986 resultados para information metrics


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The impact of technology on the health and well-being of workers has been a topic of interest since computers and computerized technology were widely introduced in the 1980s. Of recent concern is the impact of rapid technological advances on individuals’ psychological well-being, especially due to advancements in mobile technology which have increased many workers’ accessibility and expected productivity. In this chapter we focus on the associations between occupational stress and technology, especially behavioral and psychological reactions. We discuss some key facilitators and barriers associated with users’ acceptance of and engagement with information and communication technology. We conclude with recommendations for ongoing research on managing occupational health and well-being in conjunction with technological advancements.

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Dynamic load sharing can be defined as a measure of the ability of a heavy vehicle multi-axle group to equalise load across its wheels under typical travel conditions; i.e. in the dynamic sense at typical travel speeds and operating conditions of that vehicle. Various attempts have been made to quantify the ability of heavy vehicles to equalise the load across their wheels during travel. One of these was the concept of the load sharing coefficient (LSC). Other metrics such as the dynamic load coefficient (DLC) have been used to compare one heavy vehicle suspension with another for potential road damage. This paper compares these metrics and determines a relationship between DLC and LSC with sensitivity analysis of this relationship. The shortcomings of these presently-available metrics are discussed with a new metric proposed - the dynamic load equalisation (DLE) measure.

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Information Retrieval is an important albeit imperfect component of information technologies. A problem of insufficient diversity of retrieved documents is one of the primary issues studied in this research. This study shows that this problem leads to a decrease of precision and recall, traditional measures of information retrieval effectiveness. This thesis presents an adaptive IR system based on the theory of adaptive dual control. The aim of the approach is the optimization of retrieval precision after all feedback has been issued. This is done by increasing the diversity of retrieved documents. This study shows that the value of recall reflects this diversity. The Probability Ranking Principle is viewed in the literature as the “bedrock” of current probabilistic Information Retrieval theory. Neither the proposed approach nor other methods of diversification of retrieved documents from the literature conform to this principle. This study shows by counterexample that the Probability Ranking Principle does not in general lead to optimal precision in a search session with feedback (for which it may not have been designed but is actively used). Retrieval precision of the search session should be optimized with a multistage stochastic programming model to accomplish the aim. However, such models are computationally intractable. Therefore, approximate linear multistage stochastic programming models are derived in this study, where the multistage improvement of the probability distribution is modelled using the proposed feedback correctness method. The proposed optimization models are based on several assumptions, starting with the assumption that Information Retrieval is conducted in units of topics. The use of clusters is the primary reasons why a new method of probability estimation is proposed. The adaptive dual control of topic-based IR system was evaluated in a series of experiments conducted on the Reuters, Wikipedia and TREC collections of documents. The Wikipedia experiment revealed that the dual control feedback mechanism improves precision and S-recall when all the underlying assumptions are satisfied. In the TREC experiment, this feedback mechanism was compared to a state-of-the-art adaptive IR system based on BM-25 term weighting and the Rocchio relevance feedback algorithm. The baseline system exhibited better effectiveness than the cluster-based optimization model of ADTIR. The main reason for this was insufficient quality of the generated clusters in the TREC collection that violated the underlying assumption.

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Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly as the level of background noise is increased. Speech enhancement is a popular method for making ASR systems more ro- bust. Single-channel spectral subtraction was originally designed to improve hu- man speech intelligibility and many attempts have been made to optimise this algorithm in terms of signal-based metrics such as maximised Signal-to-Noise Ratio (SNR) or minimised speech distortion. Such metrics are used to assess en- hancement performance for intelligibility not speech recognition, therefore mak- ing them sub-optimal ASR applications. This research investigates two methods for closely coupling subtractive-type enhancement algorithms with ASR: (a) a computationally-efficient Mel-filterbank noise subtraction technique based on likelihood-maximisation (LIMA), and (b) in- troducing phase spectrum information to enable spectral subtraction in the com- plex frequency domain. Likelihood-maximisation uses gradient-descent to optimise parameters of the enhancement algorithm to best fit the acoustic speech model given a word se- quence known a priori. Whilst this technique is shown to improve the ASR word accuracy performance, it is also identified to be particularly sensitive to non-noise mismatches between the training and testing data. Phase information has long been ignored in spectral subtraction as it is deemed to have little effect on human intelligibility. In this work it is shown that phase information is important in obtaining highly accurate estimates of clean speech magnitudes which are typically used in ASR feature extraction. Phase Estimation via Delay Projection is proposed based on the stationarity of sinusoidal signals, and demonstrates the potential to produce improvements in ASR word accuracy in a wide range of SNR. Throughout the dissertation, consideration is given to practical implemen- tation in vehicular environments which resulted in two novel contributions – a LIMA framework which takes advantage of the grounding procedure common to speech dialogue systems, and a resource-saving formulation of frequency-domain spectral subtraction for realisation in field-programmable gate array hardware. The techniques proposed in this dissertation were evaluated using the Aus- tralian English In-Car Speech Corpus which was collected as part of this work. This database is the first of its kind within Australia and captures real in-car speech of 50 native Australian speakers in seven driving conditions common to Australian environments.

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One of role of the nurse in the clinical setting is that of coordinating communication across the healthcare team. On a daily basis nurses interact with the person receiving care, their family members, and multiple care providers thus placing the nurse in the central position with access to a vast array of information on the person. Through this nurses have historically functioned as “information repositories”. With the advent of Health Information Technology (HIT) tools there is a potential that HIT could impact interdisciplinary communication, practice efficiency and effectiveness, relationships and workflow in acute care settings \[1]\[3]. In 2005, the HIMSS Nursing Informatics Community developed the IHITScale to measure the impact of HIT on the nursing role and interdisciplinary communication in USA hospitals. In 2007, nursing informatics colleagues from Australia, Finland, Ireland, New Zealand, Scotland and the USA formed a research collaborative to validate the IHIT in six additional countries. This paper will discuss the background, methodology, results and implications from the Australian IHIT survey of over 1100 nurses. The results are currently being analyzed and will be presented at the conference.

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In 2005, the Healthcare Information Management Systems Society (HIMSS) Nursing Informatics Community developed a survey to measure the impact of health information technology (HIT), the IHIT Scale, on the role of nurses and interdisciplinary communication in hospital settings. In 2007, nursing informatics colleagues from Australia, England, Finland, Ireland, New Zealand, Scotland and the United States formed a research collaborative to validate the IHIT across countries. All teams have completed construct and face validation in their countries. Five out of six teams have initiated reliability testing by practicing nurses. This paper reports the international collaborative’s validation of the IHIT Scale completed to date.

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We examine the nature and extent of statutory executive stock option (ESO) disclosures by Australian listed companies over the 2001 to 2004 period, and the influence of corporate governance mechanisms on these disclosures. Our results show a progressive increase in overall compliance from 2001 to 2004. However, despite the improved compliance, the results reveal managements’ continued reluctance to disclose more sensitive ESO information. Factors associated with good internal governance, including board independence, audit committee independence and effectiveness, and compensation committee independence and effectiveness are found to contribute to improved compliance. Similarly, certain external governance factors are associated with improved disclosure, including external auditor quality, shareholder activism (as proxied by companies identified as poor performers by the Australian Shareholders’ Association), and regulatory intervention.

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Market failures involving the sale of complex merchandise, such as residential property, financial products and credit, have principally been attributed to information asymmetries. Existing legislative and regulatory responses were developed having regard to consumer protection policies based on traditional economic theories that focus on the notion of the ‘rational consumer’. Governmental responses therefore seek to impose disclosure obligations on sellers of complex goods or products to ensure that consumers have sufficient information upon which to make a decision. Emergent research, based on behavioural economics, challenges traditional ideas and instead focuses on the actual behaviour of consumers. This approach suggests that consumers as a whole do not necessarily benefit from mandatory disclosure because some, if not most, consumers do not pay attention to the disclosed information before they make a decision to purchase. The need for consumer policies to take consumer characteristics and behaviour into account is being increasingly recognised by governments, and most recently in the policy framework suggested by the Australian Productivity Commission

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The challenge for all educators is to fuse the learning of information literacy to an academic education in such a way that the outcome is systematic and sustainable learning for students. This challenge can be answered through long-term commitment to information literacy education bound to organisation-wide, renewable strategic planning and driven through systemic reform. This chapter seeks to explore the two sides of reforming information literacy education in an academic environment. Specifically, it will examine how one Australian university has undertaken the implementation of a rigorous strategic, systemic approach to information literacy learning and teaching.

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Genetically modified (GM) food products are the source of much controversy and in the context of consumer behaviour, the way in which consumers perceive such food products is of paramount importance both theoretically and practically. Despite this, relatively little research has focused on GM food products from a consumer perspective, and as such, this study seeks to better understand what effects consumer willingness to buy GM food products in Australian consumers.

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Evidence-based practice is increasingly being recognised as an important issue in a range of professional contexts including education, nursing, occupational therapy and librarianship. Many of these professions have observed a relationship or interface between evidence-based practice and information literacy. Using a phenomenographic approach this research explores variation in the how library and information professionals are experiencing evidence-based practice as part of their professional work. The findings of the research provide a basis for arguing that evidence-based practice represents the professional's enactment of information literacy in the workplace.

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Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

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This volume examines the social, cultural, and political implications of the shift from traditional forms of print-based libraries to the delivery of online information in educational contexts. Despite the central role of libraries in literacy and learning, research of them has, in the main, remained isolated within the disciplinary boundaries of information and library science. By contrast, this book problematizes and thereby mainstreams the field. It brings together scholars from a wide range of academic fields to explore the dislodging of library discourse from its longstanding apolitical, modernist paradigm. Collectively, the authors interrogate the presuppositions of current library practice and examine how library as place and library as space blend together in ways that may be both complementary and contradictory. Seeking a suitable term to designate this rapidly evolving and much contested development, the editors devised the word “libr@ary,” and use the term arobase to signify the conditions of formation of new libraries within contexts of space, knowledge, and capital.

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The field of collaborative health planning faces significant challenges created by the narrow focus of the available information, the absence of a framework to organise that information and the lack of systems to make information accessible and guide decision-making. These challenges have been magnified by the rise of the ‘healthy communities movement’, as a result of which, there have been more frequent calls for localised, collaborative and evidence-driven health related decision-making. This paper discusses the role of decision support systems as a mechanism to facilitate collaborative health decision-making. The paper presents a potential information management framework to underpin a health decision support system and describes the participatory process that is currently being used to create an online tool for health planners using geographic information systems. The need for a comprehensive information management framework to guide the process of planning for healthy communities has been emphasised. The paper also underlines the critical importance of the proposed framework not only in forcing planners to engage with the entire range of health determinants, but also in providing sufficient flexibility to allow exploration of the local setting-based determinants of health.

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A graduate destination survey can provide a snap shot in time of a graduate’s career progression and outcome. This paper will present the results of a Queensland University of Technology study exploring the employment outcomes of students who had completed a library and information science course from the Faculty of Information Technology between 2000 and 2008. Seventy-four graduates completed an online questionnaire administered in July 2009. The study found that 90% of the graduates surveyed were working and living in Queensland, with over three quarters living and working in Brisbane. Nearly 70% were working full-time, while only 1.4% indicating that they were unemployed and looking for work. Over 80% of the graduates identified themselves as working in “librarianship”. This study is the first step in understanding the progression and destination of QUT’s library and information science graduates. It is recommended that this survey becomes an ongoing initiative so that the results can be analysed and compared over time.