The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogo...The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogonality error of grating grooves not only improves the positioning accuracy of grating interferometers but also provides essential feedback for optimizing two-dimensional grating fabrication.This study proposes a method for simultaneous calibration of these parameters using orthogonal heterodyne laser interferometry.A two-dimensional grating interferometer is built with the grating to be measured,and a biaxial laser interferometer provides a displacement reference for it.The phase mapping relationship between grating interference and laser interference is established.The interference phase information obtained by any two displacements can simultaneously solve the above three parameters and obtain the grating installation error.The feasibility of the proposed method is verified by using a 1200 gr/mm two-dimensional grating.The standard deviation of the grating groove density in the X and Y directions is 0.012 gr/mm and 0.014 gr/mm,respectively.The standard deviation of the orthogonality error of grating grooves is 0.004°,and the standard deviation of the installation error is 0.002°.Compared with the atomic force microscope method,the consistency of the grating groove density in the X and Y directions is better than 0.03 gr/mm and 0.06 gr/mm,and the orthogonality error of grating grooves is better than 0.008°.The experimental results show that the proposed method can be simply and efficiently applied to the calibration of the grating line parameters of the two-dimensional grating.展开更多
This study investigates the reduction in polarization measurement accuracy caused by varying in-cident angles in a liquid crystal variable retarder(LCVR).The phase delay characteristics of the LCVR were examined,with ...This study investigates the reduction in polarization measurement accuracy caused by varying in-cident angles in a liquid crystal variable retarder(LCVR).The phase delay characteristics of the LCVR were examined,with particular emphasis on the influence of different two-dimensional incident angles on phase delay behavior.Building upon the calibration of phase delay under normal incidence,a phase delay calibra-tion model was developed to account for variations in incident angle and driving voltage.A mathematical re-lationship was established between phase delay and the azimuth angle(α)and pitch angle(β).Experimental validation was conducted under three conditions:α=20°,β=0°;α=0°,β=20°;and an arbitrary angle whereα=5°,β=15°.The results demonstrated that the maximum average deviation between theoretical pre-dictions and experimental measurements did not exceed 0.059 rad.The proposed calibration method proved to be both accurate and practical.This approach offers robust support for LCVR parameter calibration and performance optimization in optical systems,particularly in polarization imaging applications.展开更多
LiDAR and camera are two of the most common sensors used in the fields of robot perception,autonomous driving,augmented reality,and virtual reality,where these sensors are widely used to perform various tasks such as ...LiDAR and camera are two of the most common sensors used in the fields of robot perception,autonomous driving,augmented reality,and virtual reality,where these sensors are widely used to perform various tasks such as odometry estimation and 3D reconstruction.Fusing the information from these two sensors can significantly increase the robustness and accuracy of these perception tasks.The extrinsic calibration between cameras and LiDAR is a fundamental prerequisite for multimodal systems.Recently,extensive studies have been conducted on the calibration of extrinsic parameters.Although several calibration methods facilitate sensor fusion,a comprehensive summary for researchers and,especially,non-expert users is lacking.Thus,we present an overview of extrinsic calibration and discuss diverse calibration methods from the perspective of calibration system design.Based on the calibration information sources,this study classifies these methods as target-based or targetless.For each type of calibration method,further classification was performed according to the diverse types of features or constraints used in the calibration process,and their detailed implementations and key characteristics were introduced.Thereafter,calibration-accuracy evaluation methods are presented.Finally,we comprehensively compare the advantages and disadvantages of each calibration method and suggest directions for practical applications and future research.展开更多
Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper ...Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper equations are one of the main and most efficient methods for estimating stem volume to any merchantable limit of a species.There is currently no taper equation for Eucalyptus species in Nigeria.Therefore,this study developed taper equations for E.camaldulensis in northern Nigeria.Data for this study were obtained from a private plantation in Jalingo Local Government Area,Taraba State,Nigeria.68 trees were felled and sectioned into 1-m bolt across the stem to a merchantable limit of 5 cm,which were used as the fitting dataset.An additional 22 trees were felled and used to validate the taper equations for stem volume estimation.Seven taper equations were initially fitted to the dataset using nonlinear least squares.The best taper equation was then refitted using a nonlinear mixed-effects approach and calibrated using diameters of one to five sections from the butt end.The taper equations were numerically integrated to obtain the stem volume,which was compared with empirical volume equations.The result shows that the Kozak(Can J For Res 27(5):619-629.10.1139/x97-011,1997)equation,which included eight parameters,provided the best fit for predicting section diameters for under and over bark.The mixed-effects taper equation(NLME-TE)explained most stem diameter variations in the fitting dataset(pseudo-R2:0.986-0.987;RMSE:0.547-0.578 cm)without substantial residual trends.The validation showed that the prediction accuracy of the integrated NLME-TE improved as the number of sectional diameter measurements increased,with at least a 35%reduction in volume estimate error.For practical implementation,two calibration sectional diameter measurements taken from the butt end per tree are recommended.This approach would reduce measurement effort and cost while improving model performance.展开更多
In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorit...In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system.An output-based event-triggered scheme is first employed to alleviate transmission burden.Accounting for the limited-communication-induced measurement bias,a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation,thereby achieving accurate system state estimates.Subsequently,the Field Programmable Gate Array(FPGA)implementation of the proposed algorithm is also realized with the hope of providing fast bias calibration in practical scenarios.A simulation about a numerical example and a practical example(for gyroscope’s angular velocity bias calibration)on MATLAB is provided to demonstrate the feasibility and effectiveness of the proposed algorithm.展开更多
The segmented solar telescope described in this study employs a simultaneous dual-wavelength measurement technique to achieve co-phase alignment.To meet the measurement requirements of a 20μm range,5 nm root mean squ...The segmented solar telescope described in this study employs a simultaneous dual-wavelength measurement technique to achieve co-phase alignment.To meet the measurement requirements of a 20μm range,5 nm root mean square precision,and edge jump rates of<10^(−6),this study focused on calibrating the dual-wavelength measurement system for the segmented-mirror solar telescope.Analysis of the relative error in the measurement system revealed that assembly-induced errors such as defocus,translation,scaling,and rotation markedly degrade measurement accuracy.To address these issues,we propose a defocus error compensation algorithm,based on the light intensity distribution of the point spread function(PSF)and an affine transformation model,to calibrate spatial pose deviations across the two measurement channels.A dual-wavelength measurement system was implemented on a segmented-mirror experimental platform for calibration.Experimental results demonstrated that the mean relative error decreased from−0.6423 to−0.0345 nm after calibration,reflecting improved reliability and stability of the co-phase measurements.展开更多
With the widespread adoption of digital equipment in intelligent substations,testing digital signals in power systems has become an important role for relay protection test equipment.Testing and calibrating digital si...With the widespread adoption of digital equipment in intelligent substations,testing digital signals in power systems has become an important role for relay protection test equipment.Testing and calibrating digital signals require high accuracy.However,existing methods have low precision,cannot be calibrated at full range for all indexes,and have complex configuration,making them unsuitable for routine calibration work.To solve the above problems,a novel calibration method is designed and implemented using field programmable gate array(FPGA)to achieve accurate input and output time control.Accurate calibration relies on multiple forms of traceability including theoretical value traceability based on waveform comparison,time scale value traceability based on accurate time stamps,and algorithm traceability based on typical algorithms.Compared with other existing methods,the proposed approach reduces the mean absolute error of action time and time measurement by 92.88%,effectively addressing a key industry challenge and offering a valuable reference for further research,application,and standardization.展开更多
Considering the drastic variations in the surface elevation of the piedmont region in the Bai Cheng West Area,there is no reference point within the Reference Ground Line(RG line)of the starting point of the synthetic...Considering the drastic variations in the surface elevation of the piedmont region in the Bai Cheng West Area,there is no reference point within the Reference Ground Line(RG line)of the starting point of the synthetic seismic records in the process of calibration of the horizon.Through the analysis of the process and properties of the production of the RG line,in the processing of seismic data,it is indicated that the position of the synthetic data of seismic records is not located at the beginning of the RG line.Rather,it must be at the time point of the seismic profile at the elevation of a datum position of the static value of less than the datum plane.Both the RG line and the elevation static correction value line can easily be seen by computerizing the calculated value of the elevation static correction of the datum plane relating to the seismic section and plotting it on the seismic section.To achieve a good calibration with the synthetic seismogram,it is possible to set the starting point of the synthetic seismogram on the elevation static correction value line that is situated at the place of the Common Mid-Point(CMP).In the current paper,a systematic overview of methods and safety procedures for establishing the seismic interpretation work area and horizon calibration in seismic interpretation has been reviewed,which will form an effective guide towards seismic interpretation under the complicated surface conditions in the Bai Cheng west region.展开更多
We present the preparation and measurement of the radioactive isotope^(37)Ar,which was produced using thermal neutrons from a reactor,as a calibration source for liquid xenon time projection chambers.^(37)Ar is a low-...We present the preparation and measurement of the radioactive isotope^(37)Ar,which was produced using thermal neutrons from a reactor,as a calibration source for liquid xenon time projection chambers.^(37)Ar is a low-energy calibration source with a half-life of 35.01 days,making it suitable for calibration in the low-energy region of liquid xenon dark-matter experiments.Radioactive isotope^(37)Ar was produced by irradiating ^(36)Ar with thermal neutrons.It was subsequently measured in a gaseous xenon time projection chamber(GXe TPC)to validate its radioactivity.Our results demonstrate that^(37)Ar is an effective and viable calibration source that offers precise calibration capabilities in the low-energy domain of xenon-based detectors.展开更多
To address crop depredation by intelligent species(e.t,macaques)and the habituation from traditional methods,this study proposes an intelligent,closed-loop,adaptive laser deterrence system.A core contribution is an ef...To address crop depredation by intelligent species(e.t,macaques)and the habituation from traditional methods,this study proposes an intelligent,closed-loop,adaptive laser deterrence system.A core contribution is an efficient multi-stage Semi-Supervised Learning(SSL)and incremental fine-tuning(IFT)framework,which reduced manual annotation by~60%and training time by~68%.This framework was benchmarked against YOLOv8n,v10n,and v11n.Our analysis revealed that YOLOv12n’s high Signal-to-Noise Ratio(SNR)(47.1%retention)pseudo-labels made it the onlymodel to gain performance(+0.010mAP)fromSSL,allowing it to overtake competitors.Subsequently,in the IFT stress test,YOLOv12n proved most robust(a minimal−0.019 mAP decline),whereas YOLOv10n suffered catastrophic failure(−0.233mAP),highlighting its incompatibility with IFT.Thefinalmodel achieved high performance(mAP@0.5 of 0.947 for macaques,0.946 for laser spots).In Multi-Object Tracking(MOT),this study quantitatively confirms that Bottom-Up Tracking by Sorting(BoT-SORT)(1.88 s avg.tracklet lifetime)significantly outperforms ByteTrack(0.81 s)in identity preservation for visually similar macaques.System integration achieved 480 Frames Per Second(FPS)real-time inference on edge devices.A quadratic polynomial fittingmodel ensured high-precision aiming(RMSE<2 pixels;best 1.2 pixels)by compensating for distortion.To fundamentally solve habituation,an adaptive strategy driven by a Deep Deterministic Policy Gradient(DDPG)framework was introduced.By using a habituation penalty term(Rhabituation)to force unpredictable sequences,theDDPGstrategy achieved a stable 88%average Intrusion Frequency Reduction Rate(IFRR)in field experiments,suppressing habituation in highly intelligent species.This study develops an efficient,precise,low-cost,and habituation-resistant automated wildlife defense system.展开更多
The rapid proliferation of multimodal misinformation on social media demands detection frameworks that are not only accurate but also robust to noise,adversarial manipulation,and semantic inconsistency between modalit...The rapid proliferation of multimodal misinformation on social media demands detection frameworks that are not only accurate but also robust to noise,adversarial manipulation,and semantic inconsistency between modalities.Existing multimodal fake news detection approaches often rely on deterministic fusion strategies,which limits their ability to model uncertainty and complex cross-modal dependencies.To address these challenges,we propose Q-ALIGNer,a quantum-inspired multimodal framework that integrates classical feature extraction with quantumstate encoding,learnable cross-modal entanglement,and robustness-aware training objectives.The proposed framework adopts quantumformalism as a representational abstraction,enabling probabilisticmodeling ofmultimodal alignment while remaining fully executable on classical hardware.Q-ALIGNer is evaluated on four widely used benchmark datasets—FakeNewsNet,Fakeddit,Weibo,and MediaEval VMU—covering diverse platforms,languages,and content characteristics.Experimental results demonstrate consistent performance improvements over strong text-only,vision-only,multimodal,and quantum-inspired baselines,including BERT,RoBERTa,XLNet,ResNet,EfficientNet,ViT,Multimodal-BERT,ViLBERT,and QEMF.Q-ALIGNer achieves accuracies of 91.2%,92.9%,91.7%,and 92.1%on FakeNewsNet,Fakeddit,Weibo,and MediaEval VMU,respectively,with F1-score gains of 3–4 percentage points over QEMF.Robustness evaluation shows a reduced adversarial accuracy gap of 2.6%,compared to 7%–9%for baseline models,while calibration analysis indicates improved reliability with an expected calibration error of 0.031.In addition,computational analysis shows that Q-ALIGNer reduces training time to 19.6 h compared to 48.2 h for QEMF at a comparable parameter scale.These results indicate that quantum-inspired alignment and entanglement can enhance robustness,uncertainty awareness,and efficiency in multimodal fake news detection,positioning Q-ALIGNer as a principled and practical content-centric framework for misinformation analysis.展开更多
Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to t...Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.展开更多
Large-volume presses(LVPs)are widely utilized in diverse research fields—including high-pressure physics,chemistry,materials science,and Earth and planetary sciences—to investigate the physical and chemical properti...Large-volume presses(LVPs)are widely utilized in diverse research fields—including high-pressure physics,chemistry,materials science,and Earth and planetary sciences—to investigate the physical and chemical properties of materials under extreme high-pressure and hightemperature conditions.A prerequisite for achieving reproducible property measurements is the determination and control of pressure within experimental setups.However,the lack of precise pressure calibration in LVPs hinders the broader application of such devices in ultrahigh-pressure studies.This study employs a suite of standard phase transition-based pressure markers—comprising metallic conductors,semiconductors,and minerals—through both in situ and ex situ identification approaches,to establish pressure calibration curves ranging from 0.4 to>30 GPa for various types of LVP installed at the Center for High Pressure Science and Technology Advanced Research(HPSTAR),Beijing,including piston–cylinder,cubic,and multi-anvil presses.The results provide a unified and traceable pressure reference for highpressure experiments conducted at HPSTAR,while also offering technical guidance and calibration standards for other researchers utilizing similar LVP systems,thereby enabling more consistent comparison between different laboratories.This work facilitates the advancement of LVP research toward broader applications in higher-pressure regimes.展开更多
Intrusion detection in Internet of Things(IoT)environments presents challenges due to heterogeneous devices,diverse attack vectors,and highly imbalanced datasets.Existing research on the ToN-IoT dataset has largely em...Intrusion detection in Internet of Things(IoT)environments presents challenges due to heterogeneous devices,diverse attack vectors,and highly imbalanced datasets.Existing research on the ToN-IoT dataset has largely emphasized binary classification and single-model pipelines,which often showstrong performance but limited generalizability,probabilistic reliability,and operational interpretability.This study proposes a stacked ensemble deep learning framework that integrates random forest,extreme gradient boosting,and a deep neural network as base learners,with CatBoost as the meta-learner.On the ToN-IoT Linux process dataset,the model achieved near-perfect discrimination(macro area under the curve=0.998),robust calibration,and superior F1-scores compared with standalone classifiers.Interpretability was achieved through SHapley Additive exPlanations–based feature attribution,which highlights actionable drivers ofmalicious behavior,such as command-line patterns,process scheduling anomalies,and CPU usage spikes,and aligns these indicators with MITRE ATT&CK tactics and techniques.Complementary analyses,including cumulative lift and sensitivity-specificity trade-offs,revealed the framework’s suitability for deployment in security operations centers,where calibrated risk scores,transparent explanations,and resource-aware triage are essential.These contributions bridge methodological rigor in artificial intelligence/machine learning with operational priorities in cybersecurity,delivering a scalable and explainable intrusion detection system suitable for real-world deployment in IoT environments.展开更多
Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calc...Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calculating the sky area visibility distribution via extinction measurement challenging.To address this issue,we propose the Photometry-Free Sky Area Visibility Estimation(PFSAVE)method.This method uses the standard magnitude of the faintest star observed within a given sky area to estimate visibility.By employing a pertransformation refitting optimization strategy,we achieve a high-precision coordinate transformation model with an accuracy of 0.42 pixels.Using the results of HEALPix segmentation is also introduced to achieve high spatial resolution.Comprehensive analysis based on real allsky images demonstrates that our method exhibits higher accuracy than the extinction-based method.Our method supports both manual and robotic dynamic scheduling,especially under partially cloudy conditions.展开更多
Defining an ERBB2(HER2/neu)gene amplification status is critical to guiding human epidermal growth factor receptor 2(HER2)-targeted therapy in breast cancer.Up to 40%of breast cancer patients are reported as having an...Defining an ERBB2(HER2/neu)gene amplification status is critical to guiding human epidermal growth factor receptor 2(HER2)-targeted therapy in breast cancer.Up to 40%of breast cancer patients are reported as having an immunohistochemistry(IHC)of HER22+and requiring additional testing using fluorescence in situ hybridization to confirm the results.This paper aims to establish an automatically weighted calibration deep learning(AWCDL)algorithm to predict ERBB2 amplification based on IHC images.In this study,we applied IHC HER22+images from 1,073 breast cancer patients at three cancer centers in China and extracted 376,099 tiles.Among these,269,664 tiles were used for internal and external validation.The designed AWCDL consists of two steps.In Step 1,the internal validation achieved an accuracy of 89%,with a specificity of 0.89 and a sensitivity of 0.89.The external validation in the two other centers showed an average accuracy of 85%,with a specificity of 0.86 and a sensitivity of 0.82.In Step 2,the model achieved higher accuracy for the slides predicted as negative in Step 1 by automatically calibrating the weight.Collectively,these results suggest that this AWCDL model has successfully proved useful as an alternative method to fluorescence in situ hybridization for assessing the ERBB2 amplification status in breast cancer.展开更多
High-precision magnetic field measurements are crucial for understanding Earth’s internal structure,space environment,and dynamic geomagnetic variations.Data from the Fluxgate Magnetometer (FGM) on the Macao Science ...High-precision magnetic field measurements are crucial for understanding Earth’s internal structure,space environment,and dynamic geomagnetic variations.Data from the Fluxgate Magnetometer (FGM) on the Macao Science Satellite-1A (MSS-1A),added to data from other space-based magnetometers,should increase significantly the ability of scientists to observe changes in Earth’s magnetic field over time and space.Additionally,the MSS-1A’s FGM is intended to help identify magnetic disturbances affecting the spacecraft itself.This report focuses on the in-flight calibration of the MSS-1 FGM.A scalar calibration,independent of geomagnetic field models,was performed to correct offsets,sensitivities,and misalignment angles of the FGM.Using seven months of data,we find that the in-flight calibration parameters show good stability.We determined Euler angles describing the rotational relationship between the FGM and the Advanced Stellar Compass (ASC) coordinate system using two approaches:calibration with the CHAOS-7 geomagnetic field model,and simultaneous estimation of Euler angles and Gaussian spherical harmonic coefficients through self-consistent modeling.The accuracy of Euler angles describing the rotation was better than 18 arcsec.The calibrated FGM data exhibit good agreement with the calibrated data of the Vector Field Magnetometer (VFM),which is the primary vector magnetometer of the satellite.These calibration efforts have significantly improved the accuracy of the FGM measurements,which are now providing reliable data for geomagnetic field studies that promise to advance our understanding of the Earth’s magnetic environment.展开更多
1.A.Mertha,“‘Stressing Out’:Cadre Calibration and Affective Proximity to the CCP in Reform-Era China”,The China Quarterly,Vol.229,2017,pp.64-85.2.B.L.McCormick,“Book Review of‘The Chinese Communist Party's C...1.A.Mertha,“‘Stressing Out’:Cadre Calibration and Affective Proximity to the CCP in Reform-Era China”,The China Quarterly,Vol.229,2017,pp.64-85.2.B.L.McCormick,“Book Review of‘The Chinese Communist Party's Capacity to Rule:Ideology,Legitimacy and Party Cohesion’”,The China Journal,Vol.77,2017,pp.161-163.展开更多
Currently,there is a lack of in-situ or model test results for cone penetration tests(CPTs)conducted in deep,dense sand layers under high overburden stresses,restricting the development of empirical relationships betw...Currently,there is a lack of in-situ or model test results for cone penetration tests(CPTs)conducted in deep,dense sand layers under high overburden stresses,restricting the development of empirical relationships between CPT results and the characteristics of such deep,dense sand layers.This study addresses this gap by proposing an empirical relationship to predict the relative density of dense silica sand based on stress level and cone tip resistance.The relationship was developed through CPTs performed in a calibration chamber using dense sand specimens(with relative densities of 74%-91%)subjected to high stresses(under overburden stresses of 0.5-2.0 MPa)and numerical simulations employing the large deformation finite element method.The Arbitrary Lagrangian Eulerian method was used to regularly regenerate the mesh to prevent soil element distortion around the cone tip.Additionally,the modified Mohr-Coulomb model was integrated to capture the stress-strain behavior of dense silica sand under high stresses.A reasonable agreement was achieved between the numerical and experimental penetration profiles,which verifies the reliability of the numerical model.A sufficient number of parametric analyses were carried out,and then an empirical equation was proposed to establish the relationship between the relative density of dense sand,stress level and cone resistance.The empirical equation provides predictions with acceptable accuracy,as the discrepancies between the predicted and measured relative density values fall within±30%.展开更多
文摘The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogonality error of grating grooves not only improves the positioning accuracy of grating interferometers but also provides essential feedback for optimizing two-dimensional grating fabrication.This study proposes a method for simultaneous calibration of these parameters using orthogonal heterodyne laser interferometry.A two-dimensional grating interferometer is built with the grating to be measured,and a biaxial laser interferometer provides a displacement reference for it.The phase mapping relationship between grating interference and laser interference is established.The interference phase information obtained by any two displacements can simultaneously solve the above three parameters and obtain the grating installation error.The feasibility of the proposed method is verified by using a 1200 gr/mm two-dimensional grating.The standard deviation of the grating groove density in the X and Y directions is 0.012 gr/mm and 0.014 gr/mm,respectively.The standard deviation of the orthogonality error of grating grooves is 0.004°,and the standard deviation of the installation error is 0.002°.Compared with the atomic force microscope method,the consistency of the grating groove density in the X and Y directions is better than 0.03 gr/mm and 0.06 gr/mm,and the orthogonality error of grating grooves is better than 0.008°.The experimental results show that the proposed method can be simply and efficiently applied to the calibration of the grating line parameters of the two-dimensional grating.
文摘This study investigates the reduction in polarization measurement accuracy caused by varying in-cident angles in a liquid crystal variable retarder(LCVR).The phase delay characteristics of the LCVR were examined,with particular emphasis on the influence of different two-dimensional incident angles on phase delay behavior.Building upon the calibration of phase delay under normal incidence,a phase delay calibra-tion model was developed to account for variations in incident angle and driving voltage.A mathematical re-lationship was established between phase delay and the azimuth angle(α)and pitch angle(β).Experimental validation was conducted under three conditions:α=20°,β=0°;α=0°,β=20°;and an arbitrary angle whereα=5°,β=15°.The results demonstrated that the maximum average deviation between theoretical pre-dictions and experimental measurements did not exceed 0.059 rad.The proposed calibration method proved to be both accurate and practical.This approach offers robust support for LCVR parameter calibration and performance optimization in optical systems,particularly in polarization imaging applications.
基金Supported by Beijing Natural Science Foundation(Grant No.L241012)the National Natural Science Foundation of China(Grant No.62572468).
文摘LiDAR and camera are two of the most common sensors used in the fields of robot perception,autonomous driving,augmented reality,and virtual reality,where these sensors are widely used to perform various tasks such as odometry estimation and 3D reconstruction.Fusing the information from these two sensors can significantly increase the robustness and accuracy of these perception tasks.The extrinsic calibration between cameras and LiDAR is a fundamental prerequisite for multimodal systems.Recently,extensive studies have been conducted on the calibration of extrinsic parameters.Although several calibration methods facilitate sensor fusion,a comprehensive summary for researchers and,especially,non-expert users is lacking.Thus,we present an overview of extrinsic calibration and discuss diverse calibration methods from the perspective of calibration system design.Based on the calibration information sources,this study classifies these methods as target-based or targetless.For each type of calibration method,further classification was performed according to the diverse types of features or constraints used in the calibration process,and their detailed implementations and key characteristics were introduced.Thereafter,calibration-accuracy evaluation methods are presented.Finally,we comprehensively compare the advantages and disadvantages of each calibration method and suggest directions for practical applications and future research.
文摘Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper equations are one of the main and most efficient methods for estimating stem volume to any merchantable limit of a species.There is currently no taper equation for Eucalyptus species in Nigeria.Therefore,this study developed taper equations for E.camaldulensis in northern Nigeria.Data for this study were obtained from a private plantation in Jalingo Local Government Area,Taraba State,Nigeria.68 trees were felled and sectioned into 1-m bolt across the stem to a merchantable limit of 5 cm,which were used as the fitting dataset.An additional 22 trees were felled and used to validate the taper equations for stem volume estimation.Seven taper equations were initially fitted to the dataset using nonlinear least squares.The best taper equation was then refitted using a nonlinear mixed-effects approach and calibrated using diameters of one to five sections from the butt end.The taper equations were numerically integrated to obtain the stem volume,which was compared with empirical volume equations.The result shows that the Kozak(Can J For Res 27(5):619-629.10.1139/x97-011,1997)equation,which included eight parameters,provided the best fit for predicting section diameters for under and over bark.The mixed-effects taper equation(NLME-TE)explained most stem diameter variations in the fitting dataset(pseudo-R2:0.986-0.987;RMSE:0.547-0.578 cm)without substantial residual trends.The validation showed that the prediction accuracy of the integrated NLME-TE improved as the number of sectional diameter measurements increased,with at least a 35%reduction in volume estimate error.For practical implementation,two calibration sectional diameter measurements taken from the butt end per tree are recommended.This approach would reduce measurement effort and cost while improving model performance.
基金support from the National Natural Science Foundation of China(Grant Nos.U2330206,U2230206,62173068)Sichuan Science and Technology Program(Grants Nos.2024NSFSC1483,2024ZYD0156,2023NSFC1962,DQ202412).
文摘In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system.An output-based event-triggered scheme is first employed to alleviate transmission burden.Accounting for the limited-communication-induced measurement bias,a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation,thereby achieving accurate system state estimates.Subsequently,the Field Programmable Gate Array(FPGA)implementation of the proposed algorithm is also realized with the hope of providing fast bias calibration in practical scenarios.A simulation about a numerical example and a practical example(for gyroscope’s angular velocity bias calibration)on MATLAB is provided to demonstrate the feasibility and effectiveness of the proposed algorithm.
基金supported by the Yunnan Revitalization Talent Support Program(202305AS350029 and 202305AT350005)Yunnan Revitalization Talent Support Program-Science&Technology Champion Project(202105AB160001)+1 种基金Yunnan Key Laboratory of Solar Physics and Space Science(202205AG070009)Yunnan Provincial Science and Technology Department(202401AU070062).
文摘The segmented solar telescope described in this study employs a simultaneous dual-wavelength measurement technique to achieve co-phase alignment.To meet the measurement requirements of a 20μm range,5 nm root mean square precision,and edge jump rates of<10^(−6),this study focused on calibrating the dual-wavelength measurement system for the segmented-mirror solar telescope.Analysis of the relative error in the measurement system revealed that assembly-induced errors such as defocus,translation,scaling,and rotation markedly degrade measurement accuracy.To address these issues,we propose a defocus error compensation algorithm,based on the light intensity distribution of the point spread function(PSF)and an affine transformation model,to calibrate spatial pose deviations across the two measurement channels.A dual-wavelength measurement system was implemented on a segmented-mirror experimental platform for calibration.Experimental results demonstrated that the mean relative error decreased from−0.6423 to−0.0345 nm after calibration,reflecting improved reliability and stability of the co-phase measurements.
基金supported by the Key Technologies R&D Program of Henan Province(No.242102211065)Postgraduate Education Reform and Quality Im-provement Project of Henan Province(No.YJS2025GZZ36).
文摘With the widespread adoption of digital equipment in intelligent substations,testing digital signals in power systems has become an important role for relay protection test equipment.Testing and calibrating digital signals require high accuracy.However,existing methods have low precision,cannot be calibrated at full range for all indexes,and have complex configuration,making them unsuitable for routine calibration work.To solve the above problems,a novel calibration method is designed and implemented using field programmable gate array(FPGA)to achieve accurate input and output time control.Accurate calibration relies on multiple forms of traceability including theoretical value traceability based on waveform comparison,time scale value traceability based on accurate time stamps,and algorithm traceability based on typical algorithms.Compared with other existing methods,the proposed approach reduces the mean absolute error of action time and time measurement by 92.88%,effectively addressing a key industry challenge and offering a valuable reference for further research,application,and standardization.
文摘Considering the drastic variations in the surface elevation of the piedmont region in the Bai Cheng West Area,there is no reference point within the Reference Ground Line(RG line)of the starting point of the synthetic seismic records in the process of calibration of the horizon.Through the analysis of the process and properties of the production of the RG line,in the processing of seismic data,it is indicated that the position of the synthetic data of seismic records is not located at the beginning of the RG line.Rather,it must be at the time point of the seismic profile at the elevation of a datum position of the static value of less than the datum plane.Both the RG line and the elevation static correction value line can easily be seen by computerizing the calculated value of the elevation static correction of the datum plane relating to the seismic section and plotting it on the seismic section.To achieve a good calibration with the synthetic seismogram,it is possible to set the starting point of the synthetic seismogram on the elevation static correction value line that is situated at the place of the Common Mid-Point(CMP).In the current paper,a systematic overview of methods and safety procedures for establishing the seismic interpretation work area and horizon calibration in seismic interpretation has been reviewed,which will form an effective guide towards seismic interpretation under the complicated surface conditions in the Bai Cheng west region.
基金supported by National Key R&D grant from the Ministry of Science and Technology of China(Nos.2021YFA1601600,2023YFA1606200)National Science Foundation of China(Nos.12090062,12105008)the Major State Basic Research Development Program of China.
文摘We present the preparation and measurement of the radioactive isotope^(37)Ar,which was produced using thermal neutrons from a reactor,as a calibration source for liquid xenon time projection chambers.^(37)Ar is a low-energy calibration source with a half-life of 35.01 days,making it suitable for calibration in the low-energy region of liquid xenon dark-matter experiments.Radioactive isotope^(37)Ar was produced by irradiating ^(36)Ar with thermal neutrons.It was subsequently measured in a gaseous xenon time projection chamber(GXe TPC)to validate its radioactivity.Our results demonstrate that^(37)Ar is an effective and viable calibration source that offers precise calibration capabilities in the low-energy domain of xenon-based detectors.
基金Part of the research funding was provided by Tatung University.
文摘To address crop depredation by intelligent species(e.t,macaques)and the habituation from traditional methods,this study proposes an intelligent,closed-loop,adaptive laser deterrence system.A core contribution is an efficient multi-stage Semi-Supervised Learning(SSL)and incremental fine-tuning(IFT)framework,which reduced manual annotation by~60%and training time by~68%.This framework was benchmarked against YOLOv8n,v10n,and v11n.Our analysis revealed that YOLOv12n’s high Signal-to-Noise Ratio(SNR)(47.1%retention)pseudo-labels made it the onlymodel to gain performance(+0.010mAP)fromSSL,allowing it to overtake competitors.Subsequently,in the IFT stress test,YOLOv12n proved most robust(a minimal−0.019 mAP decline),whereas YOLOv10n suffered catastrophic failure(−0.233mAP),highlighting its incompatibility with IFT.Thefinalmodel achieved high performance(mAP@0.5 of 0.947 for macaques,0.946 for laser spots).In Multi-Object Tracking(MOT),this study quantitatively confirms that Bottom-Up Tracking by Sorting(BoT-SORT)(1.88 s avg.tracklet lifetime)significantly outperforms ByteTrack(0.81 s)in identity preservation for visually similar macaques.System integration achieved 480 Frames Per Second(FPS)real-time inference on edge devices.A quadratic polynomial fittingmodel ensured high-precision aiming(RMSE<2 pixels;best 1.2 pixels)by compensating for distortion.To fundamentally solve habituation,an adaptive strategy driven by a Deep Deterministic Policy Gradient(DDPG)framework was introduced.By using a habituation penalty term(Rhabituation)to force unpredictable sequences,theDDPGstrategy achieved a stable 88%average Intrusion Frequency Reduction Rate(IFRR)in field experiments,suppressing habituation in highly intelligent species.This study develops an efficient,precise,low-cost,and habituation-resistant automated wildlife defense system.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R77)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia,the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,through the project number NBU-FFR-2026-2248-02.
文摘The rapid proliferation of multimodal misinformation on social media demands detection frameworks that are not only accurate but also robust to noise,adversarial manipulation,and semantic inconsistency between modalities.Existing multimodal fake news detection approaches often rely on deterministic fusion strategies,which limits their ability to model uncertainty and complex cross-modal dependencies.To address these challenges,we propose Q-ALIGNer,a quantum-inspired multimodal framework that integrates classical feature extraction with quantumstate encoding,learnable cross-modal entanglement,and robustness-aware training objectives.The proposed framework adopts quantumformalism as a representational abstraction,enabling probabilisticmodeling ofmultimodal alignment while remaining fully executable on classical hardware.Q-ALIGNer is evaluated on four widely used benchmark datasets—FakeNewsNet,Fakeddit,Weibo,and MediaEval VMU—covering diverse platforms,languages,and content characteristics.Experimental results demonstrate consistent performance improvements over strong text-only,vision-only,multimodal,and quantum-inspired baselines,including BERT,RoBERTa,XLNet,ResNet,EfficientNet,ViT,Multimodal-BERT,ViLBERT,and QEMF.Q-ALIGNer achieves accuracies of 91.2%,92.9%,91.7%,and 92.1%on FakeNewsNet,Fakeddit,Weibo,and MediaEval VMU,respectively,with F1-score gains of 3–4 percentage points over QEMF.Robustness evaluation shows a reduced adversarial accuracy gap of 2.6%,compared to 7%–9%for baseline models,while calibration analysis indicates improved reliability with an expected calibration error of 0.031.In addition,computational analysis shows that Q-ALIGNer reduces training time to 19.6 h compared to 48.2 h for QEMF at a comparable parameter scale.These results indicate that quantum-inspired alignment and entanglement can enhance robustness,uncertainty awareness,and efficiency in multimodal fake news detection,positioning Q-ALIGNer as a principled and practical content-centric framework for misinformation analysis.
文摘Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.
基金supported by the National Science Foundation of China(Grant Nos.U1530402 and U1930401).
文摘Large-volume presses(LVPs)are widely utilized in diverse research fields—including high-pressure physics,chemistry,materials science,and Earth and planetary sciences—to investigate the physical and chemical properties of materials under extreme high-pressure and hightemperature conditions.A prerequisite for achieving reproducible property measurements is the determination and control of pressure within experimental setups.However,the lack of precise pressure calibration in LVPs hinders the broader application of such devices in ultrahigh-pressure studies.This study employs a suite of standard phase transition-based pressure markers—comprising metallic conductors,semiconductors,and minerals—through both in situ and ex situ identification approaches,to establish pressure calibration curves ranging from 0.4 to>30 GPa for various types of LVP installed at the Center for High Pressure Science and Technology Advanced Research(HPSTAR),Beijing,including piston–cylinder,cubic,and multi-anvil presses.The results provide a unified and traceable pressure reference for highpressure experiments conducted at HPSTAR,while also offering technical guidance and calibration standards for other researchers utilizing similar LVP systems,thereby enabling more consistent comparison between different laboratories.This work facilitates the advancement of LVP research toward broader applications in higher-pressure regimes.
文摘Intrusion detection in Internet of Things(IoT)environments presents challenges due to heterogeneous devices,diverse attack vectors,and highly imbalanced datasets.Existing research on the ToN-IoT dataset has largely emphasized binary classification and single-model pipelines,which often showstrong performance but limited generalizability,probabilistic reliability,and operational interpretability.This study proposes a stacked ensemble deep learning framework that integrates random forest,extreme gradient boosting,and a deep neural network as base learners,with CatBoost as the meta-learner.On the ToN-IoT Linux process dataset,the model achieved near-perfect discrimination(macro area under the curve=0.998),robust calibration,and superior F1-scores compared with standalone classifiers.Interpretability was achieved through SHapley Additive exPlanations–based feature attribution,which highlights actionable drivers ofmalicious behavior,such as command-line patterns,process scheduling anomalies,and CPU usage spikes,and aligns these indicators with MITRE ATT&CK tactics and techniques.Complementary analyses,including cumulative lift and sensitivity-specificity trade-offs,revealed the framework’s suitability for deployment in security operations centers,where calibrated risk scores,transparent explanations,and resource-aware triage are essential.These contributions bridge methodological rigor in artificial intelligence/machine learning with operational priorities in cybersecurity,delivering a scalable and explainable intrusion detection system suitable for real-world deployment in IoT environments.
基金supported by Natural Science Foundation of Jilin Province(20210101468JC)Chinese Academy of Sciences and Local Government Cooperation Project(2023SYHZ0027,23SH04)National Natural Science Foundation of China(12273063&12203078)。
文摘Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calculating the sky area visibility distribution via extinction measurement challenging.To address this issue,we propose the Photometry-Free Sky Area Visibility Estimation(PFSAVE)method.This method uses the standard magnitude of the faintest star observed within a given sky area to estimate visibility.By employing a pertransformation refitting optimization strategy,we achieve a high-precision coordinate transformation model with an accuracy of 0.42 pixels.Using the results of HEALPix segmentation is also introduced to achieve high spatial resolution.Comprehensive analysis based on real allsky images demonstrates that our method exhibits higher accuracy than the extinction-based method.Our method supports both manual and robotic dynamic scheduling,especially under partially cloudy conditions.
基金supported by the National Natural Science Foundation of China(Grant No.:81672743 and 81974464).
文摘Defining an ERBB2(HER2/neu)gene amplification status is critical to guiding human epidermal growth factor receptor 2(HER2)-targeted therapy in breast cancer.Up to 40%of breast cancer patients are reported as having an immunohistochemistry(IHC)of HER22+and requiring additional testing using fluorescence in situ hybridization to confirm the results.This paper aims to establish an automatically weighted calibration deep learning(AWCDL)algorithm to predict ERBB2 amplification based on IHC images.In this study,we applied IHC HER22+images from 1,073 breast cancer patients at three cancer centers in China and extracted 376,099 tiles.Among these,269,664 tiles were used for internal and external validation.The designed AWCDL consists of two steps.In Step 1,the internal validation achieved an accuracy of 89%,with a specificity of 0.89 and a sensitivity of 0.89.The external validation in the two other centers showed an average accuracy of 85%,with a specificity of 0.86 and a sensitivity of 0.82.In Step 2,the model achieved higher accuracy for the slides predicted as negative in Step 1 by automatically calibrating the weight.Collectively,these results suggest that this AWCDL model has successfully proved useful as an alternative method to fluorescence in situ hybridization for assessing the ERBB2 amplification status in breast cancer.
文摘High-precision magnetic field measurements are crucial for understanding Earth’s internal structure,space environment,and dynamic geomagnetic variations.Data from the Fluxgate Magnetometer (FGM) on the Macao Science Satellite-1A (MSS-1A),added to data from other space-based magnetometers,should increase significantly the ability of scientists to observe changes in Earth’s magnetic field over time and space.Additionally,the MSS-1A’s FGM is intended to help identify magnetic disturbances affecting the spacecraft itself.This report focuses on the in-flight calibration of the MSS-1 FGM.A scalar calibration,independent of geomagnetic field models,was performed to correct offsets,sensitivities,and misalignment angles of the FGM.Using seven months of data,we find that the in-flight calibration parameters show good stability.We determined Euler angles describing the rotational relationship between the FGM and the Advanced Stellar Compass (ASC) coordinate system using two approaches:calibration with the CHAOS-7 geomagnetic field model,and simultaneous estimation of Euler angles and Gaussian spherical harmonic coefficients through self-consistent modeling.The accuracy of Euler angles describing the rotation was better than 18 arcsec.The calibrated FGM data exhibit good agreement with the calibrated data of the Vector Field Magnetometer (VFM),which is the primary vector magnetometer of the satellite.These calibration efforts have significantly improved the accuracy of the FGM measurements,which are now providing reliable data for geomagnetic field studies that promise to advance our understanding of the Earth’s magnetic environment.
文摘1.A.Mertha,“‘Stressing Out’:Cadre Calibration and Affective Proximity to the CCP in Reform-Era China”,The China Quarterly,Vol.229,2017,pp.64-85.2.B.L.McCormick,“Book Review of‘The Chinese Communist Party's Capacity to Rule:Ideology,Legitimacy and Party Cohesion’”,The China Journal,Vol.77,2017,pp.161-163.
基金National Natural Science Foundation of China(Nos.42025702,52394251)。
文摘Currently,there is a lack of in-situ or model test results for cone penetration tests(CPTs)conducted in deep,dense sand layers under high overburden stresses,restricting the development of empirical relationships between CPT results and the characteristics of such deep,dense sand layers.This study addresses this gap by proposing an empirical relationship to predict the relative density of dense silica sand based on stress level and cone tip resistance.The relationship was developed through CPTs performed in a calibration chamber using dense sand specimens(with relative densities of 74%-91%)subjected to high stresses(under overburden stresses of 0.5-2.0 MPa)and numerical simulations employing the large deformation finite element method.The Arbitrary Lagrangian Eulerian method was used to regularly regenerate the mesh to prevent soil element distortion around the cone tip.Additionally,the modified Mohr-Coulomb model was integrated to capture the stress-strain behavior of dense silica sand under high stresses.A reasonable agreement was achieved between the numerical and experimental penetration profiles,which verifies the reliability of the numerical model.A sufficient number of parametric analyses were carried out,and then an empirical equation was proposed to establish the relationship between the relative density of dense sand,stress level and cone resistance.The empirical equation provides predictions with acceptable accuracy,as the discrepancies between the predicted and measured relative density values fall within±30%.
