouraged to reflect weekly learning processes and outcomes. A survey evaluating for students’ learning experience was conducted, and its outcomes indicate that social network site based reflective learning will not be effective without considering students’ learning circumstances and designing peer-to-peer interactions.

The Evolution of the creative industries : creative clusters, creative citizens and social network markets 創意產業的演化 : 創意集群 ,創意公民, 社會網絡市場 [published in Chinese]

The creative industries are important because they are clustered at the point of attraction for a billion or more young people around the world. They're the drivers of demographic, economic and political change. They start from the individual talent of the creative artist and the individual desire and aspiration of the audience. These are the raw materials for innovation, change and emergent culture, scaled up to form new industries and coordinated into global markets based on social networks.

The impact of institutional, instrumental and interpersonal underpinnings on network dynamics and outcomes

Networks form a key part of the infrastructure of contemporary governance arrangements and, as such, are likely to continue for some time. Networks can take many forms and be formed for many reasons. Some networks have been explicitly designed to generate a collective response to an issue; some arise from a top down perspective through mandate or coercion; while others rely more heavily on interpersonal relations and doing the right thing. In this paper, these three different perspectives are referred to as the “3I”s: Instrumental, Institutional or Interpersonal. It is proposed that these underlying motivations will affect the process dynamics within the different types of networks in different ways and therefore influence the type of outcomes achieved. This proposition is tested through a number of case studies. An understanding of these differences will lead to more effective design, management and clearer expectations of what can be achieved through networks.

The importance of a new kind of learning in collaborative networks

There is wide agreement that in order to manage the increasingly complex and uncertain tasks of business, government and community, organizations can no longer operate in supreme isolation, but must develop a more networked approach. Networks are not ‘business as usual’. Of particular note is what has been referred to as collaborative networks. Collaborative networks now constitute a significant part of our institutional infrastructure. A key driver for the proliferation of these multiorganizational arrangements is their ability to facilitate the learning and knowledge necessary to survive or to respond to increasingly complex social issues In this regard the emphasis is on the importance of learning in networks. Learning applies to networks in two different ways. These refer to the kinds of learning that occur as part of the interactive processes of networks. This paper looks at the importance of these two kinds of learning in collaborative networks. The first kind of learning relates to networks as learning networks or communities of practice. In learning networks people exchange ideas with each other and bring back this new knowledge for use in their own organizations. The second type of learning is referred to as network learning. Network learning refers to how people in collaborative networks learn new ways of communicating and behaving with each other. Network learning has been described as transformational in terms of leading to major systems changes and innovation. In order to be effective, all networks need to be involved as learning networks; however, collaborative networks must also be involved in network learning to be effective. In addition to these two kinds of learning in collaborative networks this paper also focuses on the importance of how we learn about collaborative networks. Maximizing the benefits of working through collaborative networks is dependent on understanding their unique characteristics and how this impacts on their operation. This requires a new look at how we specifically teach about collaborative networks and how this is similar to and/or different from how we currently teach about interorgnizational relations.