1000 resultados para simulated drift


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Background: Few studies have specifically investigated the functional effects of uncorrected astigmatism on measures of reading fluency. This information is important to provide evidence for the development of clinical guidelines for the correction of astigmatism. Methods: Participants included 30 visually normal, young adults (mean age 21.7 ± 3.4 years). Distance and near visual acuity and reading fluency were assessed with optimal spectacle correction (baseline) and for two levels of astigmatism, 1.00DC and 2.00DC, at two axes (90° and 180°) to induce both against-the-rule (ATR) and with-the-rule (WTR) astigmatism. Reading and eye movement fluency were assessed using standardized clinical measures including the test of Discrete Reading Rate (DRR), the Developmental Eye Movement (DEM) test and by recording eye movement patterns with the Visagraph (III) during reading for comprehension. Results: Both distance and near acuity were significantly decreased compared to baseline for all of the astigmatic lens conditions (p < 0.001). Reading speed with the DRR for N16 print size was significantly reduced for the 2.00DC ATR condition (a reduction of 10%), while for smaller text sizes reading speed was reduced by up to 24% for the 1.00DC ATR and 2.00DC condition in both axis directions (p<0.05). For the DEM, sub-test completion speeds were significantly impaired, with the 2.00DC condition affecting both vertical and horizontal times and the 1.00DC ATR condition affecting only horizontal times (p<0.05). Visagraph reading eye movements were not significantly affected by the induced astigmatism. Conclusions: Induced astigmatism impaired performance on selected tests of reading fluency, with ATR astigmatism having significantly greater effects on performance than did WTR, even for relatively small amounts of astigmatic blur of 1.00DC. These findings have implications for the minimal prescribing criteria for astigmatic refractive errors.

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Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.

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In this video, text floats on screen amidst a field of swirling coloured orbs and a stock music soundtrack. The text is sourced from Internet dating websites and combine into a single animated portrait charting an array of likes, dislikes, influences, beliefs and hobbies. This work examines the nature of consciousness and identity in a contemporary context. It reworks the languages of Internet dating websites to question how we construct and communicate our sense of self. Drawing on Zygmunt Bauman’s theoretical work on “liquid modernity”, this work presents an exaggerated take on contemporary identity that emphasizes its construction through consumer tastes, lifestyle choices and relationships with popular culture.

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This paper discusses commonly encountered diesel engine problems and the underlying combustion related faults. Also discussed are the methods used in previous studies to simulate diesel engine faults and the initial results of an experimental simulation of a common combustion related diesel engine fault, namely diesel engine misfire. This experimental fault simulation represents the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank-angle encoder and top-dead centre signals. Using these signals, it was possible to characterise the diesel engine in-cylinder pressure profiles and the effect of different combustion conditions on both vibration and acoustic emission signals.

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The Exeter stems vary in length from 90 to 150 mm. The shorter stems generally have lower offsets. The purpose of this study was to determine if length of stem, with fixed offset, affected rotational stability. Mechanical testing was carried out on 10 implant-cement constructs with 2 loading profiles, rising from chair and stair climbing, at different simulated implant lengths using purpose-built apparatus. This paper presents a mechanism for clinically observed rotational stability and explains the mechanical characteristics required for rotational stability in Exeter femoral stems. © 2012.

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Limited research is available on how well visual cues integrate with auditory cues to improve speech intelligibility in persons with visual impairments, such as cataracts. We investigated whether simulated cataracts interfered with participants’ ability to use visual cues to help disambiguate a spoken message in the presence of spoken background noise. We tested 21 young adults with normal visual acuity and hearing sensitivity. Speech intelligibility was tested under three conditions: auditory only with no visual input, auditory-visual with normal viewing, and auditory-visual with simulated cataracts. Central Institute for the Deaf (CID) Everyday Speech Sentences were spoken by a live talker, mimicking a pre-recorded audio track, in the presence of pre-recorded four-person background babble at a signal-to-noise ratio (SNR) of -13 dB. The talker was masked to the experimental conditions to control for experimenter bias. Relative to the normal vision condition, speech intelligibility was significantly poorer, [t (20) = 4.17, p < .01, Cohen’s d =1.0], in the simulated cataract condition. These results suggest that cataracts can interfere with speech perception, which may occur through a reduction in visual cues, less effective integration or a combination of the two effects. These novel findings contribute to our understanding of the association between two common sensory problems in adults: reduced contrast sensitivity associated with cataracts and reduced face-to-face communication in noise.

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Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

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Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.

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Microenterprise development programs (MEPs) have been recognised as a valuable way to help the poor engage in micro-businesses (Green et al., 2006; Vargas, 2000), presenting a way out of poverty (Choudhury et al., 2008; Strier, 2010). Concerns have been raised however, that the benefits of MEPs often don’t reach the extremely poor (Jones et al., 2004; Midgley, 2008; Mosley and Hulme, 1998; Nawaz, 2010; Pritchett, 2006). Balancing reach of these programs with depth is a challenging task. Targeting as many poor people as possible often results in MEPs focusing on the upper or middle poor, overlooking the most challenging group. As such, MEPs have been criticised for mission drift – losing sight of the organisation’s core purpose; assisting those more likely to succeed.

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This report, prepared by QUT Social Work and Human Services, in collaboration with key sector stakeholders, identifies the current and potentially expanded uses of Simulated Learning Environments (SLE) as part of the Health Workforce Australia (HWA) National Project. An expert Reference Group guided the project, facilitated the data collection, and provided feedback and support on the findings and broad recommendations.

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Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

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Young men figure prominently in sleep-related road crashes. Non-driving studies show them to be particularly vulnerable to sleep loss, compared with older men. We assessed the effect of a normal night's sleep vs. prior sleep restricted to 5 h, in a counterbalanced design, on prolonged (2 h) afternoon simulated driving in 20 younger (av. 23 y) and 19 older (av. 67 y) healthy men. Driving was monitored for sleepiness related lane deviations, EEGs were recorded continuously and subjective ratings of sleepiness taken every 200 s. Following normal sleep there were no differences between groups for any measure. After sleep restriction younger drivers showed significantly more sleepiness-related deviations and greater 4–11 Hz EEG power, indicative of sleepiness. There was a near significant increase in subjective sleepiness. Correlations between the EEG and subjective measures were highly significant for both groups, indicating good self-insight into increasing sleepiness. We confirm the greater vulnerability of younger drivers to sleep loss under prolonged afternoon driving.