Power relations and small and medium-sized enterprise strategies for capturing value in global production networks: visual effects (VFX) service firm in the Hollywood film industry

Power relations and small and medium-sized enterprise strategies for capturing value in global production networks: visual effects (VFX) service firms in the Hollywood film industry, Regional Studies. This paper provides insights into the way in which non-lead firms manoeuvre in global value chains in the pursuit of a larger share of revenue and how power relations affect these manoeuvres. It examines the nature of value capture and power relations in the global supply of visual effects (VFX) services and the range of strategies VFX firms adopt to capture higher value in the global value chain. The analysis is based on a total of thirty-six interviews with informants in the industry in Australia, the United Kingdom and Canada, and a database of VFX credits for 3323 visual products for 640 VFX firms.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

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.

The relationship between academic library usage and educational performance in Kuwait

University libraries play an important role in contributing to student and faculty members��� academic achievement. This study examines perceptions of university library usage to consider factors that influence achievement of students, academics and administrators. A thorough review of relevant literature examined approaches to determining user satisfaction of students and faculty, and factors that influence library usage. It highlighted the value of usage on educational performance. It enabled development of a theoretical framework leading to the Factors of Academic Library Usage (FALU) model, which was developed to investigate the effect of usage factors. FALU was tested in Kuwait university libraries. The study used validated questionnaires from 792 students, 143 academics and 121 administrators to measure five library factors. Interviews were conducted across the three University libraries. The findings are useful in measuring the correlation between the current academic library usage and educational performance.

Educational stress scale for adolescents : development, validity, and reliability with Chinese students

This article describes the development and initial validation of a new instrument to measure academic stress���the Educational Stress Scale for Adolescents (ESSA). A series of cross-sectional questionnaire surveys were conducted with more than 2,000 Chinese adolescents to examine the psychometric properties. The final 16-item ESSA contains five latent variables: Pressure from study, Workload, Worry about grades, Self-expectation, and Despondency, which together explain 64% of the total item variance. Scale scores showed adequate internal consistency, 2-week test���retest reliability, and satisfactory concurrent validity. A confirmatory factor analysis suggested the proposed factor model fits well in a different sample. For researchers who have a particular interest in academic stress among adolescents, the ESSA promises to be a useful tool.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Understanding learning and teaching : elementary teacher trainers in Papua New Guinea engaged in cultural authorship in the context of national educational reform

Over the last decade, Papua New Guinea (PNG) has pursued educational reform in elementary teacher education. Because elementary teachers and teacher education are central to the reform agenda, there is a need to gain empirical evidence about how PNG teacher trainers��� understandings about learning and teaching impact on their practice. The study uses cultural-authorship as a theoretical framework to investigate the nature of changes in understanding about learning and teaching for 18 teacher trainers as they progressed through a two-year Bachelor of Early Childhood upgrade course. It addresses the research question: What do elementary teacher trainers in PNG understanding about learning and teaching and how has this changed during their course? The focus on such understandings provides valuable insights into their professional identities at a critical time in PNG���s education reform agenda. Analysis of journal entries at the beginning and end of the course showed that, over time, teacher trainers described increasingly more complex ways of understanding learning and teaching. These views shifted from a focus on learning and teaching as transmission of ideas to one in which the critical role played by communities and families in educational processes and the teacher as a change agent became focal. This watershed finding demonstrates notable shifts in teacher trainers��� professional identities from trainers to community leaders in elementary education.

Microstrip decoupling networks for low-order multi-port arrays with reduced element spacing

An array of monopole elements with reduced element spacing of ��/6 to ��/20 is considered for application in digital beam-forming and direction-finding. The small element spacing introduces strong mutual coupling between the array elements. This paper discusses that decoupling can be achieved analytically for arrays with three elements and describes Kuroda���s identities to realize the lumped elements of the derived decoupling network. Design procedures and equations are proposed. Experimental results are presented. The decoupled array has a bandwidth of 1% and a superdirective radiation pattern.

Diversified service provisioning in global business networks

Companies and their services are being increasingly exposed to global business networks and Internet-based ondemand services. Much of the focus is on flexible orchestration and consumption of services, beyond ownership and operational boundaries of services. However, ways in which third-parties in the ���global village��� can seamlessly self-create new offers out of existing services remains open. This paper proposes a framework for service provisioning in global business networks that allows an open-ended set of techniques for extending services through a rich, multi-tooling environment. The Service Provisioning Management Framework, as such, supports different modeling techniques, through supportive tools, allowing different parts of services to be integrated into new contexts. Integration of service user interfaces, business processes, operational interfaces and business object are supported. The integration specifications that arise from service extensions are uniformly reflected through a kernel technique, the Service Integration Technique. Thus, the framework preserves coherence of service provisioning tasks without constraining the modeling techniques needed for extending different aspects of services.

Impact of embeddedness in ethnic networks on business growth : evidence from Chinese immigrant entrepreneurs in Australia

Immigrant entrepreneurship, or, self-employment by immigrants (Light & Bonacich, 1988), has been of growing interest to researchers (Hosler, 1996). This is due in part to major immigrant receiving countries, such as Australia, the United States, Canada, the United Kingdom and Western Europe, experiencing a high growth rate in their immigrant populations, leading to a more visible presence of immigrant business in major cities (Woon, 2008). By starting their own businesses, immigrant entrepreneurs may circumvent some of the barriers and disadvantages encountered in looking for a job (Sequeira & Rasheed, 2006). Successful immigrant entrepreneurs will integrate into the economy by creating jobs, providing products and services for members of their own ethnic community and society, as well as introducing new products and services that expand consumers��� choices (Rath & Kloosterman, 2000). Immigrant entrepreneurs tend to start business within their ethnic enclave, as it is an integral part of their social and cultural context and the location where ethnic resources reside (Logan et al., 2002). An ethnic enclave is an interdependent network of social and business relationships that are geographically concentrated with its co-ethnic people (Portes & Bach, 1985).

Book Review: "Mark Considine, Jenny Lewis and Damon Alexander Networks, Innovation and Public Policy : Politicians, Bureaucrats and the Pathways to Change inside Government Houndsmills, UK: Palgrave Macmillan, 2009"

Having wrung the most from workforce and workplace productivity initiaitves, innovation has come to the fore as a key goal and directive for public sector organisations to become more efficient. This clarion call for innovation can be heard all around the world, with public services everywhere taking up the message to develop better, smarter, novel, more innovative processes, programs and policies. In the current push for innovation, networks are considered to be a superior vehicle through which collective knowledge can be shared and leveraged; replacing or at least supplementing the role function previously provided by inventive leaders...

VET and VET educators : understanding teacher dilemmas in providing quality educational experience to international students in Brisbane

In the past fifteen years, increasing attention has been given to the role of Vocational Education and Training (VET) in attracting large numbers of international students and its contribution to the economic development of Australia. This trend has given rise to many challenges in vocational education, especially with regard to providing quality education that ensures international students��� stay in Australia is a satisfactory experience. Teachers are key stakeholders in international education and share responsibility for ensuring international students gain quality learning experiences and positive outcomes. However, the challenges and needs of these teachers are generally not well understood. Therefore, this paper draws on the dilemmas faced by teachers of international students associated with professional, personal, ethical and educational aspects. This paper reports on a Masters Research project that is designed to investigate the dilemmas that teachers of international students face in VET in Australia, particularly in Brisbane. This study uses a qualitative approach within the interpretive constructivist paradigm to gain real-life insights through responsive interviewing and inductive data analysis. While the data collection has been done, the analysis of data is in progress. Responsive interviews with teachers of VET with different academic and national backgrounds, ages, industry experience have identified particular understandings, ideologies and representations of what it means to be a teacher in today's multicultural VET environment; provoking both resistances and new pedagogical understanding of teacher dilemmas and their work environment through the eyes of teachers of international students. The paper considers the challenges for the VET practitioners within the VET system while reflecting on the theme for the 2011 AVETRA conference, ���Research in VET: Janus- Reflecting Back, Projecting Forward��� by focusing particularly on ���Rethinking pedagogies and pathways in VET work through the voice of VET workers���.

Learning Landscapes 2.0: Adaptable educational environments

This project has blended two streams of enquiry: temporary and transportable construction technology, and flexible blended-learning environments. It seeks to develop prototypes for a series of environments suited for the activities of learning (future-proofed schools), as practiced in the twenty first century. The research utilises techniques of: historic survey, case study, first-hand observation, and architectural design (as research). The design comprises three major components: The determinate landscape: in-situ concrete ���plate��� that is permanent. The indeterminate landscape: a kit of pre-fabricated 2-D panels assembled in a unique manner at each site to suit the client and context; manufactured to the principles of design-for-disassembly. The stations: pre-fabricated packages of highly-serviced space connected through the determinate landscape. This project was submitted to the ���Future Proofing Schools��� competition (professional category) in October 2011. The competition was part of a research project supported under the Australian Research Council���s Linkage Grant funding scheme (project LP0991146).

Finding and matching communities in social networks using data mining

The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.

Ad hoc innovation by users of social networks : the case of Twitter

Generic, flexible social media spaces such as Facebook and Twitter constitute an increasingly important element in our overall media repertoires. They provide a technological basis for instant and world-wide, ad hoc, many-to-many communication, and their effect on global communication patterns has already been highlighted. The short-messaging platform Twitter, for example, caters for uses ranging from interpersonal and quasi-private phatic exchanges to ���ambient journalism���: ad hoc new reporting and dissemination as major events break. Many such uses have themselves emerged through user-driven processes: even standard Twitter conventions such as the @reply (to publicly address a fellow user) or the #hashtag(to collect related messages in an easily accessible space) are user inventions, in fact, and were incorporated into Twitter���s own infrastructure only subsequently. This demonstrates the substantial potential of social, user-led innovation in social media spaces.