Comparison of active-set method deconvolution and matched-filtering for derivation of an ultrasound transit time spectrum

The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs vs. 0.18 μs standard deviation), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity.

Combining detached watchdog journalism with development ideals: An exploration of Fijian journalism culture

Development journalism has been a key focus of discussion among journalism scholars for around half a decade, but most of the attention has been firmly on African and Asian countries. This paper examines the situation on the little-researched island nation of Fiji, which has experienced considerable political instability since independence in 1970. Based on interviews with 77 of the country’s small population of just over 100 journalists, we find that journalism in Fiji exhibits similarities to Western journalism ideals, but also a significant development journalism orientation. A comparison with six other countries from the global South shows that this mix is not unique, and we argue that Western journalism approaches and development ideals are not by necessity mutually exclusive, as has often been argued. In this way, the article aims to contribute to a reassessment of our understanding of development journalism and how journalists in developing societies view their work.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Rank-based regression for analysis of repeated measures

We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of estimating function for more efficient estimation.

A simple method for estimating growth parameters from multiple length-frequency data in presence of continuous recruitment

The extended recruitment season for short-lived species such as prawns biases the estimation of growth parameters from length-frequency data when conventional methods are used. We propose a simple method for overcoming this bias given a time series of length-frequency data. The difficulties arising from extended recruitment are eliminated by predicting the growth of the succeeding samples and the length increments of the recruits in previous samples. This method requires that some maximum size at recruitment can be specified. The advantages of this multiple length-frequency method are: it is simple to use; it requires only three parameters; no specific distributions need to be assumed; and the actual seasonal recruitment pattern does not have to be specified. We illustrate the new method with length-frequency data on the tiger prawn Penaeus esculentus from the north-western Gulf of Carpentaria, Australia.

A quasi-likelihood method for fractal-dimension estimation

We propose a simple method of constructing quasi-likelihood functions for dependent data based on conditional-mean-variance relationships, and apply the method to estimating the fractal dimension from box-counting data. Simulation studies were carried out to compare this method with the traditional methods. We also applied this technique to real data from fishing grounds in the Gulf of Carpentaria, Australia

An extension of the continual reassessment method using decision theory

The primary goal of a phase I trial is to find the maximally tolerated dose (MTD) of a treatment. The MTD is usually defined in terms of a tolerable probability, q*, of toxicity. Our objective is to find the highest dose with toxicity risk that does not exceed q*, a criterion that is often desired in designing phase I trials. This criterion differs from that of finding the dose with toxicity risk closest to q*, that is used in methods such as the continual reassessment method. We use the theory of decision processes to find optimal sequential designs that maximize the expected number of patients within the trial allocated to the highest dose with toxicity not exceeding q*, among the doses under consideration. The proposed method is very general in the sense that criteria other than the one considered here can be optimized and that optimal dose assignment can be defined in terms of patients within or outside the trial. It includes as an important special case the continual reassessment method. Numerical study indicates the strategy compares favourably with other phase I designs.

A maximum-likelihood method for estimating natural mortality and catchability coefficient from catch-and-effort data

A simple stochastic model of a fish population subject to natural and fishing mortalities is described. The fishing effort is assumed to vary over different periods but to be constant within each period. A maximum-likelihood approach is developed for estimating natural mortality (M) and the catchability coefficient (q) simultaneously from catch-and-effort data. If there is not enough contrast in the data to provide reliable estimates of both M and q, as is often the case in practice, the method can be used to obtain the best possible values of q for a range of possible values of M. These techniques are illustrated with tiger prawn (Penaeus semisulcatus) data from the Northern Prawn Fishery of Australia.

An improved Fabens method for estimation of growth parameters in the vonBertalanffy model with individual asymptotes

In the analysis of tagging data, it has been found that the least-squares method, based on the increment function known as the Fabens method, produces biased estimates because individual variability in growth is not allowed for. This paper modifies the Fabens method to account for individual variability in the length asymptote. Significance tests using t-statistics or log-likelihood ratio statistics may be applied to show the level of individual variability. Simulation results indicate that the modified method reduces the biases in the estimates to negligible proportions. Tagging data from tiger prawns (Penaeus esculentus and Penaeus semisulcatus) and rock lobster (Panulirus ornatus) are analysed as an illustration.

Method for comparing the capture efficiency of benthic sampling devices

Traditional comparisons between the capture efficiency of sampling devices have generally looked at the absolute differences between devices. We recommend that the signal-to-noise ratio be used when comparing the capture efficiency of benthic sampling devices. Using the signal-to-noise ratio rather than the absolute difference has the advantages that the variance is taken into account when determining how important the difference is, the hypothesis and minimum detectable difference can be made identical for all taxa, it is independent of the units used for measurement, and the sample-size calculation is independent of the variance. This new technique is illustrated by comparing the capture efficiency of a 0.05 m(2) van Veen grab and an airlift suction device, using samples taken from Heron and One Tree lagoons, Australia.

Promoting articulated action from diverse stakeholders in response to public policy scenarios: A case analysis of the use of ‘scenario improvisation’ method

In this paper we present a novel application of scenario methods to engage a diverse constituency of senior stakeholders, with limited time availability, in debate to inform planning and policy development. Our case study project explores post-carbon futures for the Latrobe Valley region of the Australian state of Victoria. Our approach involved initial deductive development of two ‘extreme scenarios’ by a multi-disciplinary research team, based upon an extensive research programme. Over four workshops with the stakeholder constituency, these initial scenarios were discussed, challenged, refined and expanded through an inductive process, whereby participants took ‘ownership’ of a final set of three scenarios. These were both comfortable and challenging to them. The outcomes of this process subsequently informed public policy development for the region. Whilst this process did not follow a single extant structured, multi-stage scenario approach, neither was it devoid of form. Here, we seek to theorise and codify elements of our process – which we term ‘scenario improvisation’ – such that others may adopt it.

Heavy haul sleeper design: A rational cost-saving method

Heavy haul railway lines are important and expensive items of infrastructure operating in an environment which is increasingly focussed on risk-based management and constrained profit margins. It is vital that costs are minimised but also that infrastructure satisfies failure criteria and standards of reliability which account for the random nature of wheel-rail forces and of the properties of the materials in the track. In Australia and the USA, concrete railway sleepers/ties are still designed using methods which the rest of the civil engineering world discarded decades ago in favour of the more rational, more economical and probabilistically based, limit states design (LSD) concept. This paper describes a LSD method for concrete sleepers which is based on (a) billions of measurements over many years of the real, random wheel-rail forces on heavy haul lines, and (b) the true capacity of sleepers. The essential principles on which the new method is based are similar to current, widely used LSD-based standards for concrete structures. The paper proposes and describes four limit states which a sleeper must satisfy, namely: strength; operations; serviceability; and fatigue. The method has been applied commercially to two new major heavy haul lines in Australia, where it has saved clients millions of dollars in capital expenditure.

Combining propensity and influence models for product adoption prediction

This paper studies the problem of selecting users in an online social network for targeted advertising so as to maximize the adoption of a given product. In previous work, two families of models have been considered to address this problem: direct targeting and network-based targeting. The former approach targets users with the highest propensity to adopt the product, while the latter approach targets users with the highest influence potential – that is users whose adoption is most likely to be followed by subsequent adoptions by peers. This paper proposes a hybrid approach that combines a notion of propensity and a notion of influence into a single utility function. We show that targeting a fixed number of high-utility users results in more adoptions than targeting either highly influential users or users with high propensity.

An interactive method for engaging the public health workforce with evidence

Introduction Systematic review authors are increasingly directing their attention to not only ensuring the robust processes and methods of their syntheses, but also to facilitating the use of their reviews by public health decision-makers and practitioners. This latter activity is known by several terms including knowledge translation, for which one definition is a ‘dynamic and iterative process that includes synthesis, exchange and ethically sound application of knowledge’.1 Unfortunately—and despite good intentions—the successful translation of knowledge has at times been inhibited by the failure of reviews to meet the needs of decision-makers, and the limitations of the traditional avenues by which reviews are disseminated.2 Encouraging the utilization of reviews by the public health workforce is a complex challenge. An unsupportive culture within the workforce, a lack of experience in assessing evidence, the use of traditional academic language in communication and the lack of actionable messages can all act as barriers to successful knowledge translation.3 Improving communication through developing strategies that include summaries, podcasts, webinars and translational tools which target key decision-makers such as HealthEvidence.org should be considered by authors as promising actions to support the uptake of reviews into practice.4,5 Earlier work has also suggested that to better meet the research evidence needs of public health professionals, authors should aim to produce syntheses that are actionable, relevant and timely.2 Further, review authors must interact more with those who will, or could use their reviews; particularly when determining the scope and questions to which a review will be directed.2 Unfortunately, individual engagement, ideal for examining complex issues and addressing particular concerns, is often difficult, particularly when attempting to reach large groups where for efficiency purposes, the strategy tends to be didactic, ‘lecturing’ and therefore less likely to change attitudes or encourage higher order thinking.6 …

Assessment of the underreporting rate of death cause data in Shandong province using capture-mark-recapture method [应用捕获再捕获方法评估山东省死因登记漏报率水平]

To evaluate the underreporting rate of death -cause data in Shandong province during 2012 to 2013 by capture -mark -recapture method and to provide the base for health strategy. Methods All counties were divided into 5 stratifications according the death rates of 2012, and 14 counties were selected, then 3 towns or streets were selected in each country, 10 villages or neighborhood committees were selected in each town （street）. The death data collected from security bureau and civil affairs bureau were compared with the reporting death data from the National Cause of Death Surveillance, and the underreporting rate was calculated. Results In present study, 6 929 death cases were collected, it was found that 1 556 cases were underreported. The death cases estimated by CMR method were 6 227 cases （95%CI: 7 593-7 651）, and the average underreporting rate was 23.15%. There were significantly differences between different stratifications （P<0.01）. The underreporting rate in 0-4 years old group was 56.93%, the male underreporting rate was 22.31% and the female underreporting rate was 24.09%. There was no significant difference between male and female groups （P>0.05）. Conclusion There is an obvious underreport in the cause of death surveillance of Shandong province, and the underreporting rates are different among the 5 stratifications. The underreporting rate is higher in 0-4 years old group, and the investigation of the death cause surveillance for young residents is not perfect in some countries. The investigation quality of the death cause surveillance should be improved, increasing the integrity of the report data and adjusting the mortalities in different stratifications for obtaining a accurate mortality in Shandong province.