The effect of time of day on injury patterns amongst adolescents in Australia

Labour force participation of adolescents in Australia is growing at an unprecedented rate. This increased participation is coupled with a growing realisation of the vulnerability of adolescents in the labour market in terms of occupational injury. Despite recent evidence that time of day may be an important determinant of adolescent injuries, the impact of non-standard and night work on adolescent injury rates has received scant attention to date. The current study addresses this shortcoming by examining injury patterns of 3201 working adolescents in Queensland. Results revealed that female adolescents are 2.5 times more likely to sustain an injury on day shift and 4.71 times more likely to sustain an injury on night shift than their adult counterparts when total work hours are taken into consideration. Similar results were found for male adolescents with an injury to work hours ratio of 2.19 on day shift and 3.05 on night shift. These findings point to the value of considering the temporal pattern of adolescent work in future research aimed at minimising injuries at work and improving the work experience of tomorrow's workforce.     

Subjects presented at ASHP Midyear Clinical Meetings, 1967-90

The subject matter and trends of presentations made at ASHP Midyear Clinical Meetings (MCMs) were studied. A computerized database of information from MCM and Annual Meeting (AM) program and abstract books was created. The data were analyzed to determine the distribution of MCM presentations by subject and by author for the period 1967 to 1990, determine if there were differences in subjects covered between MCMs and AMs, explore the proposition that there has been duplication of material in MCM presentations, and evaluate the frequency with which MCM presentations have been published in ASHP journals. The total number of presentations made at MCMs from 1967 through 1990 was 8180, while the total for the AMs was 1547 for the two periods (1962-71 and 1985-90) studied. The most common keywords in titles were "pharmacy," "drug," "patient," "hospital," and "service." All International Pharmaceutical Abstracts subject categories and two other categories were represented; presentations in the institutional pharmacy practice category were the most frequent, while pharmacognosy-related presentations were least frequent. The overwhelming number of authors made only one presentation and were listed as the first author. The subjects of presentations were similar between AMs and MCMs. A tendency toward duplication of material was found. Of the 8180 MCM presentations, at least 1005 were published in an ASHP journal. Between 1967 and 1990, presentations at MCMs covered a wide range of subjects but were sometimes duplicative or not on the cutting edge.     

Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

In this article, energy efficient ensemble clustering method (EECM) with black widow optimization (EECM-BWO) algorithm is proposed for effective data transmission with the help of real time flood disaster monitoring wireless sensor network (WSN). Initially, unified scalable ensemble clustering algorithm based on ensemble generation and consensus function is proposed for selecting the optimal routing path among the node using BWO algorithm. Then, biologically inspired routing black widow spiders optimization algorithm is proposed to trade off the nodes energy level, self-organization, and self-configuration in the WSN. The simulation is performed using NS2 simulator for validating the performance of the proposed EECM-BWO method. Here, in node, low delay achieves 24.07%, 72.58%, 51.36%, 81.75%, 77.74%, high packet delivery ratio achieves 70.83%, 53.93%, 90.23%, 43.58%, 24.58%, low packet drop attains 77.93%, 72.76%, 61.56%, 51.87%, 34.35%, low energy consumption attains 75.9%, 52.94%, 65.81%, 58%, 41.2% compared with existing energy-efficient clustering approach consolidated game theory as well as dual-cluster-head mode for WSNs energy-aware clustering by cuckoo optimization approach (EECM-COA), energy-aware clustering-based routing using multi-path reliable transmission with routing and control board (EECM-RCB-MRT), adaptive repair algorithm with temporally ordered routing algorithms for flood control strategy (EECM-AR-TORA-FCS), passive multi-hop clustering algorithm (EECM-PMC), dynamic source routing protocol based on genetic algorithm-bacterial foraging optimization (DSR-GA-BFO).     

Randomized priority algorithms

Borodin, Nielsen and Rackoff [13] introduced the class of priority algorithms as a framework for modeling deterministic greedy-like algorithms. In this paper we address the effect of randomization in greedy-like algorithms. More specifically, we consider approximation ratios within the context of randomized priority algorithms. As case studies, we prove inapproximation results for two well-studied optimization problems, namely facility location and makespan scheduling.     

Elicitator: An expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modelling, assessing detectability or eradication, ecological condition assessments, risk analysis and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.     

An application of the technology acceptance model to the level of Internet usage by older adults

In this cross-sectional study, the principles of a technology acceptance model were used to identify variables related to the level of Internet usage by older adults. Community-dwelling older adults aged 60–88 years completed a postal questionnaire survey that elicited responses on the use of the Internet. Out of a sample of 592 older adults (236 males and 356 females), 50.7% used the Internet. A multiple linear regression analysis was carried out on the Internet users sample using the self-reported number of hours of Internet usage per week as the dependent variable. The results indicated that attitude toward using the Internet and good health status were statistically significant predictors of the level of Internet usage. A second multiple regression analysis using Internet activity as the dependent variable showed that attitude, usefulness, good health, and gender (males) were significant predictor variables.     

Benchmarking Image Segmentation Algorithms

We present a thorough quantitative evaluation of four image segmentation algorithms on images from the Berkeley Segmentation Database. The algorithms are evaluated using an efficient algorithm for computing precision and recall with regard to human ground-truth boundaries. We test each segmentation method over a representative set of input parameters, and present tuning curves that fully characterize algorithm performance over the complete image database. We complement the evaluation on the BSD with segmentation results on synthetic images. The results reported here provide a useful benchmark for current and future research efforts in image segmentation.     

The interaction between skill, postures, forces and back pain in wool handling

Wool handling is an important rural occupation where workers process 200 or more fleeces daily, separating them into various quality components. Loads and postures they experience carry substantial risk of low back pain (LBP). Although a formal skill training structure exists, interaction with loads and LBP is unknown. We examined whether skill and LBP influenced trunk postures and loads of 60 wool handlers representing 3 skill levels. LBP prevalence ranged from 20% for junior (lowest skill) to 45% for open class (highest skill) wool handlers. Open class wool handlers demonstrated increased lateral bend and more axially twisted postures, generating greater medio-lateral shear forces and lateral bend and axial twist moments. LBP was associated with open class wool handlers spending more time in severe axially twisted postures. These findings suggest that skill-based training needs to be reviewed to reduce the quantity of axially twisted posture which may help reduce the prevalence of LBP in this workforce.     

Building language resources for a Multi-Engine English-Filipino machine translation system

In this paper, we present the building of various language resources for a multi-engine bi-directional English-Filipino Machine Translation (MT) system. Since linguistics information on Philippine languages are available, but as of yet, the focus has been on theoretical linguistics and little is done on the computational aspects of these languages, attempts are reported here on the manual construction of these language resources such as the grammar, lexicon, morphological information, and the corpora which were literally built from almost non-existent digital forms. Due to the inherent difficulties of manual construction, we also discuss our experiments on various technologies for automatic extraction of these resources to handle the intricacies of the Filipino language, designed with the intention of using them for the MT system. To implement the different MT engines and to ensure the improvement of translation quality, other language tools (such as the morphological analyzer and generator, and the part of speech tagger) were developed.     

Three-dimensional spinal motion and risk of low back injury during sheep shearing

Sheep shearers are known to work in sustained flexed postures and have a high prevalence of low back pain (LBP). As sustained posture and spinal movement asymmetry under substantial loads are known risk factors for back injury our aim was to describe the 3D spinal movement of shearers while working. We hypothesised that thoraco-lumbar and lumbo-sacral movement would be tri-axial, asymmetric, and task specific. Sufficient retro-reflective markers were placed on the trunk of 12 shearers to define thoraco-lumbar and lumbo-sacral 3D motion during three tasks. Thoraco-lumbar movement consistently involved flexion, left lateral flexion, and right rotation. Lumbo-sacral movement consistently involved right lateral flexion in flexion with minimal rotation. Shearers therefore work in sustained spinal flexion where concurrent, asymmetric spinal movements into both lateral flexion and rotation occur. These asymmetric movements combined with repetitive loading may be risk factors leading to the high incidence of LBP in this occupational group.