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- 摘要
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- 实验方案
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Resolving Fine Electromechanical Structure of Collagen Fibrils via Sequential Excitation Piezoresponse Force Microscopy
摘要： Collagen is the main protein in extracellular matrix that is found in many connective tissues, and it exhibits piezoelectricity that is expected to correlate with its hierarchical microstructure. Resolving fine electromechanical structure of collagen, however, is challenging, due to its weak piezoresponse, rough topography, and microstructural hierarchy. Here we adopt the newly developed sequential excitation (SE) strategy in combination with piezoresponse force microscopy (PFM) to overcome these difficulties. It excites the local electromechanical response of collagen via a sequence of distinct frequencies, minimizing crosstalk with topography, followed by principal component analysis (PCA) to remove the background noise and simple harmonic oscillator (SHO) model for physical analysis and data reconstruction. These enable us to acquire high fidelity mappings of fine electromechanical response at the nanoscale that correlate with the gap and overlap domains of collagen fibrils, which show substantial improvement over conventional PFM techniques. It also embodies the spirit of big data atomic force microscopy (AFM) that can be readily extended into other applications with targeted data acquisition.
关键词： Principal component analysis,Sequential excitation,Simple harmonic oscillator model,Piezoresponse force microscopy,Collagen
更新于2025-09-19 17:15:36
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Near-Field Radio Holography of Slant-Axis Terahertz Antennas
摘要： Principal component analysis (PCA) and independent component analysis (ICA) for radiated emissions from printed circuits are critically intercompared, revealing similarities and differences of the extracted components between both methods. The input data in this analysis are measured wideband complex-valued magnetic radiated and evanescent fields with quasi-Gaussian spatial distributions. PCA and ICA lead to similar maps of their components when considered as spatial eigenmodes, but independent components exhibit simpler field structure than principal components.
关键词： stochastic fields,principal component analysis (PCA),uncertainty quantification,Independent component analysis (ICA),radiated emissions
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Investigation of Accuracy of various STC Correction Procedures for I-V Characteristics of PV Modules Measured at Different Temperature and Irradiances
摘要： Principal component analysis (PCA) and independent component analysis (ICA) for radiated emissions from printed circuits are critically intercompared, revealing similarities and differences of the extracted components between both methods. The input data in this analysis are measured wideband complex-valued magnetic radiated and evanescent fields with quasi-Gaussian spatial distributions. PCA and ICA lead to similar maps of their components when considered as spatial eigenmodes, but independent components exhibit simpler field structure than principal components.
关键词： Independent component analysis (ICA),principal component analysis (PCA),radiated emissions,uncertainty quantification,stochastic fields
更新于2025-09-19 17:13:59
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On the spectroscopic cum chemometric approach for differentiation and classification of inkjet, laser and photocopier printed documents
摘要： The potential of ATR-FTIR spectroscopy combined with chemometric methods is explored for the rapid and no-destructive forensic investigation of inkjet, laser and photocopier printed documents. The aim of the present study is to ascertain the source of origin of unknown printed documents, i.e., whether it belongs to the laser or inkjet or photocopier devices as well asand also to visualize the intra-variations present in the same types of printed documents. It is observed that these printing inks contain polystyrene, bisphenol A, methyl acrylate and aromatic ethers as the main chemical constituents. The standard normal variate normalization is performed in order to eliminate the differences caused by the amount of toner powder/inks. The discrimination among printed documents is achieved by using chemometric methods including hierarchal cluster analysis and principal component analysis. Further, linear discriminant analysis is used to classify the unknown printed documents into its respective class of printing devices. The present methodology provides robust, non-destructive, reproducible, and simultaneous identification methods for printed documents.
关键词： Principal Component Analysis,Photocopier,ATR-FTIR,Linear Discriminant Analysis,Laser printed,Inkjet
更新于2025-09-19 17:13:59
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Laser-Induced Breakdown Spectroscopy and Principal Component Analysis for Classification of Spectra from Gold-Bearing Ores
摘要： Laser-induced breakdown spectroscopy (LIBS) and principal component analysis (PCA) were applied to the classification of LIBS spectra from gold ores prepared as pressed pellets from pulverized bulk samples. Obtained for each sample were 5000 single-shot LIBS spectra. Although the gold concentrations in the samples were as high as 7.7 μg/g, Au emission lines were not observed in most single-shot LIBS spectra, rendering infeasible the application of the usual ensemble-averaging approach for spectral processing. Instead, a PCA approach was utilized to analyze the collection of single-shot LIBS spectra. Two spectral ranges of 21 nm and 0.15 nm wide were considered, and LIBS variables (i.e., wavelengths) reduced to no more than three principal components. Single-shot spectra containing Au emission lines (positive spectra) were discriminated by PCA from those without the spectral feature (negative spectra) in a spectral range of less than 1 nm wide around the Au(I) 267.59 nm emission line. Assuming a discrete gold distribution at very low concentration, LIBS sampling of gold particles seemed unlikely, therefore, positive spectra were considered as data outliers. Detection of data outliers was possible using two PCA statistical parameters, i.e., sample residual and Mahalanobis distance. Results from such a classification were compared with a standard database created with positive spectra identified with a filtering algorithm that rejected spectra with an Au intensity below the smallest detectable analytical LIBS signal (i.e., below the LIBS limit of detection). The PCA approach successfully identified 100% of the data outliers when compared with the standard database. False identifications in the multivariate approach were attributed to variations in shot-to-shot intensity and the presence of interfering emission lines.
关键词： gold ores analysis,Laser-induced breakdown spectroscopy,PCA,data outliers,principal component analysis,LIBS
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Impact of Transportation on Indian Roads, on PV Modules
摘要： This paper addresses the application of rotor speed signal for the detection and diagnosis of ball bearing faults in rotating electrical machines. Many existing techniques for bearing fault diagnosis (BFD) rely on vibration signals or current signals. However, vibration- or current-based BFD techniques suffer from various challenges that must be addressed. As an alternative, this paper takes the initial step of investigating the efficiency of rotor speed monitoring for BFD. The bearing failure modes are reviewed and their effects on the rotor speed signal are described. Based on this analysis, a novel BFD technique, the rotor speed-based BFD (RSB-BFD) method under variable speed and constant load conditions, is proposed to provide a benefit in terms of cost and simplicity. The proposed RSB-BFD method exploits the absolute value-based principal component analysis (PCA), which improves the performance of classical PCA by using the absolute value of weights and the sum square error. The performance and effectiveness of the RSB-BFD method is demonstrated using an experimental setup with a set of realistic bearing faults in the outer race, inner race, and balls.
关键词： principal component analysis (PCA),rotor speed,sum square error,Bearing fault diagnosis (BFD),variable speed
更新于2025-09-19 17:13:59
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Laser-induced fluorescence spectroscopy for early disease detection in grapefruit plants
摘要： Both biotic and abiotic stress causes considerable decrease in chlorophyll content in plant leaves which provide the means of early disease diagnosis. The emergence of disease affects the fluorescence of phenolic compounds and chlorophyll which have been appeared at 530, 686 and 735 nm. It has been found that the intensity of emission band of phenolic compounds at 530 nm increases and that of chlorophyll at 735 nm decreases with the onset of disease. Statistical analysis through principal component analysis (PCA) and partial least square regression (PLSR) has been performed which demonstrated the classification of apparently healthy leaf sites with diseased ones which provide the basis for the detection of disease at early stages. PLSR model was validated through the coefficient of determination (R2), standard error of prediction (SEP) and standard error of calibration (SEC) with the values 0.99, 0.394 and 0.401 which authenticated the model. The prediction accuracy of the model was evaluated through root mean square error in prediction (RMSEP) of 0.14 by predicting 22 unknown emission spectra of different leaf sites. Both PCA and PLSR models produced similar results and proved fluorescence spectroscopy as an excellent tool for early disease detection in plants.
关键词： Early disease diagnosis,Principal component analysis (PCA),Chlorophyll fluorescence,Partial least square regression (PLSR),Phenolic compounds
更新于2025-09-19 17:13:59
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[IEEE 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) - Delhi, India (2018.10.22-2018.10.24)] 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) - Adaptive Frequency Estimation Technique for Grid Connected Photovoltaic System
摘要： Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in common gene set collections, however, testing is often performed with nearly as many gene sets as underlying genomic variables. To address the challenge to statistical power posed by large gene set collections, we have developed spectral gene set filtering (SGSF), a novel technique for independent filtering of gene set collections prior to gene set testing. The SGSF method uses as a filter statistic the p-value measuring the statistical significance of the association between each gene set and the sample principal components (PCs), taking into account the significance of the associated eigenvalues. Because this filter statistic is independent of standard gene set test statistics under the null hypothesis but dependent under the alternative, the proportion of enriched gene sets is increased without impacting the type I error rate. As shown using simulated and real gene expression data, the SGSF algorithm accurately filters gene sets unrelated to the experimental outcome resulting in significantly increased gene set testing power.
关键词： screening-testing,gene set enrichment,random matrix theory,Gene set testing,principal component analysis,Tracy-Widom
更新于2025-09-19 17:13:59
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[IEEE 2019 8th International Conference on Renewable Energy Research and Applications (ICRERA) - Brasov, Romania (2019.11.3-2019.11.6)] 2019 8th International Conference on Renewable Energy Research and Applications (ICRERA) - Aggregation of Wind, Photovoltaic and Thermal Power with Demand Response
摘要： Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in common gene set collections, however, testing is often performed with nearly as many gene sets as underlying genomic variables. To address the challenge to statistical power posed by large gene set collections, we have developed spectral gene set filtering (SGSF), a novel technique for independent filtering of gene set collections prior to gene set testing. The SGSF method uses as a filter statistic the p-value measuring the statistical significance of the association between each gene set and the sample principal components (PCs), taking into account the significance of the associated eigenvalues. Because this filter statistic is independent of standard gene set test statistics under the null hypothesis but dependent under the alternative, the proportion of enriched gene sets is increased without impacting the type I error rate. As shown using simulated and real gene expression data, the SGSF algorithm accurately filters gene sets unrelated to the experimental outcome resulting in significantly increased gene set testing power.
关键词： screening-testing,gene set enrichment,random matrix theory,Gene set testing,principal component analysis,Tracy-Widom
更新于2025-09-19 17:13:59
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[IEEE 2020 IEEE 33rd International Conference on Micro Electro Mechanical Systems (MEMS) - Vancouver, BC, Canada (2020.1.18-2020.1.22)] 2020 IEEE 33rd International Conference on Micro Electro Mechanical Systems (MEMS) - 3D Laser Nanoprinting
摘要： Digital phantoms are vital for various biomedical researches. Traditional phantoms include theoretical models and voxel models reconstructed from medical images. It has been demonstrated that the homogeneous phantom filled with uniform tissue is accurate enough for wearable antenna design, body-centric channel modeling, etc. Therefore, it is interesting and necessary to investigate the novel approach of generating digital phantoms using an optical noncontact measurement system. In this letter, the point cloud data are first obtained; then, they are simplified via principal component analysis; finally, by applying surface reconstruction and mesh simplification techniques, a digital Chinese phantom is established. To verify the usability of the phantom, numerical calculation is performed to check E-fields at different positions on the body. Results sufficiently prove the feasibility of the train of thought presented in this letter.
关键词： noncontact measurement system,point cloud data,Digital phantom,numerical calculation,surface reconstruction,principal component analysis (PCA)
更新于2025-09-19 17:13:59