Look-alike, sound-alike medication errors: A novel case concerning a Slow-Na, Slow-K prescribing error

A 59-year-old man was mistakenly prescribed Slow-Na instead of Slow-K due to incorrect selection from a drop-down list in the prescribing software. This error was identified by a pharmacist during a home medicine review (HMR) before the patient began taking the supplement. The reported error emphasizes the need for vigilance due to the emergence of novel look-alike, sound-alike (LASA) drug pairings. This case highlights the important role of pharmacists in medication safety.

R-parameter: A local truncation error based adaptive framework for finite volume compressible flow solvers

A residual-based strategy to estimate the local truncation error in a finite volume framework for steady compressible flows is proposed. This estimator, referred to as the -parameter, is derived from the imbalance arising from the use of an exact operator on the numerical solution for conservation laws. The behaviour of the residual estimator for linear and non-linear hyperbolic problems is systematically analysed. The relationship of the residual to the global error is also studied. The -parameter is used to derive a target length scale and consequently devise a suitable criterion for refinement/derefinement. This strategy, devoid of any user-defined parameters, is validated using two standard test cases involving smooth flows. A hybrid adaptive strategy based on both the error indicators and the -parameter, for flows involving shocks is also developed. Numerical studies on several compressible flow cases show that the adaptive algorithm performs excellently well in both two and three dimensions.

Error correction in nonbinary words

A simple error detecting and correcting procedure is described for nonbinary symbol words; here, the error position is located using the Hamming method and the correct symbol is substituted using a modulo-check procedure.

Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Human error risk management methodology for rail crack incidents

The paper presents an innovative approach to modelling the causal relationships of human errors in rail crack incidents (RCI) from a managerial perspective. A Bayesian belief network is developed to model RCI by considering the human errors of designers, manufactures, operators and maintainers (DMOM) and the causal relationships involved. A set of dependent variables whose combinations express the relevant functions performed by each DMOM participant is used to model the causal relationships. A total of 14 RCI on Hong Kong’s mass transit railway (MTR) from 2008 to 2011 are used to illustrate the application of the model. Bayesian inference is used to conduct an importance analysis to assess the impact of the participants’ errors. Sensitivity analysis is then employed to gauge the effect the increased probability of occurrence of human errors on RCI. Finally, strategies for human error identification and mitigation of RCI are proposed. The identification of ability of maintainer in the case study as the most important factor influencing the probability of RCI implies the priority need to strengthen the maintenance management of the MTR system and that improving the inspection ability of the maintainer is likely to be an effective strategy for RCI risk mitigation.

Preoperative visual acuity of cataract patients. Repeatability of visual acuity and refractive error measurements in clinical settings

Visual acuities at the time of referral and on the day before surgery were compared in 124 patients operated on for cataract in Vaasa Central Hospital, Finland. Preoperative visual acuity and the occurrence of ocular and general disease were compared in samples of consecutive cataract extractions performed in 1982, 1985, 1990, 1995 and 2000 in two hospitals in the Vaasa region in Finland. The repeatability and standard deviation of random measurement error in visual acuity and refractive error determination in a clinical environment in cataractous, pseudophakic and healthy eyes were estimated by re-examining visual acuity and refractive error of patients referred to cataract surgery or consultation by ophthalmic professionals. Altogether 99 eyes of 99 persons (41 cataractous, 36 pseudophakic and 22 healthy eyes) with a visual acuity range of Snellen 0.3 to 1.3 (0.52 to -0.11 logMAR) were examined. During an average waiting time of 13 months, visual acuity in the study eye decreased from 0.68 logMAR to 0.96 logMAR (from 0.2 to 0.1 in Snellen decimal values). The average decrease in vision was 0.27 logMAR per year. In the fastest quartile, visual acuity change per year was 0.75 logMAR, and in the second fastest 0.29 logMAR, the third and fourth quartiles were virtually unaffected. From 1982 to 2000, the incidence of cataract surgery increased from 1.0 to 7.2 operations per 1000 inhabitants per year in the Vaasa region. The average preoperative visual acuity in the operated eye increased by 0.85 logMAR (in decimal values from 0.03to 0.2) and in the better eye 0.27 logMAR (in decimal values from 0.23 to 0.43) over this period. The proportion of patients profoundly visually handicapped (VA in the better eye <0.1) before the operation fell from 15% to 4%, and that of patients less profoundly visually handicapped (VA in the better eye 0.1 to <0.3) from 47% to 15%. The repeatability visual acuity measurement estimated as a coefficient of repeatability for all 99 eyes was ±0.18 logMAR, and the standard deviation of measurement error was 0.06 logMAR. Eyes with the lowest visual acuity (0.3-0.45) had the largest variability, the coefficient of repeatability values being ±0.24 logMAR and eyes with a visual acuity of 0.7 or better had the smallest, ±0.12 logMAR. The repeatability of refractive error measurement was studied in the same patient material as the repeatability of visual acuity. Differences between measurements 1 and 2 were calculated as three-dimensional vector values and spherical equivalents and expressed by coefficients of repeatability. Coefficients of repeatability for all eyes for vertical, torsional and horisontal vectors were ±0.74D, ±0.34D and ±0.93D, respectively, and for spherical equivalent for all eyes ±0.74D. Eyes with lower visual acuity (0.3-0.45) had larger variability in vector and spherical equivalent values (±1.14), but the difference between visual acuity groups was not statistically significant. The difference in the mean defocus equivalent between measurements 1 and 2 was, however, significantly greater in the lower visual acuity group. If a change of ±0.5D (measured in defocus equivalents) is accepted as a basis for change of spectacles for eyes with good vision, the basis for eyes in the visual acuity range of 0.3 - 0.65 would be ±1D. Differences in repeated visual acuity measurements are partly explained by errors in refractive error measurements.

False Error Study of On-line Soft Error Detection Mechanisms

With technology scaling, vulnerability to soft errors in random logic is increasing. There is a need for on-line error detection and protection for logic gates even at sea level. The error checker is the key element for an on-line detection mechanism. We compare three different checkers for error detection from the point of view of area, power and false error detection rates. We find that the double sampling checker (used in Razor), is the simplest and most area and power efficient, but suffers from very high false detection rates of 1.15 times the actual error rates. We also find that the alternate approaches of triple sampling and integrate and sample method (I&S) can be designed to have zero false detection rates, but at an increased area, power and implementation complexity. The triple sampling method has about 1.74 times the area and twice the power as compared to the Double Sampling method and also needs a complex clock generation scheme. The I&S method needs about 16% more power with 0.58 times the area as double sampling, but comes with more stringent implementation constraints as it requires detection of small voltage swings.

Improved switching frequency variation control of hysteresis controlled voltage source inverter-fed IM drives using current error space vector

A constant switching frequency current error space vector-based hysteresis controller for two-level voltage source inverter-fed induction motor (IM) drives is proposed in this study. The proposed controller is capable of driving the IM in the entire speed range extending to the six-step mode. The proposed controller uses the parabolic boundary, reported earlier, for vector selection in a sector, but uses simple, fast and self-adaptive sector identification logic for sector change detection in the entire modulation range. This new scheme detects the sector change using the change in direction of current error along the axes jA, jB and jC. Most of the previous schemes use an outer boundary for sector change detection. So the current error goes outside the boundary six times during sector change, in one cycle,, introducing additional fifth and seventh harmonic components in phase current. This may cause sixth harmonic torque pulsations in the motor and spread in the harmonic spectrum of phase voltage. The proposed new scheme detects the sector change fast and accurately eliminating the chance of introducing additional fifth and seventh harmonic components in phase current and provides harmonic spectrum of phase voltage, which exactly matches with that of constant switching frequency voltage-controlled space vector pulse width modulation (VC-SVPWM)-based two-level inverter-fed drives.

Error Checking Digit for Nonconventional Chemical Codes

In handling large volumes of data such as chemical notations, serial numbers for books, etc., it is always advisable to provide checking methods which would indicate the presence of errors. The entire new discipline of coding theory is devoted to the study of the construction of codes which provide such error-detecting and correcting means.l Although these codes are very powerful, they are highly sophisticated from the point of view of practical implementation

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.

Switching frequency variation control in hysteresis PWM controller for IM drives using variable parabolic bands for current error space phasor

Variation of switching frequency over the entire operating speed range of an induction motor (M drive is the major problem associated with conventional two-level three-phase hysteresis controller as well as the space phasor based PWM hysteresis controller. This paper describes a simple hysteresis current controller for controlling the switching frequency variation in the two-level PWM inverter fed IM drives for various operating speeds. A novel concept of continuously variable hysteresis boundary of current error space phasor with the varying speed of the IM drive is proposed in the present work. The variable parabolic boundary for the current error space phasor is suggested for the first time in this paper for getting the switching frequency pattern with the hysteresis controller, similar to that of the constant switching frequency voltage-controlled space vector PWM (VC-SVPWM) based inverter fed IM drive. A generalized algorithm is also developed to determine parabolic boundary for controlling the switching frequency variation, for any IM load. Only the adjacent inverter voltage vectors forming a triangular sector, in which tip of the machine voltage vector ties, are switched to keep current error space vector within the parabolic boundary. The controller uses a self-adaptive sector identification logic, which provides smooth transition between the sectors and is capable of taldng the inverter up to six-step mode of operation, if demanded by drive system. The proposed scheme is simulated and experimentally verified on a 3.7 kW IM drive.

Generation of parabolic trajectories for current error space phasor similar to an SVPWM controller for control of switching frequency variation in current hysteresis PWM controlled IM drives

Switching frequency variation over a fundamental period is a major problem associated with hysteresis controller based VSI fed IM drives. This paper describes a novel concept of generating parabolic trajectories for current error space phasor for controlling the switching frequency variation in the hysteresis controller based two-level inverter fed IM drives. A generalized algorithm is developed to determine unique set of parabolic trajectories for different speeds of operation for any given IM load. Proposed hysteresis controller provides the switching frequency spectrum of inverter output voltage, similar to that of the constant switching frequency VC-SVPWM based IM drive. The scheme is extensively simulated and experimentally verified on a 3.7 kW IM drive for steady state and transient performance.

Bootstrapping the Error Correction Model Cointegration Test

This paper is concerned with using the bootstrap to obtain improved critical values for the error correction model (ECM) cointegration test in dynamic models. In the paper we investigate the effects of dynamic specification on the size and power of the ECM cointegration test with bootstrap critical values. The results from a Monte Carlo study show that the size of the bootstrap ECM cointegration test is close to the nominal significance level. We find that overspecification of the lag length results in a loss of power. Underspecification of the lag length results in size distortion. The performance of the bootstrap ECM cointegration test deteriorates if the correct lag length is not used in the ECM. The bootstrap ECM cointegration test is therefore not robust to model misspecification.