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Education, Knowledge and Information Management (ICEKIM), International Conference on

作者： Jie Chen Shu Zhao Fan Lu Feng Liu Yangping Zhang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China

ISBN: (纸本)9781665416672

Patent classification is an essential task in patent information management and knowledge mining. Most existing studies are based on the textual content of individual patent texts (e.g., titles and abstracts) for classification, but the patent also has label information with hierarchical structure and semantic description. However, the semantics correlation of patent texts and their labels have been largely ignored. In this paper, we propose a novel framework called HLSPC for patent classification by leveraging the hierarchical semantics correlation of patent texts and their labels. Specifically, we first apply a patent representation learning module for capturing the semantics representation of patent texts and hierarchical labels. Then, we design a label attention learning module to build the semantics correlation between patent texts and hierarchical labels, which enhances patent representation. Finally, we deploy a multi-level fusion module to get the refined category prediction for each patent which can preserve both local and global hierarchical prediction information. Extensive experimental results on two English patent datasets demonstrate the effective power of the HLSPC model.

关键词： Representation learning Patents Correlation Semantics Text categorization Education Information management

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Cross-Polarization suppression by Comb-Shaped slots in Microstrip Patch 13

Cross-Polarization suppression by Comb-Shaped slots in Micro...

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13th International Conference on Microwave and Millimeter Wave technology, ICMMT 2021

作者： Ma, Jing Tan, Shi-Li Ni, Si-Yuan Wang, Chen Sun, Kai Luo, Yong-Yuan Peng, Lin Beijing Simulation Center Science And Technology On Special System Simulation Laboratory Beijing100854 China 95972 Troops Of PLA Jiuquan735018 China Guilin University Of Electronic Technology Guangxi Key Laboratory Of Wireless Wideband Communication And Signal Processing Guangxi Guilin541004 China

ISBN: (纸本)9781665434379

Cross-polarization (XP) of the microstrip antenna was suppressed by etching comb-shaped slots in the patch. By cutting longitudinal comb-shaped slots on the rectangular patch, the transverse current at the patch edges that lead to cross-polarization was dammed up. Then, the co-to cross-polarization (CP-XP) ratio over entire angular range around the broadside direction was increased from 20 dB of the rectangular microstrip antenna (RMA) to 35 dB of the defected patch structure (DPS). Moreover, as the longitudinal current was little affected by the slots, the proposed structure has little effect on the other performances of the antenna (including gain, directivity, radiant principle and impedance bandwidth). As the presented structure is achieved by simple adding slots to the rectangular patch, it is very easy to be fabricated. © 2021 IEEE.

关键词： Etching

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Optically transparent transmissive orbital angular momentum (OAM) metasurface with high transmittance and broadband characteristics

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Optics Express 2025年第12期33卷 24385-24395页

作者： Yong Cai Yuying Dai Yue Ma Gang Wang Guanghui Xu Xingang Ren Hui Wang Xiaohu Zhao Xianliang Wu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei 230039 China Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes Anhui University Hefei 230039 China wang_toward@*** ghxu86@*** Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Institute of Physical Science and Information Technology Anhui University Hefei 230039 China xgren@*** Hefei Normal University Hefei 230009 China

This work proposes a high-performance broadband orbital angular momentum (OAM) beam-generating metasurface based on optically transparent media. A broadband polarization-converting transmissive metasurface, which operates in the 18 - 24 (28.57% fractional bandwidth) GHz range, has been realized by collaboratively designing dual C-split ring resonator structures and bidirectional lattice-patterned surface networks. The array structure demonstrates typical helical phase distribution features in the K-band, and experimental results verify simulation design. Innovatively employing a composite structure of quartz glass substrate and patterned conductive thin films, the design achieves compatible optimization of 77% visible-light transmittance and microwave broadband performance. This approach breaks through the mutually exclusive limitations of traditional metasurfaces’ optical/electromagnetic properties, providing a highly integrated solution for transparent antenna radomes in satellite communication systems and multi-mode beam multiplexing applications.

关键词： Orbital angular momentum multiplexing Phase plates Ring resonators Spatial light modulators Spiral phase Thin films

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A Modified Multi-Objective Whale Optimization Algorithm with Dynamic Leader Selection Mechanism

A Modified Multi-Objective Whale Optimization Algorithm with...

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International Conference on Measuring technology and Mechatronics Automation, ICMTMA

作者： Wentao Feng Bing Deng National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu Sichuan China

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170824

The whale optimization algorithm (WOA) has less control parameters and it is easier to implement. The multi-objective whale optimization algorithm (MOWOA) also shows good exploration and exploitation capability. A modified multi-objective whale optimization algorithm with dynamic leader selection mechanism (MMOWOA-DLS) is proposed. First, the opposition-based learning (OBL) is employed to accelerate the convergence speed. Second, a dynamic leader selection mechanism is utilized to improve the solution accuracy. Third, a modified archive grid controller is proposed to delete redundant solutions in external archive. The simulation results show that the performance of MMOWOA-DLS outperforms other algorithms.

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Speech Topic Classification Based on Pre-trained and Graph Networks

Speech Topic Classification Based on Pre-trained and Graph N...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Fangjing Niu Tengfei Cao Ying Hu Hao Huang Liang He School of Information Science and Engineering Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology Beijing China

Speech Topic Classification (STC) automatically classifies audio clips into predefined categories, which is widely used in short video, personalized recommendation and other fields. At present, the common system is composed of two parts: first, the speech is converted into text by automatic speech recognition (ASR), and then the text topic is classified by natural language processing (NLP). Most of them have problems such as error propagation and lack of global structure. So in this paper, we propose a new end-to-end framework based on a pre-trained model and graph network. The pre-trained model is used to extract the semantic features with sequential structure instead of acoustic features, and the combination with the global features of conversational context constructed by graph network has achieved good results on the Fisher dataset.

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DOA Estimation for RIS Assisted Multi-User Wireless Communication System with Squared-Sine Error Criterion and Lawson Norm Constraint

DOA Estimation for RIS Assisted Multi-User Wireless Communic...

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

作者： Canping Yu Li Li Yingsong Li Dazhi Sun Liping Li Zhixiang Huang Tian Hong Loh Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Aircraft Airworthiness Institute China Academy of Civil Aviation Science and Technology (Center of Aviation Safety Technology CAST) Beijing China Electromagnetic and Eletrochemical Technologies Department National Physical Laboratory Teddington Middlesex UK

Reconfigurable intelligent surface (RIS) can control the phase of reflected signals, and has become a hotspot in the field of wireless communication. In this paper, we propose a direction-of-arrival (DOA) estimation algorithm for RIS assisted multi-user wireless communication systems with squared-sine error criterion and Lawson norm constraint. This algorithm utilizes the sparsity of the signal and can achieve fast and accurate DOA estimation under the interference of impulsive noises. To suppress the line-of-sight (LOS) interference and thus to maximize the received signal-to-interference-plus-noise ratio (SINR), we also propose a random optimal phase selection (ROPS) technique to design the control matrix of RIS elements. The simulation results show that the proposed algorithm performs better than the existing methods.

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Research on cancer rapid diagnosis technology based on adaptive channel attention mechanism and two-dimensional spectral fusion

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Microchemical Journal 2025年 213卷

作者： Liu, Wei Chang, Chenjie Li, Jiahe Lv, Xiaoyi Liu, Yang Chen, Chen Chen, Cheng College of Software Xinjiang University Urumqi 830046 China School of Computer Science and Technology Xinjiang University Urumqi 830046 China Key Laboratory of Signal Detection and Processing Xinjiang University Urumqi 830046 China Xinjiang Cloud Computing Application Laboratory Xinjiang Cloud Computing Engineering Technology Research Center Karamay 834000 China

With the widespread use of Artificial Intelligence (AI) in biomedicine, integrating infrared and Raman spectra with biological information offers new prospects for enhanced disease diagnosis. For these two types of data, more information can be extracted using multimodal data fusion compared to single modality, but existing studies tend to only fuse one-dimensional spectral data, ignoring the richer information of the spectra when they are converted to two-dimensional images. In this study, we propose a rapid diagnostic method for cancer, which first converts one-dimensional (1D) Raman and Infrared spectra into two-dimensional (2D) spectral images using Short-Time Fourier Transform (STFT), respectively. Then the features are fused by our designed Adaptive Graph Channel Attention Spacial Cross-Attention Fusion Module (ASCFM). This fusion module innovatively uses the adaptive graph channel attention mechanism to strengthen the model's ability to capture the key information of different spectral features, and utilizes the spatial attention fusion module and the cross-attention module for spatial information extraction and fusion. The output fused features effectively avoid feature information loss through this multimodal feature extraction and fusion, which greatly improves the performance of the model. In this study, Gradient-weighted Class Activation Mapping is also used to make the decision-making process of the neural network more interpretable. The results show that the accuracy of 2D Raman spectral images fused with 2D infrared spectral images by ASCFM followed by ResidualNetwork (ResNet) for diagnosis of lung cancer and glioma datasets is 98.88 % and 96.38 %, which suggests that it is a highly promising adjunctive technique for cancer diagnosis. © 2025

关键词： Auxiliary diagnostic technology Deep learning Infrared spectroscopy Lung cancer Multimodal fusion Raman spectroscopy

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A supervised learning detection method with pre-processing of sparsity-based adaptive line enhancer

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Chinese Journal of Acoustics 2021年第4期40卷 496-510页

作者： JIN Shenglong CHI Cheng LI Yu HUANG Haining Institute of Acoustics Chinese Academy of SciencesBeijing 100190 Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing Chinese Academy of SciencesBeijing 100190 University of Chinese Academy of Sciences Beijing 100049

For the weak line-spectrum target detection of uniiianned underwater vehicles in the complex environment,a supervised learning detection method witli pre-processing of sparsity-based adaptive line enhancer(ALE)is *** method incorporates al_(p)-nonn sparse penalty into the cost function of ALE,and it also promotes the sparse regularization model to the 0processing of sparsity-based ALE,the entropy features of target beam spectrum become obviously *** the small sample learning ability of support ve'etor machine(SVM),the method classifies the entropy characteristic curve of beam spectrum and determines if the target *** simulation result sliows that with the-20 dB input SNR,the SNR gain of l_(1/2)-nonn sparsity-based ALE is 11.5 dB higher than that of conventional *** effectiveness of the method is verified by using the unmanned underwater vehicle(UUV)experimental *** the influence of wideband strong interferences,the false alarm rate is 3.5%and the detection rate is 95.8%,which improved the detection probability of weak line-spectrum targets.

关键词： sparsity underwater spectrum

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Research on Speech Synthesis Based on Prosodic Controllability

Research on Speech Synthesis Based on Prosodic Controllabili...

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Human-Computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Wenyu Gao Askar Hamdulla Xipeng Yang Xinjiang Key Laboratory of Signal Detection and Processing School of Information Science and Engineering Xinjiang University of China Urumqi Xinjiang China Xinjiang Key Laboratory of Multilingual Information Technology School of Information Science and Engineering Xinjiang University of China Urumqi Xinjiang China Mobvoi AI Lab Suzhou China

In today's highly interactive human-computer world, speech synthesis is widely used in many scenarios, and the requirements for rhyme effects in speech synthesis technology are increasing, so rhyme-controllable models have become a research hotspot. Most current rhyme controllable models are achieved by using a separate neural network to generate reference features, but this approach requires the training of more complex neural network models and the availability of reference audio to achieve display rhyme control. This paper proposes a rhyme-controllable solution based on an end-to-end acoustic model to address the problem of models being unable to precisely control the tone at the word level. The proposed model includes a tone-controllable module, which obtains duration information through the MFA alignment tool and adjusts the tone of the words by using word-level pitch control values and duration information. The acoustic model in this paper is improved by introducing pitch control during the generation of acoustic features and generating more robust audio by combining it with the decoder. In addition, to adjust the overall tone of the audio, a fixed coefficient is multiplied to the pitch values of all frames. Furthermore, this paper also proposes a 48KHz ultra-high-definition audio model by increasing the spectral parameter dimensions and upsampling by a factor.

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Polarimetric Adaptive Radar Target Detection in Sea Clutter with Lognormal Texture

SSRN

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SSRN 2024年

作者： Xue, Jian Yan, Jiali Xu, Shuwen Liu, Jun School of Communications and Information Engineering Xi’an University of Posts and Telecommunications Xi’an710121 China National Laboratory of Radar Signal Processing and Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi’an710071 China Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei230027 China

This paper addresses the problem of polarimetric adaptive coherent detection for maritime radar targets in the non-Gaussian sea clutter background. First, the radar sea clutter data at multiple polarimetric channels are modelled using the compound Gaussian model with an unknown speckle covariance matrix and a lognormal-distributed texture. Then, three adaptive polarimetric coherent detectors are derived based on estimation of unknown parameters and the two-step versions of generalized likelihood ratio test (GLRT), complex parameter Rao and Wald tests. All the proposed detectors exploit the clutter texture distribution information and the polarimetric information of radar data to enhance the detection performance. Finally, simulation experiments on simulated and measured radar data are utilized to evaluate the performance of the proposed detectors. The experimental results indicate that three proposed detectors outperform their competitors, and that their performance is affected by polarimetric channel parameters, i.e., the number of secondary data, the correlation of target signal or clutter speckle, the difference of signal-to-clutter ratio. Moreover, the proposed detectors approximately exhibit the constant false alarm rate property in relation to the average clutter power and the speckle covariance matrix. © 2024, The Authors. All rights reserved.

关键词： Textures

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