To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in r...To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity, etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.展开更多
Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark...Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.展开更多
To seek high signal-to-noise ratio(SNR) is critical but challenging for single-shot intense terahertz(THz)coherent detection. This paper presents an improved common-path spectral interferometer for single-shot THz det...To seek high signal-to-noise ratio(SNR) is critical but challenging for single-shot intense terahertz(THz)coherent detection. This paper presents an improved common-path spectral interferometer for single-shot THz detection with a single chirped pulse as the probe for THz electro-optic(EO) sampling. Here, the spectral interference occurs between the two orthogonal polarization components with a required relative time delay generated with only a birefringent plate after the EO sensor. Our experiments show that this interferometer can effectively suppress the noise usually suffered in a non-common-path interferometer. The measured single-shot SNR is up to 88.85, and the measured THz waveforms are independent of the orientation of the used Zn Te EO sensor, so it is easy to operate and the results are more reliable. These features mean that the interferometer is quite qualified for applications where strong THz pulses, usually with single-shot or low repetition rate, are indispensable.展开更多
Antibiotics are widely used in medicine and animal husbandry.However,due to the resistance of antibiotics to degradation,large amounts of antibiotics enter the environment,posing a potential risk to the ecosystem and ...Antibiotics are widely used in medicine and animal husbandry.However,due to the resistance of antibiotics to degradation,large amounts of antibiotics enter the environment,posing a potential risk to the ecosystem and public health.Therefore,the detection of antibiotics in the environment is necessary.Nevertheless,conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation,which impose considerable time and economic costs.In this paper,we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning.With the help of a modified spectrometer,a large number of characteristic images were generated to map antibiotic information.The relationship between characteristic images and antibiotic concentrations was established by machine learning model.The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model.The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment.The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.展开更多
Optical spectroscopy is crucial for understanding the optical properties of materials,characterizing the performance of photonic devices,and monitoring industrial processes based on spectral detection[1–3].However,co...Optical spectroscopy is crucial for understanding the optical properties of materials,characterizing the performance of photonic devices,and monitoring industrial processes based on spectral detection[1–3].However,commercial spectrometers often involve intricate optical setups and have substantial physical dimensions,especially for spectrometers with high precision.Consequently,there is a motivation to develop miniaturized spectrometers with increasement in portability and environmental robustness,which will broaden the scope of information acquisition in both scientific research and industrial applications[4].展开更多
Purpose To meet the stringent requirements for high-quality processing of focusing mirror molds and reproduction mirrors,specific cleaning procedures must be both accurate and efficient.Methods This study examines the...Purpose To meet the stringent requirements for high-quality processing of focusing mirror molds and reproduction mirrors,specific cleaning procedures must be both accurate and efficient.Methods This study examines the stability and consistency of the removal rate throughout the polishing process by analyzing changes in the composition of the polishing slurry at various stages.Infrared spectroscopy was used to measure the chemical groups of compounds on the mandrel surface and assess its stress state.Additionally,the adsorption mechanism at the interface was explored in detail.Results and Conclusion The study investigates ultra-precision polishing of nickel–phosphorus alloy,focusing on factors influencing the water film formation ability on the workpiece surface.X-ray electron spectroscopy was employed to analyze the mandrel before and after the cleaning process.The effectiveness of the cleaning process was evaluated by comparing its surface removal effect with that of the polishing process.展开更多
文摘To detect high frequency （HF） first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity, etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.
基金The National Science and Technology Support Project under contract No.2014BAB12B02the Natural Science Foundation of Liaoning Province under contract No.201602042
文摘Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.
基金National Natural Science Foundation of China(NSFC)(61490710,61775142,61705132)Science and Technology Planning Project of Guangdong Province(2016B050501005)Specialized Research Fund for the Shenzhen Strategic Emerging Industries Development(JCYJ20150324141711651,JCYJ20150525092941064,JCYJ20170412105812811)
文摘To seek high signal-to-noise ratio(SNR) is critical but challenging for single-shot intense terahertz(THz)coherent detection. This paper presents an improved common-path spectral interferometer for single-shot THz detection with a single chirped pulse as the probe for THz electro-optic(EO) sampling. Here, the spectral interference occurs between the two orthogonal polarization components with a required relative time delay generated with only a birefringent plate after the EO sensor. Our experiments show that this interferometer can effectively suppress the noise usually suffered in a non-common-path interferometer. The measured single-shot SNR is up to 88.85, and the measured THz waveforms are independent of the orientation of the used Zn Te EO sensor, so it is easy to operate and the results are more reliable. These features mean that the interferometer is quite qualified for applications where strong THz pulses, usually with single-shot or low repetition rate, are indispensable.
基金supported by the National Natural Science Foundation of China(Grant No.50309011)the Research Project of Shaanxi Province(2011K17-03-06)+1 种基金the Natural Science Basic Research Plan in the Shaanxi Province of China(No.2021JQ436)the Scientific Research Foundation for the Retuned Overseas Chinese Scholars(08501041585).
文摘Antibiotics are widely used in medicine and animal husbandry.However,due to the resistance of antibiotics to degradation,large amounts of antibiotics enter the environment,posing a potential risk to the ecosystem and public health.Therefore,the detection of antibiotics in the environment is necessary.Nevertheless,conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation,which impose considerable time and economic costs.In this paper,we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning.With the help of a modified spectrometer,a large number of characteristic images were generated to map antibiotic information.The relationship between characteristic images and antibiotic concentrations was established by machine learning model.The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model.The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment.The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.
基金supported by the National Key Research and Development Program of China(2021YFA1400800)the Quantum Science Strategic Initiative(GDZX2206001 and GDZX2306003)+2 种基金the Natural Science Foundation of Guangdong Province(2022B1515020067 and 2024B1515040013)the Postdoctoral Fellowship Program of CPSF(GZB20240909)the China Postdoctoral Science Foundation(2024M763733)。
文摘Optical spectroscopy is crucial for understanding the optical properties of materials,characterizing the performance of photonic devices,and monitoring industrial processes based on spectral detection[1–3].However,commercial spectrometers often involve intricate optical setups and have substantial physical dimensions,especially for spectrometers with high precision.Consequently,there is a motivation to develop miniaturized spectrometers with increasement in portability and environmental robustness,which will broaden the scope of information acquisition in both scientific research and industrial applications[4].
基金the Strategic Priority Program on Space Science China,the Chinese Academy of Science,(Grant No.XDA15020106 and XDA15020501)the National Natural Science Foundation of China,grant number 42327802.
文摘Purpose To meet the stringent requirements for high-quality processing of focusing mirror molds and reproduction mirrors,specific cleaning procedures must be both accurate and efficient.Methods This study examines the stability and consistency of the removal rate throughout the polishing process by analyzing changes in the composition of the polishing slurry at various stages.Infrared spectroscopy was used to measure the chemical groups of compounds on the mandrel surface and assess its stress state.Additionally,the adsorption mechanism at the interface was explored in detail.Results and Conclusion The study investigates ultra-precision polishing of nickel–phosphorus alloy,focusing on factors influencing the water film formation ability on the workpiece surface.X-ray electron spectroscopy was employed to analyze the mandrel before and after the cleaning process.The effectiveness of the cleaning process was evaluated by comparing its surface removal effect with that of the polishing process.
