Development of hospital disaster resilience : conceptual framework and potential measurement

Objective Despite ‘hospital resilience’ gaining prominence in recent years, it remains poorly defined. This article aims to define hospital resilience, build a preliminary conceptual framework and highlight possible approaches to measurement. Methods Searches were conducted of the commonly used health databases to identify relevant literature and reports. Search terms included ‘resilience and framework or model’ or ‘evaluation or assess or measure and hospital and disaster or emergency or mass casualty and resilience or capacity or preparedness or response or safety’. Articles were retrieved that focussed on disaster resilience frameworks and the evaluation of various hospital capacities. Result A total of 1480 potentially eligible publications were retrieved initially but the final analysis was conducted on 47 articles, which appeared to contribute to the study objectives. Four disaster resilience frameworks and 11 evaluation instruments of hospital disaster capacity were included. Discussion and conclusion Hospital resilience is a comprehensive concept derived from existing disaster resilience frameworks. It has four key domains: hospital safety; disaster preparedness and resources; continuity of essential medical services; recovery and adaptation. These domains were categorised according to four criteria, namely, robustness, redundancy, resourcefulness and rapidity. A conceptual understanding of hospital resilience is essential for an intellectual basis for an integrated approach to system development. This article (1) defines hospital resilience; (2) constructs conceptual framework (including key domains); (3) proposes comprehensive measures for possible inclusion in an evaluation instrument, and; (4) develops a matrix of critical issues to enhance hospital resilience to cope with future disasters.

A reference station-based GNSS computing mode to support unified precise point positioning and real-time kinematic services

Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.

University Students Depression Inventory : measurement model and psychometric properties

Depression is a serious condition that impacts the academic success and emotional well-being of the university students globally. Keeping in view the debilitating nature of this condition, the present study examined the stability of the factor structure and psychometric properties of the University Student Depression Inventory (USDI; Khawaja and Bryden, 2006). There is a need to translate and validate the scale for Persian speaking students, who live in Iran, its neighboring countries and in many other Western countries. The scale was translated into the Persian language and was used as part of a battery consisting of the scales measuring suicide, depression, stress, happiness and academic achievement. The battery was administered to 359 undergraduate students, and an additional 150 students who had been referred to the mental health center of the University of Tehran as clinical sample. Confirmatory factor analysis upheld the original three-factor structure. The results exhibited internal consistency, test-retest reliability, convergent, and divergent validity, and discriminant validity. There were gender differences and male had higher mean scores on Lethargy, Cognitive\emotion, and Academic motivation subscales than female students. Findings supported the Persian version of the USDI for cross-cultural use as a valid and reliable measure in the diagnosis of depression.

Measurement of the first neutron diffraction peak of D2O flowing in a 2 mm diameter aluminium tube as a function of temperature

A pilot experiment was performed using the WOMBAT powder diffraction instrument at ANSTO in which the first neutron diffraction peak (Q0) was measured for D2O flowing in a 2 mm internal diameter aluminium tube. Measurements of Q0 were made at -9, 4.3, 6.9, 12, 18.2 and 21.5 °C. The D2O was circulated using a siphon with water in the lower reservoir returned to the upper reservoir using a small pump. This enabled stable flow to be maintained for several hours. For example, if the pump flow increased slightly, the upper reservoir level rose, increasing the siphon flow until it matched the return flow. A neutron wavelength of 2.4 Å was used and data integrated over 60 minutes for each temperature. A jet of nitrogen from a liquid N2 Dewar was directed over the aluminium tube to vary water temperature. After collection of the data, the d spacing of the aluminium peaks was used to calculate the temperature of the aluminium within the neutron beam and therefore was considered to be an accurate measure of water temperature within the beam. Sigmaplot version 12.3 was used to fit a Weibull five parameter peak fit to the first neutron diffraction peak. The values of Q0 obtained in this experiment showed an increase with temperature consistent with data in the literature [1] but were consistently higher than published values for bulk D20. For example at 21.5 °C we obtained a value of 2.008 Å-1 for Q0 compared to a literature value of 1.988 Å-1 for bulk D2O at 20 °C, a difference of 1%. Further experiments are required to see if this difference is real or artifactual.

Accuracy of mothers’ perceptions of their child’s weight status

The study examined the accuracy of maternal perceived child weight. Urban-affluent mothers with 111 children aged 2-5 years were recruited. Nearly a quarter of mothers overestimated their underweight child as healthyweight and all overweight/obese children were perceived as healthyweight. Mothers therefore were unable to recognize their child’s true weight status.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

Predicting the likelihood of QA failure using treatment plan accuracy metrics

This study used automated data processing techniques to calculate a set of novel treatment plan accuracy metrics, and investigate their usefulness as predictors of quality assurance (QA) success and failure. 151 beams from 23 prostate and cranial IMRT treatment plans were used in this study. These plans had been evaluated before treatment using measurements with a diode array system. The TADA software suite was adapted to allow automatic batch calculation of several proposed plan accuracy metrics, including mean field area, small-aperture, off-axis and closed-leaf factors. All of these results were compared the gamma pass rates from the QA measurements and correlations were investigated. The mean field area factor provided a threshold field size (5 cm2, equivalent to a 2.2 x 2.2 cm2 square field), below which all beams failed the QA tests. The small aperture score provided a useful predictor of plan failure, when averaged over all beams, despite being weakly correlated with gamma pass rates for individual beams. By contrast, the closed leaf and off-axis factors provided information about the geometric arrangement of the beam segments but were not useful for distinguishing between plans that passed and failed QA. This study has provided some simple tests for plan accuracy, which may help minimise time spent on QA assessments of treatments that are unlikely to pass.

The impact of OCR accuracy on automated cancer classification of pathology reports

Objective To evaluate the effects of Optical Character Recognition (OCR) on the automatic cancer classification of pathology reports. Method Scanned images of pathology reports were converted to electronic free-text using a commercial OCR system. A state-of-the-art cancer classification system, the Medical Text Extraction (MEDTEX) system, was used to automatically classify the OCR reports. Classifications produced by MEDTEX on the OCR versions of the reports were compared with the classification from a human amended version of the OCR reports. Results The employed OCR system was found to recognise scanned pathology reports with up to 99.12% character accuracy and up to 98.95% word accuracy. Errors in the OCR processing were found to minimally impact on the automatic classification of scanned pathology reports into notifiable groups. However, the impact of OCR errors is not negligible when considering the extraction of cancer notification items, such as primary site, histological type, etc. Conclusions The automatic cancer classification system used in this work, MEDTEX, has proven to be robust to errors produced by the acquisition of freetext pathology reports from scanned images through OCR software. However, issues emerge when considering the extraction of cancer notification items.

Evaluation and social impact measurement amongst small to medium social enterprises : process, purpose and value

In recent years, the imperative to communicate organisational impacts to a variety of stakeholders has gained increasing importance within all sectors. Despite growing external demands for evaluation and social impact measurement, there has been limited critically informed analysis about the presumed importance of these activities to organisational success and the practical challenges faced by organisations in undertaking such assessment. In this paper, we present the findings from an action research study of five Australian small to medium social enterprises’ practices and use of evaluation and social impact analysis. Our findings have implications for social enterprise operators, policy makers and social investors regarding when, why and at what level these activities contribute to organisational performance and the fulfilment of mission.

An efficient and effective localization method for networked disjoint top-view cameras

Disjoint top-view networked cameras are among the most commonly utilized networks in many applications. One of the open questions for these cameras' study is the computation of extrinsic parameters (positions and orientations), named extrinsic calibration or localization of cameras. Current approaches either rely on strict assumptions of the object motion for accurate results or fail to provide results of high accuracy without the requirement of the object motion. To address these shortcomings, we present a location-constrained maximum a posteriori (LMAP) approach by applying known locations in the surveillance area, some of which would be passed by the object opportunistically. The LMAP approach formulates the problem as a joint inference of the extrinsic parameters and object trajectory based on the cameras' observations and the known locations. In addition, a new task-oriented evaluation metric, named MABR (the Maximum value of All image points' Back-projected localization errors' L2 norms Relative to the area of field of view), is presented to assess the quality of the calibration results in an indoor object tracking context. Finally, results herein demonstrate the superior performance of the proposed method over the state-of-the-art algorithm based on the presented MABR and classical evaluation metric in simulations and real experiments.

Process compliance measurement based on behavioural profiles

Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. On the other hand, the metrics to quantify process compliance have only been defined recently. A major criticism points to the fact that existing measures appear to be unintuitive. In this paper, we trace back this problem to a more foundational question: which notion of behavioural equivalence is appropriate for discussing compliance? We present a quantification approach based on behavioural profiles, which is a process abstraction mechanism. Behavioural profiles can be regarded as weaker than existing equivalence notions like trace equivalence, and they can be calculated efficiently. As a validation, we present a respective implementation that measures compliance of logs against a normative process model. This implementation is being evaluated in a case study with an international service provider.

Simultaneous magnetic resonance imaging and consolidation measurement of articular cartilage

Magnetic resonance imaging (MRI) offers the opportunity to study biological tissues and processes in a non-disruptive manner. The technique shows promise for the study of the load-bearing performance (consolidation) of articular cartilage and changes in articular cartilage accompanying osteoarthritis. Consolidation of articular cartilage involves the recording of two transient characteristics: the change over time of strain and the hydrostatic excess pore pressure (HEPP). MRI study of cartilage consolidation under mechanical load is limited by difficulties in measuring the HEPP in the presence of the strong magnetic fields associated with the MRI technique. Here we describe the use of MRI to image and characterize bovine articular cartilage deforming under load in an MRI compatible consolidometer while monitoring pressure with a Fabry-Perot interferometer-based fiber-optic pressure transducer.