512 resultados para Reliable Computations


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In a classification problem typically we face two challenging issues, the diverse characteristic of negative documents and sometimes a lot of negative documents that are closed to positive documents. Therefore, it is hard for a single classifier to clearly classify incoming documents into classes. This paper proposes a novel gradual problem solving to create a two-stage classifier. The first stage identifies reliable negatives (negative documents with weak positive characteristics). It concentrates on minimizing the number of false negative documents (recall-oriented). We use Rocchio, an existing recall based classifier, for this stage. The second stage is a precision-oriented “fine tuning”, concentrates on minimizing the number of false positive documents by applying pattern (a statistical phrase) mining techniques. In this stage a pattern-based scoring is followed by threshold setting (thresholding). Experiment shows that our statistical phrase based two-stage classifier is promising.

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Driver sleepiness contributes substantially to fatal and severe crashes and the contribution it makes to less serious crashes is likely to as great or greater. Currently, drivers’ awareness of sleepiness (subjective sleepiness) remains a critical component for the mitigation of sleep-related crashes. Nonetheless, numerous calls have been made for technological monitors of drivers’ physiological sleepiness levels so drivers can be ‘alerted’ when approaching high levels of sleepiness. Several physiological indices of sleepiness show potential as a reliable metric to monitor drivers’ sleepiness levels, with eye blink indices being a promising candidate. However, extensive evaluations of eye blink measures are lacking including the effects that the endogenous circadian rhythm can have on eye blinks. To examine the utility of ocular measures, 26 participants completed a simulated driving task while physiological measures of blink rate and duration were recorded after partial sleep restriction. To examine the circadian effects participants were randomly assigned to complete either a morning or an afternoon session of the driving task. The results show subjective sleepiness levels increased over the duration of the task. The blink duration index was sensitive to increases in sleepiness during morning testing, but was not sensitive during afternoon testing. This finding suggests that the utility of blink indices as a reliable metric for sleepiness are still far from specific. The subjective measures had the largest effect size when compared to the blink measures. Therefore, awareness of sleepiness still remains a critical factor for driver sleepiness and the mitigation of sleep-related crashes.

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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

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The process of building safer roads and roadsides needs to be managed to minimise risks to both the road using public and roadworkers. However, detailed and accurate data on fatalities and injuries at roadworks across Australia are not available. The lack of reliable safety records and consequent poor understanding of the hazards at roadworks motivated this research to examine the common trends in incidents and to understand workers' perceptions of the causes of incidents at roadworks. To achieve these aims, 66 roadworks personnel were interviewed in Queensland including road construction workers, traffic controllers, engineers, and managers. Qualitative analyses identified several major issues and themes. Vehicles driving into work areas, traffic controllers hit by vehicles, rear end crashes at roadwork approaches, and reversing incidents involving work vehicles and machinery were the most common types of incidents. Roadworkers perceived driver errors, such as violation of speed limits, distracted driving, and ignoring signage and traffic controllers' instructions as the main causes of the incidents.

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How do agents with limited cognitive capacities flourish in informationally impoverished or unexpected circumstances? Aristotle argued that human flourishing emerged from knowing about the world and our place within it. If he is right, then the virtuous processes that produce knowledge, best explain flourishing. Influenced by Aristotle, virtue epistemology defends an analysis of knowledge where beliefs are evaluated for their truth and the intellectual virtue or competences relied on in their creation. However, human flourishing may emerge from how degrees of ignorance are managed in an uncertain world. Perhaps decision-making in the shadow of knowledge best explains human wellbeing—a Bayesian approach? In this dissertation I argue that a hybrid of virtue and Bayesian epistemologies explains human flourishing—what I term homeostatic epistemology. Homeostatic epistemology supposes that an agent has a rational credence p when p is the product of reliable processes aligned with the norms of probability theory; whereas an agent knows that p when a rational credence p is the product of reliable processes such that: 1) p meets some relevant threshold for belief (such that the agent acts as though p were true and indeed p is true), 2) p coheres with a satisficing set of relevant beliefs and, 3) the relevant set of beliefs is coordinated appropriately to meet the integrated aims of the agent. Homeostatic epistemology recognizes that justificatory relationships between beliefs are constantly changing to combat uncertainties and to take advantage of predictable circumstances. Contrary to holism, justification is built up and broken down across limited sets like the anabolic and catabolic processes that maintain homeostasis in the cells, organs and systems of the body. It is the coordination of choristic sets of reliably produced beliefs that create the greatest flourishing given the limitations inherent in the situated agent.

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Liuwei Dihuang Wan (LWD), a classic Chinese medicinal formulae, has been used to improve or restore declined functions related to aging and geriatric diseases, such as impaired mobility, vision, hearing, cognition and memory. It has attracted increasingly much attention as one of the most popular and valuable herbal medicines. However, the systematic analysis of the chemical constituents of LDW is difficult and thus has not been well established. In this paper, a rapid, sensitive and reliable ultra-performance liquid chromatography with electrospray ionization quadrupole time-of-flight high-definition mass spectrometry (UPLC-ESI-Q-TOF-MS) method with automated MetaboLynx analysis in positive and negative ion mode was established to characterize the chemical constituents of LDW. The analysis was performed on a Waters UPLCTM HSS T3 using a gradient elution system. MS/MS fragmentation behavior was proposed for aiding the structural identification of the components. Under the optimized conditions, a total of 50 peaks were tentatively characterized by comparing the retention time and MS data. It is concluded that a rapid and robust platform based on UPLC-ESI-Q-TOF-MS has been successfully developed for globally identifying multiple-constituents of traditional Chinese medicine prescriptions. This is the first report on systematic analysis of the chemical constituents of LDW. This article is protected by copyright. All rights reserved.

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Nitrous oxide emissions from soil are known to be spatially and temporally volatile. Reliable estimation of emissions over a given time and space depends on measuring with sufficient intensity but deciding on the number of measuring stations and the frequency of observation can be vexing. The question of low frequency manual observations providing comparable results to high frequency automated sampling also arises. Data collected from a replicated field experiment was intensively studied with the intention to give some statistically robust guidance on these issues. The experiment had nitrous oxide soil to air flux monitored within 10 m by 2.5 m plots by automated closed chambers under a 3 h average sampling interval and by manual static chambers under a three day average sampling interval over sixty days. Observed trends in flux over time by the static chambers were mostly within the auto chamber bounds of experimental error. Cumulated nitrous oxide emissions as measured by each system were also within error bounds. Under the temporal response pattern in this experiment, no significant loss of information was observed after culling the data to simulate results under various low frequency scenarios. Within the confines of this experiment observations from the manual chambers were not spatially correlated above distances of 1 m. Statistical power was therefore found to improve due to increased replicates per treatment or chambers per replicate. Careful after action review of experimental data can deliver savings for future work.

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Background—Palpation is an important clinical test for jumper's knee. Objectives—To (a) test the reproducibility of palpation tenderness, (b) evaluate the sensitivity and specificity of palpation in subjects with clinical symptoms of jumper's knee, and (c) determine whether tenderness to palpation may serve as a useful screening test for patellar tendinopathy. The yardstick for diagnosis of patellar tendinopathy was ultrasonographic abnormality. Methods—In 326 junior symptomatic and asymptomatic athletes' tendons, palpation was performed by a single examiner before ultrasonographic examination by a certified ultrasound radiologist. In 58 tendons, palpation was performed twice to test reliability. Tenderness to palpation was scored on a scale from 0 to 3 where 0 represented no pain, and 1, 2, and 3 represented mild, moderate, and severe tenderness respectively. Results—Patellar tendon palpation was a reliable examination for a single examiner (Pearson r = 0.82). In symptomatic tendons, the positive predictive value of palpation was 68%. As a screening examination in asymptomatic subjects, the positive predictive value of tendon palpation was 36–38%. Moderate and severe palpation tenderness were better predictors of ultrasonographic tendon pathology than absent or mild tenderness (p<0.001). Tender and symptomatic tendons were more likely to have ultrasound abnormality than tenderness alone (p<0.01). Conclusions—In this age group, palpation is a reliable test but it is not cost effective in detecting patellar tendinopathy in a preparticipation examination. In symptomatic tendons, palpation is a moderately sensitive but not specific test. Mild tenderness in the patellar tendons in asymptomatic jumping athletes should be considered normal.

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Endotoxins can significantly affect the air quality in school environments. However, there is currently no reliable method for the measurement of endotoxins and there is a lack of reference values for endotoxin concentrations to aid in the interpretation of measurement results in school settings. We benchmarked the “baseline” range of endotoxin concentration in indoor air, together with endotoxin load in floor dust, and evaluated the correlation between endotoxin levels in indoor air and settled dust, as well as the effects of temperature and humidity on these levels in subtropical school settings. Bayesian hierarchical modeling indicated that the concentration in indoor air and the load in floor dust were generally (<95th percentile) < 13 EU/m3 and < 24,570 EU/m2, respectively. Exceeding these levels would indicate abnormal sources of endotoxins in the school environment, and the need for further investigation. Metaregression indicated no relationship between endotoxin concentration and load, which points to the necessity for measuring endotoxin levels in both the air and settled dust. Temperature increases were associated with lower concentrations in indoor air and higher loads in floor dust. Higher levels of humidity may be associated with lower airborne endotoxin concentrations.

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A nanoparticles size is one of their key physical characteristics that can affect their fate in a human’s respiratory tract (in case of inhalation) and also in the environment. Hence, measuring the size distribution of nanoparticles is absolutely essential and contributes greatly to their characterization. For years, Scanning Mobility Particle Sizers (SMPS), which rely on measuring the electrical mobility diameter of particles, have been used as one of the most reliable real-time instruments for the size distribution measurement of nanoparticles. Despite its benefits, this instrument has some drawbacks, including equivalency problems for non-spherical particles (i.e. assuming a non-spherical particle is equal to a spherical particle of diameter d due to the same electrical mobility), as well as limitations in terms of its use in workplaces, because of its large size and the complexity of its operation...

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A significant amount of speech data is required to develop a robust speaker verification system, but it is difficult to find enough development speech to match all expected conditions. In this paper we introduce a new approach to Gaussian probabilistic linear discriminant analysis (GPLDA) to estimate reliable model parameters as a linearly weighted model taking more input from the large volume of available telephone data and smaller proportional input from limited microphone data. In comparison to a traditional pooled training approach, where the GPLDA model is trained over both telephone and microphone speech, this linear-weighted GPLDA approach is shown to provide better EER and DCF performance in microphone and mixed conditions in both the NIST 2008 and NIST 2010 evaluation corpora. Based upon these results, we believe that linear-weighted GPLDA will provide a better approach than pooled GPLDA, allowing for the further improvement of GPLDA speaker verification in conditions with limited development data.

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Researchers have found that transformational leadership is related to positive outcomes in educational institutions. Hence, it is important to explore constructs that may predict leadership style in order to identify potential transformational leaders in assessment and selection procedures. Several studies in non-educational settings have found that emotional intelligence is a useful predictor of transformational leadership, but these studies have generally lacked methodological rigor and contextual relevance. This project, set in Australian educational institutions, employed a more rigorous methodology to answer the question: to what extent is the Mayer and Salovey (1997) model of emotional intelligence a useful predictor of leadership style and perceived leadership outcomes? The project was designed to move research in the field forward by using valid and reliable instruments, controlling for other predictors, obtaining an adequately sized sample of current leaders and collecting multiple ratings of their leadership behaviours. The study (N = 144 leaders and 432 raters) results indicated that emotional intelligence was not a useful predictor of leadership style and perceived leadership outcomes. In contrast, several of the other predictors in the study were found to predict leadership style.

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Recently, vision-based systems have been deployed in professional sports to track the ball and players to enhance analysis of matches. Due to their unobtrusive nature, vision-based approaches are preferred to wearable sensors (e.g. GPS or RFID sensors) as it does not require players or balls to be instrumented prior to matches. Unfortunately, in continuous team sports where players need to be tracked continuously over long-periods of time (e.g. 35 minutes in field-hockey or 45 minutes in soccer), current vision-based tracking approaches are not reliable enough to provide fully automatic solutions. As such, human intervention is required to fix-up missed or false detections. However, in instances where a human can not intervene due to the sheer amount of data being generated - this data can not be used due to the missing/noisy data. In this paper, we investigate two representations based on raw player detections (and not tracking) which are immune to missed and false detections. Specifically, we show that both team occupancy maps and centroids can be used to detect team activities, while the occupancy maps can be used to retrieve specific team activities. An evaluation on over 8 hours of field hockey data captured at a recent international tournament demonstrates the validity of the proposed approach.

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The production of adequate agricultural outputs to support the growing human population places great demands on agriculture, especially in light of ever-greater restrictions on input resources. Sorghum is a drought-adapted cereal capable of reliable production where other cereals fail, and thus represents a good candidate to address food security as agricultural inputs of water and arable land grow scarce. A long-standing issue with sorghum grain is that it has an inherently lower digestibility. Here we show that a low-frequency allele type in the starch metabolic gene, pullulanase, is associated with increased digestibility, regardless of genotypic background. We also provide evidence that the beneficial allele type is not associated with deleterious pleiotropic effects in the modern field environment. We argue that increasing the digestibility of an adapted crop is a viable way forward towards addressing food security while maximizing water and land-use efficiency.

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Background: Nutrition screening is usually administered by nurses. However, most studies on nutrition screening tools have not used nurses to validate the tools. The 3-Minute Nutrition Screening (3-MinNS) assesses weight loss, dietary intake and muscle wastage, with the composite score of each used to determine risk of malnutrition. The aim of the study was to determine the validity and reliability of 3-MinNS administered by nurses, who are the intended assessors. Methods: In this cross sectional study, three ward-based nurses screened 121 patients aged 21 years and over using 3-MinNS in three wards within 24 hours of admission. A dietitian then assessed the patients’ nutritional status using Subjective Global Assessment within 48 hours of admission, whilst blinded to the results of the screening. To assess the reliability of 3-MinNS, 37 patients screened by the first nurse were re-screened by a second nurse within 24 hours, who was blinded to the results of the first nurse. The sensitivity, specificity and best cutoff score for 3-MinNS were determined using the Receiver Operator Characteristics Curve. Results: The best cutoff score to identify all patients at risk of malnutrition using 3-MinNS was three, with sensitivity of 89% and specificity of 88%. This cutoff point also identified all (100%) severely malnourished patients. There was strong correlation between 3-MinNS and SGA (r=0.78, p<0.001). The agreement between two nurses conducting the 3-MinNS tool was 78.3%. Conclusion: 3-Minute Nutrition Screening is a valid and reliable tool for nurses to identify patients at risk of malnutrition.