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An Efficient WRF Framework for Discovering Risk Genes and Abnormal Brain Regions in Parkinson's Disease Based on Imaging Genetics Data

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Journal of Computer Science & Technology 2021年第2期36卷 361-374页

作者： Xia-An Bi Zhao-Xu Xing Rui-Hui Xu Xi Hu College of Information Science and Engineering Hunan Normal UniversityChangsha 410006China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal UniversityChangsha 410006China

As an emerging research field of brain science,multimodal data fusion analysis has attracted broader attention in the study of complex brain diseases such as Parkinson's disease(PD).However,current studies primarily lie with detecting the association among different modal data and reducing data *** data mining method after fusion and the overall analysis framework are *** this study,we propose a weighted random forest(WRF)model as the feature screening *** interactions between genes and brain regions are detected as input multimodal fusion features by the correlation analysis *** implement sample classification and optimal feature selection based on WRF,and construct a multimodal analysis framework for exploring the pathogenic factors of *** experimental results in Parkinson's Progression Markers Initiative(PPMI)database show that WRF performs better compared with some advanced methods,and the brain regions and genes related to PD are *** fusion of multi-modal data can improve the classification of PD patients and detect the pathogenic factors more comprehensively,which provides a novel perspective for the diagnosis and research of *** also show the great potential of WRF to perform the multimodal data fusion analysis of other brain diseases.

关键词： multimodal fusion feature Parkinson's disease pathogenic factor detection sample classification weighted random forest model

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Joint Secure Transmit Beamforming Designs for Physical Layer Security in MIMO-ISAC System

Joint Secure Transmit Beamforming Designs for Physical Layer...

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signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Sitong Guo Hao Zheng Yinghui Zhang Junkun Yan College of Electronic Information Engineering Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Inner Mongolia University Hohhot China National Key Laboratory of Radar Signal Processing Xidian University Xian China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

This article concentrates on the physical layer security (PLS) towards an integrated sensing and communication (ISAC) system, which communicates with legitimate communication users (CUs) and detects the single sensing target, which is considered to be eavesdropper because it might intercept the transmitting message from the base station to CUs. The joint transmitting beamforming for secure communication and sensing is designed to maximize the sum secrecy rate (SR) of system under the constraints of quality-of-service of CUs, the signal-to-Noise Ratio (SNR) of sensing and the power budget of the system. The optimal solution is obtained by the semidefinite relaxation and successive convex approximation algorithms. The availability of the beamforming design in ensuring the SR of the ISAC system is showed by Simulation results.

关键词： Array signal processing Simulation Quality of service Physical layer security Integrated sensing and communication Data processing MIMO Copper Optimization signal to noise ratio

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ONE2SET + Large Language Model: Best Partners for keyphrase Generation

ONE2SET + Large Language Model: Best Partners for Keyphrase ...

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2024 Conference on Empirical Methods in Natural Language processing, EMNLP 2024

作者： Shao, Liangying Zhang, Liang Peng, Minlong Ma, Guoqi Yue, Hao Sun, Mingming Su, Jinsong School of Informatics Xiamen University China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Xiamen University Ministry of Culture and Tourism China Cognitive Computing Lab Baidu Research China Beijing Institute of Mathematical Sciences and Applications China

ISBN: (纸本)9798891761643

keyphrase generation (KPG) aims to automatically generate a collection of phrases representing the core concepts of a given document. The dominant paradigms in KPG include ONE2SEQ and ONE2SET. Recently, there has been increasing interest in applying large language models (LLMs) to KPG. Our preliminary experiments reveal that it is challenging for a single model to excel in both recall and precision. Further analysis shows that: 1) the ONE2SET paradigm owns the advantage of high recall, but suffers from improper assignments of supervision signals during training;2) LLMs are powerful in keyphrase selection, but existing selection methods often make redundant selections. Given these observations, we introduce a generate-then-select framework decomposing KPG into two steps, where we adopt a ONE2SET-based model as generator to produce candidates and then use an LLM as selector to select keyphrases from these candidates. Particularly, we make two important improvements on our generator and selector: 1) we design an Optimal Transport-based assignment strategy to address the above improper assignments;2) we model the keyphrase selection as a sequence labeling task to alleviate redundant selections. Experimental results on multiple benchmark datasets show that our framework significantly surpasses state-of-the-art models, especially in absent keyphrase prediction. We release our code at https://***/DeepLearnXMU/KPG-SetLLM. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China

ISBN: (纸本)9798350301298

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. © 2023 IEEE.

关键词： Autonomous driving

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A Novel Frequency Reconfigurable Mode Reconfigurable Ultra-Wideband Antenna

A Novel Frequency Reconfigurable Mode Reconfigurable Ultra-W...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Chen. Guo Xianliang. Wu Zhixiang. Huang Anhui University Hefei China Ministry of Education Key Laboratory of Intelligent Computing and Signal Processing Hefei China

Aiming at the inability to reconstruct the frequency and the pattern of the traditional monopole antenna, an ultra-wideband monopole antenna with frequency reconstruction and pattern reconstruction is proposed. The antenna consists of a monopole antenna and a metasurface with a distance H1 between them. Using HFSS simulation software to simulate, the size of the monopole antenna is 30mm×30mm×1.6mm, and the center frequency is 4.3 GHz. The simulation results show that the impedance bandwidth of the antenna when S11 is less than -10 dB is 3.21-13.64 GHz. In this design, the antenna widens the bandwidth while realizing the frequency reconstruction and pattern reconstruction, and basically does not affect other performances. The simulation results are basically consistent with the measured results, indicating that the antenna has good gain and radiation characteristics in the working frequency band, and can be widely used in ultra-wideband communication systems.

关键词： Antenna measurements Simulation Bandwidth Gain measurement Metasurfaces Ultra wideband antennas Software

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Design of Broadband Asymmetric Multisection Directional Coupler

Design of Broadband Asymmetric Multisection Directional Coup...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Xiaolei Geng Xianliang Wu Zhixiang Huang Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China

The multi-section coupled transmission line is equivalent to the cascade of multi-section ladder impedance filters, which provides a basis for the research of broadband directional couplers and meets the needs of microwave systems. Using this method, a multi-section -15 dB stripline directional coupler was designed in the application frequency range of 0.7-3.7 GHz, and the directional coupler was improved by loading the branch compensation capacitor. And through the electromagnetic simulation software HFSS for simulation optimization. The simulation results show that the coupling degree of the coupler is about -15 dB in 0.7-3.7 GHz, the return loss is greater than 20 dB and the isolation is greater than 30 dB, the insertion loss is less than 0.33 dB, the in-band fluctuation is less than 1 dB, and the physical size is 38mm $\times 6$ mm, which meets the design requirements of the -15 dB coupler.

关键词： Power transmission lines Stripline Simulation Software Broadband communication Impedance Microwave filters

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Pulse train coding design for MIMO radar against interrupted sampling repeater jamming with Doppler frequency shifts

Pulse train coding design for MIMO radar against interrupted...

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signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Hao Wu Hao Zheng Yinghui Zhang Junkun Yan College of Electronic Information Engineering Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Inner Mongolia University Hohhot China National Key Laboratory of Radar Signal Processing Xidian University Xian China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Intercepting and repeatedly retransmitting radar signals, interrupted sampling repeater jamming (ISRJ) generates higher power false signals that can seriously affect radar operation. To combat this interference, a scheme for countering ISRJ with Doppler frequency shifts by designing a multiple input multiple output (MIMO) radar with pulse train encoding and decoding is proposed. On the one hand, the scheme can suppress the pulse compression sidelobes of the target and ISRJ with Doppler frequency shifts. On the other hand, a detection matrix is designed to identify spurious peaks formed by interfering signals. Finally, the proposed scheme can accurately obtain target and jamming information in the environment while satisfying the constant mode (CM) constraints.

关键词： Hands MIMO radar Interference Repeaters Encoding MIMO Doppler radar Decoding Doppler effect Jamming

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Broadband external rejection miniaturized SIW filter based on C-shaped symmetric structure

Broadband external rejection miniaturized SIW filter based o...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Shuang Xiao Minquan Li Xin Qu Chen Li Zufeng Zhang Key Laboratory of Intelligent Computing&Signal Processing Ministry of Education Anhui University Hefei Liaoyang Province

To effectively improve the frequency selectivity of the filter, a substrate integrated waveguide (SIW) filter with miniaturization and out-of-band rejection was designed. To achieve the desired filter response, symmetrical C-shaped resonators are etched on the top and bottom layers of the SIW filter. The C-shaped resonator etched on the top layer of SIW achieves miniaturization and filtering characteristics. In order to improve the frequency response, a two-stage SIW filter and a SIW filter with coupled gap-ring defected ground structure (CGRDGS) are proposed, and an equivalent circuit is given to verify the transmission response. The simulation results show that the filter achieves miniaturization, out-of-band rejection and low insertion loss, which can be used in 5G wireless communication The simulation results show that the filter achieves miniaturization, out-of-band rejection and low insertion loss, which can be used in 5G wireless communication.

关键词： Wireless communication 5G mobile communication Filtering Simulation Resonator filters Resonant frequency Insertion loss

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Adversarial Example Generation Method Based on Probability Histogram Equalization

Adversarial Example Generation Method Based on Probability H...

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Chinese Control Conference (CCC)

作者： Youqing Fang Jingwen Jia Yuhai Yang Wan-Li Lyu Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China

CNNs (Convolutional Neural Networks) have a good performance on most classification tasks, but they are vulnerable when meeting adversarial examples. Research and design of highly aggressive adversarial examples can help enhance the security and robustness of CNNs. The transferability of adversarial examples is still low in black-box settings. Therefore, an adversarial example method based on probability histogram equalization, namely HE-MI-FGSM (Histogram Equalization Momentum Iterative Fast Gradient Sign Method) is proposed. In each iteration of the adversarial example generation process, the original input image is randomly histogram equalized, and then the gradient is calculated to generate adversarial perturbations to mitigate overfitting in the adversarial example. The effectiveness of the method is verified on the ImageNet dataset. Compared with the advanced method I-FGSM (Iterative Fast Gradient Sign Method) and MI-FGSM (Momentum I-FGSM), the attack success rate in the adversarial training network increased by 27.9% and 7.7% on average, respectively.

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Efficient QoS Data Prediction Based on Tensor Kernel Paradigm-Tensor Decomposition

Efficient QoS Data Prediction Based on Tensor Kernel Paradig...

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International Conference on Networking and Network Applications (NaNA)

作者： Hong Xia Jing Xu Qingyi Dong Hui Jia Yanping Chen Xi’an Key Laboratory of Big Data and Intelligent Computing Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing School of Computer Science and Technology Xi’an University of Posts and Telecommunications Xi’an Shaanxi China

ISBN: (数字)9798350376777

ISBN: (纸本)9798350376784

In the Mobile Edge computing (MEC) environment, the prediction efficiency is low when user recommendation is based on Quality of Service (QoS) data due to network environment and other factors. Traditional methods use Collaborative Filtering (CF) or tensor decomposition methods to mine the relationship between historical QoS data for prediction, but there are problems with prediction accuracy and efficiency. Given this, this paper proposes an efficient QoS data prediction method (CTT) combining tensor kernel paradigm-tensor decomposition. The method first introduces the tensor kernel norm to approximate the tensor rank function to better capture the spatio-temporal correlation of real QoS data; Second, tensor decomposition is combined to address inefficiencies. Experimental results on the public QoS dataset WS-Dream show that the method significantly improves the runtime while guaranteeing prediction accuracy and applies to scenarios with different data missing densities.

关键词： Tensors Accuracy Runtime Multi-access edge computing Computational modeling Quality of service Predictive models

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