2023

• Record 85 of
  
  Title:Microstructural and luminescence characteristics of high-linearity ZnS:Cu2+,Cl− phosphor
  
  Author(s):Xing, Xue(1,2,3); Cao, Weiwei(1,3,4); Wu, Zhaoxin(2); Bai, Xiaohong(1); Gao, Jiarui(1); Liang, Xiaozhen(1); Wang, Bo(1); Wang, Chao(1); Xiang, Junjie(1,3); Shi, Dalian(1); Lv, Linwei(1); Bai, Yonglin(1)
  Source: Journal of Materials Science: Materials in Electronics  Volume: 34  Issue: 5  Article Number: 454  DOI: 10.1007/s10854-023-09931-5  Published: February 2023  
  Abstract:In this study, we investigated the microstructural and luminescence characteristics of high-linearity ZnS:Cu2+,Cl− phosphor. Through conducting the method of high-temperature solid state reaction, we prepared the ZnS phosphors characterizing with two different doping concentrations of Cu2+ ions. The prepared two kinds of ZnS phosphors exhibit two coexisting forms of cubic phase and hexagonal phase, to which the concentration of Cu2+ imposes no influence on the microstructure of the phosphor. The average particle size is 2.68 ± 0.5 μm and the emission wavelength locating at approximate 460 nm attribute to the zinc vacancy. As the concentration of the Cu2+ ions increases, the energy bandgap, the fluorescence lifetime and the luminescence intensity decrease, causing noticeable concentration quenching. In addition, the linear correlation between the emission intensity and the current of the prepared phosphors is stronger than that of commercial ones. The prepared ZnS:Cu2+,Cl− phosphor with high linearity and short fluorescence lifetime has great potential to be applied in practical applications in the field of high-energy physics and astrophysical exploration. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
  Accession Number: 20230613564087
• Record 86 of
  
  Title:Underwater single photon 3D imaging with millimeter depth accuracy and reduced blind range
  
  Author(s):Wang, Jie(1,2,3,4); Hao, Wei(1,2,4); Chen, Songmao(1,2,4); Zhang, Zhenyang(1,2,3,4); Xu, Weihao(1,3,4); Xie, Meilin(1,2,4); Zhu, Wenhua(5); Su, Xiuqin(1,2,4)
  Source: Optics Express  Volume: 31  Issue: 19  Article Number: null  DOI: 10.1364/OE.499763  Published: September 11, 2023  
  Abstract:Mono-static system benefits from its more flexible field of view and simplified structure, however, the backreflection photons from mono-static system lead to count loss for target detection. Counting loss engender range-blind, impeding the accurate acquisition of target depth. In this paper, count loss is reduced by introducing a polarization-based underwater mono-static single-photon imaging method, and hence reduced blind range. The proposed method exploits the polarization characteristic of light to effectively reduce the count loss of the target, thus improving the target detection efficiency. Experiments demonstrate that the target profile can be visually identified under our method, while the unpolarization system can not. Moreover, the ranging precision of system reaches millimeter-level. Finally, the target profile is reconstructed using non-local pixel correlations algorithm. © 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.
  Accession Number: 20234214906210
• Record 87 of
  
  Title:Brain Connectivity Features for Automatic Seizure Detection and Prediction
  
  Author(s):Tian, Ziwei(1,2,3); Hu, Bingliang(1,3); Si, Yang(4,5); Wang, Quan(1,3)
  Source: SSRN  Volume: null  Issue: null  Article Number: null  DOI: 10.2139/ssrn.4371032  Published: March 13, 2023  
  Abstract:Objective: Epilepsy is a neurological disorder that causes repeated seizures. Because electroencephalogram (EEG) patterns differ in different states (inter-ictal, pre-ictal, and ictal), seizures can be detected and predicted by machine or deep learning. However, studies of brain connectivity features are scarce in this field. Our goal is to propose a method based on brain connectivity features for automatic seizure detection and prediction.Methods: Two window lengths (1 s and 8 s) were employed for EEG data segmentation. Five physiological wave bands (i.e., δ, θ, α, β, and γ) and five connectivity measures (i.e., Pearson correlation coefficient, phase locking value, mutual information, Granger causality, and transfer entropy) were used to extract image-like features, which were fed into a support vector machine for the subject-specific model (SSM) and into an 18-layer residual network for the subject-independent model (SIM) and cross-subject model (CSM). Finally, feature selection and efficiency analyses were conducted.Results: The classification results on the CHB-MIT dataset showed that the features extracted in the 8s-window were more effective than those in the 1s-window. For seizure detection, the best accuracies of SSM, SIM, and CSM were 99.29, 100, and 94.59%, respectively. The highest accuracies obtained for seizure prediction were 98.99, 98.98, and 84.58%, respectively. In addition, the Pearson correlation coefficient features in the β and γ bands showed good performance and high speed.Conclusion: The proposed brain connectivity features exhibited good reliability and practical value for automatic seizure detection and prediction, which is conducive to the development of portable real-time monitoring equipment. © 2023, The Authors. All rights reserved.
  Accession Number: 20230084968
• Record 88 of
  
  Title:Depth of focus extension of space-borne optical camera through variable curvature mirror
  
  Author(s):Hui, Zhao(1); Xiaopeng, Xie(1); Mingyang, Yang(1); Gangyi, Zou(1); Yating, Zhang(1); Xuewu, Fan(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 12765  Issue: null  Article Number: 127651H  DOI: 10.1117/12.2687237  Published: 2023  
  Abstract:Currently, most space-borne optical cameras have fixed focal length and depth of focus. In this case, the range within which the target can be clearly imaged has been pre-determined before launch. However, the distance of the target to the optical camera might be unknown or change very fast and therefore focus adjustment has to be carried out to obtain clear images. However, no matter which refocusing technique is used, focus adjustment might lag behind the object distance variation and depth of focus extension is a better way. Wave-front coding can be used to extend the depth of focus of incoherent imaging system but the surface profile of the phase mask could not be changed dynamically, which is not flexible for application. In this manuscript, by combing the variable curvature mirror (VCM) and coded imaging technique together, a new depth of focus extension technique is proposed. According to our previous studies, the focal plane could be quickly adjusted by changing the curvature radius of VCM. Compared with the curvature variation speed, the exposure time of the camera is quite long. Therefore, by adjusting the focal plane very fast in a wide range during the exposure through VCM, an equivalent coded optical transfer function having no null frequency points within bandwidth is generated and the image captured is uniformly blurred. After that, with the help of digital restoration, the clear image could be obtained. Because the focal plane could be adjusted through variable curvature mirror in the range of millimeter, the proposed method could be used to obtain clear images with greatly extended depth of focus. © 2023 SPIE.
  Accession Number: 20240215367623
• Record 89 of
  
  Title:Inter-dynode Voltage Optimization of Discrete Dynode Electron Multipliers by Numerical Simulation
  
  Author(s):Liu, Li(1); Hu, Wenbo(1); Zhao, Dezhen(1); Li, Jie(1); Wu, Shengli(1); Liu, Hulin(2)
  Source: 2023 24th International Vacuum Electronics Conference, IVEC 2023  Volume: null  Issue: null  Article Number: null  DOI: 10.1109/IVEC56627.2023.10157116  Published: 2023  
  Abstract:In order to improve the performance of discrete dynode electron multipliers, the effect of inter-dynode voltage on device gain was investigated by numerical simulation, and the distribution of inter-dynode voltages was optimized. The investigation results reveal that for an electron multiplier with 11-stage dynodes, when the inter-dynode voltage of the first 10 dynodes is 3.1 times that of the last 1 dynode, it can obtain a higher gain due to the improvement of electric field intensity and electron collection efficiency, whose overall electron collection efficiency and device gain increase by about 63% and 95%, respectively, in comparison with the case of applying the same inter-dynode voltage for all the dynodes. © 2023 IEEE.
  Accession Number: 20233114463237
• Record 90 of
  
  Title:X-ray transmission effects in a high-density dynamic-dusty plasma environment
  
  Author(s):Li, Yao(1); Yang, Zhiqiang(1); Zhang, Yingjun(2); Chen, Mingde(3); Xia, Fangyuan(2,4,5); Yang, Lihong(1); Zhang, Furui(1); Wu, Yinhua(1); Tan, Zhenkun(1); Yang, Chen(1); Su, Tong(3)
  Source: Vacuum  Volume: 212  Issue: null  Article Number: 112260  DOI: 10.1016/j.vacuum.2023.112260  Published: June 2023  
  Abstract:X-ray communication (XCOM), which employs modulated X-ray photons as the carrier for signal transmission, is a promising wireless optical technology for space applications, particularly during spacecraft blackout re-entry. Currently, several challenges related to XCOM require solutions, including incomplete transmission attenuation models and a lack of experimental verification of the dynamic-dusty communication effects. This study improved the XCOM transmission characteristics in high-density dynamic-dusty plasma based on a collision model. A dynamic-dusty plasma XCOM was built to verify a modulated X-ray tube and an alkali-metal plasma source. The results show that with an increase in photon energy and flow, the X-ray carrier achieves a higher transmission speed, which is sharper than that of photon energy under the influence of flow. When the average electron density of the dusty plasma is 1012–1013 cm−2, the plasma flow speed is 550–650 m/s, the macro temperature exceeds 1500 K, and the communication demonstration system achieves a stable data rate of 50 kbps at a bit error (BER) of 1.7 × 10−5 with a carrier amplitude and frequency of approximately 20 kV and 4.8 Mcps, respectively. This experiment yielded theoretical and actual values for the development of XCOM technology in space applications during re-entry blackouts. © 2023
  Accession Number: 20232314196689
• Record 91 of
  
  Title:Design of Photonic-Crystal-Modulated Narrowband Multichannel Filters for Visible Light with High Transmittance
  
  Author(s):Wang, Tianxin(1); Wang, Shuai(1); Gao, Bo(1); Yu, Weixing(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 12962  Issue: null  Article Number: 129620C  DOI: 10.1117/12.3007882  Published: 2023  
  Abstract:In this study, we introduce a novel approach for achieving narrowband filters in hyperspectral imaging spectrometers. By embedding photonic crystals within distributed Bragg reflectors (DBRs), we create resonant structures. Through meticulous simulations, we optimize a four-layer DBR configuration, resulting in spectral channels with a 3 nm average FWHM and exceeding 99% peak transmittance. Our key innovation lies in using photonic crystals to modulate transmission. By introducing TiO2 periodic structures, we control the effective refractive index and thereby tune transmission wavelengths. The method covers a 475-625 nm spectral range with exceptional transmittance. We also investigate incident light angle effects, revealing systematic shifts in transmission peak. Our design offers adaptability by adjusting DBR film thickness for defining operational ranges and selecting TiO2 cylinder radii for precise channel manipulation.Our approach simplifies fabrication and holds potential for cost-effective hyperspectral imaging filters. © 2023 SPIE. All rights reserved.
  Accession Number: 20240215343579
• Record 92 of
  
  Title:A Marine Small-Targets Classification Algorithm Based on Improved Convolutional Neural Networks
  
  Author(s):Guo, Huinan(1,2); Ren, Long(1)
  Source: Remote Sensing  Volume: 15  Issue: 11  Article Number: 2917  DOI: 10.3390/rs15112917  Published: June 2023  
  Abstract:Deep learning, especially convolutional neural network (CNN) techniques, has been shown to have superior performance in ship classification, as have small-target recognition studies in safety inspections of hydraulic structures such as ports and dams. High-resolution synthetic aperture radar (SAR)-based maritime ship classification plays an increasingly important role in marine surveillance, marine rescue, and maritime ship management. To improve ship classification accuracy and training efficiency, we proposed a CNN-based ship classification method. Firstly, the image characteristics of different ship structures and the materials of ship SAR images were analyzed. We then constructed a ship SAR image dataset and performed preprocessing operations such as averaging. Combined with a classic neural network structure, we created a new convolutional module, namely, the Inception-Residual Controller (IRC) module. A convolutional neural network was built based on the IRC module to extract image features and establish a ship classification model. Finally, we conducted simulation experiments for ship classification and analyzed the experimental results for comparison. The experimental results showed that the average accuracy of ship classification of the model in this paper reached 98.71%, which was approximately 3% more accurate than the traditional network model and approximately 1% more accurate compared with other recently improved models. The new module also performed well in evaluation metrics, such as the recall rate, with accurate classifications. The model could satisfactorily describe different ship types. Therefore, it could be applied to marine ship classification management with the possibility of being extended to hydraulic building target recognition tasks. © 2023 by the authors.
  Accession Number: 20232414233656
• Record 93 of
  
  Title:A Speed Measurement Method for High Speed Moving Target in Bright Light Environment
  
  Author(s):Dong, Sen(1); Guan, Lei(1,2); Wang, Hao(1); Huang, JiJiang(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 12747  Issue: null  Article Number: 1274722  DOI: 10.1117/12.2689221  Published: 2023  
  Abstract:The speed measurement of high-speed moving targets has extremely important significance in military fields, unmanned driving, space monitoring, and other fields. In digital image processing technology, the target coordinate system is often established through video frames for speed measurement. However, in some strong light environments, due to the strong ambient light, the reflected light of the moving target may be "submerged" in the ambient light, and the reflected light cannot be recognized by the detector in the end. Therefore, the motion trajectory of the moving target cannot be identified. For high-speed moving objects, using the backlight method is an effective method for measuring the trajectory of moving targets, but in strong light environments, the "background" light will also be unrecognizable. This article proposes a new method for accurately measuring the speed of high-speed moving targets in bright light environments. Through spectral analysis of bright light environment, laser is selected as the background light. Laser has the characteristics of high power, strong energy, good penetration, and single wavelength. Its energy in the laser band (1064nm) is much higher than other wavelengths in the bright light environment, thus ensuring the stability of the light source. At the same time, the detection device adopts a band-pass Filter design to attenuate the energy outside the specific laser band and only detect the "background" light. And dynamically adaptively adjust the video frame number of high-speed moving target acquisition devices to improve speed measurement accuracy and reduce bandwidth pressure. The experimental results show that the method proposed in this paper can accurately and efficiently identify and measure the speed of high-speed targets in strong light environments. © 2023 SPIE. All rights reserved.
  Accession Number: 20235115263096
• Record 94 of
  
  Title:Detection method of sidelobe peaks parameter for far-field measurement based on the diffraction inversion of sidelobe beam
  
  Author(s):Wang, Zhengzhou(1); Duan, Yaxuan(1); Wang, Li(1); Li, Gang(1); Guo, Jiafu(1,2)
  Source: Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering  Volume: 52  Issue: 1  Article Number: 20220281  DOI: 10.3788/IRLA20220281  Published: January 2023  
  Abstract:In order to solve the problem that high power laser far-field measurement can not effectively identify the parameters of each sidelobe peak in any direction of sidelobe beam, a detection method of sidelobe peak parameters of far-field measurement based on sidelobe beam diffraction inversion is proposed in this paper. The main idea is to quantify the sidelobe beam image according to a specific angle sampling interval, and convert the two-dimensional sidelobe beam image into a set of one-dimensional sidelobe beam curves in all directions by angle transformation, then detect the parameters of each sidelobe peak of one-dimensional sidelobe beam curve at each angle, so as to obtain the parameters of each sidelobe peak in any direction of sidelobe beam. The main optimization measures are as follows: (1) Convert the two-dimensional sidelobe beam image into a set of one-dimensional sidelobe beam curves in all directions by angle transformation; (2) Detect the parameters of each sidelobe peak of one-dimensional sidelobe beam curve at each angle, count each sidelobe peak in all directions, and generate the maximum rings of each sidelobe peak; (3) Count the gray mean values of the maximum rings of each sidelobe peak, compare the gray mean values of the maximum rings of each sidelobe peak with the background noise, and select the minimum peak mean value greater than 1.5 times the background noise as the minimum measurable sidelobe peak signal of the whole sidelobe beam. The experimental results show that this method can effectively detect the parameters of each sidelobe peak in any direction of the sidelobe beam. The error between the mean value of gray maximum value and the theoretical value of gray maximum value in any direction is 0.477, and the error between the mean value of the maximum ring radius and the radius of the theoretical value of 5 sidelobe peaks is less than 1 pixel. This method improves the experimental accuracy and reliability of far-field measurement of high power laser based on the diffraction inversion of sidelobe beam, and it will lay a foundation for the accurate measurement of the far field of the high power laser in the large scientific facility in the future. © 2023 Chinese Society of Astronautics. All rights reserved.
  Accession Number: 20230813609899
• Record 95 of
  
  Title:Feature spatial pyramid network for low-light image enhancement
  
  Author(s):Song, Xijuan(1,2); Huang, Jijiang(1); Cao, Jianzhong(1); Song, Dawei(1,2)
  Source: Visual Computer  Volume: 39  Issue: 1  Article Number: null  DOI: 10.1007/s00371-021-02343-8  Published: January 2023  
  Abstract:Low-light images usually contain high noise and low contrast. This brings bad visual feelings and hinders subsequent computer vision work. At present, many algorithms have been proposed to enhance low-light images. However, the existing methods still have some problems, such as insufficient enhancement, color distortion, or overexposure. In this paper, we propose a low-light image enhancement network based on the spatial pyramid to solve the problems existing in other methods, so as to make the enhancement result closer to the normal illumination image in brightness and color. The network is divided into two parts. Firstly, the decomposition network is designed based on Retinex theory, and the image is decomposed into the illumination image and reflection image. Then, the illumination image is processed through the three convolution kernels on the spatial pyramid module to obtain three sets of features with different scales. Next, we concatenate these three groups of features together. And the concatenated features are extracted through a convolution kernel to obtain the enhanced illumination image. Finally, the enhanced illumination image and the decomposed reflection image are multiplied pixel by pixel to obtain an enhanced image. In addition, we introduce a color loss function to solve the problem of color distortion. The experimental results show that the proposed algorithm has better visual feelings than other algorithms. We also calculate the peak signal-to-noise ratio, structural similarity index and average brightness of the enhanced results of different algorithms, and the results show that the proposed algorithm performs better. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
  Accession Number: 20220511582672
• Record 96 of
  
  Title:CSMOT: Make One-Shot Multi-Object Tracking in Crowded Scenes Great Again †
  
  Author(s):Hou, Haoxiong(1,2); Shen, Chao(1,2); Zhang, Ximing(1); Gao, Wei(1)
  Source: Sensors  Volume: 23  Issue: 7  Article Number: 3782  DOI: 10.3390/s23073782  Published: April 2023  
  Abstract:The current popular one-shot multi-object tracking (MOT) algorithms are dominated by the joint detection and embedding paradigm, which have high inference speeds and accuracy, but their tracking performance is unstable in crowded scenes. Not only does the detection branch have difficulty in obtaining the accurate object position, but the ambiguous appearance of features extracted by the re-identification (re-ID) branch also leads to identity switches. Focusing on the above problems, this paper proposes a more robust MOT algorithm, named CSMOT, based on FairMOT. First, on the basis of the encoder–decoder network, a coordinate attention module is designed to enhance the information interaction between channels (horizontal and vertical coordinates), which improves its object-detection abilities. Then, an angle-center loss that effectively maximizes intra-class similarity is proposed to optimize the re-ID branch, and the extracted re-ID features are made more discriminative. We further redesign the re-ID feature dimension to balance the detection and re-ID tasks. Finally, a simple and effective data association mechanism is introduced, which associates each detection instead of just the high-score detections during the tracking process. The experimental results show that our one-shot MOT algorithm achieves excellent tracking performance on multiple public datasets and can be effectively applied to crowded scenes. In particular, CSMOT decreases the number of ID switches by 11.8% and 33.8% on the MOT16 and MOT17 test datasets, respectively, compared to the baseline. © 2023 by the authors.
  Accession Number: 20231613942131