951 resultados para Fragmented objects


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Rapid prototyping (RP) is a common name for several techniques, which read in data from computer-aided design (CAD) drawings and manufacture automatically threedimensional objects layer-by-layer according to the virtual design. The utilization of RP in tissue engineering enables the production of three-dimensional scaffolds with complex geometries and very fine structures. Adding micro- and nanometer details into the scaffolds improves the mechanical properties of the scaffold and ensures better cell adhesion to the scaffold surface. Thus, tissue engineering constructs can be customized according to the data acquired from the medical scans to match the each patient’s individual needs. In addition RP enables the control of the scaffold porosity making it possible to fabricate applications with desired structural integrity. Unfortunately, every RP process has its own unique disadvantages in building tissue engineering scaffolds. Hence, the future research should be focused into the development of RP machines designed specifically for fabrication of tissue engineering scaffolds, although RP methods already can serve as a link between tissue and engineering.

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The osteochondral defect is a classical model for a multiple-tissue problem[1]. Tissue engineering of either bone or cartilage imposes different demands on a scaffold concerning porosity, pore size and interconnectivity. Furthermore, local release of tissue-specific growth factors necessitates a tailored architecture. For the fabrication of an osteochondral scaffold with region specific architecture, an advanced technique is required. Stereolithography is a rapid prototyping technique that allows for the creation of such 3D polymer objects with well-defined architecture. Its working principle is the partial irradiation of a resin, causing a liquid-solid transition. By irradiating this resin by a computer-driven light source, a solid 3D object is constructed layer by layer. To make biodegradable polymers applicable in stereolithography, low-molecular weight polymers have to be functionalised with double bonds to enable photo-initiated crosslinking.

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In this world of continuous change, there’s probably one certainty: more change lies ahead. Our students will encounter challenges and opportunities that we can’t even imagine. How do we prepare our students as future citizens for the challenges of the 21st century? One of the most influential public intellectuals of our time, Howard Gardner, suggests that in the future individuals will depend to a great extent on the capacity to synthesise large amounts of information. ‘They will need to be able to gather together information from disparate sources and put it together in ways that work for themselves and can be communicated to other persons’(Gardner 2008, p. xiii). One of the first steps in ‘putting things together’ so they ‘work’ in the mind is ‘to group objects and events together on the basis of some similarity between them’ (Lee & das Gupta 1995, p. 116). When we do this and give them a collective name, we are conceptualising. Apart from helping to save our sanity by simplifying the vast amounts of data we encounter every day, concepts help us to understand and gain meaning from what we experience. Concepts are essential for synthesising information and they also help us to communicate with others. Put simply, concepts serve as building blocks for knowledge, understanding and communication. This chapter addresses the importance of teaching and learning about concepts and conceptual development in studies of society and environment. It proceeds as follows: first, it considers how individuals use concepts, and, second, it explores the characteristics of concepts; the third section presents a discussion of approaches that might be adopted by teachers intending to help their students build concepts in the classroom.

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Poly(D,L-lactide) is a degradable polymer with a long history of use in medical applications. It is strong and stiff and degrades over the course of months into lactic acid, a body-own substance. In the field of tissue engineering it is commonly used to fabricate scaffolds. Stereolithography is a high resolution rapid prototyping technique by which designed 3D objects can be built using photo-initiated radical polymerisations. Poly(D,Llactide) (PDLLA) networks can be obtained by photopolymerisation of oligomers functionalised with unsaturated groups. In this work, PDLLA oligomers of varying architectures (arm lengths, numbers of arms) were synthesised and end-functionalised with methacrylate groups. These macromers were photo-crosslinked in solution to yield PDLLA networks of different architectures. The influence of the network architecture on its physical properties was studied.

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The artwork was created to respond to the exhibition theme, "DIGILOG+IN". It aimed to express the beauty when digital and analogue materials are combined. It visualised an organic harmony between digital and natural objects through digitalisation and builded a fantasy of digital world. However, there was a conceptual dilemma that a “digitalisation” of natural objects into a digital format should merely become a digital work. In other words, a harmony between digital and analogue (natural) can be only achieved through a digitalising process by removing intrinsic nature of analogues. Therefore, the substance of analogues no longer exists in a digitally visualised form, but is virtually represented. The title of art work “digitualisation” is a combined word with “digi-tal” and vir-tualisation”. It refers to a digitally virtualising the substance of natural objects. The artwork visualised the concept of digitualisation by using natural objects (flowers) that are merged within a virtual space (a building entrance foyer).

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Purpose–The growing debate in the literature indicates that the initiative to implement Knowledge Based Urban Development (KBUD) approaches in urban development process is neither simple nor quick. Many research efforts has therefore, been put forward to the development of appropriate KBUD framework and KBUD practical approaches. But this has lead to a fragmented and incoherent methodological approach. This paper outlines and compares a few most popular KBUD frameworks selected from the literature. It aims to identify some key and common features in the effort to achieve a unified method of KBUD framework. Design/methodology/approach–This paper reviews, examines and identifies various popular KBUD frameworks discussed in the literature from urban planners’ viewpoint. It employs a content analysis technique i.e. a research tool used to determine the presence of certain words or concepts within texts or sets of texts. Originality/value–The paper reports on the key and common features of a few selected most popular KBUD frameworks. The synthesis of the results is based from a perspective of urban planners. The findings which encompass a new KBUD framework incorporating the key and common features will be valuable in setting a platform to achieve a unified method of KBUD. Practical implications –The discussion and results presented in this paper should be significant to researchers and practitioners and to any cities and countries that are aiming for KBUD. Keywords – Knowledge based urban development, Knowledge based urban development framework, Urban development and knowledge economy

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Level crossing crashes have been shown to result in enormous human and financial cost to society. According to the Australian Transport Safety Bureau (ATSB) [5] a total of 632 Railway Level crossing (RLX) collisions, between trains and road vehicles, occurred in Australia between 2001 and June 2009. The cost of RLX collisions runs into the tens of millions of dollars each year in Australia [6]. In addition, loss of life and injury are commonplace in instances where collisions occur. Based on estimates that 40% of rail related fatalities occur at level crossings [12], it is estimated that 142 deaths between 2001 and June 2009 occurred at RLX. The aim of this paper is to (i) summarise crash patterns in Australia, (ii) review existing international ITS interventions to improve level crossing and (iii) highlights open human factors research related issues. Human factors (e.g., driver error, lapses or violations) have been evidenced as a significant contributing factor in RLX collisions, with drivers of road vehicles particularly responsible for many collisions. Unintentional errors have been found to contribute to 46% of RLX collisions [6] and appear to be far more commonplace than deliberate violations. Humans have been found to be inherently inadequate at using the sensory information available to them to facilitate safe decision-making at RLX and tend to underestimate the speed of approaching large objects due to the non-linear increases in perceived size [6]. Collisions resulting from misjudgements of train approach speed and distance are common [20]. Thus, a fundamental goal for improved RLX safety is the provision of sufficient contextual information to road vehicle drivers to facilitate safe decision-making regarding crossing behaviours.

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The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

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A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

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Using sculpture and drawing as my primary methods of investigation, this research explores ways of shifting the emphasis of my creative visual arts practice from object to process whilst still maintaining a primacy of material outcomes. My motivation was to locate ways of developing a sustained practice shaped as much by new works, as by a creative flow between works. I imagined a practice where a logic of structure within discrete forms and a logic of the broader practice might be developed as mutually informed processes. Using basic structural components of multiple wooden curves and linear modes of deployment – in both sculptures and drawings – I have identified both emergence theory and the image of rhizomic growth (Deleuze and Guattari, 1987) as theoretically integral to this imagining of a creative practice, both in terms of critiquing and developing works. Whilst I adopt a formalist approach for this exegesis, the emergence and rhizome models allow it to work as a critique of movement, of becoming and changing, rather than merely a formalism of static structure. In these models, therefore, I have identified a formal approach that can be applied not only to objects, but to practice over time. The thorough reading and application of these ontological models (emergence and rhizome) to visual arts practice, in terms of processes, objects and changes, is the primary contribution of this thesis. The works that form the major component of the research develop, reflect and embody these notions of movement and change.

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Griffith University is developing a digital repository system using HarvestRoad Hive software to better meet the needs of academics and students using institutional learning and teaching, course readings, and institutional intellectual capital systems. Issues with current operations and systems are discussed in terms of user behaviour. New repository systems are being designed in such a way that they address current service and user behaviour issues by closely aligning systems with user needs. By developing attractive online services, Griffith is working to change current user behaviour to achieve strategic priorities in the sharing and reuse of learning objects, improved selection and use of digitised course readings, the development of ePrint and eScience services, and the management of a research portfolio service.

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From a ‘cultural science’ perspective, this paper traces one aspect of a more general shift, from the realist representational regime of modernity to the productive DIY systems of the internet era. It argues that collecting and archiving is transformed by this change. Modern museums – and also broadcast television – were based on determinist or ‘essence’ theory; while internet archives like YouTube (and the internet as an archive) are based on ‘probability’ theory. The paper goes through the differences between modernist ‘essence’ and postmodern ‘probability’; starting from the obvious difference that in a museum each object is selected by experts for its intrinsic properties, while on the internet you don’t know what you will find. The status of individual objects is uncertain, although the productivity of the overall archive is unlimited. The paper links these differences with changes in contemporary culture – from a Newtonian to a quantum universe, progress to risk, institutional structure to evolutionary change, objectivity to uncertainty, identity to performance. Borrowing some of its methodology from science fiction, the paper uses examples from museums and online archives, ranging from the oldest stone tool in the world to the latest tribute vid on the net.

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With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

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This paper joins growing interest in the concept of practice, and uses it to reconceptualise international student engagement with the demands of study at an Australian university. Practice foregrounds institutional structures and student agency and brings together psychologically- and socially-oriented perspectives on international student learning approaches. Utilising discourse theory, practice is defined as habitual and individual instances of socially-contextualised configurations of elements such as actions and interactions, roles and relations, identities, objects, values, and language. In the university context, academic practice highlights the institutionally-sanctioned ways of knowing, doing and being that constitute academic tasks. The concept is applied here to six international students’ ‘readings’ of and strategic responses to academic work in a Master of Education course. It is argued that academic practice provides a comprehensive framework for explaining the interface between university academic requirements and international student learning, and the crucial role that teaching has in facilitating the experience.

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We have recently demonstrated the geographic isolation of rice tungro bacilliform virus (RTBV) populations in the tungro-endemic provinces of Isabela and North Cotabato, Philippines. In this study, we examined the genetic structure of the virus populations at the tungro-outbreak sites of Lanao del Norte, a province adjacent to North Cotabato. We also analyzed the virus populations at the tungro-endemic sites of Subang, Indonesia, and Dien Khanh, Vietnam. Total DNA extracts from 274 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV. In the total population, 22 EcoRV-restricted genome profiles (genotypes) were identified. Although overlapping genotypes could be observed, the outbreak sites of Lanao del Norte had a genotype combination distinct from that of Subang or Dien Khanh but a genotype combination similar to that identified earlier from North Cotabato, the adjacent endemic province. Sequence analysis of the intergenic region and part of the ORF1 RTBV genome from randomly selected genotypes confirms the geographic clustering of RTBV genotypes and, combined with restriction analysis, the results suggest a fragmented spatial distribution of RTBV local populations in the three countries. Because RTBV depends on rice tungro spherical virus (RTSV) for transmission, the population dynamics of both tungro viruses were then examined at the endemic and outbreak sites within the Philippines. The RTBV genotypes and the coat protein RTSV genotypes were used as indicators for virus diversity. A shift in population structure of both viruses was observed at the outbreak sites with a reduced RTBV but increased RTSV gene diversity