66 resultados para Data monitoring committees
Resumo:
In 1997 the Irish government adopted the National Anti-Poverty Strategy (NAPS), a global target for the reduction of poverty which illuminates a range of issues relating to official poverty targets. The Irish target is framed in terms of a relative poverty measure incorporating both relative income and direct measures of deprivation based on data on the extent of poverty from 1994. Since 1994 Ireland has experienced an unprecedented period of economic growth that makes it particularly important to assess whether the target has been achieved, but in doing so we cannot avoid asking some underlying questions about how poverty should be measured and monitored over time. After briefly outlining the nature of the NAPS measure, this article examines trends in poverty in Ireland between 1987 and 1997, Results show that the relative income and deprivation components of the NAPS measure reveal differential trends with increasing relative income poverty, but decreasing deprivation. However, this differential could be due to the fact that the direct measures of deprivation upon which NAPS is based have not been updated to take account of changes in real living standards and increasing expectations. To test whether this is so, we examine the extent to which expectations about living standards and the structure of deprivation have changed over time using confirmatory factor analysis and tests of criterion validity using different definitions of deprivation. Results show that the combined income and deprivation measure, as originally constituted, continues to identify a set of households experiencing generalised deprivation resulting from a lack of resources.
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While WiFi monitoring networks have been deployed in previous research, to date none have assessed live network data from an open access, public environment. In this paper we describe the construction of a replicable, independent WLAN monitoring system and address some of the challenges in analysing the resultant traffic. Analysis of traffic from the system demonstrates that basic traffic information from open-access networks varies over time (temporal inconsistency). The results also show that arbitrary selection of Request-Reply intervals can have a significant effect on Probe and Association frame exchange calculations, which can impact on the ability to detect flooding attacks.
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This paper discusses the importance of integrated sensing systems comprising techniques that give different types of data from a structure exposed to the marine environment so that its service life could reliably be predicted. For this purpose, a novel sensor combination was designed and installed in concrete panels which were exposed to Hangzhou Bay Bridge in China. The integrated sensor probe was used to monitor the cover concrete as well as the reinforcement. The sensor probes were connected to a monitoring station, which enabled access and control of the data remotely from Belfast, UK. The initial data obtained from the monitoring station gives interesting information on the early age properties of concrete and distinct variations in these properties with different types of concrete. This paper also reports the variation in electrical properties of different concrete samples and environmental data in response to the marine exposure condition at Hangzhou bay bridge.
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We describe the rationale for disease specific research networks in general as well as the aims and function of the European Cystic Fibrosis Society-Clinical Trials Network (ECFS-CTN) specifically. The ECFS-CTN was founded in 2009 with the aim of improving the quality and quantity of clinical research in the area of cystic fibrosis (CF) in Europe. A network of 18 clinical trial sites in 8 European countries was established according to uniform state-of-the-art quality criteria. To support the ECFS-CTN in the acquisition, planning and conduct of clinical trials, the network is equipped with a coordinating centre, steering and executive committees, and committees for protocol review, standardization, training and networking as well as a data safety monitoring board. A strong partnership with European CF patient parent organizations aims to increase awareness of the need for efficient clinical research and the participation of patients in clinical trials.
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This paper shows that current multivariate statistical monitoring technology may not detect incipient changes in the variable covariance structure nor changes in the geometry of the underlying variable decomposition. To overcome these deficiencies, the local approach is incorporated into the multivariate statistical monitoring framework to define two new univariate statistics for fault detection. Fault isolation is achieved by constructing a fault diagnosis chart which reveals changes in the covariance structure resulting from the presence of a fault. A theoretical analysis is presented and the proposed monitoring approach is exemplified using application studies involving recorded data from two complex industrial processes. © 2007 Elsevier Ltd. All rights reserved.
Resumo:
The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.
Resumo:
This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.
Resumo:
Soil carbon stores are a major component of the annual returns required by EU governments to the Intergovernmental Panel on Climate Change. Peat has a high proportion of soil carbon due to the relatively high carbon density of peat and organic-rich soils. For this reason it has become increasingly important to measure and model soil carbon stores and changes in peat stocks to facilitate the management of carbon changes over time. The approach investigated in this research evaluates the use of airborne geophysical (radiometric) data to estimate peat thickness using the attenuation of bedrock geology radioactivity by superficial peat cover. Remotely sensed radiometric data are validated with ground peat depth measurements combined with non-invasive geophysical surveys. Two field-based case studies exemplify and validate the results. Variography and kriging are used to predict peat thickness from point measurements of peat depth and airborne radiometric data and provide an estimate of uncertainty in the predictions. Cokriging, by assessing the degree of spatial correlation between recent remote sensed geophysical monitoring and previous peat depth models, is used to examine changes in peat stocks over time. The significance of the coregionalisation is that the spatial cross correlation between the remote and ground based data can be used to update the model of peat depth. The result is that by integrating remotely sensed data with ground geophysics, the need is reduced for extensive ground-based monitoring and invasive peat depth measurements. The overall goal is to provide robust estimates of peat thickness to improve estimates of carbon stocks. The implications from the research have a broader significance that promotes a reduction in the need for damaging onsite peat thickness measurement and an increase in the use of remote sensed data for carbon stock estimations.
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Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.
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The Irish and UK governments, along with other countries, have made a commitment to limit the concentrations of greenhouse gases in the atmosphere by reducing emissions from the burning of fossil fuels. This can be achieved (in part) through increasing the sequestration of CO2 from the atmosphere including monitoring the amount stored in vegetation and soils. A large proportion of soil carbon is held within peat due to the relatively high carbon density of peat and organic-rich soils. This is particularly important for a country such as Ireland, where some 16% of the land surface is covered by peat. For Northern Ireland, it has been estimated that the total amount of carbon stored in vegetation is 4.4Mt compared to 386Mt stored within peat and soils. As a result it has become increasingly important to measure and monitor changes in stores of carbon in soils. The conservation and restoration of peat covered areas, although ongoing for many years, has become increasingly important. This is summed up in current EU policy outlined by the European Commission (2012) which seeks to assess the relative contributions of the different inputs and outputs of organic carbon and organic matter to and from soil. Results are presented from the EU-funded Tellus Border Soil Carbon Project (2011 to 2013) which aimed to improve current estimates of carbon in soil and peat across Northern Ireland and the bordering counties of the Republic of Ireland.
Historical reports and previous surveys provide baseline data. To monitor change in peat depth and soil organic carbon, these historical data are integrated with more recently acquired airborne geophysical (radiometric) data and ground-based geochemical data generated by two surveys, the Tellus Project (2004-2007: covering Northern Ireland) and the EU-funded Tellus Border project (2011-2013) covering the six bordering counties of the Republic of Ireland, Donegal, Sligo, Leitrim, Cavan, Monaghan and Louth. The concept being applied is that saturated organic-rich soil and peat attenuate gamma-radiation from underlying soils and rocks. This research uses the degree of spatial correlation (coregionalization) between peat depth, soil organic carbon (SOC) and the attenuation of the radiometric signal to update a limited sampling regime of ground-based measurements with remotely acquired data. To comply with the compositional nature of the SOC data (perturbations of loss on ignition [LOI] data), a compositional data analysis approach is investigated. Contemporaneous ground-based measurements allow corroboration for the updated mapped outputs. This provides a methodology that can be used to improve estimates of soil carbon with minimal impact to sensitive habitats (like peat bogs), but with maximum output of data and knowledge.
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A novel multiplex microarray has been developed for the detection of five groups of harmful algal and cyanobacterial toxins found in marine, brackish, and freshwater environments including domoic acid (DA), okadaic acid (OA, and analogues), saxitoxin (STX, and analogues), cylindrospermopsin (CYN) and microcystins (MC, and analogues). The sensitivity and specificity were determined and feasibility to be used as a screening tool investigated. Results for algal/cyanobacterial cultures (n = 12) and seawater samples (n = 33) were compared to conventional analytical methods, such as high performance liquid chromatography (HPLC) and liquid chromatography tandem mass spectrometry (LC-MS/MS). Detection limits for the 15 min assay were 0.37, 0.44, 0.05, 0.08, and 0.40 ng/mL for DA, OA, STX, CYN, and MC, respectively. The correlation of data obtained from the microarray compared to conventional analysis for the 12 cultures was r(2) = 0.83. Analysis of seawater samples showed that 82, 82, 70, 82, and 12% of samples were positive (>IC20) compared to 67, 55, 36, 0, and 0% for DA, OA, STX, CYN, and MC, respectively, for conventional analytical methods. The discrepancies in results can be attributed to the enhanced sensitivity and cross-reactivity profiles of the antibodies in the MBio microarray. The feasibility of the microarray as a rapid, easy to use, and highly sensitive screening tool has been illustrated for the five-plex detection of biotoxins. The research demonstrates an early warning screening assay to support national monitoring agencies by providing a faster and more accurate means of identifying and quantifying harmful toxins in water samples.
Resumo:
Several theories of legislative organisation have been proposed to explain committee selection in American legislatures, but do these theories travel outside the United States? This paper tests whether these theories apply to data from the Canadian House of Commons. It was found that the distributive and partisan models of legislative organisation explain committee composition in Canada. In many cases, committees in the House of Commons are made up of preference outliers. As predicted by partisan models, it was also found that the governing party stacks committees with its members, but this is conditional upon the strength of the governing party.
Resumo:
Background: Vaginal ring devices are being actively developed for controlled delivery of HIV microbicides and as multi-purpose prevention technology (MPT) products combining hormonal contraception with prevention of HIV and other sexually transmitted diseases. Presently, there is no reliable method for monitoring user adherence in HIV vaginal ring trials; previous acceptability studies have included some type of participant self-reporting mechanism, which have often been unreliable. More objective, quantitative and accurate methods for assessing adherence are needed.
Methods: A silicone elastomer vaginal ring containing an encapsulated miniature temperature recording device has been developed that can capture and store real-time temperature data during the period of designated use. Devices were tested in both simulated vaginal environments and following vaginal placement in cynomolgus macaques. Various use protocols and data sampling rates were tested to simulate typical patient usage scenarios. Results: The temperature logging devices accurately recorded vaginal temperature in macaques, clearly showing the regular diurnal temperature cycle. When environmental temperature and vaginal temperature was significantly different, the device was able to accurately pinpoint the insertion and removal times. Based on the data collected it was possible to infer removal periods as short as 5 min when the external environmental temperature was 25 °C. Accuracy increased with data sampling rate. Conclusions: This work provides proof-of-concept for monitoring adherence using a vaginal ring device containing an encapsulated temperature logger. The addition of one or more active agents into the ring body is not anticipated to affect the temperature monitoring function. A clinical study to compare self- reported user adherence data with that obtained by the device would be highly informative.
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Sleep quality and duration are increasingly recognised as being important prognostic parameters in the assessment of an individual's health. However, reliable non-invasive long-term monitoring of sleep in a non-clinical setting remains a challenging problem. This paper describes the validation of a novel under mattress pressure sensing sleep monitoring modality that can be seamlessly integrated into existing home environments and provides a pervasive and distributed solution for monitoring long-term changes in sleep patterns and sleep disorders in adults. 410 minutes of concomitant Under Mattress Bed Sensor (UMBS) and strain gauge data were analysed from eight healthy adults lying passively. In this analysis, customised respirations rate detection algorithms yielded a mean difference of −0.12 breaths per five minutes and a mean percentage error (MPE) of 0.16% when the sensor was placed beneath the mattress. 1,491 minutes of UMBS and video data were recorded simultaneously from four participants in order to assess the movement detection efficacy of customised UMBS algorithms. These algorithms yielded accuracies, sensitivities and specificities of over 90% when compared to a video-based movement detection gold standard. A reduced data set (267 minutes) of wrist actigraphy, the gold standard ambulatory sleep monitor, was recorded. The UMBS was shown to outperform the movement detection ability of wrist actigraphy and has the added advantage of not requiring active subject participation.
Resumo:
BACKGROUND: Age-related macular degeneration is the most common cause of sight impairment in the UK. In neovascular age-related macular degeneration (nAMD), vision worsens rapidly (over weeks) due to abnormal blood vessels developing that leak fluid and blood at the macula.
OBJECTIVES: To determine the optimal role of optical coherence tomography (OCT) in diagnosing people newly presenting with suspected nAMD and monitoring those previously diagnosed with the disease.
DATA SOURCES: Databases searched: MEDLINE (1946 to March 2013), MEDLINE In-Process & Other Non-Indexed Citations (March 2013), EMBASE (1988 to March 2013), Biosciences Information Service (1995 to March 2013), Science Citation Index (1995 to March 2013), The Cochrane Library (Issue 2 2013), Database of Abstracts of Reviews of Effects (inception to March 2013), Medion (inception to March 2013), Health Technology Assessment database (inception to March 2013).
REVIEW METHODS: Types of studies: direct/indirect studies reporting diagnostic outcomes.
INDEX TEST: time domain optical coherence tomography (TD-OCT) or spectral domain optical coherence tomography (SD-OCT).
COMPARATORS: clinical evaluation, visual acuity, Amsler grid, colour fundus photographs, infrared reflectance, red-free images/blue reflectance, fundus autofluorescence imaging, indocyanine green angiography, preferential hyperacuity perimetry, microperimetry. Reference standard: fundus fluorescein angiography (FFA). Risk of bias was assessed using quality assessment of diagnostic accuracy studies, version 2. Meta-analysis models were fitted using hierarchical summary receiver operating characteristic curves. A Markov model was developed (65-year-old cohort, nAMD prevalence 70%), with nine strategies for diagnosis and/or monitoring, and cost-utility analysis conducted. NHS and Personal Social Services perspective was adopted. Costs (2011/12 prices) and quality-adjusted life-years (QALYs) were discounted (3.5%). Deterministic and probabilistic sensitivity analyses were performed.
RESULTS: In pooled estimates of diagnostic studies (all TD-OCT), sensitivity and specificity [95% confidence interval (CI)] was 88% (46% to 98%) and 78% (64% to 88%) respectively. For monitoring, the pooled sensitivity and specificity (95% CI) was 85% (72% to 93%) and 48% (30% to 67%) respectively. The FFA for diagnosis and nurse-technician-led monitoring strategy had the lowest cost (£39,769; QALYs 10.473) and dominated all others except FFA for diagnosis and ophthalmologist-led monitoring (£44,649; QALYs 10.575; incremental cost-effectiveness ratio £47,768). The least costly strategy had a 46.4% probability of being cost-effective at £30,000 willingness-to-pay threshold.
LIMITATIONS: Very few studies provided sufficient information for inclusion in meta-analyses. Only a few studies reported other tests; for some tests no studies were identified. The modelling was hampered by a lack of data on the diagnostic accuracy of strategies involving several tests.
CONCLUSIONS: Based on a small body of evidence of variable quality, OCT had high sensitivity and moderate specificity for diagnosis, and relatively high sensitivity but low specificity for monitoring. Strategies involving OCT alone for diagnosis and/or monitoring were unlikely to be cost-effective. Further research is required on (i) the performance of SD-OCT compared with FFA, especially for monitoring but also for diagnosis; (ii) the performance of strategies involving combinations/sequences of tests, for diagnosis and monitoring; (iii) the likelihood of active and inactive nAMD becoming inactive or active respectively; and (iv) assessment of treatment-associated utility weights (e.g. decrements), through a preference-based study.
STUDY REGISTRATION: This study is registered as PROSPERO CRD42012001930.
FUNDING: The National Institute for Health Research Health Technology Assessment programme.