There has been an increasing emphasis on performing deep neural network(DNN)inference locally on edge devices due to challenges such as network congestion and security concerns.However,as DRAM process technology conti...There has been an increasing emphasis on performing deep neural network(DNN)inference locally on edge devices due to challenges such as network congestion and security concerns.However,as DRAM process technology continues to scale down,the bit-flip errors in the memory of edge devices become more frequent,thereby leading to substantial DNN inference accuracy loss.Though several techniques have been proposed to alleviate the accuracy loss in edge environments,they require complex computations and additional parity bits for error correction,thus resulting in significant performance and storage overheads.In this paper,we propose FeatherGuard,a data-driven lightweight error protection scheme for DNN inference on edge devices.FeatherGuard selectively protects critical bit positions(that have a significant impact on DNN inference accuracy)against bit-flip errors,by considering various DNN characteristics(e.g.,data format,layer-wise weight distribution,actually stored logical values).Thus,it achieves high error tolerability during DNN inference.Since FeatherGuard reduces the bit-flip errors based on only a few simple arithmetic operations(e.g.,NOT operations)without parity bits,it causes negligible performance overhead and no storage overhead.Our experimental results show that FeatherGuard improves the error tolerability by up to 6667×and 4000×,compared to the conventional systems and the state-of-the-art error protection technique for edge environments,respectively.展开更多
Online programming platforms are popular in programming education.However,there has been no research investigating students’real opinions and expectations of the error feedback mechanisms,leaving educators without a ...Online programming platforms are popular in programming education.However,there has been no research investigating students’real opinions and expectations of the error feedback mechanisms,leaving educators without a solid data foundation when attempting to improve the error feedback mechanisms.This paper makes a survey of 834 students across various programming courses and investigates student perceptions of error feedback mechanisms on online programming platforms.It explores the effectiveness of existing feedback,student satisfaction,and preferences for potential improvements,focusing on automatic error localization and program repair mechanisms.Results reveal a significant portion of students are dissatisfied with current feedback due to its limited informativeness.Students also express a clear demand for stronger feedback mechanisms,such as error localization and repair hints.Nevertheless,they prefer feedback that subtly guides them toward solutions,rather than providing direct and explicit answers,valuing the opportunity to enhance their debugging skills.The findings suggest a need for balanced,educational-focused feedback mechanisms that aid learning while promoting independent problem-solving.展开更多
Due to the inability of manufacturing a single monolithic mirror at the 10-meter scales,segmented mirrors have become indispensable tools in modern astronomical research.However,to match the imaging performance of the...Due to the inability of manufacturing a single monolithic mirror at the 10-meter scales,segmented mirrors have become indispensable tools in modern astronomical research.However,to match the imaging performance of the monolithic counterpart,the sub-mirrors must maintain precise co-phasing.Piston error critically degrades segmented mirror imaging quality,necessitating efficient and precise detection.To ad-dress the limitations that the conventional circular-aperture diffraction with two-wavelength algorithm is sus-ceptible to decentration errors,and the traditional convolutional neural networks(CNNs)struggle to capture global features under large-range piston errors due to their restricted local receptive fields,this paper pro-poses a method that integrates extended Young’s interference principles with a Vision Transformer(ViT)to detect piston error.By suppressing decentration error interference through two symmetrically arranged aper-tures and extending the measurement range to±7.95μm via a two-wavelength(589 nm/600 nm)algorithm.This approach exploits ViT’s self-attention mechanism to model global characteristics of interference fringes.Unlike CNNs constrained by local convolutional kernels,the ViT significantly improves sensitivity to inter-ferogram periodicity.The simulation results demonstrate that the proposed method achieves a measurement accuracy of 5 nm(0.0083λ0)across the range of±7.95μm,while maintaining an accuracy exceeding 95%in the presence of Gaussian noise(SNR≥15 dB),Poisson noise(λ≥9 photons/pixel),and sub-mirror gap er-ror(Egap≤0.2)interference.Moreover,the detection speed shows significant improvement compared to the cross-correlation algorithm.This study establishes an accurate,robust framework for segmented mirror error detection,advancing high-precision astronomical observation.展开更多
This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administratio...This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administration.The analysis reveals systematic improvements in both track and intensity forecasts over the decade,with distinct error characteristics observed across various forecast parameters.Track forecast errors have steadily decreased,particularly for longer lead times,while error magnitudes have increased with longer forecast lead times.Intensity forecasts show similar progressive enhancements,with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts.The study also identifies several key patterns in forecast performance:typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems;intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems;and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases.These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems,and the remaining challenges in predicting TC changes and landfall behavior,providing valuable benchmarks for future forecast system development.展开更多
AIM:To evaluate the efficacy of the total computer vision syndrome questionnaire(CVS-Q)score as a predictive tool for identifying individuals with symptomatic binocular vision anomalies and refractive errors.METHODS:A...AIM:To evaluate the efficacy of the total computer vision syndrome questionnaire(CVS-Q)score as a predictive tool for identifying individuals with symptomatic binocular vision anomalies and refractive errors.METHODS:A total of 141 healthy computer users underwent comprehensive clinical visual function assessments,including evaluations of refractive errors,accommodation(amplitude of accommodation,positive relative accommodation,negative relative accommodation,accommodative accuracy,and accommodative facility),and vergence(phoria,positive and negative fusional vergence,near point of convergence,and vergence facility).Total CVS-Q scores were recorded to explore potential associations between symptom scores and the aforementioned clinical visual function parameters.RESULTS:The cohort included 54 males(38.3%)with a mean age of 23.9±0.58y and 87 age-matched females(61.7%)with a mean age of 23.9±0.53y.The multiple regression model was statistically significant[R²=0.60,F=13.28,degrees of freedom(DF=17122,P<0.001].This indicates that 60%of the variance in total CVS-Q scores(reflecting reported symptoms)could be explained by four clinical measurements:amplitude of accommodation,positive relative accommodation,exophoria at distance and near,and positive fusional vergence at near.CONCLUSION:The total CVS-Q score is a valid and reliable tool for predicting the presence of various nonstrabismic binocular vision anomalies and refractive errors in symptomatic computer users.展开更多
Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling ap...Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling approach enhanced by negative learning,employing a Bidirectional Long Short-Term Memory(BiLSTM)network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals.By penalizing the model for accurately reconstructing seismic anomalies,the negative learning approach effectively magnifies the differences between normal and anomalous data.This strategic differentiation enhances the sensitivity of the BiLSTM network,enabling improved detection of subtle geomagnetic anomalies that may serve as earthquake precursors.Experimental validation clearly demonstrated statistically significant higher reconstruction errors for seismic signals compared to non-seismic signals,confirmed through the Mann-Whitney U test with a p-value of 0.0035 for Root Mean Square Error(RMSE).These results provide compelling evidence of the enhanced anomaly detection capability achieved through negative learning.Unlike traditional classification-based methods,negative learning explicitly encourages sensitivity to subtle precursor signals embedded within complex geomagnetic data,establishing a robust basis for further development of reliable earthquake prediction methods.展开更多
Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a prom...Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity.Unequal error protection(UEP)involves nonuniform error safeguarding for distinct data segments,achieving a fine balance between error resilience and resource allocation,which ultimately enhancing system performance and efficiency.In this paper,we propose a novel class of UEP rateless polar codes.The codes are designed based on matrix extension of polar codes,and elegant mapping and duplication operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes.Superior UEP performance is attained without significant modifications to conventional polar codes,making it straightforward for compatibility with existing polar codes.A theoretical analysis is conducted on the block error rate and throughput efficiency performance.To the best of our knowledge,this work provides the first theoretical performance analysis of UEP rateless polar codes.Simulation results show that the proposed codes significantly outperform existing polar coding schemes in both block error rate and throughput efficiency.展开更多
Conventional error cancellation approaches separate molecules into smaller fragments and sum the errors of all fragments to counteract the overall computational error of the parent molecules.However,these approaches m...Conventional error cancellation approaches separate molecules into smaller fragments and sum the errors of all fragments to counteract the overall computational error of the parent molecules.However,these approaches may be ineffective for systems with strong localized chemical effects,as fragmenting specific substructures into simpler chemical bonds can introduce additional errors instead of mitigating them.To address this issue,we propose the Substructure-Preserved Connection-Based Hierarchy(SCBH),a method that automatically identifies and freezes substructures with significant local chemical effects prior to molecular fragmentation.The SCBH is validated by the gas-phase enthalpy of formation calculation of CHNO molecules.Therein,based on the atomization scheme,the reference and test values are derived at the levels of Gaussian-4(G4)and M062X/6-31+G(2df,p),respectively.Compared to commonly used approaches,SCBH reduces the average computational error by half and requires only15%of the computational cost of G4 to achieve comparable accuracy.Since different types of local effect structures have differentiated influences on gas-phase enthalpy of formation,substituents with strong electronic effects should be retained preferentially.SCBH can be readily extended to diverse classes of organic compounds.Its workflow and source code allow flexible customization of molecular moieties,including azide,carboxyl,trinitromethyl,phenyl,and others.This strategy facilitates accurate,rapid,and automated computations and corrections,making it well-suited for high-throughput molecular screening and dataset construction for gas-phase enthalpy of formation.展开更多
The aerostatic spindle is a key component of ultra-precision machine tools,and its error motion is crucial to machining accuracy and reliability.Spindle error motion is unavoidable,and its online monitoring and predic...The aerostatic spindle is a key component of ultra-precision machine tools,and its error motion is crucial to machining accuracy and reliability.Spindle error motion is unavoidable,and its online monitoring and prediction are quite important.Currently,there are relatively few studies on the online monitoring and prediction methods for the aerostatic spindle,and the level of intelligence is relatively low.To address this problem,an error motion monitoring system based on digital twin(DT)technology was established for the aerostatic spindle.A spindle error motion prediction method based on a mechanism and data fusion model(MDFM)was proposed.Additionally,a highly available and interactive aerostatic spindle DT service platform was developed.Experimental results have verified the good performance of this platform.The platform facilitates interaction between the physical and virtual entities of the aerostatic spindle,enabling three-dimensional visualization,monitoring,prediction,and simulation of spindle error motion,and shows good potential for engineering applications.展开更多
Inborn errors of metabolism(IEMs)are a large group of disorders resulting from deficient activities in several metabolic pathways due to the dysfunction of a distinct enzyme associated with a biochemical pathway[1,2]....Inborn errors of metabolism(IEMs)are a large group of disorders resulting from deficient activities in several metabolic pathways due to the dysfunction of a distinct enzyme associated with a biochemical pathway[1,2].Toxic intermediates will be produced due to the dysfunction of biochemical pathways.The liver is responsible for many essential metabolic processes,therefore it becomes one of the most severely affected organ by metabolic diseases[3].Early onset of liver disorders in IEMs includes jaundice,hepatomegaly,splenomegaly,ascites,hepatic encephalopathy,and liver failure[4].In infants and young children under 3 years old with acute liver failure(ALF),IEMs account for 18.9%-43%[5].展开更多
Inborn errors of metabolism(IEM)are rare disorders,most are liver-based with liver transplantation(LT)emerging as an effective cure in the pediatric population.LT has been shown to offer a cure or deter disease progre...Inborn errors of metabolism(IEM)are rare disorders,most are liver-based with liver transplantation(LT)emerging as an effective cure in the pediatric population.LT has been shown to offer a cure or deter disease progression and provide symptomatic improvement in patients with IEM.Each metabolic disorder is unique,with the missing enzyme or transporter protein causing substrate deficiency or toxic byproduct production.Knowledge about the distribution of deficient enzymes,the percentage of enzymes replaced by LT,and the extent of extrahepatic involvement helps anticipate and manage complications in the perioperative period.Most patients have multisystem involvement and can be on complex dietary regimens.Metabolic decompensation can be triggered due to the stress response to surgery,fasting and other unanticipated complications perioperatively.Thus,a multidisciplinary team’s input including those from metabolic specialists is essential to develop disease and patient-specific strategies for the perioperative management of these patients during LT.In this review,we outline the classification of IEM,indications for LT along with potential benefits,basic metabolic defects and their implications,details of extrahepatic involvement and perioperative management strategies for LT in children with some of the commonly presenting IEM,to assist anesthesiologists handling this cohort of patients.展开更多
Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimila...Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.展开更多
Industrial robots are integral to modern manufacturing systems,enabling high precision,high throughput,and flexibility.However,errors in accuracy and repeatability,which arise from a variety of sources such as mechani...Industrial robots are integral to modern manufacturing systems,enabling high precision,high throughput,and flexibility.However,errors in accuracy and repeatability,which arise from a variety of sources such as mechanical wear,calibration issues,and environmental factors,can significantly impact the performance of industrial robots.This paper aims to explore the theoretical modeling of errors in industrial robot systems and propose compensation strategies to enhance their accuracy and repeatability.Key factors contributing to errors,such as kinematic,dynamic,and environmental influences,are discussed in detail.Additionally,the paper explores various compensation techniques,including geometric error compensation,dynamic compensation,and adaptive control approaches.Through the integration of error modeling and compensation methods,industrial robots can achieve improved performance,ensuring higher operational efficiency and product quality.The paper concludes by highlighting the challenges and future research directions for improving the accuracy and repeatability of industrial robots in practical applications.展开更多
Error-tolerant IR(international relation)theory is constructed on the base of error-tolerant powers paradigm and error-tolerant economics.Error-tolerant powers paradigm takes the integration between trial and error an...Error-tolerant IR(international relation)theory is constructed on the base of error-tolerant powers paradigm and error-tolerant economics.Error-tolerant powers paradigm takes the integration between trial and error and anarchy as the starting point of IR theory and upholds that the power to trial and error is an original power,for which states compete.So the core concept of realism should be the original power to trial and error;error-tolerant economics argues that liberal IR theory enables hegemonic powers to compete for their original power to trial and error in an implicit way.Error-tolerant powers paradigm regards that states who truly control original powers to trial and error can define identities and create shared knowledge,which is the core of constructivism.Besides taking the original power to trial and error as the core concept,error-tolerant IR theory can unify three major schools of realism,liberalism,and constructivism by relative right-doing and trial-and-error capabilities,and corresponding costs as endogenous drives.展开更多
Geometric error,mainly due to imperfect geometry and dimensions of machine components,is one of the major error sources of machine tools.Considering that geometric error has significant effects on the machining qualit...Geometric error,mainly due to imperfect geometry and dimensions of machine components,is one of the major error sources of machine tools.Considering that geometric error has significant effects on the machining quality of manufactured parts,it has been a popular topic for academic and industrial research for many years.A great deal of research work has been carried out since the 1970s for solving the problem and improving the machining accuracy.Researchers have studied how to measure,detect,model,identify,reduce,and compensate the geometric errors.This paper presents a thorough review of the latest research activities and gives an overview of the state of the art in understanding changes in machine tool performance due to geometric errors.Recent advances in measuring the geometrical errors of machine tools are summarized,and different kinds of error identification methods of translational axes and rotation axes are illustrated respectively.Besides,volumetric geometric error modeling,tracing,and compensation techniques for five-axis machine tools are emphatically introduced.Finally,research challenges in order to improve the volumetric accuracy of machine tools are also highlighted.展开更多
Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address th...Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.展开更多
In order to improve the process precision of an XY laser annealing table, a geometric error modeling, and an identification and compensation method were proposed. Based on multi-body system theory, a geometric error m...In order to improve the process precision of an XY laser annealing table, a geometric error modeling, and an identification and compensation method were proposed. Based on multi-body system theory, a geometric error model for the laser annealing table was established. It supports the identification of 7 geometric errors affecting the annealing accuracy. An original identification method was presented to recognize these geometric errors. Positioning errors of 5 lines in the workspace were measured by a laser interferometer, and the 7 geometric errors were identified by the proposed algorithm. Finally, a software-based error compensation method was adopted, and a compensation mechanism was developed in a postprocessor based on LabVIEW. The identified geometric errors can be compensated by converting ideal NC codes to actual NC codes. A validation experiment has been conducted on the laser annealing table, and the results indicate that positioning errors of two validation lines decreased from ±37 μm and ±33 μm to ±5 μm and ±4.5 μm, respectively. The geometric error modeling, identification and compensation method presented in this work can be straightforwardly extended to any configurations of 2-dimensional worktable.展开更多
Thermal errors in CNC machine tools,particularly those involving the spindle,significantly affect machining accuracy and performance.These errors,caused by temperature fluctuations in the spindle and surrounding compo...Thermal errors in CNC machine tools,particularly those involving the spindle,significantly affect machining accuracy and performance.These errors,caused by temperature fluctuations in the spindle and surrounding components,result in dimensional deviations that can lead to poor part quality and reduced precision in high-speed manufacturing processes.This paper explores thermal error modeling and compensation methods for the spindle of five-axis CNC machine tools.A detailed analysis of the heat generation,transfer mechanisms,and finite element analysis(FEA)is presented to develop accurate thermal error models.Compensation techniques,such as model-based methods,sensor-based methods,real-time compensation algorithms,and hybrid approaches,are critically reviewed.This study also discusses the challenges in real-time compensation and the integration of thermal error compensation with machine tool control systems.The objective is to provide a comprehensive understanding of thermal error phenomena and their compensation strategies,ultimately contributing to the enhancement of machining accuracy in advanced manufacturing applications.展开更多
Contour error is the deviation between the actual displacement and reference trajectory,which is directly related to the machining accuracy.Contour error compensation poses substantial challenges because of the time-v...Contour error is the deviation between the actual displacement and reference trajectory,which is directly related to the machining accuracy.Contour error compensation poses substantial challenges because of the time-varying,nonlinear,and strongly coupled characteristics of parallel machining modules.In addition,the time delay in the system reduces the timeliness of the feedback data,thereby making online contour error calculations and compensation particularly difficult.To solve this problem,the generation mechanism of the time delay of the feedback data and contour error is revealed,and a systematic method for the identification of the time-delay parameter based on Beckhoff’s tracking error calculation mechanism is proposed.The temporal alignment between the position commands and feedback data enables the online calculation of the contour error.On this basis,the tracking error of the drive axes(an important factor resulting in end-effector contour errors)is used for the contour error calculation.Considering the ambiguous parameter-setting logic of the servo drive,the servo parameter is calculated in reverse using the steady-state error to obtain the tracking error model of the drive axes.Furthermore,combined with the system time-delay model,an online correction method for the tracking error estimation model is established.To achieve an accurate mapping of the drive-axis tracking error and end-effector contour error,a bounded iterative search method for the nearest contour point and online calculation model for the contour error are respectively established.Finally,an online compensation controller for contour error is designed.Its effectiveness is verified by a machining experiment on a frame workpiece.The machining results show that the contour error reduces from 68μm to 45μm,and the finish machining accuracy increases by 34%.This study provides a feasible method for online compensation of contour error in a system with time delay.展开更多
In the field of quantum error mitigation,most current research separately addresses quantum gate noise mitigation and measurement noise mitigation.However,due to the typically high complexity of measurement noise miti...In the field of quantum error mitigation,most current research separately addresses quantum gate noise mitigation and measurement noise mitigation.However,due to the typically high complexity of measurement noise mitigation methods,such as those based on estimating response matrices,the overall complexity of noise mitigation schemes increases when combining measurement noise mitigation with other quantum gate noise mitigation approaches.This paper proposes a low-complexity quantum error mitigation scheme that jointly mitigates quantum gate and measurement noise,specifically when measurement noise manifests as an amplitude damping channel.The proposed scheme requires estimating only three parameters to jointly mitigate both types of noise,whereas the zero-noise extrapolation method enhanced by response matrix estimation requires estimating at least six parameters under the same conditions.展开更多
基金the“Convergence and Open sharing System”Project,supported by the Ministry of Education and National Research Foundation of Korea.
文摘There has been an increasing emphasis on performing deep neural network(DNN)inference locally on edge devices due to challenges such as network congestion and security concerns.However,as DRAM process technology continues to scale down,the bit-flip errors in the memory of edge devices become more frequent,thereby leading to substantial DNN inference accuracy loss.Though several techniques have been proposed to alleviate the accuracy loss in edge environments,they require complex computations and additional parity bits for error correction,thus resulting in significant performance and storage overheads.In this paper,we propose FeatherGuard,a data-driven lightweight error protection scheme for DNN inference on edge devices.FeatherGuard selectively protects critical bit positions(that have a significant impact on DNN inference accuracy)against bit-flip errors,by considering various DNN characteristics(e.g.,data format,layer-wise weight distribution,actually stored logical values).Thus,it achieves high error tolerability during DNN inference.Since FeatherGuard reduces the bit-flip errors based on only a few simple arithmetic operations(e.g.,NOT operations)without parity bits,it causes negligible performance overhead and no storage overhead.Our experimental results show that FeatherGuard improves the error tolerability by up to 6667×and 4000×,compared to the conventional systems and the state-of-the-art error protection technique for edge environments,respectively.
基金supported by the National Natural Science Foundation of China under Grant No.92582204,No.62577007,and No.62177003the Fundamental Research Funds for the Central Universities under Grant No.JKF-2025011975129.
文摘Online programming platforms are popular in programming education.However,there has been no research investigating students’real opinions and expectations of the error feedback mechanisms,leaving educators without a solid data foundation when attempting to improve the error feedback mechanisms.This paper makes a survey of 834 students across various programming courses and investigates student perceptions of error feedback mechanisms on online programming platforms.It explores the effectiveness of existing feedback,student satisfaction,and preferences for potential improvements,focusing on automatic error localization and program repair mechanisms.Results reveal a significant portion of students are dissatisfied with current feedback due to its limited informativeness.Students also express a clear demand for stronger feedback mechanisms,such as error localization and repair hints.Nevertheless,they prefer feedback that subtly guides them toward solutions,rather than providing direct and explicit answers,valuing the opportunity to enhance their debugging skills.The findings suggest a need for balanced,educational-focused feedback mechanisms that aid learning while promoting independent problem-solving.
文摘Due to the inability of manufacturing a single monolithic mirror at the 10-meter scales,segmented mirrors have become indispensable tools in modern astronomical research.However,to match the imaging performance of the monolithic counterpart,the sub-mirrors must maintain precise co-phasing.Piston error critically degrades segmented mirror imaging quality,necessitating efficient and precise detection.To ad-dress the limitations that the conventional circular-aperture diffraction with two-wavelength algorithm is sus-ceptible to decentration errors,and the traditional convolutional neural networks(CNNs)struggle to capture global features under large-range piston errors due to their restricted local receptive fields,this paper pro-poses a method that integrates extended Young’s interference principles with a Vision Transformer(ViT)to detect piston error.By suppressing decentration error interference through two symmetrically arranged aper-tures and extending the measurement range to±7.95μm via a two-wavelength(589 nm/600 nm)algorithm.This approach exploits ViT’s self-attention mechanism to model global characteristics of interference fringes.Unlike CNNs constrained by local convolutional kernels,the ViT significantly improves sensitivity to inter-ferogram periodicity.The simulation results demonstrate that the proposed method achieves a measurement accuracy of 5 nm(0.0083λ0)across the range of±7.95μm,while maintaining an accuracy exceeding 95%in the presence of Gaussian noise(SNR≥15 dB),Poisson noise(λ≥9 photons/pixel),and sub-mirror gap er-ror(Egap≤0.2)interference.Moreover,the detection speed shows significant improvement compared to the cross-correlation algorithm.This study establishes an accurate,robust framework for segmented mirror error detection,advancing high-precision astronomical observation.
基金supported by the National Key R&D Program of China [grant number 2023YFC3008004]。
文摘This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administration.The analysis reveals systematic improvements in both track and intensity forecasts over the decade,with distinct error characteristics observed across various forecast parameters.Track forecast errors have steadily decreased,particularly for longer lead times,while error magnitudes have increased with longer forecast lead times.Intensity forecasts show similar progressive enhancements,with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts.The study also identifies several key patterns in forecast performance:typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems;intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems;and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases.These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems,and the remaining challenges in predicting TC changes and landfall behavior,providing valuable benchmarks for future forecast system development.
基金Supported by Ongoing Research Funding Program(ORFFT-2025-054-1),King Saud University,Riyadh,Saudi Arabia.
文摘AIM:To evaluate the efficacy of the total computer vision syndrome questionnaire(CVS-Q)score as a predictive tool for identifying individuals with symptomatic binocular vision anomalies and refractive errors.METHODS:A total of 141 healthy computer users underwent comprehensive clinical visual function assessments,including evaluations of refractive errors,accommodation(amplitude of accommodation,positive relative accommodation,negative relative accommodation,accommodative accuracy,and accommodative facility),and vergence(phoria,positive and negative fusional vergence,near point of convergence,and vergence facility).Total CVS-Q scores were recorded to explore potential associations between symptom scores and the aforementioned clinical visual function parameters.RESULTS:The cohort included 54 males(38.3%)with a mean age of 23.9±0.58y and 87 age-matched females(61.7%)with a mean age of 23.9±0.53y.The multiple regression model was statistically significant[R²=0.60,F=13.28,degrees of freedom(DF=17122,P<0.001].This indicates that 60%of the variance in total CVS-Q scores(reflecting reported symptoms)could be explained by four clinical measurements:amplitude of accommodation,positive relative accommodation,exophoria at distance and near,and positive fusional vergence at near.CONCLUSION:The total CVS-Q score is a valid and reliable tool for predicting the presence of various nonstrabismic binocular vision anomalies and refractive errors in symptomatic computer users.
基金funded by the Ministry of Higher Education through Universiti Putra Malaysia(UPM)under Grant FRGS/1/2023/STG07/UPM/02/4.
文摘Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling approach enhanced by negative learning,employing a Bidirectional Long Short-Term Memory(BiLSTM)network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals.By penalizing the model for accurately reconstructing seismic anomalies,the negative learning approach effectively magnifies the differences between normal and anomalous data.This strategic differentiation enhances the sensitivity of the BiLSTM network,enabling improved detection of subtle geomagnetic anomalies that may serve as earthquake precursors.Experimental validation clearly demonstrated statistically significant higher reconstruction errors for seismic signals compared to non-seismic signals,confirmed through the Mann-Whitney U test with a p-value of 0.0035 for Root Mean Square Error(RMSE).These results provide compelling evidence of the enhanced anomaly detection capability achieved through negative learning.Unlike traditional classification-based methods,negative learning explicitly encourages sensitivity to subtle precursor signals embedded within complex geomagnetic data,establishing a robust basis for further development of reliable earthquake prediction methods.
基金supported by National Natural Science Foundation of China(No.62301008)China Postdoctoral Science Foundation(No.2022M720272)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘Mobile communications are reaching out to every aspect of our daily life,necessitating highefficiency data transmission and support for diverse data types and communication scenarios.Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity.Unequal error protection(UEP)involves nonuniform error safeguarding for distinct data segments,achieving a fine balance between error resilience and resource allocation,which ultimately enhancing system performance and efficiency.In this paper,we propose a novel class of UEP rateless polar codes.The codes are designed based on matrix extension of polar codes,and elegant mapping and duplication operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes.Superior UEP performance is attained without significant modifications to conventional polar codes,making it straightforward for compatibility with existing polar codes.A theoretical analysis is conducted on the block error rate and throughput efficiency performance.To the best of our knowledge,this work provides the first theoretical performance analysis of UEP rateless polar codes.Simulation results show that the proposed codes significantly outperform existing polar coding schemes in both block error rate and throughput efficiency.
基金the support of the National Natural Science Foundation of China(22575230)。
文摘Conventional error cancellation approaches separate molecules into smaller fragments and sum the errors of all fragments to counteract the overall computational error of the parent molecules.However,these approaches may be ineffective for systems with strong localized chemical effects,as fragmenting specific substructures into simpler chemical bonds can introduce additional errors instead of mitigating them.To address this issue,we propose the Substructure-Preserved Connection-Based Hierarchy(SCBH),a method that automatically identifies and freezes substructures with significant local chemical effects prior to molecular fragmentation.The SCBH is validated by the gas-phase enthalpy of formation calculation of CHNO molecules.Therein,based on the atomization scheme,the reference and test values are derived at the levels of Gaussian-4(G4)and M062X/6-31+G(2df,p),respectively.Compared to commonly used approaches,SCBH reduces the average computational error by half and requires only15%of the computational cost of G4 to achieve comparable accuracy.Since different types of local effect structures have differentiated influences on gas-phase enthalpy of formation,substituents with strong electronic effects should be retained preferentially.SCBH can be readily extended to diverse classes of organic compounds.Its workflow and source code allow flexible customization of molecular moieties,including azide,carboxyl,trinitromethyl,phenyl,and others.This strategy facilitates accurate,rapid,and automated computations and corrections,making it well-suited for high-throughput molecular screening and dataset construction for gas-phase enthalpy of formation.
基金supported by the National Natural Science Foundation of China(Grant No.52475494),the Zhejiang Provincial Natural Science Foundation of China(Grant No.LY22E050003),the Fundamental Research Funds for the Provincial Universities of Zhejiang(Grant No.RF-A2020005).
文摘The aerostatic spindle is a key component of ultra-precision machine tools,and its error motion is crucial to machining accuracy and reliability.Spindle error motion is unavoidable,and its online monitoring and prediction are quite important.Currently,there are relatively few studies on the online monitoring and prediction methods for the aerostatic spindle,and the level of intelligence is relatively low.To address this problem,an error motion monitoring system based on digital twin(DT)technology was established for the aerostatic spindle.A spindle error motion prediction method based on a mechanism and data fusion model(MDFM)was proposed.Additionally,a highly available and interactive aerostatic spindle DT service platform was developed.Experimental results have verified the good performance of this platform.The platform facilitates interaction between the physical and virtual entities of the aerostatic spindle,enabling three-dimensional visualization,monitoring,prediction,and simulation of spindle error motion,and shows good potential for engineering applications.
文摘Inborn errors of metabolism(IEMs)are a large group of disorders resulting from deficient activities in several metabolic pathways due to the dysfunction of a distinct enzyme associated with a biochemical pathway[1,2].Toxic intermediates will be produced due to the dysfunction of biochemical pathways.The liver is responsible for many essential metabolic processes,therefore it becomes one of the most severely affected organ by metabolic diseases[3].Early onset of liver disorders in IEMs includes jaundice,hepatomegaly,splenomegaly,ascites,hepatic encephalopathy,and liver failure[4].In infants and young children under 3 years old with acute liver failure(ALF),IEMs account for 18.9%-43%[5].
文摘Inborn errors of metabolism(IEM)are rare disorders,most are liver-based with liver transplantation(LT)emerging as an effective cure in the pediatric population.LT has been shown to offer a cure or deter disease progression and provide symptomatic improvement in patients with IEM.Each metabolic disorder is unique,with the missing enzyme or transporter protein causing substrate deficiency or toxic byproduct production.Knowledge about the distribution of deficient enzymes,the percentage of enzymes replaced by LT,and the extent of extrahepatic involvement helps anticipate and manage complications in the perioperative period.Most patients have multisystem involvement and can be on complex dietary regimens.Metabolic decompensation can be triggered due to the stress response to surgery,fasting and other unanticipated complications perioperatively.Thus,a multidisciplinary team’s input including those from metabolic specialists is essential to develop disease and patient-specific strategies for the perioperative management of these patients during LT.In this review,we outline the classification of IEM,indications for LT along with potential benefits,basic metabolic defects and their implications,details of extrahepatic involvement and perioperative management strategies for LT in children with some of the commonly presenting IEM,to assist anesthesiologists handling this cohort of patients.
基金sponsored by the National Natural Science Foundation of China[grant number U2442218]。
文摘Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.
文摘Industrial robots are integral to modern manufacturing systems,enabling high precision,high throughput,and flexibility.However,errors in accuracy and repeatability,which arise from a variety of sources such as mechanical wear,calibration issues,and environmental factors,can significantly impact the performance of industrial robots.This paper aims to explore the theoretical modeling of errors in industrial robot systems and propose compensation strategies to enhance their accuracy and repeatability.Key factors contributing to errors,such as kinematic,dynamic,and environmental influences,are discussed in detail.Additionally,the paper explores various compensation techniques,including geometric error compensation,dynamic compensation,and adaptive control approaches.Through the integration of error modeling and compensation methods,industrial robots can achieve improved performance,ensuring higher operational efficiency and product quality.The paper concludes by highlighting the challenges and future research directions for improving the accuracy and repeatability of industrial robots in practical applications.
文摘Error-tolerant IR(international relation)theory is constructed on the base of error-tolerant powers paradigm and error-tolerant economics.Error-tolerant powers paradigm takes the integration between trial and error and anarchy as the starting point of IR theory and upholds that the power to trial and error is an original power,for which states compete.So the core concept of realism should be the original power to trial and error;error-tolerant economics argues that liberal IR theory enables hegemonic powers to compete for their original power to trial and error in an implicit way.Error-tolerant powers paradigm regards that states who truly control original powers to trial and error can define identities and create shared knowledge,which is the core of constructivism.Besides taking the original power to trial and error as the core concept,error-tolerant IR theory can unify three major schools of realism,liberalism,and constructivism by relative right-doing and trial-and-error capabilities,and corresponding costs as endogenous drives.
基金supported by the National Natural Science Foundation of China(Nos.52005413,52022082)Natural Science Basic Research Plan in Shaanxi Province of China(No.2021JM-054)the Fundamental Research Funds for the Central Universities(No.D5000220135)。
文摘Geometric error,mainly due to imperfect geometry and dimensions of machine components,is one of the major error sources of machine tools.Considering that geometric error has significant effects on the machining quality of manufactured parts,it has been a popular topic for academic and industrial research for many years.A great deal of research work has been carried out since the 1970s for solving the problem and improving the machining accuracy.Researchers have studied how to measure,detect,model,identify,reduce,and compensate the geometric errors.This paper presents a thorough review of the latest research activities and gives an overview of the state of the art in understanding changes in machine tool performance due to geometric errors.Recent advances in measuring the geometrical errors of machine tools are summarized,and different kinds of error identification methods of translational axes and rotation axes are illustrated respectively.Besides,volumetric geometric error modeling,tracing,and compensation techniques for five-axis machine tools are emphatically introduced.Finally,research challenges in order to improve the volumetric accuracy of machine tools are also highlighted.
基金supported by the Key R&D Program of Zhejiang Province(Nos.2023C01166 and 2024SJCZX0046)the Zhejiang Provincial Natural Science Foundation of China(Nos.LDT23E05013E05 and LD24E050009)the Natural Science Foundation of Ningbo(No.2021J150),China.
文摘Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.
基金Projects(2012ZX04010-011,2009ZX02037-02) supported by the Key National Science and Technology Project of China
文摘In order to improve the process precision of an XY laser annealing table, a geometric error modeling, and an identification and compensation method were proposed. Based on multi-body system theory, a geometric error model for the laser annealing table was established. It supports the identification of 7 geometric errors affecting the annealing accuracy. An original identification method was presented to recognize these geometric errors. Positioning errors of 5 lines in the workspace were measured by a laser interferometer, and the 7 geometric errors were identified by the proposed algorithm. Finally, a software-based error compensation method was adopted, and a compensation mechanism was developed in a postprocessor based on LabVIEW. The identified geometric errors can be compensated by converting ideal NC codes to actual NC codes. A validation experiment has been conducted on the laser annealing table, and the results indicate that positioning errors of two validation lines decreased from ±37 μm and ±33 μm to ±5 μm and ±4.5 μm, respectively. The geometric error modeling, identification and compensation method presented in this work can be straightforwardly extended to any configurations of 2-dimensional worktable.
文摘Thermal errors in CNC machine tools,particularly those involving the spindle,significantly affect machining accuracy and performance.These errors,caused by temperature fluctuations in the spindle and surrounding components,result in dimensional deviations that can lead to poor part quality and reduced precision in high-speed manufacturing processes.This paper explores thermal error modeling and compensation methods for the spindle of five-axis CNC machine tools.A detailed analysis of the heat generation,transfer mechanisms,and finite element analysis(FEA)is presented to develop accurate thermal error models.Compensation techniques,such as model-based methods,sensor-based methods,real-time compensation algorithms,and hybrid approaches,are critically reviewed.This study also discusses the challenges in real-time compensation and the integration of thermal error compensation with machine tool control systems.The objective is to provide a comprehensive understanding of thermal error phenomena and their compensation strategies,ultimately contributing to the enhancement of machining accuracy in advanced manufacturing applications.
基金Supported by National Natural Science Foundation of China(Grant Nos.52375018,92148301).
文摘Contour error is the deviation between the actual displacement and reference trajectory,which is directly related to the machining accuracy.Contour error compensation poses substantial challenges because of the time-varying,nonlinear,and strongly coupled characteristics of parallel machining modules.In addition,the time delay in the system reduces the timeliness of the feedback data,thereby making online contour error calculations and compensation particularly difficult.To solve this problem,the generation mechanism of the time delay of the feedback data and contour error is revealed,and a systematic method for the identification of the time-delay parameter based on Beckhoff’s tracking error calculation mechanism is proposed.The temporal alignment between the position commands and feedback data enables the online calculation of the contour error.On this basis,the tracking error of the drive axes(an important factor resulting in end-effector contour errors)is used for the contour error calculation.Considering the ambiguous parameter-setting logic of the servo drive,the servo parameter is calculated in reverse using the steady-state error to obtain the tracking error model of the drive axes.Furthermore,combined with the system time-delay model,an online correction method for the tracking error estimation model is established.To achieve an accurate mapping of the drive-axis tracking error and end-effector contour error,a bounded iterative search method for the nearest contour point and online calculation model for the contour error are respectively established.Finally,an online compensation controller for contour error is designed.Its effectiveness is verified by a machining experiment on a frame workpiece.The machining results show that the contour error reduces from 68μm to 45μm,and the finish machining accuracy increases by 34%.This study provides a feasible method for online compensation of contour error in a system with time delay.
基金supported by the National Natural Science Foundation of China(Grant No.62271265)。
文摘In the field of quantum error mitigation,most current research separately addresses quantum gate noise mitigation and measurement noise mitigation.However,due to the typically high complexity of measurement noise mitigation methods,such as those based on estimating response matrices,the overall complexity of noise mitigation schemes increases when combining measurement noise mitigation with other quantum gate noise mitigation approaches.This paper proposes a low-complexity quantum error mitigation scheme that jointly mitigates quantum gate and measurement noise,specifically when measurement noise manifests as an amplitude damping channel.The proposed scheme requires estimating only three parameters to jointly mitigate both types of noise,whereas the zero-noise extrapolation method enhanced by response matrix estimation requires estimating at least six parameters under the same conditions.
