Various novel conjugated polymers(CPs)have been developed for organic photodetectors(OPDs),but their application to practical image sensors such as X-ray,R/G/B,and fingerprint sensors is rare.In this article,we report...Various novel conjugated polymers(CPs)have been developed for organic photodetectors(OPDs),but their application to practical image sensors such as X-ray,R/G/B,and fingerprint sensors is rare.In this article,we report the entire process from the synthesis and molecular engineering of novel CPs to the development of OPDs and fingerprint image sensors.We synthesized six benzo[1,2-d:4,5-d’]bis(oxazole)(BBO)-based CPs by modifying the alkyl side chains of the CPs.Several relationships between the molecular structure and the OPD performance were revealed,and increasing the number of linear octyl side chains on the conjugated backbone was the best way to improve Jph and reduce Jd in the OPDs.The optimized CP demonstrated promising OPD performance with a responsivity(R)of 0.22 A/W,specific detectivity(D^(*))of 1.05×10^(13)Jones at a bias of-1 V,rising/falling response time of 2.9/6.9μs,and cut-off frequency(f_(-3dB))of 134 kHz under collimated 530 nm LED irradiation.Finally,a fingerprint image sensor was fabricated by stacking the POTB1-based OPD layer on the organic thin-film transistors(318 ppi).The image contrast caused by the valleys and ridges in the fingerprints was obtained as a digital signal.展开更多
The fingerprint image quality has a significant effect on the performance of automatic fingerprint identification system. A method for measure of fingerprint image quality based on Fourier spectrum is proposed. First ...The fingerprint image quality has a significant effect on the performance of automatic fingerprint identification system. A method for measure of fingerprint image quality based on Fourier spectrum is proposed. First the band frequency which corresponds to the global average period of ridge is searched. Then the quality score of the fingerprint image is computed by measuring relative magnitude of the band frequency components. The method is verified to have good performance by experiments.展开更多
An adaptive algorithm for removing false ridges,bridges and filling gaps in binary fingerprint images based on morphological operations is presented.A novel procedure for structuring elements design based on the speci...An adaptive algorithm for removing false ridges,bridges and filling gaps in binary fingerprint images based on morphological operations is presented.A novel procedure for structuring elements design based on the specific fingerprint characteristic is described.Using the images from FVC2000 database,we have compared our method proposed here with the approach proposed by other ones.The Experimental results have demonstrated the efficiency of our method.展开更多
With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-base...With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based estimation.Since the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed.First,an image fingerprint construction is proposed for training data.After the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline interpolation.Then,the linear mapping and the gray-color transformation method are proposed to form the color image fingerprint.Second,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance improvement.At last,an experiment is carried out to evaluate the estimation performance.Compared with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.展开更多
This study introduces an innovative contour detection algorithm,PeakCET,designed for rapid and efficient analysis of natural product image fingerprints using comprehensive two-dimensional gas chromatogram(GC×GC)....This study introduces an innovative contour detection algorithm,PeakCET,designed for rapid and efficient analysis of natural product image fingerprints using comprehensive two-dimensional gas chromatogram(GC×GC).This method innovatively combines contour edge tracking with affinity propagation(AP)clustering for peak detection in GC×GC fingerprints,the first in this field.Contour edge tracking signif-icantly reduces false positives caused by“burr”signals,while AP clustering enhances detection accuracy in the face of false negatives.The efficacy of this approach is demonstrated using three medicinal products derived from Curcuma wenyujin.PeakCET not only performs contour detection but also employs inter-group peak matching and peak-volume percentage calculations to assess the compositional similarities and differences among various samples.Furthermore,this algorithm compares the GC×GC fingerprints of Radix/Rhizoma Curcumae Wenyujin with those of products from different botanical origins.The findings reveal that genetic and geographical factors influence the accumulation of secondary metabolites in various plant tissues.Each sample exhibits unique characteristic components alongside common ones,and vari-ations in content may influence their therapeutic effectiveness.This research establishes a foundational data-set for the quality assessment of Curcuma products and paves the way for the application of computer vision techniques in two-dimensional(2D)fingerprint analysis of GC×GC data.展开更多
Fluorescence-based imaging has emerged as a powerful tool for detecting latent fingerprints(LFPs).However,existing fluorescent developers face challenges in differentiating friction ridges from backgrounds with intrac...Fluorescence-based imaging has emerged as a powerful tool for detecting latent fingerprints(LFPs).However,existing fluorescent developers face challenges in differentiating friction ridges from backgrounds with intractable fluorescence,and to date,post-processing techniques fail to effectively enhance poorly visualized fingerprints.Herein,trichromatic-emitting carbon dots(CDs)were synthesized via a one-step solvothermal method using dyes and ethylene glycol as precursors.Experimental and theoretical results revealed that the high photostability and photobleaching resistance of the synthesized CDs originated from the hydrogen-bond interactions between the carbonaceous matrix and dye-related functional groups and fragments,which served as the fluorophore of these Dye-CDs.By combining CDs with diatomite,the resulting composite powders demonstrated high sensitivity and selectivity in fluorescence visualization of both fresh and aging LFPs.Using a typical powdering method with Dye-CDs/diatomite stored for 30 days,levels 1–3 detailed features of LFPs deposited on various porous or non-porous substrates were identified with high contrast.The developed tunable multicolor post-processing technique,achieved by separating ridge patterns from background noise,ensured highresolution details and overcame the challenges of weakly developed fingerprints.Thus,the proposed dual-mode strategy provides a promising solution for practical fingerprint imaging.展开更多
A new class of near-infrared(NIR)fluorescent organoboron AIEgens was successfully developed for latent fingerprints(LFPs)imaging.They exhibit real-time and in situ high-resolution imaging performance at 1-3 levels of ...A new class of near-infrared(NIR)fluorescent organoboron AIEgens was successfully developed for latent fingerprints(LFPs)imaging.They exhibit real-time and in situ high-resolution imaging performance at 1-3 levels of LFPs by spraying method.In addition,we systematically elucidate the fingerprint imaging mechanism of these AIEgens.Significantly,the excellent level 3 structural imaging capabilities enable the application of them for analyzing incomplete LFPs and identifying individuals in different scenarios.展开更多
Frequency combs show various applications in molecular fingerprinting,imaging,communications,and so on.In the terahertz frequency range,semiconductor-based quantum cascade lasers(QCLs)are ideal platforms for realizing...Frequency combs show various applications in molecular fingerprinting,imaging,communications,and so on.In the terahertz frequency range,semiconductor-based quantum cascade lasers(QCLs)are ideal platforms for realizing the frequency comb operation.Although self-started frequency comb operation can be obtained in free-running terahertz QCLs due to the four-wave mixing locking effects,resonant/off-resonant microwave injection,phase locking,and femtosecond laser based locking techniques have been widely used to broaden and stabilize terahertz QCL combs.These active locking methods indeed show significant effects on the frequency stabilization of terahertz QCL combs,but they simultaneously have drawbacks,such as introducing large phase noise and requiring complex optical coupling and/or electrical circuits.Here,we demonstrate Farey tree locking of terahertz QCL frequency combs under microwave injection.The frequency competition between the Farey fraction frequency and the cavity round-trip frequency results in the frequency locking of terahertz QCL combs,and the Farey fraction frequencies can be accurately anticipated based on the downward trend of the Farey tree hierarchy.Furthermore,dual-comb experimental results show that the phase noise of the dual-comb spectral lines is significantly reduced by employing the Farey tree locking method.These results pave the way to deploying compact and low phase noise terahertz frequency comb sources.展开更多
基金funded by the National Research Foundation(NRF)of Korea(2020M3H4A3081816,RS-2023-00304936,and RS-2024-00398065).
文摘Various novel conjugated polymers(CPs)have been developed for organic photodetectors(OPDs),but their application to practical image sensors such as X-ray,R/G/B,and fingerprint sensors is rare.In this article,we report the entire process from the synthesis and molecular engineering of novel CPs to the development of OPDs and fingerprint image sensors.We synthesized six benzo[1,2-d:4,5-d’]bis(oxazole)(BBO)-based CPs by modifying the alkyl side chains of the CPs.Several relationships between the molecular structure and the OPD performance were revealed,and increasing the number of linear octyl side chains on the conjugated backbone was the best way to improve Jph and reduce Jd in the OPDs.The optimized CP demonstrated promising OPD performance with a responsivity(R)of 0.22 A/W,specific detectivity(D^(*))of 1.05×10^(13)Jones at a bias of-1 V,rising/falling response time of 2.9/6.9μs,and cut-off frequency(f_(-3dB))of 134 kHz under collimated 530 nm LED irradiation.Finally,a fingerprint image sensor was fabricated by stacking the POTB1-based OPD layer on the organic thin-film transistors(318 ppi).The image contrast caused by the valleys and ridges in the fingerprints was obtained as a digital signal.
文摘The fingerprint image quality has a significant effect on the performance of automatic fingerprint identification system. A method for measure of fingerprint image quality based on Fourier spectrum is proposed. First the band frequency which corresponds to the global average period of ridge is searched. Then the quality score of the fingerprint image is computed by measuring relative magnitude of the band frequency components. The method is verified to have good performance by experiments.
基金supported by the National Nature Science Foundation of China under Grant No.60605007J
文摘An adaptive algorithm for removing false ridges,bridges and filling gaps in binary fingerprint images based on morphological operations is presented.A novel procedure for structuring elements design based on the specific fingerprint characteristic is described.Using the images from FVC2000 database,we have compared our method proposed here with the approach proposed by other ones.The Experimental results have demonstrated the efficiency of our method.
文摘With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based estimation.Since the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed.First,an image fingerprint construction is proposed for training data.After the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline interpolation.Then,the linear mapping and the gray-color transformation method are proposed to form the color image fingerprint.Second,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance improvement.At last,an experiment is carried out to evaluate the estimation performance.Compared with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.
基金supported by Hunan 2011 Collaborative Innovation Center of Chemical Engineering&Technology with Environmental Benignity and Effective Resource Utilization,Hunan Province Natural Science Fund,China(Grant Nos.:2020JJ4569,2023JJ60378)Hunan Province College Students'Innovation and Entrepreneurship Training Program,China(Grant Nos.:S202110530044,S202210530048).
文摘This study introduces an innovative contour detection algorithm,PeakCET,designed for rapid and efficient analysis of natural product image fingerprints using comprehensive two-dimensional gas chromatogram(GC×GC).This method innovatively combines contour edge tracking with affinity propagation(AP)clustering for peak detection in GC×GC fingerprints,the first in this field.Contour edge tracking signif-icantly reduces false positives caused by“burr”signals,while AP clustering enhances detection accuracy in the face of false negatives.The efficacy of this approach is demonstrated using three medicinal products derived from Curcuma wenyujin.PeakCET not only performs contour detection but also employs inter-group peak matching and peak-volume percentage calculations to assess the compositional similarities and differences among various samples.Furthermore,this algorithm compares the GC×GC fingerprints of Radix/Rhizoma Curcumae Wenyujin with those of products from different botanical origins.The findings reveal that genetic and geographical factors influence the accumulation of secondary metabolites in various plant tissues.Each sample exhibits unique characteristic components alongside common ones,and vari-ations in content may influence their therapeutic effectiveness.This research establishes a foundational data-set for the quality assessment of Curcuma products and paves the way for the application of computer vision techniques in two-dimensional(2D)fingerprint analysis of GC×GC data.
基金supported by the Key Laboratory of Impression Evidence Examination and Identification Technology,Criminal Investigation Police University of China,Ministry of Public Security,People’s Republic of China(No.2018HJKF12)the Natural Science Foundation of Liaoning Province(No.2023-BS-081)the Foundation of Education Department of Liaoning Province(Nos.LJKMZ20221366 and LJKQZ20222296).
文摘Fluorescence-based imaging has emerged as a powerful tool for detecting latent fingerprints(LFPs).However,existing fluorescent developers face challenges in differentiating friction ridges from backgrounds with intractable fluorescence,and to date,post-processing techniques fail to effectively enhance poorly visualized fingerprints.Herein,trichromatic-emitting carbon dots(CDs)were synthesized via a one-step solvothermal method using dyes and ethylene glycol as precursors.Experimental and theoretical results revealed that the high photostability and photobleaching resistance of the synthesized CDs originated from the hydrogen-bond interactions between the carbonaceous matrix and dye-related functional groups and fragments,which served as the fluorophore of these Dye-CDs.By combining CDs with diatomite,the resulting composite powders demonstrated high sensitivity and selectivity in fluorescence visualization of both fresh and aging LFPs.Using a typical powdering method with Dye-CDs/diatomite stored for 30 days,levels 1–3 detailed features of LFPs deposited on various porous or non-porous substrates were identified with high contrast.The developed tunable multicolor post-processing technique,achieved by separating ridge patterns from background noise,ensured highresolution details and overcame the challenges of weakly developed fingerprints.Thus,the proposed dual-mode strategy provides a promising solution for practical fingerprint imaging.
基金supported by the Topnotch Talents Program of Henan Agricultural University(30501032)the National Natural Science Foundation of China(52003228 and 52273197)+2 种基金the Science,Technology and Innovation Commission of Shenzhen Municipality(JCYJ2021324134613038)the Shenzhen Key Laboratory of Functional Aggregate Materials(ZDSYS20211021111400001)Shenzhen Peacock Team Project(KQTD20210811090142053).
文摘A new class of near-infrared(NIR)fluorescent organoboron AIEgens was successfully developed for latent fingerprints(LFPs)imaging.They exhibit real-time and in situ high-resolution imaging performance at 1-3 levels of LFPs by spraying method.In addition,we systematically elucidate the fingerprint imaging mechanism of these AIEgens.Significantly,the excellent level 3 structural imaging capabilities enable the application of them for analyzing incomplete LFPs and identifying individuals in different scenarios.
基金supported by the Innovation Program for Quantum Science and Technology(2023ZD0301000)the National Science Fund for Distinguished Young Scholars(62325509)+2 种基金the National Natural Science Foundation of China(62235019,61875220,61927813,61991430,62035005,62105351,and 62305364)the“From 0 to 1”Innovation Program of the Chinese Academy of Sciences(ZDBS-LY-JSC009)the CAS Project for Young Scientists in Basic Research(YSBR-069).
文摘Frequency combs show various applications in molecular fingerprinting,imaging,communications,and so on.In the terahertz frequency range,semiconductor-based quantum cascade lasers(QCLs)are ideal platforms for realizing the frequency comb operation.Although self-started frequency comb operation can be obtained in free-running terahertz QCLs due to the four-wave mixing locking effects,resonant/off-resonant microwave injection,phase locking,and femtosecond laser based locking techniques have been widely used to broaden and stabilize terahertz QCL combs.These active locking methods indeed show significant effects on the frequency stabilization of terahertz QCL combs,but they simultaneously have drawbacks,such as introducing large phase noise and requiring complex optical coupling and/or electrical circuits.Here,we demonstrate Farey tree locking of terahertz QCL frequency combs under microwave injection.The frequency competition between the Farey fraction frequency and the cavity round-trip frequency results in the frequency locking of terahertz QCL combs,and the Farey fraction frequencies can be accurately anticipated based on the downward trend of the Farey tree hierarchy.Furthermore,dual-comb experimental results show that the phase noise of the dual-comb spectral lines is significantly reduced by employing the Farey tree locking method.These results pave the way to deploying compact and low phase noise terahertz frequency comb sources.
