2021

• Record 217 of
  
  Title:Photonic radio frequency channelizers based on Kerr optical micro-combs
  
  Author(s):Tan, Mengxi(1); Xu, Xingyuan(2); Wu, Jiayang(1); Nguyen, Thach G.(3); Chu, Sai T.(4); Little, Brent E.(5); Morandotti, Roberto(6,7); Mitchell, Arnan(3); Moss, David J.(1)
  Source: Journal of Semiconductors  Volume: 42  Issue: 4  DOI: 10.1088/1674-4926/42/4/041302  Published: April 2021  
  Abstract:We review recent work on broadband RF channelizers based on integrated optical frequency Kerr micro-combs combined with passive micro-ring resonator filters, with microcombs having channel spacings of 200 and 49 GHz. This approach to realizing RF channelizers offers reduced complexity, size, and potential cost for a wide range of applications to microwave signal detection. © 2021 Chinese Institute of Electronics.
  Accession Number: 20212010361118
• Record 218 of
  
  Title:Effect of melting atmospheres on the optical property of radiation-hard fluorophosphate glass
  
  Author(s):Ma, Yuan(1,2); Su, Haiqin(1,3); Zhang, Zhijun(1); Wan, Rui(1,2); Li, Shengwu(1,2); Peng, Bo(1,2); Wang, Pengfei(1,2)
  Source: Ceramics International  Volume: 47  Issue: 16  DOI: 10.1016/j.ceramint.2021.04.256  Published: August 15, 2021  
  Abstract:High-energy radiation in space and nuclear irradiation environment induces colour centres in optical glass, causing solarisation, and a serious condition can render optical systems and optical loads unusable. To develop space radiation-resistant optical glass, CeO2-stabilised radiation-hard fluorophosphate glass was prepared under three different atmospheres (nitrogen, oxygen, and ambient air). The glass-melting atmospheres' effects on the glass's transmission, defect formation, and structural changes before and after exposure to gamma radiation were investigated by a comprehensive study on their transmittance, absorption, and electron paramagnetic resonance spectra. Introducing a small amount of CeO2 (～0.34 wt%) into the fluorophosphate base glass converted NBO and BO into ABO in the glass network, red-shifted the UV absorption edge, and decreased the optical density increment by almost half after radiation. As the total dose of gamma radiation increased, the transmittance of the irradiated glass at a wavelength of 385 nm significantly increased due to absorption of POHC2 defects. After exposure to 250 k of rad gamma irradiation, the corresponding optical density increment per centimeter thickness at 385 nm of the radiation-hard fluorophosphate glass that melted in the nitrogen, oxygen, and air atmospheres decreased from 1.839 to 1.388 and 1.215. As it melted in air, the NBO ratio of the fluorophosphate glass reached the lowest level and the Ce4+ ratio in the glass was 92.49%, which helped suppress the generation of POHC, Fe3+, PO4-EC, and PO3-EC defects during the gamma irradiation process, improving the glass's radiation resistance. © 2021 Elsevier Ltd and Techna Group S.r.l.
  Accession Number: 20211810306677
• Record 219 of
  
  Title:Human behaviour recognition with mid-level representations for crowd understanding and analysis
  
  Author(s):Sun, Bangyong(1,2); Yuan, Nianzeng(1); Li, Shuying(4); Wu, Siyuan(2); Wang, Nan(2,3)
  Source: IET Image Processing  Volume: 15  Issue: 14  DOI: 10.1049/ipr2.12147  Published: December 2021  
  Abstract:Crowd understanding and analysis have received increasing attention for couples of decades, and development of human behaviour recognition strongly supports the application of crowd understanding and analysis. Human behaviour recognition usually seeks to automatically analyse ongoing movements and actions in different camera views by using various machine learning methodologies in unknown video clips or image sequences. Compared to other data modalities such as documents and images, processing video data demands much higher computational and storage resources. The idea of using middle level semantic concepts to represent human actions from videos is explored and it is argued that these semantic attributes enable the construction of more descriptive methods for human action recognition. The mid-level attributes, initialized by a cluster processing, are built upon low level features and fully utilize the discrepancies in different action classes, which can capture the importance of each attribute for each action class. In this way, the representation is constructed to be semantically rich and capable of highly discriminative performance even paired with simple linear classifiers. The method is verified on three challenging datasets (KTH, UCF50 and HMDB51), and the experimental results demonstrate that our method achieves better results than the baseline methods on human action recognition. © 2021 The Authors. IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
  Accession Number: 20210909996869
• Record 220 of
  
  Title:Orthogonally polarized RF optical single sideband generation with integrated ring resonators
  
  Author(s):Tan, Mengxi(1); Xu, Xingyuan(2); Wu, Jiayang(1); Nguyen, Thach G.(3); Chu, Sai T.(4); Little, Brent E.(5); Mitchell, Arnan(3); Morandotti, Roberto(6,7); Moss, David J.(1)
  Source: Journal of Semiconductors  Volume: 42  Issue: 4  DOI: 10.1088/1674-4926/42/4/041305  Published: April 2021  
  Abstract:We review recent work on narrowband orthogonally polarized optical RF single sideband generators as well as dual-channel equalization, both based on high-Q integrated ring resonators. The devices operate in the optical telecommunications C-band and enable RF operation over a range of either fixed or thermally tuneable frequencies. They operate via TE/TM mode birefringence in the resonator. We achieve a very large dynamic tuning range of over 55 dB for both the optical carrier-to-sideband ratio and the dual-channel RF equalization for both the fixed and tunable devices. © 2021 Chinese Institute of Electronics.
  Accession Number: 20212010361090
• Record 221 of
  
  Title:Infrared and visible image fusion based on weighted variance guided filter and image contrast enhancement
  
  Author(s):Ren, Long(1,2,3); Pan, Zhibin(2,5,6); Cao, Jianzhong(1); Liao, Jiawen(1,2,3); Wang, Yang(4,5)
  Source: Infrared Physics and Technology  Volume: 114  Issue:   DOI: 10.1016/j.infrared.2021.103662  Published: May 2021  
  Abstract:With extraordinary advances in sensor technology, infrared and visible image fusion has been widely used in both military and civilian applications. In this paper, we propose a novel image fusion method based on decomposition and division based strategy. The proposed method improves the guided filter to better decompose images and restrict artifacts around image boundaries. Furthermore, because the quality of visible images is easily affected by low light conditions and noises, it is necessary to enhance the contrast of visible images to improve the visual quality before applying image fusion. Subsequently, we divide the infrared and visible image into several sub-images in vertical direction, because there is more similar image content in this direction such as the sky and land. Additionally, each sub-image is decomposed into a base layer and a detail layer. Different from previous methods, the fusion in our proposed method is executed by two different strategies, one takes the sub infrared base layer as the main image to get the fusion result, while the other one takes the sub visible base layer as the main image, and two different sub-fusion results are obtained. We also propose a new fusion strategy called gradient-brightness criterion to adaptively output the final fused image. As a result, the fused image preserves more details of visible image and clearer infrared objects at the same time, which is well suited for human visual perception. Experimental results indicate that our proposed method achieves a superior performance compared with previous fusion methods in both subjective and objective assessments. © 2021 Elsevier B.V.
  Accession Number: 20210809943896
• Record 222 of
  
  Title:Ligand-Free BaF2: Nd Nanoparticles With Low Cytotoxicity, High Stability and Enhanced Fluorescence Intensity as NIR-II Imaging Probes
  
  Author(s):Cui, Xiaoxia(1,2); Xu, Yantao(1,2); She, Shengfei(1,2); Xiao, Xusheng(1,2); Hou, Chaoqi(1,2); Guo, Haitao(1,2)
  Source: Frontiers in Physics  Volume: 9  Issue:   DOI: 10.3389/fphy.2021.665956  Published: May 13, 2021  
  Abstract:Ligand-free BaF2:Nd nanoparticles (NPs) with a size of 10 nm were fabricated by a novel synthetic route in the liquid phase. A transparent dispersion of the BaF2:Nd NPs mixed with propanetriol and DMSO-d6 was done. Highly stable and outstanding near-infrared (NIR) fluorescence centered at 1,058 nm was detected using an excitation wavelength of 808 nm laser. Moreover, the dispersion can be found to be stable for over 1 month, and the cytotoxicity of the BaF2:Nd NP dispersion has also been studied by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. The superior performance of these NPs exhibits their great potential application in high-contrast and high-penetration in vivo imaging. © Copyright © 2021 Cui, Xu, She, Xiao, Hou and Guo.
  Accession Number: 20233514654865
• Record 223 of
  
  Title:Numerical study of the influence of thermal radiation on measuring semi-transparent thermal insulation material with hot wire method
  
  Author(s):Zhang, H.(1); Ma, Y.X.(2); Wang, X.(1); Tang, G.H.(3)
  Source: International Communications in Heat and Mass Transfer  Volume: 121  Issue:   DOI: 10.1016/j.icheatmasstransfer.2021.105120  Published: February 2021  
  Abstract:Semi-transparent thermal insulation material has very low extinction coefficient and will transmit infrared spectrum within some wavelength range. When measuring the thermal conductivity (TC) of such kinds of material with transient methods, both heat conduction and thermal radiation occur within material. Transient hot wire (HW) method is a widely used method for thermal insulation measurement. It is developed with the assumption that heat only transfers via conduction. Since thermal radiation within low density thermal insulation material is a pronounced heat transfer mode at high temperature, the TC of radiation participating medium measured by HW method might be incorrect. To reveal the inconsistency between test theory and practical heat transfer process when measuring semi-transparent thermal insulation material with HW method, the transient conduction and radiation coupled heat transfer process is simulated numerically. The uncertainty caused by thermal radiation is investigated for material with different extinction coefficient at various temperature. The deviation increases with the increment of temperature and decreases with increment of extinction coefficient compared to results obtained from the one dimensional (1D) steady state method. The numerical analysis indicates that the TC of thermal insulation material with low extinction ability measured by HW method is overestimated at high temperature. © 2021 Elsevier Ltd
  Accession Number: 20210309787605
• Record 224 of
  
  Title:Distribution equalization learning mechanism for road crack detection
  
  Author(s):Fang, Jie(1,2); Qu, Bo(1); Yuan, Yuan(3)
  Source: Neurocomputing  Volume: 424  Issue:   DOI: 10.1016/j.neucom.2019.12.057  Published: February 1, 2021  
  Abstract:Visual-based road crack detection becomes a hot research topic over the last decade because of its huge application demands. Road crack detection is actually a special form of salient object detection task, whose objects are small and distribute randomly in the image compared to the traditional ones, which increase the difficulty of detecting. Most conventional methods utilize bottom information, such as color, texture, and contrast, to extract the crack regions in the image. Even though these methods can achieve satisfactory performances for images with simple scenarios, they are easily interfered by some factors such as light and shadow, which may decrease the detection result directly. Inspired by the competitive performances of deep convolutional neural networks on many visual tasks, we propose a distribution equalization learning mechanism for road crack detection in this paper. Firstly, we consider the crack detection task as a pixel-level classification and use a U-Net based architecture to finalize it. Secondly, the occurrence probability of crack and non-crack are so different, which results in the ill-conditioned classifier and undesirable detection performance, especially the high false detection rate. In this case, we propose a weighted cross entropy loss term and a data augmentation strategy to avoid influence from imbalanced samples through emphasizing the crack regions. Additionally, we propose an auxiliary interaction loss, and combine it with the popular self-attention strategy to alleviate the fracture situations through considering relationships among different local regions in the image. Finally, we tested the proposed method on three public and challenging datasets, and the experimental results demonstrate its effectiveness. © 2019
  Accession Number: 20200107963384
• Record 225 of
  
  Title:Atomistic evidence of nucleation mechanism for the direct graphite-to-diamond transformation
  
  Author(s):Luo, Duan(1,2,3); Yang, Liuxiang(4); Xie, Hongxian(5); Srinivasan, Srilok(1); Tian, Jinshou(2); Sankaranarayanan, Subramanian(1); Arslan, Ilke(1); Yang, Wenge(4); Mao, Ho-Kwang(4,6); Wen, Jianguo(1)
  Source: arXiv  Volume:   Issue:   DOI: null  Published: November 26, 2021  
  Abstract:The direct graphite-to-diamond transformation mechanism has been a subject of intense study and remains debated concerning the initial stages of the conversion, the intermediate phases, and their transformation pathways. Here, we successfully recover samples at early conversion stage by tuning high-pressure/high-temperature conditions and reveal direct evidence supporting the nucleation-growth mechanism. Atomistic observations show that intermediate orthorhombic graphite phase mediates the growth of diamond nuclei. Furthermore, we observe that quenchable orthorhombic and rhombohedra graphite are stabilized in buckled graphite at lower temperatures. These intermediate phases are further converted into hexagonal and cubic diamond at higher temperatures following energetically favorable pathways in the order: graphite → orthorhombic graphite → hexagonal diamond, graphite → orthorhombic graphite → cubic diamond, graphite → rhombohedra graphite → cubic diamond. These results significantly improve our understanding of the transformation mechanism, enabling the synthesis of different high-quality forms of diamond from graphite. Copyright © 2021, The Authors. All rights reserved.
  Accession Number: 20210402193
• Record 226 of
  
  Title:Remote Sensing Image Generation from Audio
  
  Author(s):Zheng, Zhiyuan(1,2); Chen, Jun(1); Zheng, Xiangtao(2); Lu, Xiaoqiang(2)
  Source: IEEE Geoscience and Remote Sensing Letters  Volume: 18  Issue: 6  DOI: 10.1109/LGRS.2020.2992324  Published: June 2021  
  Abstract:Generating image from other modal data has attracted much attention in cross-modal studies, since the generated image offers intuitive vision information. Unlike the previous works which generate an image from text, a novel task is introduced, generating an image from audio. However, semantic gap intrinsically exists in cross-modal data, which disturbs the generative results. In order to explore the relevance between the audio and image, a novel reranking audio-image translation method is proposed. The proposed method: 1) maps the audio and image into a uniform feature space; 2) designs an audio-audio matching network to match the related audio; and 3) adopts an audio-image matching network for every matched audio to generate a related image, and the most frequent image is voted as the final result. Extensive experiments on two remote sensing cross-modal data sets demonstrate that the proposed method can visualize the content of audio. © 2004-2012 IEEE.
  Accession Number: 20212210436960
• Record 227 of
  
  Title:Local and correlation attention learning for subtle facial expression recognition
  
  Author(s):Wang, Shaocong(1,2); Yuan, Yuan(3); Zheng, Xiangtao(1); Lu, Xiaoqiang(1)
  Source: Neurocomputing  Volume: 453  Issue:   DOI: 10.1016/j.neucom.2020.07.120  Published: September 17, 2021  
  Abstract:Subtle facial expression recognition (SFER) aims to classify facial expressions with very low intensity into corresponding human emotions. Subtle facial expression can be regarded as a special kind of facial expression, whose facial muscle movements are more difficult to capture. In the last decade, various methods have been developed for common facial expression recognition (FER). However, most of them failed to automatically find the most discriminative parts of facial expression and the correlation of muscle movements when human makes facial expression, which makes them unsuitable for SFER. To better solve SFER problem, an attention mechanism based model focusing on salient local regions and their correlations is proposed in this paper. The proposed method: 1) utilizes multiple attention blocks to attend to distinct discriminative regions and extract corresponding local features automatically, 2) a correlation attention module is integrated in the model to extract global correlation feature over the salient regions, and finally 3) fuses the correlation feature and local features in an efficient way for the final facial expression classification. By this way, the useful but subtle local information can be utilized in more detail, and the correlation of different local regions is also extracted. Extensive experiment on the LSEMSW and CK+ datasets shows that the method proposed in this paper achieves superior results, which demonstrates its effectiveness. © 2020 Elsevier B.V.
  Accession Number: 20203909248807
• Record 228 of
  
  Title:Structure-Preserving Super-Resolution Reconstruction Based on Multi-residual Network
  
  Author(s):Zhang, Mingjin(1,2); Peng, Xiaoqi(1); Guo, Jie(1); Li, Yunsong(1); Wang, Nannan(1); Gao, Xinbo(1,3)
  Source: Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence  Volume: 34  Issue: 3  DOI: 10.16451/j.cnki.issn1003-6059.202103005  Published: March 2021  
  Abstract:Aiming at the problems of geometric structure distortion and missing details in image super-resolution reconstruction, a structure-preserving super-resolution reconstruction algorithm based on multi-residual network is proposed. Deep learning is carried out in the wavelet transform domain and the gradient domain. Three kinds of residual networks are introduced. The structure and the edge information are reconstructed by the residual gradient network. The high-frequency information of the image is reconstructed as a whole by the residual wavelet transform network. The network attention is adjusted by the residual channel attention network, the important channel features are emphatically learned, and the high frequency information of the image is recovered locally. Experiments show that the proposed algorithm achieves better performance in both quantitative results and visual effects. © 2021, Science Press. All right reserved.
  Accession Number: 20212010365541