887 resultados para Context-aware applications
Resumo:
Melt electrospinning is relatively under-investigated compared to solution electrospinning but provides opportunities in numerous areas, in which solvent accumulation or toxicity are a concern. These applications are diverse, and provide a broad set of challenges to researchers involved in electrospinning. In this context, melt electrospinning provides an alternative approach that bypasses some challenges to solution electronspinning, while bringing new issues to the forefront, such as the thermal stability of polymers. This Focus Review describes the literature on melt electrospinning, as well as highlighting areas where both melt and solution are combined, and potentially merge together in the future.
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Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.
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In computational linguistics, information retrieval and applied cognition, words and concepts are often represented as vectors in high dimensional spaces computed from a corpus of text. These high dimensional spaces are often referred to as Semantic Spaces. We describe a novel and efficient approach to computing these semantic spaces via the use of complex valued vector representations. We report on the practical implementation of the proposed method and some associated experiments. We also briefly discuss how the proposed system relates to previous theoretical work in Information Retrieval and Quantum Mechanics and how the notions of probability, logic and geometry are integrated within a single Hilbert space representation. In this sense the proposed system has more general application and gives rise to a variety of opportunities for future research.
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In wireless mobile ad hoc networks (MANETs), packet transmission is impaired by radio link fluctuations. This paper proposes a novel channel adaptive routing protocol which extends the Ad-hoc On-Demand Multipath Distance Vector routing protocol (AOMDV) to accommodate channel fading. Specifically, the proposed Channel Aware AOMDV (CA-AOMDV) uses the channel average non-fading duration as a routing metric to select stable links for path discovery, and applies a preemptive handoff strategy to maintain reliable connections by exploiting channel state information. Using the same information, paths can be reused when they become available again, rather than being discarded. We provide new theoretical results for the downtime and lifetime of a live-die-live multiple path system, as well as detailed theoretical expressions for common network performance measures, providing useful insights into the differences in performance between CA-AOMDV and AOMDV. Simulation and theoretical results show that CA-AOMDV has greatly improved network performance over AOMDV.
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This paper raises the question of whether comparative national models of communications research can be developed, along the lines of Hallin and Mancini’s (2004) analysis of comparative media policy, or the work of Perraton and Clift (2004) on comparative national capitalisms. Taking consideration of communications research in Australia and New Zealand as its starting point, the paper will consider what are relevant variables in shaping an “intellectual milieu” for communications research in these countries, as compared to those of Europe, North America and Asia. Some possibly relevant variables include: • Type of media system (e.g. how significant is public service media?); • Political culture (e.g. are there significant left-of-centre political parties?); • Dominant intellectual traditions; • Level and types of research funding; • Overall structure of higher education system, and where communications sits within it. In considering whether such an exercise can or should be undertaken, we can also evaluate, as Hallin and Mancini do, the significance of potentially homogenizing forces. These would include globalization, new media technologies, and the rise of a global “audit culture”. The paper will raise these issues as questions that emerge as we consider, as Curran and Park (2000) and Thussu (2009) have proposed, what a “de-Westernized” media and communications research paradigm may look like.
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The study of the creative industries is not much more than a decade old. What makes it fascinating is that it is dealing with a rapidly evolving process, where a good deal of Schumpeterian ‘creative destruction’ – of old industries, business models, and some familiar cultural and creative pursuits – can already be observed. What happens next – and who will be the winner – is hard to predict. Furthermore, the creative industries encompass both large-scale ‘industry’ (media, publishing, digital applications) and individual creative talent; both economic and cultural values, and both global reach and local context. Thus, the challenge is to integrate ‘top-down’ policy and planning with ‘bottom-up’ experimentation and innovation. There is always the promise that this new creative ecology will provide some novel answers to problems of wealth-creation for emergent economies, new solutions to problems of intellectual emancipation for individuals, and sustainable development for that most intense incubator of creative ideas, the city.
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Australia is just one of many developed countries facing the challenge of delivering value for money in the provision of a substantial infrastructure pipeline amidst severe construction and private finance constraints. To help address this challenge, this chapter focuses on developing an understanding of the determinants of value at key procurement decision points that range from the make-or-buy decision, to buying in the context of market structures, including the exchange relationship and contractual arrangement decision. This understanding is based on theoretical pluralism and illustrated by research in the field of construction and maintenance, and in public-private partnerships.
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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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Sustainable Urban and Regional Infrastructure Development: Technologies, Applications and Management, bridges the gap in the current literature by addressing the overall problems present in society's major infrastructures, and the technologies that may be applied to overcome these problems. It focuses on ways in which energy intensive but 'invisible' (to the general public) facilities can become green or greener. The studies presented re lessons to be learnt from our neighbors and from our own backyard, and provide an excellent general overview of the issues facing us all.
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The concept of ‘sustainability’ has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of the modern urban lifestyle. Climate change has emerged to be one of the biggest challenges faced by our planet today, threatening both built and natural systems with long term consequences which may be irreversible. While there is a vast literature in the market on sustainable cities and urban development, there is currently none that bring together the vital issues of urban and regional development, and the planning, management and implementation of sustainable infrastructure. Large scale infrastructure plays an important part in modern society by not only promoting economic growth, but also by acting as a key indicator for it. More importantly, it supplies municipal/local amenity and services: water, electricity, social and communication facilities, waste removal, transport of people and goods, as well as numerous other services. For the most part, infrastructure has been built by teams lead by engineers who are more concerned about functionality than the concept of sustainability. However, it has been widely stated that current practices and lifestyle cannot continue if we are to leave a healthy living planet to not only the next generation, but also to the generations beyond. Therefore, in order to be sustainable, there are drastic measures that need to be taken. Current single purpose and design infrastructures that are open looped are not sustainable; they are too resource intensive, consume too much energy and support the consumption of natural resources at a rate that will exhaust their supply. Because of this, it is vital that modern society, policy-makers, developers, engineers and planners become pioneers in introducing and incorporating sustainable features into urban and regional infrastructure.
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Work-related driving crashes are the most common cause of work-related injury, death, and absence from work in Australia and overseas. Surprisingly however, limited attention has been given to initiatives designed to improve safety outcomes in the work-related driving setting. This research paper will present preliminary findings from a research project designed to examine the effects of increasing work-related driving safety discussions on the relationship between drivers and their supervisors and motivations to drive safely. The research project was conducted within a community nursing population, where 112 drivers were matched with 23 supervisors. To establish discussions between supervisors and drivers, safety sessions were conducted on a monthly basis with supervisors of the drivers. At these sessions, the researcher presented context specific, audio-based anti-speeding messages. Throughout the course of the intervention and following each of these safety sessions, supervisors were instructed to ensure that all drivers within their workgroup listened to each particular anti-speeding message at least once a fortnight. In addition to the message, supervisors were also encouraged to frequently promote the anti-speeding message through any contact they had with their drivers (i.e., face to face, email, SMS text, and/or paper based contact). Fortnightly discussions were subsequently held with drivers, whereby the researchers ascertained the number and type of discussions supervisors engaged in with their drivers. These discussions also assessed drivers’ perceptions of the group safety climate. In addition to the fortnightly discussion, drivers completed a daily speed reporting form which assessed the proportion of their driving day spent knowingly over the speed limit. As predicted, the results found that if supervisors reported a good safety climate prior to the intervention, increasing the number of safety discussions resulted in drivers reporting a high quality relationship (i.e., leader-member exchange) with their supervisor post intervention. In addition, if drivers reported a good safety climate, increasing the number of discussions resulted in increased motivation to drive safely post intervention. Motivations to drive safely prior to the intervention also predicted self-reported speeding over the subsequent three months of reporting. These results suggest safety discussions play an important role in improving the exchange between supervisors and their drivers and drivers’ subsequent motivation to drive safely and, in turn, self reported speeding.
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As the world’s rural populations continue to migrate from farmland to sprawling cities, transport networks form an impenetrable maze within which monocultures of urban form erupt from the spaces in‐between. These urban monocultures are as problematic to human activity in cities as cropping monocultures are to ecosystems in regional landscapes. In China, the speed of urbanisation is exacerbating the production of mono‐functional private and public spaces. Edges are tightly controlled. Barriers and management practices at these boundaries are discouraging the formation of new synergistic relationships, critical in the long‐term stability of ecosystems that host urban habitats. Some urban planners, engineers, urban designers, architects and landscape architects have recognised these shortcomings in contemporary Chinese cities. The ideology of sustainability, while critically debated, is bringing together thinking people in these and other professions under the umbrella of an ecological ethic. This essay aims to apply landscape ecology theory, a conceptual framework used by many professionals involved in land development processes, to a concept being developed by BAU International called Networks Cities: a city with its various land uses arranged in nets of continuity, adjacency, and superposition. It will consider six lesser‐known concepts in relation to creating enhanced human activity along (un)structured edges between proposed nets and suggest new frontiers that might be challenged in an eco‐city. Ecological theory suggests that sustaining biodiversity in regions and landscapes depends on habitat distribution patterns. Flora and fauna biologists have long studied edge habitats and have been confounded by the paradox that maximising the breadth of edges is detrimental to specialist species but favourable to generalist species. Generalist species of plants and animals tolerate frequent change in the landscape, frequenting two or more habitats for their survival. Specialist species are less tolerant of change, having specific habitat requirements during their life cycle. Protecting species richness then may be at odds with increasing mixed habitats or mixed‐use zones that are dynamic places where diverse activities occur. Forman (1995) in his book Land Mosaics however argues that these two objectives of land use management are entirely compatible. He postulates that an edge may be comprised of many small patches, corridors or convoluting boundaries of large patches. Many ecocentrists now consider humans to be just another species inhabiting the ecological environments of our cities. Hence habitat distribution theory may be useful in planning and designing better human habitats in a rapidly urbanising context like China. In less‐constructed environments, boundaries and edges provide important opportunities for the movement of multi‐habitat species into, along and from adjacent land use areas. For instance, invasive plants may escape into a national park from domestic gardens while wildlife may forage on garden plants in adjoining residential areas. It is at these interfaces that human interactions too flow backward and forward between land types. Spray applications of substances by farmers on cropland may disturb neighbouring homeowners while suburban residents may help themselves to farm produce on neighbouring orchards. Edge environments are some of the most dynamic and contested spaces in the landscape. Since most of us require access to at least two or three habitats diurnally, weekly, monthly or seasonally, their proximity to each other becomes critical in our attempts to improve the sustainability of our cities.
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The launch of the Apple iPad on January 2010 has seen considerable interest from the newspaper and publishing industry in developing content and business models for the tablet PC device that can address the limits of both the print and online news and information media products. It is early days in the iPad’s evolution, and we wait to see what competitor devices will emerge in the near future. It is apparent, however, that it has become a significant “niche” product, with considerable potential for mass market expansion over the next few years, possibly at the expense of netbook sales. The scope for the iPad and tablet PCs to become a “fourth screen” for users, alongside the TV, PC and mobile phone, is in early stages of evolution. The study used five criteria to assess iPad apps: • Content: timeliness; archive; personalisation; content depth; advertisements; the use of multimedia; and the extent to which the content was in sync with the provider brand. • Useability: degree of static content; ability to control multimedia; file size; page clutter; resolution; signposts; and customisation. • Interactivity: hyperlinks; ability to contribute content or provide feedback to news items; depth of multimedia; search function; ability to use plug-ins and linking; ability to highlight, rate and/or save items; functions that may facilitate a community of users. • Transactions capabilities: ecommerce functionality; purchase and download process; user privacy and transaction security. • Openness: degree of linking to outside sources; reader contribution processes; anonymity measures; and application code ownership.
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This paper presents a robust place recognition algorithm for mobile robots. The framework proposed combines nonlinear dimensionality reduction, nonlinear regression under noise, and variational Bayesian learning to create consistent probabilistic representations of places from images. These generative models are learnt from a few images and used for multi-class place recognition where classification is computed from a set of feature-vectors. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions and blurring. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.
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Alternative dispute resolution (a.d.r.) processes are entrenched in western style legal systems. Forms of dispute resolution are utilised within schools and health systems; built in to commercial contracts; found in workplaces, clubs and organisations; and accepted in general day-to-day community disputes. The a.d.r. literature includes references to ‘apology’, but is largely silent on ‘forgiveness’. Where an apology is offered as part of a dispute resolution process, practice suggests that formalised ‘forgiveness’ rarely follows. Mediators may agree there is a meaningful place for apology in dispute resolution processes, but are most unlikely to support a view that forgiveness, as a conscious act, has an equivalent place. Yet, if forgiveness is not limited to the ‘pardoning of an offence’, but includes a ‘giving up of resentment’, or the relinquishing of a grudge, then forgiveness may play an underestimated role in dispute management. In the context of some day-to-day dispute management practice, this paper questions whether forgiveness should follow an apology; and concludes that meaningful resolutions can be reached without any formal element of ‘forgiveness’ or absolution. However, dispute management practitioners need to be aware of the latent role other aspects of forgiveness may play for the disputing parties.