934 resultados para Subjective information


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Automatic spoken Language Identi¯cation (LID) is the process of identifying the language spoken within an utterance. The challenge that this task presents is that no prior information is available indicating the content of the utterance or the identity of the speaker. The trend of globalization and the pervasive popularity of the Internet will amplify the need for the capabilities spoken language identi¯ca- tion systems provide. A prominent application arises in call centers dealing with speakers speaking di®erent languages. Another important application is to index or search huge speech data archives and corpora that contain multiple languages. The aim of this research is to develop techniques targeted at producing a fast and more accurate automatic spoken LID system compared to the previous National Institute of Standards and Technology (NIST) Language Recognition Evaluation. Acoustic and phonetic speech information are targeted as the most suitable fea- tures for representing the characteristics of a language. To model the acoustic speech features a Gaussian Mixture Model based approach is employed. Pho- netic speech information is extracted using existing speech recognition technol- ogy. Various techniques to improve LID accuracy are also studied. One approach examined is the employment of Vocal Tract Length Normalization to reduce the speech variation caused by di®erent speakers. A linear data fusion technique is adopted to combine the various aspects of information extracted from speech. As a result of this research, a LID system was implemented and presented for evaluation in the 2003 Language Recognition Evaluation conducted by the NIST.

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his case study aims to describe how general parenting principles can be used as part of parent-led, family-focused child weight management that is in line with current Australian Clinical Practice Guidelines. A parent-led, family-focused child weight management program was designed for use by dietitians with parents of young children (five- to nine-year-olds). The program utilises the cornerstones of overweight treatment: diet, activity, behaviour modification and family support delivered in an age-appropriate, family-focused manner. Parents participate in 16 sessions (4 parenting-focused, 8 lifestyle-focused and 4 individual telephone support calls) conducted weekly, fortnightly then monthly over six months. This case study illustrates how a family used the program, resulting in reduced degree of overweight and stabilised waist circumference in the child over 12 months. In conclusion, linking parenting skills to healthy family lifestyle education provides an innovative approach to family-focused child weight management. It addresses key Australian Clinical Practice Guidelines, works at the family level, and provides a means for dietitians to easily adopt age-appropriate behaviour modification as part of their practice.

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Internationally, collection of reliable data on new and evolving health-care roles is crucial. We describe a protocol for design and administration of a national census of an emergent health-care role, namely nurse practitioners in Australia using databases held by regulatory authorities. A questionnaire was developed to obtain data on the role and scope of practice of Australian nurse practitioners. Our tool comprised five sections and included a total of 56 questions, using 28 existing items from the National Nursing and Midwifery Labour Force Census and nine items recommended in the Nurse Practitioner Workforce Planning Minimum Data Set. Australian Nurse Registering Authorities (n = 6) distributed the survey on our behalf. This paper outlines our instrument and methods. The survey was administered to 238 authorized Australian nurse practitioners (85% response rate). Rigorous collection of standardized items will ensure health policy is informed by reliable and valid data. We will re-administer the survey 2 years following the first survey to measure change over time.

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Establishing a nationwide Electronic Health Record system has become a primary objective for many countries around the world, including Australia, in order to improve the quality of healthcare while at the same time decreasing its cost. Doing so will require federating the large number of patient data repositories currently in use throughout the country. However, implementation of EHR systems is being hindered by several obstacles, among them concerns about data privacy and trustworthiness. Current IT solutions fail to satisfy patients’ privacy desires and do not provide a trustworthiness measure for medical data. This thesis starts with the observation that existing EHR system proposals suer from six serious shortcomings that aect patients’ privacy and safety, and medical practitioners’ trust in EHR data: accuracy and privacy concerns over linking patients’ existing medical records; the inability of patients to have control over who accesses their private data; the inability to protect against inferences about patients’ sensitive data; the lack of a mechanism for evaluating the trustworthiness of medical data; and the failure of current healthcare workflow processes to capture and enforce patient’s privacy desires. Following an action research method, this thesis addresses the above shortcomings by firstly proposing an architecture for linking electronic medical records in an accurate and private way where patients are given control over what information can be revealed about them. This is accomplished by extending the structure and protocols introduced in federated identity management to link a patient’s EHR to his existing medical records by using pseudonym identifiers. Secondly, a privacy-aware access control model is developed to satisfy patients’ privacy requirements. The model is developed by integrating three standard access control models in a way that gives patients access control over their private data and ensures that legitimate uses of EHRs are not hindered. Thirdly, a probabilistic approach for detecting and restricting inference channels resulting from publicly-available medical data is developed to guard against indirect accesses to a patient’s private data. This approach is based upon a Bayesian network and the causal probabilistic relations that exist between medical data fields. The resulting definitions and algorithms show how an inference channel can be detected and restricted to satisfy patients’ expressed privacy goals. Fourthly, a medical data trustworthiness assessment model is developed to evaluate the quality of medical data by assessing the trustworthiness of its sources (e.g. a healthcare provider or medical practitioner). In this model, Beta and Dirichlet reputation systems are used to collect reputation scores about medical data sources and these are used to compute the trustworthiness of medical data via subjective logic. Finally, an extension is made to healthcare workflow management processes to capture and enforce patients’ privacy policies. This is accomplished by developing a conceptual model that introduces new workflow notions to make the workflow management system aware of a patient’s privacy requirements. These extensions are then implemented in the YAWL workflow management system.

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Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.

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Australian privacy law regulates how government agencies and private sector organisations collect, store and use personal information. A coherent conceptual basis of personal information is an integral requirement of information privacy law as it determines what information is regulated. A 2004 report conducted on behalf of the UK’s Information Commissioner (the 'Booth Report') concluded that there was no coherent definition of personal information currently in operation because different data protection authorities throughout the world conceived the concept of personal information in different ways. The authors adopt the models developed by the Booth Report to examine the conceptual basis of statutory definitions of personal information in Australian privacy laws. Research findings indicate that the definition of personal information is not construed uniformly in Australian privacy laws and that different definitions rely upon different classifications of personal information. A similar situation is evident in a review of relevant case law. Despite this, the authors conclude the article by asserting that a greater jurisprudential discourse is required based on a coherent conceptual framework to ensure the consistent development of Australian privacy law.

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The exchange of design models in the design and construction industry is evolving away from 2-dimensional computer-aided design (CAD) and paper towards semantically-rich 3-dimensional digital models. This approach, known as Building Information Modelling (BIM), is anticipated to become the primary means of information exchange between the various parties involved in construction projects. From a technical perspective, the domain represents an interesting study in model-based interoperability, since the models are large and complex, and the industry is one in which collaboration is a vital part of business. In this paper, we present our experiences with issues of model-based interoperability in exchanging building information models between various tools, and in implementing tools which consume BIM models, particularly using the industry standard IFC data modelling format. We report on the successes and challenges in these endeavours, as the industry endeavours to move further towards fully digitised information exchange.

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With the increasing threat of cyber and other attacks on critical infrastructure, governments throughout the world have been organizing industry to share information on possible threats. In Australia the Office of the Attorney General has formed Trusted Information Sharing Networks (TISN) for the various critical industries such as banking and electricity. Currently the majority of information for a TISN is shared at physical meetings. To meet cyber threats there are clearly limitations to physical meetings. Many of these limitations can be overcome by the creation of a virtual information sharing network (VISN). However there are many challenges to overcome in the design of a VISN both from a policy and technical viewpoint. We shall discuss some of these challenges in this talk.

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A statistical modeling method to accurately determine combustion chamber resonance is proposed and demonstrated. This method utilises Markov-chain Monte Carlo (MCMC) through the use of the Metropolis-Hastings (MH) algorithm to yield a probability density function for the combustion chamber frequency and find the best estimate of the resonant frequency, along with uncertainty. The accurate determination of combustion chamber resonance is then used to investigate various engine phenomena, with appropriate uncertainty, for a range of engine cycles. It is shown that, when operating on various ethanol/diesel fuel combinations, a 20% substitution yields the least amount of inter-cycle variability, in relation to combustion chamber resonance.

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Measures and theories of information abound, but there are few formalised methods for treating the contextuality that can manifest in different information systems. Quantum theory provides one possible formalism for treating information in context. This paper introduces a quantum-like model of the human mental lexicon, and shows one set of recent experimental data suggesting that concept combinations can indeed behave non-separably. There is some reason to believe that the human mental lexicon displays entanglement.

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Optimal decision-making requires us to accurately pinpoint the basis of our thoughts, e.g. whether they originate from our memory or our imagination. This paper argues that the phenomenal qualities of our subjective experience provide permissible evidence to revise beliefs, particularly as it pertains to memory. I look to the source monitoring literature to reconcile circumstances where mnemic beliefs and mnemic qualia conflict. By separating the experience of remembering from biological facts of memory, unusual cases make sense, such as memory qualia without memory (e.g. déjà vu, false memories) or a failure to have memory qualia with memory (e.g. functional amnesia, unintentional plagiarism). I argue that a pragmatic, probabilistic approach to belief revision is a way to rationally incorporate information from conscious experience, whilst acknowledging its inherent difficulties as an epistemic source. I conclude with a Bayesian defense of source monitoring based on C.I. Lewis’ coherence argument for memorial knowledge.

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Information security policy defines the governance and implementation strategy for information security in alignment with the corporate risk policy objectives and strategies. Research has established that alignment between corporate concerns may be enhanced when strategies are developed concurrently using the same development process as an integrative relationship is established. Utilizing the corporate risk management framework for security policy management establishes such an integrative relationship between information security and corporate risk management objectives and strategies. There is however limitation in the current literature on presenting a definitive approach that fully integrates security policy management with the corporate risk management framework. This paper presents an approach that adopts a conventional corporate risk management framework for security policy development and management to achieve alignment with the corporate risk policy. A case example is examined to illustrate the alignment achieved in each process step with a security policy structure being consequently derived in the process. It is shown that information security policy management outcomes become both integral drivers and major elements of the corporate-level risk management considerations. Further study should involve assessing the impact of the use of the proposed framework in enhancing alignment as perceived in this paper.

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The MPEG-21 Multimedia Framework provides for controlled distribution of multimedia works through its Intellectual Property Management and Protection ("IPMP") Components and Rights Expression Language ("MPEG REL"). The IPMP Components provide a framework by which the components of an MPEG-21 digital item can be protected from undesired access, while MPEG REL provides a mechanism for describing the conditions under which a component of a digital item may be used and distributed. This chapter describes how the IPMP Components and MPEG REL were used to implement a series of digital rights management applications at the Cooperative Research Centre for Smart Internet Technology in Australia. While the IPMP Components and MPEG REL were initially designed to facilitate the protection of copyright, the applications also show how the technology can be adapted to the protection of private personal information and sensitive corporate information.

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National estimates of the prevalence of child abuse-related injuries are obtained from a variety of sectors including welfare, justice, and health resulting in inconsistent estimates across sectors. The International Classification of Diseases (ICD) is used as the international standard for categorising health data and aggregating data for statistical purposes, though there has been limited validation of the quality, completeness or concordance of these data with other sectors. This research study examined the quality of documentation and coding of child abuse recorded in hospital records in Queensland and the concordance of these data with child welfare records. A retrospective medical record review was used to examine the clinical documentation of over 1000 hospitalised injured children from 20 hospitals in Queensland. A data linkage methodology was used to link these records with records in the child welfare database. Cases were sampled from three sub-groups according to the presence of target ICD codes: Definite abuse, Possible abuse, unintentional injury. Less than 2% of cases coded as being unintentional were recoded after review as being possible abuse, and only 5% of cases coded as possible abuse cases were reclassified as unintentional, though there was greater variation in the classification of cases as definite abuse compared to possible abuse. Concordance of health data with child welfare data varied across patient subgroups. This study will inform the development of strategies to improve the quality, consistency and concordance of information between health and welfare agencies to ensure adequate system responses to children at risk of abuse.