Definition Of Error Research Articles

Comparative Analysis of Psychometric Frameworks and Properties of Scores from Autogenerated Test Forms

AbstractThis paper explores the psychometric properties of scores derived from autogenerated test forms by introducing three conceptual frameworks: Alternate Test Forms, Randomly Parallel Forms, and Approximately Parallel Forms. Each framework provides a distinct perspective on score comparability, definitions of true score and standard error of measurement (SEM), and the necessity of equating. Through a simulation study, we illustrate how these frameworks compare in terms of true scores and SEMs, while also assessing the impact of equating on score comparability across varying levels of form variability. Ultimately, this study seeks to lay the groundwork for implementing scoring practices in large‐scale standardized assessments that use autogenerated forms.

On Covariance Switch-Based Invariant Extended Kalman Filter for Multi-Source Fusion

The good estimation consistency of Invariant Extended Kalman Filter (InEKF) is mainly attributed to its excellent trajectory-independent property. However, when the InEKF is applied to multi-source inertial-based navigation that coexists left-invariant and right-invariant observations, the observation matrix would be unavoidably trajectory-dependent and might lead to the degradation of estimation performance. This paper for the first time performs theoretical analyses on the covariance switch between the left error and the right error in multi-source inertial-based navigation. Furthermore, detailed realizations of the covariance switch-based InEKF are formulated in this work, which are lacked in previous works. Numerical simulations and experiments demonstrate that the covariance switch significantly reduces the attitude errors during the transient phase in contrast with the original method using the incompatible error definition.

A robust iterative algorithm for SINS/USBL integrated navigation based on dual hydrophone differential model

Aiming at the complex underwater environment which leads to large measurement errors and outliers in ultrashort baseline, a robust iterative Kalman filtering algorithm based on the differential model of dual hydrophones is proposed in this paper. Firstly, to achieve accurate navigation under large initial misalignment angles, the algorithm builds an inertial navigation error equation based on the right invariant error definition of Lie groups. Then a dual hydrophone differential model is proposed based on SINS/USBL tightly coupled. It successfully improves the accuracy of integrated navigation and significantly mitigating the issue of SINS/USBL positioning accuracy degradation caused by USBL slant distance noise that grows with distance. Finally, a robust iterative Kalman filter based on the dual hydrophone differential model is proposed to counter the threat to the vehicle’s safe operation and the accuracy loss caused by outliers. The algorithm’s superiority and effectiveness are verified through simulation and sea trial.

Minimum zone fitting and error evaluation for arc correction type convex contour of bearing roller

The minimum zone fitting and error evaluation for the arc-modified convex contour of a bearing roller have important applications for consistency detection and quantificational research of the elastohydrodynamic lubrication of a bearing roller. Based on the definition of the shape error and the geometric characteristics of the arc corrected roller convexity line of the bearing, a new fitting and error evaluation method for the total convexity contour of a bearing roller is presented. First, the reference cutoff points of the arc segment and straight line are determined based on the curvature difference of each measurement point. Then, the measuring points on both sides of the two reference cutoff points are selected as auxiliary cutoff points for arc fitting. The fitting error is obtained based on the minimum area method. Finally, a series of tangent equations are obtained based on the tangent principle between a line and two arcs, and the straightness error is determined by calculating the distances between the measuring points and the tangents. The example results show that an arc-modified convex contour can be fitted, and its global error can be evaluated effectively and precisely using the presented method. This study also provides a new idea for the minimum zone fitting of multi-segment curves along a plane.

Estimation of the error in determining the motion parameters of maneuvering objects

The study contains the definition of errors in estimating the motion parameters of maneuvering objects that arise due to the discrepancy between the real model and the model used to build the filter. In the real model, along with noise and stochastic uncertainties, non-stochastic uncertainties act. The solution to the problem of estimation errors is based on the use of convex polyhedra. The statement of the research problem is given. It is shown that since the observer uses the motion model and the measurement equation, the source of estimation errors is not only the above, but also the fact that along with the random component of the measurement noise, there is also a non-stochastic component that is not taken into account by the observer. At the same time, the statistical characteristics of the latter do not exist or are unknown. It is shown that the use of a filter, for example, Kalman, will lead to errors. The conditions that determine the average filtering error and the total standard error of the estimation are described. It is noted that the obtained calculation results allow us to estimate the maximum permissible values used in the design of the filter for the most unfavorable case of evaluation. The relationship between the filtration quality and the parameters of the effects is determined. Expressions are obtained regarding the filtration quality for the worst and the best for object maintenance. The asymptotic properties of filtering errors are considered. It is shown that the "convergence" of the filter means its final "memory", since errors at the next step do not depend on errors from all previous steps, but only on steps from a certain value. The conditions under which the potential accuracy of the filter is achieved are also determined. The solution of extreme problems is described. You can determine the maximum filtering quality by iterating over the values on a set of corner points or using extremum conditions. Numerical simulation of extreme values of filtering errors is given. The asymptotic properties of filtering errors are considered. It is shown that the "convergence" of the filter means its final "memory", since errors at the next step do not depend on errors from all previous steps, but only on steps from a certain value. The conditions under which the potential accuracy of the filter is achieved are also determined. The solution of extreme problems is described. You can determine the maximum filtering quality by iterating over the values on a set of corner points or using extremum conditions. Numerical simulation of extreme values of filtering errors is given. Expressions for the set of average values of filtering errors are found, asymptotic and extreme properties of errors and sets are considered. It is shown that the conducted analysis of the accuracy of the filtering algorithm is evaluative in nature and is designed for the worst case. If the accuracy is not satisfactory, it is necessary to either change the model or synthesize a minimax-stochastic filter.

Nurses' perspectives and experiences on medical errors: A qualitative study.

Medical errors are among the most important factors that threaten patient safety. Therefore, nurses' perspectives and experiences about medical errors are important for this manner. The aim of this study was to determine in depth the perspectives and experiences of nurses related to how they define medical error, as well as its causes, management and reporting. This descriptive, exploratory study involved a qualitative design. A total of 15 clinical nurses from eleven provinces were reached by snowball sampling method. In the study, nurses' perspectives on medical errors were obtained through semistructured in-depth online interviews conducted based on phenomenological methods. Descriptive analysis was used in the analysis of the data obtained from the interviews. The research was conducted following the COnsolidated criteria for REporting Qualitative checklist. The resulting 26 codes were categorized under seven themes: "Definition of medical error", "Experience of medical errors", "Frequency of medical errors", "Causes of medical errors", "Reporting of medical errors", "Medical error approach" and "Prevention of medical errors". The results show that it is still necessary to increase the awareness of nurses about medical errors and the importance of error reporting. In addition, it reveals the need for leadership to eliminate the negative approach to medical errors and shows that nurse managers should be empowered accordingly. It is the first step of quality and safe care to reveal nurses' perspectives on medical errors, their thoughts about medical errors and their experiences about errors in their institutions. In this study, nurses' knowledge, opinions and experiences regarding medical errors were revealed in this qualitative study. Therefore, this study offers important clues to nursing services, hospital managers and policy makers for clinical and institutional arrangements.

The Kinematic Models of the SINS and Its Errors on the SE(3) Group in the Earth-Centered Inertial Coordinate System.

In this paper, the kinematic models of the Strapdown Inertial Navigation System (SINS) and its errors on the SE(3) group in the Earth-Centered Inertial frame (ECI) are established. On the one hand, with the ECI frame being regarded as the reference, based on the joint representation of attitude and velocity on the SE(3) group, the dynamic of the local geographic coordinate system (n-frame) and the body coordinate system (b-frame) evolve on the differentiable manifold, respectively, and the high-order expansion of the Baker-Campbell-Haussdorff equation compensates for the non-commutative motion errors stimulated by strong maneuverability. On the other hand, the kinematics of the left- and right-invariant errors of the n-frame and the b-frame on the SE(3) group are separately derived, where the errors of the b-frame completely depend on inertial sensor errors, while the errors of the n-frame rely on position errors and velocity errors. In this way, the errors brought by the inconsistency of the reference coordinate system are tackled, and a novel attitude error definition is introduced to separate and decouple the factors affecting the dynamic of the n-frame errors and the b-frame errors for better attitude estimation. Through a turntable experiment and a car-mounted field experiment, the effectiveness of the proposed kinematic models in estimating attitude has been verified, with a remarkable improvement in yaw angle accuracy in the case of large initial misalignment angles, and the models developed have better robustness compared to the traditional SE(3) group-based model.

A novel identification method for all geometric errors of rotary axis based on boundaryless constraint optimization method

For the redundancy in definition of position independent geometric errors(PIGEs) and position dependent geometric errors(PDGEs), it is difficult to identify all geometric errors of rotational axis simultaneously. A novel identification method using boundaryless constraint optimization method(BCOM) is established to improve PIGEs and PDGEs identification accuracy of rotary axis. For PIGEs, the two different dimension errors are identified separately based on least square method through appropriate measurement direction by double ball bar(DBB), and thus decrease condition number of identification matrix. For PDGEs, the B-spline curve is applied to fit the geometric errors and the objective function has been established. Several measurement paths are conducted and geometric errors are figured out by iterations of objective function. Furthermore, setup errors of DBB are investigated and discussed based on the sensitivity analysis. Finally, Simulations and experiments are conducted and their results demonstrate the effectiveness of the proposed method.

An Improved Initial Alignment Method Based on SE2(3)/EKF for SINS/GNSS Integrated Navigation System with Large Misalignment Angles.

This paper proposes an improved initial alignment method for a strap-down inertial navigation system/global navigation satellite system (SINS/GNSS) integrated navigation system with large misalignment angles. Its methodology is based on the three-dimensional special Euclidean group and extended Kalman filter (SE2(3)/EKF) and aims to overcome the challenges of achieving fast alignment under large misalignment angles using traditional methods. To accurately characterize the state errors of attitude, velocity, and position, these elements are constructed as elements of a Lie group. The nonlinear error on the Lie group can then be well quantified. Additionally, a group vector mixed error model is developed, taking into account the zero bias errors of gyroscopes and accelerometers. Using this new error definition, a GNSS-assisted SINS dynamic initial alignment algorithm is derived, which is based on the invariance of velocity and position measurements. Simulation experiments demonstrate that the alignment method based on SE2(3)/EKF can achieve a higher accuracy in various scenarios with large misalignment angles, while the attitude error can be rapidly reduced to a lower level.

Examining Barriers and Perceptions in Reporting Medication Administration Errors among Nurses at the Tertiary Care Hospitals in Peshawar Pakistan

Medication administration is vital for patient safety, yet medication errors can lead to life-threatening situations and increased mortality rates. Nurses, being essential members of the healthcare team, are constantly present with patients and regularly tasked with drug administration, facing a significant burden of medication errors compared to other healthcare providers. Objectives: To explore the barriers and perceptions of nurses' regarding medication errors reporting in public sector tertiary care hospitals. Methods: A convenient sample of 209 staff nurses participated in this cross-sectional survey from June to October 2022. A three-part questionnaire was used to gather information on the general characteristics of nurses, the causes of medication errors, and the justifications for not reporting them. Results: The Pharmacy supplies inappropriate doses to this unit with a mean of (2.53 ± 1.28) and an insufficient number of staff nurses in each working shift (4.23 ± 0.76) were the two least and most significant contributing factors to medication errors. Additionally, the two most and least significant factors for not reporting medication errors were that nurses may be held accountable if the patient suffered harm (3.94 ± 1.16) and that nurses did not agree with the hospital's definition of a medication error (2.33 ± 1.26) on average. Conclusions: The main causes of drug mistakes and failure to reveal them were nursing and management issues. Moreover, attempt to establish a blame-free culture to motivate reporting errors.

Implementation of AI for forecasting of wind speed and solar irradiation using different Machine Learning techniques

High penetration of solar and wind power in the electricity system provides a number of challenges to the grid such as grid stability and security, system operation, and market economics. Ones of the considerable problems of solar and wind systems, they depend on the weather, as compared to the conventional generation. As we know, the balance in managing load and generated power in energy system is very import ant. If the power which is supplied from solar and wind perfectly predictable, the extra cost of operating power system with a large penetration of renewable energy will be reduced. Since, the accurate and reliable forecasting system for renewable sources represents an important topic as a major contribution for increasing non-programmable renewable on over the world. The target of this research is to describe the advanced hybrid evolutionary techniques of computational intelligence applied for PV as well as wind power forecast. The evaluation of this investigation is obtained by comparing different definitions of the forecasting error. Moreover, the meaning of NWP (numerical weather prediction) values based on meteorological information on solar and wind power forecasting at Indore has been highlighted in this research.

Online calibration method for SINS/LDV integrated navigation system based on left group error definition

The integration of strapdown inertial navigation system (SINS) and laser Doppler velocimeter (LDV) is a reliable technology for land vehicle positioning. To ensure the best positioning performance of the SINS/LDV integrated navigation system, it is necessary to calibrate it accurately. However, the accuracy of the error model of the traditional calibration method is seriously affected by the large misalignment angle, which in turn affects the accuracy and consistency of the filtering, and eventually leads to the decline of the calibration accuracy. Therefore, this paper introduces the Lie group theory for the first time into the calibration study of the SINS/LDV integrated navigation system. Based on the error state vector defined by the left group error definition in the Lie group, the three calibration models of the SINS/LDV integrated navigation system are derived in the Earth-centered Earth-fixed frame, using velocity, displacement increment, and dead reckoning (DR) position, which are the three common observation information. The most significant advantage of these calibration models is their ability to handle large initial misalignment angles. The calibration models proposed in this paper are comprehensively evaluated by two long-distance vehicle experiments. The test results show that under normal conditions (no large attitude misalignment angle and all sensors are working properly), the Lie group-based calibration methods have similar performance to the traditional calibration method, but they have significant advantages in the case of large initial attitude deviation. In addition, using displacement increment and DR position as observations improves calibration performance compared to velocity.

VEHICLE VOLUME FORECASTING SYSTEM ON TOLL ROADS USING DOUBLE MOVING AVERAGE AND DOUBLE EXPONENTIAL SMOOTHING METHODS

Forecasting or forecasting has been used as one of the considerations, especially in the field of business and economics. This is done so that company losses can be minimized and company profits can be maximized. Therefore we need a system that can make it easier to get accurate forecasting results. However, in real cases procurement of IT consultants requires quite expensive costs. So the research provides a solution to design a website-based vehicle volume forecasting system on toll roads conducted at PT. Jasamarga Pandaan Tol. This system is expected to facilitate the Traffic Collection team in projecting the volume of vehicles on toll roads in the future. The method used in forecasting vehicle volume is the Double Moving Average and Double Exponential Smoothing methods. The Double Moving Average method is a time series method where the results of this method are influenced by the order or time period. The Exponential Smoothing method is a time series method where the results of this method are influenced by the alpha parameter. The results of these two methods will be compared based on the accuracy of the data so that the user can easily see the results of forecasting vehicle volume in the future. Mean Absolute Percentage Error (MAPE) is the absolute (absolute) average percentage error. Definition of Mean Absolute Percentage Error is a statistical measurement of the accuracy of estimates (predictions) in forecasting methods. The results of the accuracy of applying the Double Moving Average method give an average MAPE value of 30,124% and the Double Exponential Smoothing method gives an average MAPE value of 5,368%.

Exploiting Equivariance in the Design of Tracking Controllers for Euler-Poincare Systems on Matrix Lie Groups

The trajectory tracking problem is a fundamental control task in the study of mechanical systems. Hamiltonian systems are posed on the cotangent bundle of configuration space of a mechanical system, however, symmetries for the full cotangent bundle are not commonly used in geometric control theory. In this paper, we propose a group structure on the cotangent bundle of a Lie group and leverage this to define momentum and configuration errors for trajectory tracking, drawing on recent work on equivariant observer design. We show that this error definition leads to error dynamics that are themselves “Euler-Poincare like” and use these to derive simple, almost global trajectory tracking control for fully-actuated Euler-Poincare systems on a Lie group state space.

Enhancing Patient Safety: A Cross-Sectional Study to Assess Medical Interns' Attitude and Knowledge About Medication Safety in Saudi Arabia.

Introduction and aim Medication errors (MEs) pose a severe threat in the medical field. Since such errors are preventable, it is paramount for all healthcare workers to be educated on the matter. This study aimed to assess medical interns' attitudes and knowledge of medication safety and errors. We also aimed to validate current university programs to educate students about medication safety and errors. Methods A cross-sectional study that utilized a self-administered online questionnaire comprised 31 questions. The questionnaire was distributed via social media networks, such as WhatsApp, Twitter, email, Instagram, and Snapchat among 100 medical, pharmacy, and nursing interns in Saudi Arabia. The study population included both Saudi and non-Saudi interns. Results The majority of participants, comprising 92% (n=92), indicated that they were familiar with the definition of medication errors (ME). Additionally, 85% (n=85) expressed their willingness to report instances of MEs when medications were not prescribed but required. Moreover, 90% (n=90) of the surveyed individuals expressed their willingness to report MEs in situations where patients did not receive medications as prescribed. In cases where patients experienced harm and required treatment due to an ME, 91% (n=91) of respondents committed to reporting such incidents. A total of 52 (52%) respondents stated that they would report MEs regardless of whether they reached/harmed the patient. A good ME knowledge level was observed in 48% of respondents. A higher likelihood of good ME knowledge was significantly associated with safety reporting system (SRS) awareness and reporting MEs regardless of whether they reached/harmed the patient (p<0.05). College, awareness/attitude, or other demographic factors were not significantly related to ME knowledge (p>0.05). Conclusion This study showed that although interns in the healthcare field do have some knowledge about MEs, there is still a significant need to improve their knowledge. This can be achieved through various ways, one of which is by implementing this topic into the university curricula.

An invariant error-based SINS/DVL/USBL tightly coupled integrated navigation algorithm and its robust state estimator

The existing strapdown inertial navigation system (SINS)/Doppler velocity log (DVL)/ultra-short baseline system (USBL) integrated navigation error models directly apply algebraic differences to define the vector error, which is not strictly accurate. Considering that the invariant error definitions derived from Lie group theory have been used in the navigation field to obtain more accurate linear error models, in this paper, a new SINS/DVL/USBL integrated navigation system is investigated based on the invariant error definition and tightly coupled structure. In order to suppress the effect of measurement outliers on navigation accuracy, a new statistical similarity measure (SSM)-based multiple adaptive outlier-robust state estimator (MAORSE) is proposed. It decomposes the noise covariance matrix into multiple sub-matrices. Through the estimation and adjustment of sub-matrices, the influence of abnormal observations on the filtering results is weakened while realizing the full utilization of normal observation information. The test results demonstrate the effectiveness and superiority of the proposed invariant error-based SINS/DVL/USBL tightly coupled integrated navigation algorithm and SSM-based MAORSE.

Original Research: Exploring Medication Safety Practices from the Nurse's Perspective.

Medication preparation and administration are complex tasks that nurses must perform daily within today's complicated health care environment. Despite more than two decades of efforts to reduce medication errors, it's well known that such errors remain prevalent. Obtaining insight from direct care nurses may clarify where opportunities for improvement exist and guide future efforts to do so. The study purpose was to explore direct care nurses' perspectives on and experiences with medication safety practices and errors. A qualitative descriptive study was conducted among direct care nurses employed across a large health care system. Data were collected using semistructured interview questions with participants in focus groups and one-on-one meetings and were analyzed using qualitative direct content analysis. A total of 21 direct care nurses participated. Four major themes emerged that impact the medication safety practices of and errors by nurses: the care environment, nurse competency, system influences, and the error paradigm. These themes were often interrelated. Most participants depicted chaotic environments, heavy nursing workloads, and distractions and interruptions as increasing the risk of medication errors. Many seemed unsure about what an error was or could be. The complexity of medication safety practices makes it difficult to implement improvement strategies. Understanding the perspectives and experiences of direct care nurses is imperative to implementing such strategies effectively. Based on the study findings, potential solutions should include actively addressing environmental barriers to safe medication practices, ensuring more robust medication management education and training (including guidance regarding the definition of medication errors and the importance of reporting), and revising policies and procedures with input from direct care nurses.

Factors associated with continuing education needs in medication administration among school nurses.

To investigate the continuing education requirements and factors influencing school nurses' needs in relation to medication administration on school campuses. A total of 391 school nurses working in K-12 schools in Taiwan were invited to participate in an online questionnaire survey. This cross-sectional study employed a probability proportionate to size technique along with a random sampling method. Data were collected from February to April 2023. School nurses reported a significant demand for continuing education and perceived moderate levels of stress and government support related to medication administration. Among the various dimensions, the highest demand was observed for 'definition of campus medication errors' and 'regulations for campus medical orders.' Moreover, the 'identifying drug interactions' and 'adverse drug effects and referrals' dimensions were identified as the most stressful aspects. Notably, perceived stress emerged as the sole predictive factor for continuing education demand, accounting for 16.1% of the variance. The study found that there was a significant demand for and moderate stress related to continuing education among school nurses. Therefore, it is crucial for the government and school nursing organizations to develop targeted programs focusing on medication administration. These initiatives should be designed to enhance nurses' capabilities and reduce their stress, thereby ensuring safe medication administration on campuses. Continuing education enables school nurses to acquire up-to-date knowledge and improve the workflow in their practice. This study highlights a strong need for education in medication administration with a focus on 'campus medication error definitions' and 'campus medical order regulations.' The government and relevant school nursing organizations should prioritize the development and implementation of continuing education programs to decrease the school nurses' stress related to medication administration. No patient or public contribution. This study adhered to the relevant cross-sectional EQUATOR STROBE guidelines.

Medication error reporting attitudes and practices in a regional Australian hospital: a qualitative study

AbstractBackgroundMedication errors are events that may cause or lead to inappropriate medication use or patient harm. Australians living outside metropolitan areas have poorer health outcomes than those living in urban areas. Medication error reporting (MER) practices vary due to the attitude of healthcare professionals (HCPs). MER can improve patient safety in community and hospital settings.AimTo explore HCPs' attitudes, practices, and recommendations towards MER in a regional hospital setting in Australia.MethodSemistructured interviews were employed to identify the attitudes, practices, and recommendations of HCPs for the best utilisation of medication error reports. The study recruited HCPs (nurses, pharmacists, and doctors) working in all clinical areas from November 2021–February 2022. Interviews were recorded and transcribed via thematic analysis. Ethics approval was obtained from the Goulburn Valley Health (GVH) Human Research Ethics Committee (Reference no: GVH 35/21). Informed consent was obtained from participants via an information sheet and completion of a written consent form.ResultsInterviews with twelve HCPs elucidated four themes: barriers and enablers to reporting, and perceived benefits and recommendations for medication error reports. There was good understanding among regional HCPs about the benefits of MER. Attitudes and practices varied, with nurses reporting more medication errors than doctors, and pharmacists being concerned about the impact of reporting on interprofessional relations. Their recommendations involved standardising medication error definition and improving electronic system education.ConclusionDespite HCPs' understanding of the role of MER, their practices varied. We recommend improved protected time for learning, training with the incident reporting software, education about medication errors, and formalisation of test feedback to clinicians. The implementation of workplace cultural practice changes to improve organisational systems and enhance error reporting without fear of repercussions, and the adoption of additional solutions such as electronic prescribing are also encouraged.

What is a standard error? (And how should we compute it?)

I review the definition of a standard error from a frequentist perspective, including both exact analysis and asymptotic analysis. Using the linear model for illustration, I discuss the model-based, design-based, and sampling-based approaches to uncertainty in obtaining standard errors. The model-based approach is widely applicable and produces reasonable measures of estimator precision in many settings. In some situations, particularly in the context of clustering, the model-based approach can suffer from ambiguity, and can lead to standard errors that are systematically biased. A combination of the design-based and sampling-based approaches requires the researcher to think about the variation in key explanatory variables when computing standard errors, and it can even apply to cases where the entire population is observed.