Sources Of Error Research Articles

Analisis Sumber Penyebab Kesalahan Berbahasa Pada Konten Youtube Nadia Omara Dalam Meningkatkan Keterampilan Berbicara

This research discusses the analysis of language errors based on their sources and causes. This research aims to determine the source and cause of language errors from Nadia Omara's YouTube content "Holy Tree KHW Part 203" and relate it to speaking skills. Using appropriate language can influence someone in improving their speaking skills. The method used is descriptive qualitative with data collection techniques using note-taking techniques. The results of this analysis show 3 sources and causes of language errors with several words.

Advances in Atom Interferometry and their Impacts on the Performance of Quantum Accelerometers On-board Future Satellite Gravity Missions

Recent advances in cold atom interferometry have cleared the path for space applications of quantum inertial sensors, whose level of stability is expected to increase dramatically with the longer interrogation times accessible in space. In this study, an in-orbit model is developed for a Mach–Zehnder-type cold-atom accelerometer. Performance tests are realized under different assumptions about the positioning and rotation compensation method, and the impact of various sources of errors on instrument stability is evaluated. Current and future advances for space-based atom interferometry are discussed, and their impact on the performance of quantum sensors on-board satellite gravity missions is investigated in three different scenarios: state-of-the-art scenario (expected to be ready to launch in 5 years), near-future (expected to be launched in the next 10 to 15 years) and far-future scenarios (expected for the next 20 to 25 years). Our results indicate that the highest sensitivity is achievable by positioning the electrostatic accelerometer at the center of mass of the satellite and the quantum accelerometer aside, on the cross-track axis of the satellite. We show that one can achieve a sensitivity level close to 5 × 10−10 m/s2/Hz with the current state-of-the-art technology. We also estimate that in the near and far-future, atom interferometry in space is expected to achieve sensitivity levels of 1 × 10−11 m/s2/Hz and 1 × 10−12 m/s2/Hz, respectively. A roadmap for improvements in atom interferometry is provided that would maximize the performance of future quantum accelerometers, considering their technical capabilities. Finally, the possibility and challenges of having ultra-sensitive atom interferometry in space for future space missions are discussed.

A Preliminary Scoping Review of the Impact of e-Prescribing on Pharmacists in Community Pharmacies.

This scoping review aims to map the available literature and provide an overview of the published articles discussing the impact of electronic prescribing on medication errors and pharmacy workflow. The literature search was conducted using PubMed®, Web of Science®, and the Cochrane Database of Systematic Reviews®, as well as grey literature reports, using the search terms and related components of "pharmacists", "electronic prescribing", "medication errors", and "efficiency". The search included all articles that were published from January 2011 to September 2023. Twenty-two relevant articles were identified and fully reviewed, ten of which were included in this review. Electronic prescribing (e-prescribing) provides a solution for some of the challenges that are associated with handwritten and paper prescriptions. However, the implementation of e-prescribing systems has been recognized as a source of new unforeseen medication errors in all the reviewed articles. Productivity in community pharmacies has been affected with receiving electronic prescriptions (e-prescriptions) and having to deal with the issues that arise from them. The pharmacists' interventions were not eliminated with e-prescriptions compared to other prescription formats. The most frequently reported reason for intervention was related to incomplete instructions in the field of directions of use. Other common challenges with e-prescriptions were related to missing information, quantity, inappropriate dose, dosage form, and drug. This review demonstrates the scarcity of research about the impact of electronic prescribing on medication error and efficiency in community pharmacies. In the literature, most of the studies had mainly focused on hospital pharmacies. The literature search demonstrated that there are still some barriers to overcome with e-prescribing systems and that medication errors were not fully eliminated with e-prescriptions. New errors have been identified with e-prescriptions, all of which caused delays in processing, which affected the productivity of the pharmacy staff, and could have negatively impacted patients' safety if not properly resolved. e-Prescribing solved some of the challenges associated with illegibility of handwritten prescriptions. However, more time is required to allow e-prescribing systems to mature. Further training for prescribers and pharmacists is also recommended before and after the implementation.

How to: correctly read scientific articles : Research design and methodology

Criteria for assessment of the significance of scientific articles are presented. The focus is on research design and methodology, illustrated by the classical study on prehospital volume treatment of severely injured individuals with penetrating torso injuries by Bickell etal. (1994). Awell-thought out research design is crucial for the success of ascientific study and is documented in astudy protocol beforehand. Ahypothesis is aprovisional explanation or prediction and must be testable, falsifiable, precise, and relevant. There are various types of randomization methods, with the randomized controlled trial being the gold standard for clinical interventional studies. When reading ascientific article it is important to verify whether the research design and setting align with the research question and whether potential sources of error have been considered and controlled. Critical scrutiny should also be applied to references, the funding and expertise of the researchers.

Modelling internal stem damage in savanna trees: Error in aboveground biomass with terrestrial laser scanning and allometry

Abstract Forests and woodlands are critical terrestrial carbon stores. Tree aboveground biomass (AGB) can be estimated using allometric models and terrestrial laser scanning (TLS). However, internal tree stem damage from biotic decay is an unresolved source of error for both TLS and allometries, with implications for accurate carbon assessment. We destructively harvested 63 TLS‐scanned trees in an Australian savanna, quantified internal damage in each tree by sampling cross sections at multiple heights, and modelled the effect of damage on AGB estimation for individual trees and total estimated biomass. We tested the performance of TLS AGB modelling against five allometries, applying both database and field‐measured wood specific gravity. For TLS‐modelled and allometric AGB estimates, we tested if tree size and level of internal stem damage contributed to AGB deviations. Approximately half of the trees in the study sustained 1–10% damage by volume, which was most extensive in the base and main trunk, decreasing into the crown. On average, damaged trees had 5% internal stem damage (by volume, SD = 6.65%), with some as high as 30%. We found TLS‐derived quantitative structural models (TLS‐QSMs) using field‐measured wood specific gravity to be most accurate in estimating total biomass (R2 = 0.99, +0.59% bias). TLS‐QSMs tended to overpredict AGB of large, damaged trees, and AGB estimates from allometric models were largely unaffected by internal damage. For individual trees, all methods were effective for predicting field‐measured AGB (R2 > 0.84) and several ASMs performed well (± ~10% bias). In the absence of local wood specific gravity calibration, a pantropical ASM was most accurate. For systems where internal stem damage is low (<10% of tree volume), TLS can be used to estimate AGB with low levels of error, however more damaged wooded ecosystems (>10%) are likely to produce inflated biomass estimates if TLS is used without calibration for damage. Internal stem damage should be quantified in ASMs and incorporated into TLS‐modelled AGB calibration to avoid biomass overestimation and maintain high standards of precision in forest carbon accounting.

Experimental methods in chemical engineering: Monte Carlo

AbstractMonte Carlo (MC) methods employ a statistical approach to evaluate complex mathematical models that lack analytical solutions and assess their uncertainties. To this end, techniques such as Markov chain Monte Carlo (MCMC), bootstrap, and sequential MC methods repeat the same operations over a specified range of conditions. Consequently, both the frequentist and Bayesian statistical approaches are computationally intensive, depending on the problem formulation. Improving sampling techniques and identifying sources of error reduce the computational demand but do not guarantee that the solution reaches the global optimum. Moreover, efficient algorithms and advances in hardware continue to decrease computation time. MC methods are applicable to a plethora of problems ranging from medicine to computational chemistry, economics, and industrial safety, making them integral to the ongoing industrial digitalization by evaluating the quality of applied models. In chemical engineering, MC simulations are used in four clusters of research: design, systems, and optimization; molecular simulation, including CO2 and carbon capture; adsorption and molecular dynamics; and thermodynamics. There is limited cross‐referencing between the design cluster and the other three, which presents an interesting area for future research. This mini‐review presents two applications within chemical engineering: emissions and energy forecasting.

Reference Electrode Types for Zero-Gap CO2 Electrolyzers: Benefits and Limitations.

Integrated reference electrodes allow to deconvolute voltage contributions of anode and cathode and contribute to a better understanding of CO2 electrolyzers. However, in zero-gap cell configurations, this integration can be challenging and obtaining error-free data with such a setup is a non-trivial task. This study compares five different methods to integrate a reference electrode into an alkaline zero-gap CO2 electrolysis cell. Sources of error and measures to circumvent them are investigated and finite-element simulation is used to gain a better understanding of observed effects. Placing a reference electrode into the inactive area of the cell is found to be a reliable method, as long as the placement of electrodes is sufficiently controlled. Sandwiching a wire quasi-reference electrode between two membranes is especially useful for electrochemical impedance spectroscopy; however, it can affect the overall cell performance. Contacting the catalyst layer from the backside with a salt-bridge is promising for localized measurements if sufficient reproducibility can be ensured.

SREDet: Semantic-Driven Rotational Feature Enhancement for Oriented Object Detection in Remote Sensing Images

Significant progress has been achieved in the field of oriented object detection (OOD) in recent years. Compared to natural images, objects in remote sensing images exhibit characteristics of dense arrangement and arbitrary orientation while also containing a large amount of background information. Feature extraction in OOD becomes more challenging due to the diversity of object orientations. In this paper, we propose a semantic-driven rotational feature enhancement method, termed SREDet, to fully leverage the joint semantic and spatial information of oriented objects in the remote sensing images. We first construct a multi-rotation feature pyramid network (MRFPN), which leverages a fusion of multi-angle and multiscale feature maps to enhance the capability to extract features from different orientations. Then, considering feature confusion and contamination caused by the dense arrangement of objects and background interference, we present a semantic-driven feature enhancement module (SFEM), which decouples features in the spatial domain to separately enhance the features of objects and weaken those of backgrounds. Furthermore, we introduce an error source evaluation metric for rotated object detection to further analyze detection errors and indicate the effectiveness of our method. Extensive experiments demonstrate that our SREDet method achieves superior performance on two commonly used remote sensing object detection datasets (i.e., DOTA and HRSC2016).

Strategies for Spoken Error Correction in English Classroom

In Middle school, spoken language is paid less attention to by the teacher, which causes many students cannot recognize whether they have made mistakes in pronunciation. It’s inevitable for students to have errors in speaking. However, the teacher should take proper measures to correct students’ errors and cannot ignore them based on teaching objectives and the severity of errors. This study takes the method of specific case analysis and error analysis. The paper introduces the types and source of errors, the principles of error correction and strategies for error correction in English class.

On the consideration of signal trapping for soot sizing by angular light scattering in laminar flames

Soot particles are known to be harmful to health and the environment, and reducing their production in industrial systems is a crucial task in the pursuit of green energy production. Characterization and accurate modeling of these particles are essential yet complex. In particular, information on aggregate sizing remains limited. Angular light scattering is an established in-situ method for precise, spatially resolved, non-intrusive characterization of soot aggregates. However, the associated post-processing is prone to various error sources. Specifically, signal trapping during light scattering is suspected to lead significant errors. Moreover, current techniques for reconstructing the line-of-sight integrated scattering signal (Abel inversion) are inherently noisy. This work addresses both issues by implementing a noise-free Abel inversion method based on piecewise spline functions. This method accounts for signal trapping and can be applied to any axisymmetric and spatially continuous flame. The correction for the signal trapping effect relies on extinction measurements from the line-of-sight attenuation (LOSA). The technique is tested on a canonical laminar diffusion ethylene flame at five different angles. The impact of this correction is evaluated on the equivalent monodisperse radius of gyration, denoted as Rg∗, and the forward scattering coefficient, represented as κvv(0∘). The results show that the calculation of Rg∗ is robust regarding signal trapping effect. However, correcting for this effect significantly increases κvv(0∘).

The Effects of Pointing Error Sources on Energy Delivery from Orbiting Solar Reflectors

Many proposals are being made for cleaner, more sustainable forms of energy production. Terrestrial solar photovoltaic farms (SPFs) could potentially deliver large quantities of energy to the grid, although these are limited to daytime use. The output from these SPFs could be enhanced, particularly around dawn and dusk, by the use of orbiting solar reflectors (OSRs) in near-polar orbit. These would reflect an image of the solar disk, or solar image (SI), onto the SPFs to augment their energy output. Pointing requirements are therefore to ensure that reflected sunlight is delivered to the terrestrial SPF, avoiding the losses incurred by an offset of the SI and the SPF itself. The SI would typically be of order 10 km for a reflector in a 1000 km orbit. Given the potentially large size of the reflectors, this presents a challenge for the attitude determination and control system (ADCS) to ensure that the maximum quantity of energy can be delivered to a SPF, typically requiring large control moment gyro actuators. In addition, there exist numerous sources of error in the ADCS which can cause further degradation in the quantity of energy delivered to the SPF. These errors can manifest in the resolution of the various sensors, flexible structural modes, manufacturing inaccuracies, and misalignments due to vibration during launch. This paper will investigate the effects of pointing error sources (PES) on the reflector ADCS and so on the quantity of energy delivered to the SPF. With the application of a PD controller with feedforward compensation, and the set of noise characteristics defined in this paper, numerical simulations will show the typical losses in energy delivered to SPFs of 0.015% when the model accounts for PES in onboard sensors, actuator uncertainty and flexible structural modes.

Evaluation of the Planetary Boundary Layer Height From ERA5 Reanalysis With MOSAiC Observations Over the Arctic Ocean

AbstractThe planetary boundary layer height (PBLH) is a crucial indicator reflecting the region of the atmosphere characterized by continuous turbulence. Here, we use radiosonde and surface meteorological observations (4–7 times per day, year‐round measurements) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to derive the PBLH (PBLHMOSAiC), and further evaluate the PBLH from the ERA5 reanalysis (PBLHERA5). Comparisons between PBLHMOSAiC and PBLHERA5 from different perspectives reveal that: (a) The overestimation of PBLHERA5 when the sea ice concentration is >90% is significant with the centered root mean squared error reaching up to 201 m; (b) The difference between the two products is notably pronounced in cold seasons, while it is comparatively diminished in warm seasons; (c) In neutral boundary layers, differences in PBLHERA5 are larger compared with stable and convective boundary layers. In addition, the analysis of error sources indicates that the bias of PBLHERA5 is sensitive to the bias of vertical thermal structure and wind speed profiles in ERA5 data sets in all conditions. Finally, we find a Random Forest model effectively reduces the bias of PBLHERA5 with the index of agreement reaching up to 0.71 in the test data set, while a multiple linear regression demonstrates comparable performance to the Random Forest model.

Towards high‐definition vector map construction based on multi‐sensor integration for intelligent vehicles: Systems and error quantification

AbstractA lightweight, high‐definition vector map (HDVM) enables fully autonomous vehicles. However, the generation of HDVM remains a challenging problem, especially in complex urban scenarios. Moreover, numerous factors in the urban environment can degrade the accuracy of HDVM, necessitating a reliable error quantification. To address these challenges, this paper presents an open‐source and generic HDVM generation pipeline that integrates the global navigation satellite system (GNSS), inertial navigation system (INS), light detection and ranging (LiDAR), and camera. The pipeline begins by extracting semantic information from raw images using the Swin Transformer. The absolute 3D information of semantic objects is then retrieved using depth from the 3D LiDAR, and pose estimation from GNSS/INS integrated navigation system. Vector information (VI), such as lane lines, is extracted from the semantic information to construct the HDVM. To assess the potential error of the HDVM, this paper systematically quantifies the impacts of two key error sources, segmentation and LiDAR‐camera extrinsic parameter error. An error propagation scheme is first formed to illustrate how these errors fundamentally influence the accuracy of the HDVM. The effectiveness of the proposed pipeline is demonstrated through our codeavailable at https://github.com/ebhrz/HDMap. The performance is verified using typical datasets, including indoor garages and complex urban scenarios.

Robust Quantum Gates against Correlated Noise in Integrated Quantum Chips.

As quantum circuits become more integrated and complex, additional error sources that were previously insignificant start to emerge. Consequently, the fidelity of quantum gates benchmarked under pristine conditions falls short of predicting their performance in realistic circuits. To overcome this problem, we must improve their robustness against pertinent error models besides isolated fidelity. Here, we report the experimental realization of robust quantum gates in superconducting quantum circuits based on a geometric framework for diagnosing and correcting various gate errors. Using quantum process tomography and randomized benchmarking, we demonstrate robust single-qubit gates against quasistatic noise and spatially correlated noise in a broad range of strengths, which are common sources of coherent errors in large-scale quantum circuits. We also apply our method to nonstatic noises and to realize robust two-qubit gates. Our Letter provides a versatile toolbox for achieving noise-resilient complex quantum circuits.

High-Rate and High-Fidelity Modular Interconnects between Neutral Atom Quantum Processors

Quantum links between physically separated modules are important for scaling many quantum computing technologies. The key metrics are the generation rate and fidelity of remote Bell pairs. In this work, we propose an experimental protocol for generating remote entanglement between neutral ytterbium atom qubits using an optical cavity. By loading a large number of atoms into a single cavity, and controlling their coupling using only local light shifts, we amortize the cost of transporting and initializing atoms over many entanglement attempts, maximizing the entanglement generation rate. A twisted ring cavity geometry suppresses many sources of error, allowing high-fidelity entanglement generation. We estimate a spin-photon entanglement rate of 5×105s−1, and a Bell pair rate approaching 105s−1, with an average fidelity near 0.999. Furthermore, we show that the photon detection times provide a significant amount of soft information about the location of errors, which may be used to improve the logical qubit performance. This approach provides a practical path to scalable modular quantum computing using neutral ytterbium atoms. Published by the American Physical Society 2024

Reliability of Students’ Teaching Practice Scores Using Generalizability Theory

Purpose: The aim was to demonstrate the potency of using Generalisability Theory (GT) over Classical Test Theory (CTT) in reliability estimation. The objectives are to find the major source of error in the Intern Teaching Evaluation Form (ITEF) scores and to identify the optimum number of occasions of rating of teaching practice that would give the most reliable scores. Design/ Methodology/ Approach: A random effects one-facet fully crossed design in which intern (p) was fully crossed with occasion (o) was adopted for the study. In all, 9,082 bachelor’s degree teaching practice triplicate scores for three academic years from 2015/2016 to 2017/2018 were analysed in this study. A univariate generalisability analysis with EduG was performed to analyse data. Findings: The finding for relative interpretation, the scores were strongly reliable. For absolute interpretation, the scores were moderate to strongly dependable. The major source of error in the ITEF scores was the p x o interaction combined with unidentified sources. Research Limitation/Implications: A firm conclusion on one major source of error being a single facet in the ITEF scores could not be made. Practical Implication: The level of reliability and the optimum scoring design of the ITEF established by this study will aid in selecting the ITEF by teacher training institutions in Ghana for evaluation of teaching practice to train pre-service teachers for effective curriculum implementation to achieve national educational aims. Social Implication: Reliable evaluation data can inform policy decisions related to teacher certification, professional development, and educational standards. Policymakers can use this data to develop evidence-based policies that support teacher quality and student achievement. Originality/ Value: It has unearthed the psychometric properties and the ideal scoring design of the ITEF which were hitherto unknown.

Evaluation of the Dimensional Accuracy of Robot-Guided Laser Osteotomy in Reconstruction with Patient-Specific Implants-An Accuracy Study of Digital High-Tech Procedures.

Background/Objective: With the rapid advancement in surgical technologies, new workflows for mandibular reconstruction are constantly being evaluated. Cutting guides are extensively employed for defining osteotomy planes but are prone to errors during fabrication and positioning. A virtually defined osteotomy plane and drilling holes in robotic surgery minimize potential sources of error and yield highly accurate outcomes. Methods: Ten mandibular replicas were evaluated after cutting-guided saw osteotomy and robot-guided laser osteotomy following reconstruction with patient-specific implants. The descriptive data analysis summarizes the mean, standard deviation (SD), median, minimum, maximum, and root mean square (RMS) values of the surface comparison for 3D printed models regarding trueness and precision. Results: The saw group had a median trueness RMS value of 2.0 mm (SD ± 1.7) and a precision of 1.6 mm (SD ± 1.4). The laser group had a median trueness RMS value of 1.2 mm (SD ± 1.1) and an equal precision of 1.6 mm (SD ± 1.4). These results indicate that robot-guided laser osteotomies have a comparable accuracy to cutting-guided saw osteotomies, even though there was a lack of statistical significance. Conclusions: Despite the limited sample size, this digital high-tech procedure has been shown to be potentially equivalent to the conventional osteotomy method. Robotic surgery and laser osteotomy offers enormous advantages, as they enable the seamless integration of precise virtual preoperative planning and exact execution in the human body, eliminating the need for surgical guides in the future.

Modeling and compensation of phase error in projection moiré

The phase error caused by the non-sinusoidal characteristics of the projector and reference grating seriously reduces the measurement accuracy of projection moiré, yet relevant research is lacking. This work presents a phase error model and a phase compensation method to address this issue. The model is established by considering the multiple error sources and phase-solving principles. By employing the phase error model difference, the method accurately fits the model parameters from the non-ideal phase error. With these parameters, the phase error is iteratively extracted and eliminated from the measured phase. Due to its comprehensive consideration of the impacting factors, the model can clarify the phase error mechanism. The method not only significantly enhances the measurement accuracy but also requires only relatively few images for calibration. Experimental results demonstrate an improvement in the morphology measurement accuracy by up to 50%.

A calorimetric evaluation method for beam targets with IR imaging: Implementation for the negative ion source BATMAN Upgrade

A comprehensive calorimetric evaluation method is presented for the beam target installed in the testbed BATMAN Upgrade (BUG). BUG hosts the prototype RF-driven negative ion source for the ITER Neutral Beam Heating System. In nominal conditions BUG features an array of negative ion beamlets (5 horizontal × 14 vertical) with 20 mm spacing among them. Each beamlet is accelerated electrostatically up to a maximum of 45 kV and transports currents in the range from 0.01 to 0.05 A. BUG has two beam targets at different distances from the beam acceleration system. The furthest (2.08 m downstream) is a water-cooled diagnostic CW-calorimeter, which can measure the heat flux distribution of the beam with a resolution of 20 × 20 mm² over a surface of 600 (H) × 800 (V) mm² and water calorimetry. The closest (0.86 m downstream) beam target with sub-millimetric resolution consists of a (376 × 142 × 20 mm³) tile made of a composite anisotropic material with carbon fibers oriented in the thickness direction (1D-CFC). It can only be exposed to beams for limited time, therefore it is retractable. Infrared (IR) imaging of beam targets yields time-resolved high-resolution spatial temperature footprints. A simple algorithm is proposed to reconstruct the heat flux at the front of a beam target, from the IR footprints at the rear. The reconstructed heat flux profiles are lower and broader due to heat conduction effects in the beam target. A correction algorithm is proposed through simulation-based inference of 2D axisymmetrical FEM simulations that reduces the power and shape fit errors over an order of magnitude, to a few percent. The calorimetric evaluation method is applied to experimental shots and two advanced heat flux distribution analysis are shown. The most relevant error sources are discussed and quantified to assess systematic errors. Finally, the method is validated in BUG comparing total beam power estimations with the two calorimetric diagnostics from the CW-calorimeter, showing good agreement.

Model‐free inversion‐based iterative learning control algorithm with adaptive gain: Achieving superior robustness and convergence

AbstractThe main objective of this work is to address the challenge of simultaneously ensuring robustness and convergence performance in model‐free inversion‐based iterative learning control. Initially, this research provides a mathematical analysis of the sources of errors in the iterative process, followed by proposing a gain design guideline to enhance both convergence speed and the final value error. Based on the gain design guideline, a gain design method associated with the number of iterations is proposed, resulting in a novel model‐free inversion‐based iterative learning control algorithm. Subsequently, a robustness analysis of the proposed algorithm is conducted. Finally, a comprehensive simulation and numerical comparison of the proposed algorithm with existing MFIIC‐like algorithms are presented to demonstrate the superior performance of the proposed control algorithm.