195 resultados para False confession


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Paramedics are at high risk of exposure to infectious diseases because they frequently undertake procedures such as the use and disposal of sharps as components of everyday practice. While the literature demonstrates that the management of sharps is problematic across all health disciplines, there is a paucity of research examining sharps management practices in the Australian pre-hospital paramedic context. This study examines knowledge and practices of sharps control among paramedics in Queensland, Australia. A mail survey focusing on infection control knowledge and practices was sent to all clinical personnel of the Queensland Ambulance Service (QAS) (N = 2274). A total of 1258 surveys were returned, a response rate of 55.3%. Participants responded to 12 true/false statements on the management of sharps and three questions about recapping practices. Most respondents were knowledgeable about the correct management of sharps, with a mean of 11.28 (out of 12, SD = 1.32). When gauging reported practices, more than half (59.1%, n = 736) of participants reported recapping a needle, and 38.5% (n = 479) reported never having done so. These results reflect good knowledge of general management of sharps among respondents, but suggest deficits regarding reported practices. The results suggest that a comprehensive ambulance in-service education programme focusing particularly on sharps management is required. The study highlights the need for further research on sharps management practices in the field, identification of barriers to safe sharps practices in pre-hospital settings, and 'best practice' for translating good sharps management knowledge into practice.

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Improving the performance of a incident detection system was essential to minimize the effect of incidents. A new method of incident detection was brought forward in this paper based on an in-car terminal which consisted of GPS module, GSM module and control module as well as some optional parts such as airbag sensors, mobile phone positioning system (MPPS) module, etc. When a driver or vehicle discovered the freeway incident and initiated an alarm report the incident location information located by GPS, MPPS or both would be automatically send to a transport management center (TMC), then the TMC would confirm the accident with a closed-circuit television (CCTV) or other approaches. In this method, detection rate (DR), time to detect (TTD) and false alarm rate (FAR) were more important performance targets. Finally, some feasible means such as management mode, education mode and suitable accident confirming approaches had been put forward to improve these targets.

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This paper will examine the literature on ‘anorexia nervosa’, and argue that it is underpinned by three fundamental assumptions. First, ‘anorexia nervosa’ is a reflection of the mismatch between true ‘inner self’ and the external ‘false self’, the latter self being the distorted product of a male dominated society. Second, the explanation for the severe fasting practices constitutive of ‘anorexia nervosa’ (a new social problem) is to be found within the binary opposition of resistance/conformity to contemporary cultural expectations. Finally, ‘anorexia nervosa’ is a problem which exists in nature (i.e., independently of analysis). It was eventually discovered, named and explained. This paper will problematise each of these assumptions in turn, and in doing so, it will propose an alternative way of understanding contemporary fasting practices.

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One of the definitions of the term myth is ‘an unproved or false collective belief that is used to justify a social institution’ (see http://dictionary.reference.com/browse/myth). Before we are criticized for suggesting such an irreverent thought might apply to tourism academia, readers must recognize that organizations and industries often operate using shared collective myths (see Meyer and Rowan 1977). Institutionalized rules and processes function as myths that provide legitimacy. The question of interest in this paper is not in the context of the quality of tourism academic research output, which is addressed by other papers in this research probe section. Rather, of importance is enhancing understanding of the extent to which our collective knowledge, legitimized through publishing in peer reviewed academic publications, is proving of value to industry stakeholders, an axiom that appears to be largely unquestioned and unproven.

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Economists rely heavily on self-reported measures to examine the relationship between income and health. We directly compare survey responses of a self-reported measure of health that is commonly used in nationally representative surveys with objective measures of the same health condition. We focus on hypertension. We find no evidence of an income/health greadient using self-reported hypertension but a sizeable gradient when using objectively measured hypertension. We also find that the probability of a false negative reporting is significantly income graded. Our results suggest that using commonly available self-reported chronic health measures might underestimate true income-related inequalities in health.

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It has long been recognised that government and public sector services suffer an innovation deficit compared to private or market-based services. This paper argues that this can be explained as an unintended consequence of the concerted public sector drive toward the elimination of waste through efficiency, accountability and transparency. Yet in an evolving economy this can be a false efficiency, as it also eliminates the 'good waste' that is a necessary cost of experimentation. This results in a systematic trade0off in the public sector between the static efficiency of minimizing the misuse of public resources and the dynamic efficiency of experimentation. this is inherently biased against risk and uncertainty and therein, explains why governments find service innovation so difficult. In the drive to eliminate static inefficiencies, many political systems have susequently overshot and stifled policy innovation. I propose the 'Red Queen' solution of adaptive economic policy.

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Computer tomography has been used to image and reconstruct in 3-D an Egyptian mummy from the collection of the British Museum. This study of Tjentmutengebtiu, a priestess from the 22nd dynasty (945-715 BC) revealed invaluable information of a scientific, Egyptological and palaeopathological nature without mutilation and destruction of the painted cartonnage case or linen wrappings. Precise details on the removal of the brain through the nasal cavity and the viscera from the abdominal cavity were obtained. The nature and composition of the false eyes were investigated. The detailed analysis of the teeth provided a much closer approximation of age at death. The identification of materials used for the various amulets including that of the figures placed in the viscera was graphically demonstrated using this technique.

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As virtual communities become more central to the everyday activities of connected individuals, we face increasingly pressing questions about the proper allocation of power, rights and responsibilities. This paper argues that our current legal discourse is ill-equipped to provide answers that will safeguard the legitimate interests of participants and simultaneously refrain from limiting the future innovative development of these spaces. From social networking sites like Facebook to virtual worlds like World of Warcraft and Second Life, participants who are banned from these communities stand to lose their virtual property, their connections to their friends and family, and their personal expression. Because our legal system views the proprietor’s interests as absolute private property rights, however, participants who are arbitrarily, capriciously or maliciously ejected have little recourse under law. This paper argues that, rather than assuming that a private property and freedom of contract model will provide the most desirable outcomes, a more critical approach is warranted. By rejecting the false dichotomy between ‘public’ and ‘private’ spaces, and recognising some of the absolutist and necessitarian trends in the current property debate, we may be able to craft legal rules that respect the social bonds between participants while simultaneously protecting the interests of developers.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.

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Integrity of Real Time Kinematic (RTK) positioning solutions relates to the confidential level that can be placed in the information provided by the RTK system. It includes the ability of the RTK system to provide timely valid warnings to users when the system must not be used for the intended operation. For instance, in the controlled traffic farming (CTF) system that controls traffic separates wheel beds and root beds, RTK positioning error causes overlap and increases the amount of soil compaction. The RTK system’s integrity capacity can inform users when the actual positional errors of the RTK solutions have exceeded Horizontal Protection Levels (HPL) within a certain Time-To-Alert (TTA) at a given Integrity Risk (IR). The later is defined as the probability that the system claims its normal operational status while actually being in an abnormal status, e.g., the ambiguities being incorrectly fixed and positional errors having exceeded the HPL. The paper studies the required positioning performance (RPP) of GPS positioning system for PA applications such as a CTF system, according to literature review and survey conducted among a number of farming companies. The HPL and IR are derived from these RPP parameters. A RTK-specific rover autonomous integrity monitoring (RAIM) algorithm is developed to determine the system integrity according to real time outputs, such as residual square sum (RSS), HDOP values. A two-station baseline data set is analyzed to demonstrate the concept of RTK integrity and assess the RTK solution continuity, missed detection probability and false alarm probability.

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There is a “reality” to being online which we know to be false. We are simultaneously “there” but “not there” as we talk, work and play with others in online spaces. We move between physical and virtual spaces in ways that realise the predictions made for computers in the mid-20th Century and enact scenarios from science fiction. We are left wondering if our thoughts - through our disembodied selves - have become a “second self” or if we have become part of the machine itself. Information and communication technology (ICT) have brought differing human and technological agencies to all aspects of contemporary life including teaching and learning. This paper attempts to identify and categorise these agencies through the genres of technics and to illustrate them – and our relationships with technology - through reference to philosophy, fiction and reality. It also stands as an introduction to this special issue on the agency of technology.

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The brain-derived neurotrophic factor (BDNF) has been suggested to play a pivotal role in the aetiology of affective disorders. In order to further clarify the impact of BDNF gene variation on major depression as well as antidepressant treatment response, association of three BDNF polymorphisms [rs7103411, Val66Met (rs6265) and rs7124442] with major depression and antidepressant treatment response was investigated in an overall sample of 268 German patients with major depression and 424 healthy controls. False discovery rate (FDR) was applied to control for multiple testing. Additionally, ten markers in BDNF were tested for association with citalopram outcome in the STAR*D sample. While BDNF was not associated with major depression as a categorical diagnosis, the BDNF rs7124442 TT genotype was significantly related to worse treatment outcome over 6 wk in major depression (p=0.01) particularly in anxious depression (p=0.003) in the German sample. However, BDNF rs7103411 and rs6265 similarly predicted worse treatment response over 6 wk in clinical subtypes of depression such as melancholic depression only (rs7103411: TT

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Information fusion in biometrics has received considerable attention. The architecture proposed here is based on the sequential integration of multi-instance and multi-sample fusion schemes. This method is analytically shown to improve the performance and allow a controlled trade-off between false alarms and false rejects when the classifier decisions are statistically independent. Equations developed for detection error rates are experimentally evaluated by considering the proposed architecture for text dependent speaker verification using HMM based digit dependent speaker models. The tuning of parameters, n classifiers and m attempts/samples, is investigated and the resultant detection error trade-off performance is evaluated on individual digits. Results show that performance improvement can be achieved even for weaker classifiers (FRR-19.6%, FAR-16.7%). The architectures investigated apply to speaker verification from spoken digit strings such as credit card numbers in telephone or VOIP or internet based applications.

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This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.