408 resultados para TIME-VARIATION


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Abstract Background Understanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring. Methods Monthly surveillance data between 1991 and 2006 for Plasmodium vivax and Plasmodium falciparum malaria across 128 counties were assembled for Yunnan, a province of China with one of the highest burdens of malaria. County-level Bayesian Poisson regression models of incidence were constructed, with effects for rainfall, maximum temperature and temporal trend. The model also allowed for spatial variation in county-level incidence and temporal trend, and dependence between incidence in June–September and the preceding January–February. Results Models revealed strong associations between malaria incidence and both rainfall and maximum temperature. There was a significant association between incidence in June–September and the preceding January–February. Raw standardised morbidity ratios showed a high incidence in some counties bordering Myanmar, Laos and Vietnam, and counties in the Red River valley. Clusters of counties in south-western and northern Yunnan were identified that had high incidence not explained by climate. The overall trend in incidence decreased, but there was significant variation between counties. Conclusion Dependence between incidence in summer and the preceding January–February suggests a role of intrinsic host-pathogen dynamics. Incidence during the summer peak might be predictable based on incidence in January–February, facilitating malaria control planning, scaled months in advance to the magnitude of the summer malaria burden. Heterogeneities in county-level temporal trends suggest that reductions in the burden of malaria have been unevenly distributed throughout the province.

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This paper presents channel measurements and weather data collection experiments conducted in a rural environment for an innovative Multi-User-Single-Antenna (MUSA) MIMO-OFDM technology, proposed for rural areas. MUSA MIMO-OFDM uplink channels are established by placing six user terminals (UT) around one access point (AP). Generated terrain profiles and relative received power plots are presented based on the experimental data. According to the relative received signal, MUSA-MIMO-OFDM uplink channels experience temporal fading. Moreover, the correlation between the relative received power and weather variables are presented. Results show that all weather variables exhibit a negative average correlation with received power. Wind speed records the highest average negative correlation coefficient of -0.35. Local maxima of negative correlation, ranging from 0.49 to 0.78, between the weather variables and relative received signals were registered between 5-6 a.m. The highest measured correlation (-0.78) of this time of the day was exhibited by wind speed. These results show the extend of time variation effects experienced by MUSA-MIMO-OFDM channels deployed in rural environments.

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Employing multilevel inverters is a proper solution to reduce harmonic content of output voltage and electromagnetic interference in high power electronic applications. In this paper, a new pulse width modulation method for multilevel inverters is proposed in which power devices’ on-off switching times have been considered. This method can be surveyed in order to analyse the effect of switching time on harmonic contents of output voltage in high frequency applications when a switching time is not negligible compared to a switching cycle. Fast Fourier transform calculation and analysis of output voltage waveforms and harmonic contents with regard to switching time variation are presented in this paper for a single phase (3, 5)-level inverters used in high voltage and high frequency converters. Mathematical analysis and MATLAB simulation results have been carried out to validate the proposed method.

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High-speed broadband internet access is widely recognised as a catalyst to social and economic development, having a significant impact on global economy. Rural Australia’s inherent dispersed population over a large geographical area make the delivery of efficient, well-maintained and cost-effective internet a challenging task. The novel and highly-efficient Multi-User-Single-Antenna for MIMO (MUSA-MIMO) broadband wireless communication technology can effectively be used to deliver wireless broadband access to rural areas. This research aims to develop for the first time, an efficient and accurate algorithm for the tracking and prediction of Channel State Information (CSI) at the transmitter, by characterising time variation effects of the wireless communication channel on the performance of a highly-efficient MUSA-MIMO technology particularly suited for rural communities, improving their quality of life and economic prosperity.

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This paper reports an empirical study on measuring transit service reliability using the data from a Web-based passenger survey on a major transit corridor in Brisbane, Australia. After an introduction of transit service reliability measures, the paper presents the results from the case study including study area, data collection, and reliability measures obtained. This includes data exploration of boarding/arrival lateness, in-vehicle time variation, waiting time variation, and headway adherence. Impacts of peak-period effects and separate operation on service reliability are examined. Relationships between transit service characteristics and passenger waiting time are also discussed. A summary of key findings and an agenda of future research are offered in conclusions.

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Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

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This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.

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Measures of transit accessibility are important in evaluating transit services, planning for future services and investment on land use development. Existing tools measure transit accessibility using averaged walking distance or walking time to public transit. Although the mode captivity may have significant implications on one’s willingness to walk to use public transit, this has not been addressed in the literature to date. Failed to distinguish transit captive users may lead to overestimated ridership and spatial coverage of transit services. The aim of this research is to integrate the concept of transit captivity into the analysis of walking access to public transit. The conventional way of defining “captive” and “choice” transit users showed no significant difference in their walking times according to a preliminary analysis. A cluster analysis technique is used to further divide “choice” users by three main factors, namely age group, labour force status and personal income. After eliminating “true captive” users, defined as those without driver’s licence or without a car in respective household, “non-true captive” users were classified into a total of eight groups having similar socio-economic characteristics. The analysis revealed significant differences in the walking times and patterns by their level of captivity to public transit. This paper challenges the rule-of-thumb of 400m walking distance to bus stops. In average, people’s willingness to walk dropped drastically at 268m and continued to drop constantly until it reached the mark of 670m, where there was another drastic drop of 17%, which left with only 10% of the total bus riders willing to walk 670m or more. This research found that mothers working part time were the ones with lowest transit captivity and thus most sensitive to the walking time, followed by high-income earners and the elderly. The level of captivity increases when public transit users earned lesser income, such as students and students working part time.

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The central thesis in the article is that the venture creation process is different for innovative versus imitative ventures. This holds up; the pace of the process differs by type of venture as do, in line with theory-based hypotheses, the effects of certain human capital (HC) and social capital (SC) predictors. Importantly, and somewhat unexpectedly, the theoretically derived models using HC, SC, and certain controls are relatively successful explaining progress in the creation process for the minority of innovative ventures, but achieve very limited success for the imitative majority. This may be due to a rationalistic bias in conventional theorizing and suggests that there is need for considerable theoretical development regarding the important phenomenon of new venture creation processes. Another important result is that the building up of instrumental social capital, which we assess comprehensively and as a time variant construct, is important for making progress with both types of ventures, and increasingly, so as the process progresses. This result corroborates with stronger operationalization and more appropriate analysis method what previously published research has only been able to hint at.

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Purpose: To investigate associations between the diurnal variation in a range of corneal parameters, including anterior and posterior corneal topography, and regional corneal thickness. ----- Methods: Fifteen subjects had their corneas measured using a rotating Scheimpflug camera (Pentacam) every 3-7 hours over a 24-hour period. Anterior and posterior corneal axial curvature, pachymetry and anterior chamber depth were analysed. The best fitting corneal sphero-cylinder from the axial curvature, and the average corneal thickness for a series of different corneal regions were calculated. Intraocular pressure and axial length were also measured at each measurement session. Repeated measures ANOVA were used to investigate diurnal change in these parameters. Analysis of covariance was used to examine associations between the measured ocular parameters. ----- Results: Significant diurnal variation was found to occur in both the anterior and posterior corneal curvature and in the regional corneal thickness. Flattening of the anterior corneal best sphere was observed at the early morning measurement (p < 0.0001). The posterior cornea also underwent a significant steepening (p < 0.0001) and change in astigmatism 90/180° at this time. A significant swelling of the cornea (p < 0.0001) was also found to occur immediately after waking. Highly significant associations were found between the diurnal variation in corneal thickness and the changes in corneal curvature. ----- Conclusions: Significant diurnal variation occurs in the regional thickness and the shape of the anterior and posterior cornea. The largest changes in the cornea were typically evident upon waking. The observed non-uniform regional corneal thickness changes resulted in a steepening of the posterior cornea, and a flattening of the anterior cornea to occur at this time.

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Survey-based health research is in a boom phase following an increased amount of health spending in OECD countries and the interest in ageing. A general characteristic of survey-based health research is its diversity. Different studies are based on different health questions in different datasets; they use different statistical techniques; they differ in whether they approach health from an ordinal or cardinal perspective; and they differ in whether they measure short-term or long-term effects. The question in this paper is simple: do these differences matter for the findings? We investigate the effects of life-style choices (drinking, smoking, exercise) and income on six measures of health in the US Health and Retirement Study (HRS) between 1992 and 2002: (1) self-assessed general health status, (2) problems with undertaking daily tasks and chores, (3) mental health indicators, (4) BMI, (5) the presence of serious long-term health conditions, and (6) mortality. We compare ordinal models with cardinal models; we compare models with fixed effects to models without fixed-effects; and we compare short-term effects to long-term effects. We find considerable variation in the impact of different determinants on our chosen health outcome measures; we find that it matters whether ordinality or cardinality is assumed; we find substantial differences between estimates that account for fixed effects versus those that do not; and we find that short-run and long-run effects differ greatly. All this implies that health is an even more complicated notion than hitherto thought, defying generalizations from one measure to the others or one methodology to another.

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The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone at the calcaneus for the assessment of osteoporosis was first described within this journal 25 years ago. It was recognized in 2006 by Universities UK as being one of the ‘100 discoveries and developments in UK Universities that have changed the world’ over the past 50 years. In 2008, the UK's Department of Health also recognized BUA assessment of osteoporosis in a publication highlighting 11 projects that have contributed to ‘60 years of NHS research benefiting patients’. The BUA technique has been extensively clinically validated and is utilized worldwide, with at least seven commercial systems currently providing calcaneal BUA measurement. However, there is still no fundamental understanding of the dependence of BUA upon the material and structural properties of cancellous bone. This review aims to provide an ‘engineering in medicine’ perspective and proposes a new paradigm based upon phase cancellation due to variation in propagation transit time across the receive transducer face to explain the non-linear relationship between BUA and bone volume fraction in cancellous bone.

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Real‐time kinematic (RTK) GPS techniques have been extensively developed for applications including surveying, structural monitoring, and machine automation. Limitations of the existing RTK techniques that hinder their applications for geodynamics purposes are twofold: (1) the achievable RTK accuracy is on the level of a few centimeters and the uncertainty of vertical component is 1.5–2 times worse than those of horizontal components and (2) the RTK position uncertainty grows in proportional to the base‐torover distances. The key limiting factor behind the problems is the significant effect of residual tropospheric errors on the positioning solutions, especially on the highly correlated height component. This paper develops the geometry‐specified troposphere decorrelation strategy to achieve the subcentimeter kinematic positioning accuracy in all three components. The key is to set up a relative zenith tropospheric delay (RZTD) parameter to absorb the residual tropospheric effects and to solve the established model as an ill‐posed problem using the regularization method. In order to compute a reasonable regularization parameter to obtain an optimal regularized solution, the covariance matrix of positional parameters estimated without the RZTD parameter, which is characterized by observation geometry, is used to replace the quadratic matrix of their “true” values. As a result, the regularization parameter is adaptively computed with variation of observation geometry. The experiment results show that new method can efficiently alleviate the model’s ill condition and stabilize the solution from a single data epoch. Compared to the results from the conventional least squares method, the new method can improve the longrange RTK solution precision from several centimeters to the subcentimeter in all components. More significantly, the precision of the height component is even higher. Several geosciences applications that require subcentimeter real‐time solutions can largely benefit from the proposed approach, such as monitoring of earthquakes and large dams in real‐time, high‐precision GPS leveling and refinement of the vertical datum. In addition, the high‐resolution RZTD solutions can contribute to effective recovery of tropospheric slant path delays in order to establish a 4‐D troposphere tomography.

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Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.