937 resultados para T-box


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Fibre composite structures have become the most attractive candidate for civil engineering applications. Fibre reinforced plastic polymer (FRP) composite materials have been used in the rehabilitation and replacement of the old degrading traditional structures or build new structures. However, the lack of design standards for civil infrastructure limits their structural applications. The majority of the existing applications have been designed based on the research and guidelines provided by the fibre composite manufacturers or based on the designer’s experience. It has been a tendency that the final structure is generally over-designed. This paper provides a review on the available studies related to the design optimization of fibre composite structures used in civil engineering such as; plate, beam, box beam, sandwich panel, bridge girder, and bridge deck. Various optimization methods are presented and compared. In addition, the importance of using the appropriate optimization technique is discussed. An improved methodology, which considering experimental testing, numerical modelling, and design constrains, is proposed in the paper for design optimization of composite structures.

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Collaboration has been enacted as a core strategy by both the government and nongovernment sectors to address many of the intractable issues confronting contemporary society. The cult of collaboration has become so pervasive that it is now an elastic term referring generally to any form of ‘working together’. The lack of specificity about collaboration and its practice means that it risks being reduced to mere rhetoric without sustained practice or action. Drawing on an extensive data set (qualitative, quantitative) of broadly collaborative endeavours gathered over ten years in Queensland, Australia, this paper aims to fill out the black box of collaboration. Specifically it examines the drivers for collaboration, dominant structures and mechanisms adopted, what has worked and unintended consequences. In particular it investigates the skills and competencies required in an embeded collaborative endeavour within and across organisations. Social network analysis is applied to isolate the structural properties of collaborations over other forms of integration as well as highlighting key roles and tasks. Collaboration is found to be a distinctive form of working together, characterised by intense and interdependent relationships and exchanges, higher levels of cohesion (density) and requiring new ways of behaving, working, managing and leading. These elements are configured into a practice framework. Developing an empirical evidence base for collaboration structure, practice and strategy provides a useful foundation for theory extension. The paper concludes that for collaboration, to be successfully employed as a management strategy it must move beyond rhetoric and develop a coherent model for action.

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The purpose of this paper is to advance our understanding of what contextual factors influence the service bundling process in an organizational setting. Although previous literature contains insights into the mechanisms underlying bundling and the artefacts for performing the bundling task itself, the body of knowledge seems to lack a comprehensive framework for analysing the actual scenario in which the bundling process is performed. This is required as the scenario will influence the bundling method and the IT support. We address this need by designing a morphological box for analysing bundling scenarios in different organizational settings. The factors featured in the box are systematised into a set of four categories of bundling layers which we identify from reviewing literature. The two core layers in the framework are the service bundling on a type level and on an instance level (i.e. configuration). To demonstrate the applicability and utility of the proposed morphological box, we apply it to assess the underlying differences and commonalities of two different bundling scenarios from the B2B and G2C sectors which stress the differences between bundling on a type and instance level. In addition, we identify several prospects for future research that can benefit from the proposed morphological box.

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Light plays a unique role for plants as it is both a source of energy for growth and a signal for development. Light captured by the pigments in the light harvesting complexes is used to drive the synthesis of the chemical energy required for carbon assimilation. The light perceived by photoreceptors activates effectors, such as transcription factors (TFs), which modulate the expression of light-responsive genes. Recently, it has been speculated that increasing the photosynthetic rate could further improve the yield potential of three carbon (C3) crops such as wheat. However, little is currently known about the transcriptional regulation of photosynthesis genes, particularly in crop species. Nuclear factor Y (NF-Y) TF is a functionally diverse regulator of growth and development in the model plant species, with demonstrated roles in embryo development, stress response, flowering time and chloroplast biogenesis. Furthermore, a light-responsive NF-Y binding site (CCAAT-box) is present in the promoter of a spinach photosynthesis gene. As photosynthesis genes are co-regulated by light and co-regulated genes typically have similar regulatory elements in their promoters, it seems likely that other photosynthesis genes would also have light-responsive CCAAT-boxes. This provided the impetus to investigate the NF-Y TF in bread wheat. This thesis is focussed on wheat NF-Y members that have roles in light-mediated gene regulation with an emphasis on their involvement in the regulation of photosynthesis genes. NF-Y is a heterotrimeric complex, comprised of the three subunits NF-YA, NF-YB and NF-YC. Unlike the mammalian and yeast counterparts, each of the three subunits is encoded by multiple genes in Arabidopsis. The initial step taken in this study was the identification of the wheat NF-Y family (Chapter 3). A search of the current wheat nucleotide sequence databases identified 37 NF-Y genes (10 NF-YA, 11 NF-YB, 14 NF-YC & 2 Dr1). Phylogenetic analysis revealed that each of the three wheat NF-Y (TaNF-Y) subunit families could be divided into 4-5 clades based on their conserved core regions. Outside of the core regions, eleven motifs were identified to be conserved between Arabidopsis, rice and wheat NF-Y subunit members. The expression profiles of TaNF-Y genes were constructed using quantitative real-time polymerase chain reaction (RT-PCR). Some TaNF-Y subunit members had little variation in their transcript levels among the organs, while others displayed organ-predominant expression profiles, including those expressed mainly in the photosynthetic organs. To investigate their potential role in light-mediated gene regulation, the light responsiveness of the TaNF-Y genes were examined (Chapters 4 and 5). Two TaNF-YB and five TaNF-YC members were markedly upregulated by light in both the wheat leaves and seedling shoots. To identify the potential target genes of the light-upregulated NF-Y subunit members, a gene expression correlation analysis was conducted using publically available Affymetrix Wheat Genome Array datasets. This analysis revealed that the transcript expression levels of TaNF-YB3 and TaNF-YC11 were significantly correlated with those of photosynthesis genes. These correlated express profiles were also observed in the quantitative RT-PCR dataset from wheat plants grown under light and dark conditions. Sequence analysis of the promoters of these wheat photosynthesis genes revealed that they were enriched with potential NF-Y binding sites (CCAAT-box). The potential role of TaNF-YB3 in the regulation of photosynthetic genes was further investigated using a transgenic approach (Chapter 5). Transgenic wheat lines constitutively expressing TaNF-YB3 were found to have significantly increased expression levels of photosynthesis genes, including those encoding light harvesting chlorophyll a/b-binding proteins, photosystem I reaction centre subunits, a chloroplast ATP synthase subunit and glutamyl-tRNA reductase (GluTR). GluTR is a rate-limiting enzyme in the chlorophyll biosynthesis pathway. In association with the increased expression of the photosynthesis genes, the transgenic lines had a higher leaf chlorophyll content, increased photosynthetic rate and had a more rapid early growth rate compared to the wild-type wheat. In addition to its role in the regulation of photosynthesis genes, TaNF-YB3 overexpression lines flower on average 2-days earlier than the wild-type (Chapter 6). Quantitative RT-PCR analysis showed that there was a 13-fold increase in the expression level of the floral integrator, TaFT. The transcript levels of other downstream genes (TaFT2 and TaVRN1) were also increased in the transgenic lines. Furthermore, the transcript levels of TaNF-YB3 were significantly correlated with those of constans (CO), constans-like (COL) and timing of chlorophyll a/b-binding (CAB) expression 1 [TOC1; (CCT)] domain-containing proteins known to be involved in the regulation of flowering time. To summarise the key findings of this study, 37 NF-Y genes were identified in the crop species wheat. An in depth analysis of TaNF-Y gene expression profiles revealed that the potential role of some light-upregulated members was in the regulation of photosynthetic genes. The involvement of TaNF-YB3 in the regulation of photosynthesis genes was supported by data obtained from transgenic wheat lines with increased constitutive expression of TaNF-YB3. The overexpression of TaNF-YB3 in the transgenic lines revealed this NF-YB member is also involved in the fine-tuning of flowering time. These data suggest that the NF-Y TF plays an important role in light-mediated gene regulation in wheat.

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This publication is the first in a series of scholarly reports on research-based practice related to the First Year Experience in Higher Education. This report synthesises evidence about practice-based initiatives and pragmatic approaches in Aotearoa (New Zealand) and Australia that aim to enhance the experience of commencing students in the higher education sector. Trends in policies, programs and practices ... examines the first year experience literature from 2000-2010. It acknowledges the uniqueness of the Australasian socio-political context and its influence on the interests and output of researchers. The review surveyed almost 400 empirical reports and conceptual discussions produced over the decade that dealt with the stakeholders, institutions and the higher education sector in Australasia. The literature is examined through two theoretical constructs or “lenses”: first, a set of first year curriculum design principles and second, the generational approach to describing the maturation of initiatives. These outcomes and suggested directions for further research provide the challenges and the opportunities for FYE adherents, both scholars and practitioners, to grapple with in the next decade.

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We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.

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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.

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This is the final report of an Australian Learning and Teaching Council Teaching Fellowship which addressed the needs of two separate groups of learners: (1) final year law students studying ethics and (2) law academics and other interested educators in higher education wishing to use information and communication technologies (ICT) to create engaging learning environments for their students but lacking the capacity to do so. The Fellowship resulted in final year law students being infused with an improved appreciation of ethical practice than they receive from traditional lecture/tutorial means by the development of an integrated program of blended learning including an online program entitled "Entry into Valhalla". This "ethics capstone‟ utilises multimedia produced using cost effective resources (including the "Second Life" virtual environment) to create engaging, contextualised learning experiences. The Fellowship also constructed the knowledge of producing cost-effective multimedia projects in other law academics and other educators in higher education by staff development activities comprising workshops, conference presentations and an interactive website using the "Entry into Valhalla" program as a case study exemplar.

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Magnetohydrodynamic (MHD) natural convection laminar flow from an iso-thermal horizontal circular cylinder immersed in a fluid with viscosity proportional to a linear function of temperature will be discussed with numerical simulations. The governing boundary layer equations are transformed into a non-dimensional form and the resulting nonlinear system of partial differential equa-tions are reduced to convenient form, which are solved numerically by two very efficient methods, namely, (i) Implicit finite difference method together with Keller box scheme and (ii) Direct numerical scheme. Numerical results are presented by velocity and temperature distributions of the fluid as well as heat transfer characteristics, namely the shearing stress and the local heat transfer rate in terms of the local skin-friction coefficient and the local Nusselt number for a wide range of magnetohydrodynamic parameter, viscosity-variation parameter and viscous dissipation parameter. MHD flow in this geometry with temperature dependent viscosity is absent in the literature. The results obtained from the numerical simulations have been veri-fied by two methodologies.

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The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

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Both the SSS and SOBER-t32 stream cipher designs use a single word-based shift register and a nonlinear filter function to produce keystream. In this paper we show that the algebraic attack method previously applied to SOBER-t32 is prevented from succeeding on SSS by the use of the key dependent substitution box (SBox) in the nonlinear filter of SSS. Additional assumptions and modifications to the SSS cipher in an attempt to enable algebraic analysis result in other difficulties that also render the algebraic attack infeasible. Based on these results, we conclude that a well chosen key-dependent substitution box used in the nonlinear filter of the stream cipher provides resistance against such algebraic attacks.

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The field of research was internationally-oriented contemporary theatre practice. The research challenge was to adapt an iconic Queensland novel – David Malouf’s Johnno - to the stage in a way that would engage, resonate with and be relevant to national and international audiences. This project represented an international collaboration between La Boite Theatre Company, the Derby Playhouse, UK, and the Brisbane Festival. It was the first time that an English and an Australian company had collaborated in such a way, sharing both creative vision and financial costs and providing performances on both continents. The production was well received in both countries, suggesting that a culturally idiosyncratic work such as Johnno can be created that can fulfil not only the needs of the localised audience but also have broad global cultural resonance. The work was performed at the Brisbane Festival and the Derby Playhouse. In Brisbane, it was performed at the Brisbane Powerhouse as the signature work of the 2006 festival, with 30 performances, receiving favourable national reviews and achieving 90% box office. In the UK, it was performed at the Derby Playhouse for 22 performances, once again to favourable national reviews and 60% audiences, a good result for a new work in a regional theatre in the UK. The success of Johnno was also in the power of the collaboration between the three creative companies involved in the work.

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Failure of buried pipes due to reactive soil movement (e.g. shrinking/swelling) is a common problem for water and gas pipe networks in Australia and the world. Soil movement is closely related to seasonal climatic change, and particularly to the moisture content of soil. Although some research has been carried out to understand the effect of freezing and thawing of soils and temperature effects in colder climates, very limited research has been undertaken to examine the possible failure mechanisms of pipes buried in reactive soils. This study reports the responses of a 2 m long polyethylene pipe buried in reactive clay in a box under laboratory conditions. The soil and pipe movements were measured as the soil was wetted from the bottom of the box. It was observed that the pipe underwent substantial deformation as the soil swelled with increase of the moisture content. The results are explained with a simplified numerical analysis.

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Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

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The purpose of this paper is to show how project management governance is addressed through the use of a specific meta-method. Governance is defined here on two criteria: accountability and performance. Accountability is promoted through transparency and performance is promoted by responsive and responsible decision-making. According to a systemic perspective, transparency and decision-making involve having information, tacit or explicit knowledge, as well as understanding of the context, the different parameters and variables, their interaction and conditions of change. Although this method of methods was built according a heuristic process involving 25 years of various researches and consulting activities, it seems appropriate to draw its foundations. I clarify first my epistemological position and the notion of project and project management, as Art and Science. This lead me to define a "Be" / "Have" posture to this regards. Then, the main theoretical roots of MAP Method are exposed: Boisot' s Social Learning Cycle, Praxeology and Theory of Convention. Then we introduced the main characteristics of the method and the 17 methods and tools constituting MAP "tool box", thus with regard to the project management governance perspective. Finally, I discuss the integration of two managerial modes (operational and project modes) and the consequence in term of governance in a specific socio-techno-economic project/context ecosystem.