- 标题
- 摘要
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- 实验方案
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REGULARIZATION IMAGING ALGORITHM WITH ACCURATE G MATRIX FOR NEAR-FIELD MMW SYNTHETIC APERTURE IMAGING RADIOMETER
摘要： In order to improve the reconstruction accuracy of near-?eld SAIR, a novel regularization imaging algorithm based on an accurate G matrix is proposed in this paper. Due to the fact that the regularization reconstruction is usually an underdetermined problem, inaccurate operation matrix G will lead to great reconstruction error in the imaging results, or even the normal imaging cannot be obtained. In this paper, we establish an accurate G matrix based on the accurate imaging model of near-?eld SAIR. Compared with the traditional G matrix with some unnecessary approximations, the proposed G matrix without approximation can improve the reconstruction accuracy e?ectively. For improving the accuracy of matrix G further, the corresponding parameters are corrected according to the RMSE between the imaging results of the regularization method and modi?ed FFT method which is not sensitive to the parameters’ change. The e?ectiveness of this calibration method has been tested by 1D simulation experiments. Moreover, the 2D simulation experiments demonstrate that the proposed accurate G matrix can improve the imaging accuracy of regularization method e?ectively. Finally, the 1D imaging experiment is performed to test the e?ectiveness of the proposed method for the actual synthetic aperture imaging further.
关键词： near-field MMW synthetic aperture imaging radiometer,Regularization imaging algorithm,accurate G matrix,reconstruction accuracy
更新于2025-09-09 09:28:46
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Diagnostic Accuracy of Glaucoma With Sector-Based and a New Total Profile–Based Analysis of Neuroretinal Rim and Retinal Nerve Fiber Layer Thickness
摘要： PURPOSE. To compare the diagnostic accuracy of conventional sector-based analysis with a method devised to detect the smallest localized neuroretinal rim and retinal nerve fiber layer thickness (RNFLT) damage. METHODS. One eye of 151 glaucoma patients and 83 healthy controls (median age and MD, 71.7 and 66.7 years, and (cid:2)3.6 and (cid:2)0.3 dB, respectively) was imaged with spectral-domain optical coherence tomography (OCT). Bruch’s membrane opening-minimum rim width (BMO-MRW) and RNFLT were determined at 18 intervals and also averaged for each sector. A classification of glaucoma was made with sectoral analysis when the sectoral value was below the 1%, 5%, or 10% normative limit (from an independent normative dataset); and with total analysis when a given number of measurements was below the 1%, 5%, or 10% normative limit. RESULTS. With the 1% normative limit, BMO-MRW sectoral analysis yielded sensitivity of 87% and specificity of 92%; while at the same specificity (92%), total analysis yielded sensitivity of 88%. With RNFLT, sectoral analysis yielded sensitivity of 85% and specificity of 95%; while at the same specificity (95%), total analysis yielded sensitivity of 83%. The results for the 5% and 10% normative limits yielded lower specificity but higher sensitivity. In the whole glaucoma population, none of the sensitivity values of the sectoral and total analysis at the same specificities were statistically different. CONCLUSIONS. The diagnostic accuracy of sectoral analysis was equivalent to total analysis. These results indicate that BMO-MRW and RNFLT defects were wide and deep enough for detection by conventional sectoral analysis.
关键词： diagnostic accuracy,neuroretinal rim,retinal nerve fiber layer
更新于2025-09-09 09:28:46
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Improving Color Accuracy of Colorimetric Sensors
摘要： Accurate measurements of re?ectance and color require spectrophotometers with prices often exceeding $3000. Recently, new “color instruments” became available with much lower prices, thanks to the availability of inexpensive colorimetric sensors. We investigated the Node+ChromaPro and the Color Muse, launched in 2015 and 2016 by Variable Inc. Both instruments are colorimeters, combining a colorimetric sensor with LED lighting. We investigated color accuracy compared to a high-end spectrophotometer from BYK Gardner. With different sets of samples we ?nd for the Node an average value of dECMC (1:1) = 1.50, and a maximum of 7.86, when comparing with the 45? geometry of the spectrophotometer. Utilizing measurement data on the Spectral Power Distributions of the LEDs, we developed three methods to improve color accuracy as compared to the spectrophotometer data. We used these methods on different sets of samples with various degrees of gloss, both for training the models underlying the methods and for independent tests of model accuracy. Average color accuracy of the Node+ChromaPro improves from dECMC (1:1) = 1.82 to 1.16 with respect to spectrophotometer data. The percentage of samples with dECMC (1:1) < 1.0 increases from 30.9% (uncorrected) to 64%. With the improved color accuracy, these sensors become useful for many more applications.
关键词： measurement accuracy,colorimetric sensor
更新于2025-09-04 15:30:14
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Onset Classification in Hemodynamic Signals Measured during Three Working Memory Tasks Using Wireless Functional Near-Infrared Spectroscopy
摘要： Wireless wearable functional near-infrared spectroscopy (fNIRS) has attracted growing attention as a candidate for real-life brain monitoring systems. It is important to determine the onsets at which neuronal activation is evoked by cognitive status in real-time analysis. We propose a machine learning approach for the classification of cognitive event onsets (CogEOs) in hemodynamic signals during three cognitive tasks. The approach does not require a threshold to be set or additional measurement for the rest state. A support vector machine is trained by labeled features obtained from the mean amplitude of hemodynamic changes and then predicts the type of onset points. The problems caused by the imbalance between CogEOs and non-event onsets (NonEO) are solved by oversampling the feature samples labeled by cognitive events. By oversampling, the classification accuracy from an average of five classification scores reaches 74%, 77%, and 75% for the simple arithmetic, 1-back and 2-back tasks. We achieve the best onset classification performance when the NonEOs are randomly distributed and when the subject is performing the 1-back task. Our study extends fNIRS to real-life applications by detecting the time point when brain activation starts among random observations using machine learning without additional triggers or threshold settings.
关键词： functional near-infrared spectroscopy,onset classification,and working memory,classification accuracy
更新于2025-09-04 15:30:14
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Impact of the Acquisition Geometry of Very High-Resolution Pléiades Imagery on the Accuracy of Canopy Height Models over Forested Alpine Regions
摘要： This work focuses on the accuracy estimation of canopy height models (CHMs) derived from image matching of Pléiades stereo imagery over forested mountain areas. To determine the height above ground and hence canopy height in forest areas, we use normalised digital surface models (nDSMs), computed as the differences between external high-resolution digital terrain models (DTMs) and digital surface models (DSMs) from Pléiades image matching. With the overall goal of testing the operational feasibility of Pléiades images for forest monitoring over mountain areas, two questions guide this work whose answers can help in identifying the optimal acquisition planning to derive CHMs. Specifically, we want to assess (1) the benefit of using tri-stereo images instead of stereo pairs, and (2) the impact of different viewing angles and topography. To answer the first question, we acquired new Pléiades data over a study site in Canton Ticino (Switzerland), and we compare the accuracies of CHMs from Pléiades tri-stereo and from each stereo pair combination. We perform the investigation on different viewing angles over a study area near Ljubljana (Slovenia), where three stereo pairs were acquired at one-day offsets. We focus the analyses on open stable and on tree covered areas. To evaluate the accuracy of Pléiades CHMs, we use CHMs from aerial image matching and airborne laser scanning as reference for the Ticino and Ljubljana study areas, respectively. For the two study areas, the statistics of the nDSMs in stable areas show median values close to the expected value of zero. The smallest standard deviation based on the median of absolute differences (σMAD) was 0.80 m for the forward-backward image pair in Ticino and 0.29 m in Ljubljana for the stereo images with the smallest absolute across-track angle (?5.3?). The differences between the highest accuracy Pléiades CHMs and their reference CHMs show a median of 0.02 m in Ticino with a σMAD of 1.90 m and in Ljubljana a median of 0.32 m with a σMAD of 3.79 m. The discrepancies between these results are most likely attributed to differences in forest structure, particularly tree height, density, and forest gaps. Furthermore, it should be taken into account that temporal vegetational changes between the Pléiades and reference data acquisitions introduce additional, spurious CHM differences. Overall, for narrow forward–backward angle of convergence (12?) and based on the used software and workflow to generate the nDSMs from Pléiades images, the results show that the differences between tri-stereo and stereo matching are rather small in terms of accuracy and completeness of the CHM/nDSMs. Therefore, a small angle of convergence does not constitute a major limiting factor. More relevant is the impact of a large across-track angle (19?), which considerably reduces the quality of Pléiades CHMs/nDSMs.
关键词： acquisition geometry,canopy height model,forested mountain,very high-resolution Pléiades imagery,accuracy assessment
更新于2025-09-04 15:30:14
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[IEEE 2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) - Rochester, MN, USA (2017.5.7-2017.5.10)] 2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) - The calibration of targeting errors for an ultrasound-guided high-intensity focused ultrasound system
摘要： Accurate targeting is one indispensable feature of image-guided high-intensity focused ultrasound (HIFU) systems for treatment safety and efficacy. In our previously developed ultrasound-guided phased-array HIFU system, a rotatable imaging probe was mounted into the central hole of applicator for targeting and monitoring. Two-dimensional image sequence of different imaging planes can be obtained by rotation of the probe. The misalignment between the spots predetermined in the image and the spots sonicated in the tissue can result in the ablation of normal tissue outside the targeting volume, and thus targeting error is unavoidable. An acrylic plate internally placing two flat-head bolts was constructed to measure and calibrate the targeting error. The imaging planes were switched from ?90° to 90° with a 30° step, and the targeting errors were measured 12 times for each of these planes before and after calibration. The targeting errors in other imaging planes could be estimated by linear interpolation using the measured errors in the nearest two imaging planes. The coordinates of the spots to be sonicated were corrected in consideration of the targeting errors in the selected imaging plane. After calibration, the mean targeting errors were reduced to 0.30~0.68 mm from 0.86~1.74 mm. Besides, in the ex vivo experiment the needle-thermocouple tip was used as the target which could be identified in the image. The temperature rise measured by the thermocouple during sonication was in accordance with the theoretical result. In conclusion, the calibration of targeting errors is effective for our system, and the targeting accuracy is also capable to ensure safe sonication.
关键词： Phased-array,Ultrasound-guided high-intensity focused ultrasound (USgHIFU),Targeting accuracy,Calibration
更新于2025-09-04 15:30:14
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[IEEE 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA) - Paris, France (2018.10.14-2018.10.17)] 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA) - From Solar Microgrid Simulation to Field Deployment: Accuracy and Uncertainties
摘要： Economical, stand-alone, solar microgrids can be quickly implemented in most un-electrified regions of the world. Solar resource maps developed by the National Aeronautics and Space Administration (NASA) and the National Renewable Energy Laboratory (NREL), together with HOMER Pro software, have been widely used to determine the optimal design of microgrids. Repercussions of imprecise predictions of solar resources and electrical power generation lead to an increased likelihood of energy shortage in a stand-alone microgrid, or increases overall project costs. Actual solar energy productions of two sites in Kerala, India, were compared with solar electricity generation, predicted by the HOMER Pro tool. For both test sites, the results showed that the simulated, solar production was within 8.1% of the actual annual production. However, monthly variations in solar production led to unanticipated energy shortages in the simulated microgrids. These findings reaffirm the inexorable need of the following actions for cost-effective design of microgrids: a) systematic analysis of reliability of electrical supply, and b) deployment of schemes for demand response and flexible load. Statistical analysis of temporal variation of solar irradiance in the United States were used to inform recommendations for stand-alone microgrid design.
关键词： accuracy,HOMER,solar,resource,model,microgrid,design
更新于2025-09-04 15:30:14
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Performance Evaluation of Radiation Sensors for the Solar Energy Sector
摘要： Rotating Shadowband Irradiometers (RSI) and SPN1 Sunshine Pyranometers allow determining the diffuse and direct components of solar radiation without sun trackers; they can be deployed in networks for continuous field operation with modest maintenance. Their performances are evaluated here by analyzing their errors with respect to well characterized references. The analysis is based on 1-minute data recorded over a 15-month period at the Payerne BSRN station in Switzerland. The analysis was applied both to the whole dataset and data subsets reflecting particular conditions to allow a better understanding of how instrument performance depends on such conditions.
关键词： accuracy,RSI,rotating shadowband irradiometer,shortwave radiation,pyranometer,SPN1,uncertainty
更新于2025-09-04 15:30:14
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Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes
摘要： Satellite remote sensing is a highly useful tool for monitoring chlorophyll-a concentration (Chl-a) in water bodies. Remote sensing algorithms based on near-infrared-red (NIR-red) wavelengths have demonstrated great potential for retrieving Chl-a in inland waters. This study tested the performance of a recently developed NIR-red based algorithm, SAMO-LUT (Semi-Analytical Model Optimizing and Look-Up Tables), using an extensive dataset collected from five Asian lakes. Results demonstrated that Chl-a retrieved by the SAMO-LUT algorithm was strongly correlated with measured Chl-a (R2 = 0.94), and the root-mean-square error (RMSE) and normalized root-mean-square error (NRMS) were 8.9 mg?m?3 and 72.6%, respectively. However, the SAMO-LUT algorithm yielded large errors for sites where Chl-a was less than 10 mg?m?3 (RMSE = 1.8 mg?m?3 and NRMS = 217.9%). This was because differences in water-leaving radiances at the NIR-red wavelengths (i.e., 665 nm, 705 nm and 754 nm) used in the SAMO-LUT were too small due to low concentrations of water constituents. Using a blue-green algorithm (OC4E) instead of the SAMO-LUT for the waters with low constituent concentrations would have reduced the RMSE and NRMS to 1.0 mg?m?3 and 16.0%, respectively. This indicates (1) the NIR-red algorithm does not work well when water constituent concentrations are relatively low; (2) different algorithms should be used in light of water constituent concentration; and thus (3) it is necessary to develop a classification method for selecting the appropriate algorithm.
关键词： Asian lakes,blue-green algorithms,chlorophyll-a concentration,accuracy assessment,NIR-red algorithms
更新于2025-09-04 15:30:14
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Characterizing wafer stage transmission errors via binary decision diagram and dynamic fault tree
摘要： The wafer stage, as a key subsystem of the dual-stage lithographic tool, possesses the characteristic of high moving accuracy. The fault tree analysis (FTA), which plays an important role in the design stage of the wafer stage, is performed to distinguish the critical events leading to the overall transmission error. However, in view of the complexity of the wafer stage’s structure and operation mechanism, the binary decision diagrams and dynamic fault tree analysis methods are implemented in this paper to obtain a simplified calculation process and a supplement with the dynamic characteristic respectively. This is not achieved by the traditional FTA method. The event “wafer stage’s repetitive error along X axis exceeds 5 nm” is viewed as the top event of the fault tree. In this paper, we identify the critical factors affecting the kinematic accuracy of the wafer stage.
关键词： Fault tree analysis,Binary decision diagram,Wafer stage,Dynamic fault tree analysis,Kinematic accuracy
更新于2025-09-04 15:30:14