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

作者： Wang, Wen-Tao Zhu, Hao-Ran Sun, Yu-Fa Huang, Zhi-Xiang Wu, Xian-Liang Anhui University Key Laboratory Of Intelligent Computing And Signal Processing Ministry Of Education Hefei230039 China

ISBN: (纸本)9781665434379

In this paper, a compact and high selectivity millimeter wave on-chip band-pass filter using GaAs pHEMT technology is proposed. A compact lumped element unit, which consists of a series LC resonator and an extra capacitor, is used to produce a transmission zero near the pass-band without occupying much area. The proposed filter consists two of the proposed resonators. An additional series resonator is grounded to produce a transmission zero. The area of the proposed filter is only 0.816×0.607mm2. The presented filter is worked on 25.5 GHz, the 3-dB bandwidth is 21.5 GHz to 29.5GHz. The insertion loss is around 1.1dB, and the return loss is better than 17dB. © 2021 IEEE.

关键词： Bandpass filters

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Femtosecond laser-induced flexible and highly sensitive capacitive pressure sensor with treefrog suckers bionic microstructure 2

Femtosecond laser-induced flexible and highly sensitive capa...

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2nd International Symposium on Sensor Technology and Control, ISSTC 2023

作者： Wang, Zhiyun Chu, Mengyang Su, Yahui Guo, Xiaohui Liu, Rui Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Electronic and Information Engineering Hefei China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University School of Integrated Circuits Hefei China Anhui Xinhuai Electronics Co. Ltd Huaibei China

ISBN: (纸本)9798350314465

Flexible capacitive pressure sensors are optimal for wearable electronic equipment owing to their advantages of simplicity in architecture and low power consumption. However, fabricating a bionic flexible capacitive pressure sensor with high sensitivity and a wide dynamic range of detection is still a great challenge. In this article, we propose a flexible pressure sensor based on femtosecond laser ablation with a treefrog suckers bionic microstructure. The treefrog suckers capacitive pressure sensor (TSCPS) has high sensitivity (0-10 kPa, 0.0762 kPa-1), wide detection range (500 kPa), high repeatability (>12000 s at 10 kPa), and fast response time (62.5 ms). For practical applications, the TSCPS was positioned on the wrist, palm, and sole of the hand to detect the movements of each part accordingly. The experimental findings indicate that the TSCPS has broad promising applications in bionic wearable products such as human locomotion monitoring. © 2023 IEEE.

关键词： Pressure sensors

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A Multi-Stage Expensive Constrained Multi-Objective Optimization Algorithm Based on Ensemble Infill Criterion

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Wu, Haofeng Chen, Qingda Chen, Jiaxin Jin, Yaochu Ding, Jinliang Zhang, Xingyi Chai, Tianyou State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Computer Science and Technology Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

Surrogate-assisted evolutionary algorithms (SAEAs) rely on the infill criterion to select candidate solutions for expensive evaluations. However, in the context of expensive constrained multi-objective optimization problems (ECMOPs) with complex feasible regions, guiding the optimization algorithm towards the constrained Pareto optimal front and achieving a balance between feasibility, convergence, diversity, exploration, and exploitation using a single infill criterion pose significant challenges. We propose an ensemble infill criterion-based multi-stage SAEA (EIC-MSSAEA) to tackle these challenges. Specifically, EIC-MSSAEA comprises three stages. In the first stage, we ignore constraints to facilitate the rapid traversal of infeasible obstacles. In the second stage, only one constraint is activated at a time to increase algorithm diversity. Finally, in the last stage, we activate all constraints to improve overall feasibility. In each stage, EIC-MSSAEA first employs NSGA-III as the underlying baseline solver to explore the search space, in which promising solutions are then selected by an ensemble infill criterion that incorporates multiple base-infill criteria to measure the feasibility, convergence, diversity, and uncertainty of candidate solutions. Experimental results demonstrate the competitiveness of EIC-MSSAEA against state-of-the-art SAEAs for ECMOPs. IEEE

关键词： Linear programming

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Hybrid particle swarm optimization with adaptive learning strategy

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Soft computing 2024年第17-18期28卷 9759-9784页

作者： Wang, Lanyu Tian, Dongping Gou, Xiaorui Shi, Zhongzhi School of Mathematics and Information Sciences Baoji University of Arts and Science Shaanxi Baoji721007 China Institute of Computer Software Baoji University of Arts and Sciences Shaanxi Baoji721007 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

Particle swarm optimization (PSO) is a meta-heuristic algorithm that can be used to solve different real-world optimization problems. However, PSO suffers from some intrinsic drawbacks, including falling into local optimal and slow convergence in the latter evolution process. To deal with these issues, a hybrid PSO with adaptive learning strategy (abbreviated as HPSO-ALS) is proposed in this paper. To start with, the chaotic opposition-learning method is employed to generate the uniformly distributed particles so as to enhance the quality of the initial swarm. Next, a self-logical mapping-based nonlinear decreasing inertia weight is formulated to trade off the global search and local search abilities. Meanwhile, different adaptive position updating strategies are leveraged to achieve better convergence according to different evolution status. In addition, inspired by the cask effect, the global worst particle (gworst) is introduced into the velocity updating to make full use of the potential information of the particles. Finally, extensive experiments on sixteen benchmark functions and CEC’13 test suite have verified the promising performance of HPSO-ALS proposed in this paper. Alternatively, HPSO-ALS is also applied to the classical traveling salesman problem (TSP) and the experimental results have further validated the effectiveness and efficiency of our proposal. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Traveling salesman problem

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An attention-based cascade R-CNN model for sternum fracture detection in X-ray images

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CAAI Transactions on Intelligence Technology 2022年第4期7卷 658-670页

作者： Yang Jia Haijuan Wang Weiguang Chen Yagang Wang Bin Yang School of Computer Xi'an University of Posts and TelecommunicationsXi'anShaanxiChina Shaanxi Key Laboratory of Network Data Intelligent Processing Xi'an University of Posts and TelecommunicationsXi'anShaanxiChina Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'anShaanxiChina Department of Radiology Xi'an Honghui HospitalXi'anChina

Fracture is one of the most common and unexpected *** not treated in time,it may cause serious consequences such as joint stiffness,traumatic arthritis,and nerve *** computer vision technology to detect fractures can reduce the workload and misdiagnosis of fractures and also improve the fracture detection ***,there are still some problems in sternum fracture detection,such as the low detection rate of small and occult *** this work,the authors have constructed a dataset with 1227 labelled X-ray images for sternum fracture *** authors designed a fully automatic fracture detection model based on a deep convolution neural network(CNN).The authors used cascade R-CNN,attention mechanism,and atrous convolution to optimise the detection of small fractures in a large X-ray image with big local *** authors compared the detection results of YOLOv5 model,cascade R-CNN and other state-of-the-art *** authors found that the convolution neural network based on cascade and attention mechanism models has a better detection effect and arrives at an mAP of 0.71,which is much better than using the YOLOv5 model(mAP=0.44)and cascade R-CNN(mAP=0.55).

关键词： attention mechanism cascade R-CNN fracture detection X-ray image

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Improving Fake News Video Detection by Correlating with Neighbors 61

Improving Fake News Video Detection by Correlating with Neig...

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Findings of the Association for Computational Linguistics, ACL 2023

作者： Qi, Peng Zhao, Yuyang Shen, Yufeng Ji, Wei Cao, Juan Chua, Tat-Seng Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China National University of Singapore Singapore

ISBN: (纸本)9781959429623

The prevalence of short video platforms has spawned a lot of fake news videos, which have stronger propagation ability than textual fake news. Thus, automatically detecting fake news videos has been an important countermeasure in practice. Previous works commonly verify each news video individually with multimodal information. Nevertheless, news videos from different perspectives regarding the same event are commonly posted together, which contain complementary or contradictory information and thus can be used to evaluate each other mutually. To this end, we introduce a new and practical paradigm, i.e., cross-sample fake news video detection, and propose a novel framework, Neighbor-Enhanced fakE news video Detection (NEED), which integrates the neighborhood relationship of new videos belonging to the same event. NEED can be readily combined with existing single-sample detectors and further enhance their performances with the proposed graph aggregation (GA) and debunking rectification (DR) modules. Specifically, given the feature representations obtained from single-sample detectors, GA aggregates the neighborhood information with the dynamic graph to enrich the features of independent samples. After that, DR explicitly leverages the relationship between debunking videos and fake news videos to refute the candidate videos via textual and visual consistency. Extensive experiments on the public benchmark demonstrate that NEED greatly improves the performance of both single-modal (up to 8.34% in accuracy) and multimodal (up to 4.97% in accuracy) base detectors. Codes are available in https://***/ICTMCG/NEED. © 2023 Association for Computational Linguistics.

关键词： Benchmarking

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On some properties of the bibasic Humbert hypergeometric functions Ξ_(1) and Ξ_(2)

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Applied Mathematics(A Journal of Chinese Universities) 2023年第4期38卷 614-630页

作者： CAI Qing-bo Ghazi S.Khammash Shimaa I.Moustafa Ayman Shehata Provincial Key Laboratory of Data-Intensive Computing Key Laboratory of Intelligent Computing and Information ProcessingSchool of Mathematics and Computer ScienceQuanzhou Normal UniversityQuanzhou 362000China Department of Mathematics Al-Aqsa UniversityGazaGaza StripPalestine Department of Mathematics Faculty of ScienceAssiut UniversityAssiut 71516Egypt Department of Mathematics Unaizah College of Science and ArtsUnaizah 56264Qassim UniversityBuraydah 52571QassimSaudi Arabia

The main object of this paper is to deduce the bibasic Humbert functions Ξ_(1) and Ξ_(2)Some interesting results and elementary summations technique that was successfully employed,q-recursion,q-derivatives relations,the q-differential recursion relations,the q-integral representations for Ξ_(1) and Ξ_(2)are *** summation formula derives a list of p-analogues of transformation formulas for bibasic Humbert functions that have been studied,also some hypergeometric functions properties of some new interesting special cases have been given.

关键词： q-calculus bibasic Humbert hypergeometric functions q-derivative

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Research on signal Denoising Method Based on Symplectic Geometric Mode Decomposition and Savitzky-Golay Filtering

Research on Signal Denoising Method Based on Symplectic Geom...

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

作者： Xuelong Xu Jin Zhao Bo Wu Xianliang Wu Jincheng Ni Ping Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Anhui University Hefei China

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

The paper proposes a noise reduction algorithm based on symplectic Geometric Mode Decomposition (SGMD) and Savitzky-Golay (SG)filtering to address the issue of noise interference during signal transmission. Firstly, the noisy signal is decomposed using symplectic geometric mode decomposition to obtain several symplectic geometric components. The component with less noise is then selected and superimposed based on its energy entropy. Finally, the reconstructed signal undergoes denoising through SG filtering. The proposed method is applied to conduct comparison experiments on noise reduction for linear frequency modulation signals and multicomponent periodic signals. The results demonstrate a significant noise reduction effect of the proposed method, which holds great significance for signal analysis and research on noise reduction.

关键词： Smoothing methods Noise reduction Noise Interference Information filters Robustness signal denoising

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Slew-Driven Layer Assignment for Advanced Non-default-rule Wires 20th

Slew-Driven Layer Assignment for Advanced Non-default-rule W...

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Proceedings of the 20th Web Information Systems and Applications Conference, WISA 2023

作者： Lu, Ren Zhang, Wei Jiang, Lieqiu Liu, Genggeng College of Computer and Data Science Fuzhou University Fuzhou350116 China Key Laboratory of Network Computing and Intelligent Information Processing Fujian Province Fuzhou350116 China

ISBN: (纸本)9789819962211

With the rapid increase in circuit density in Very Large Scale Integration, the proportion of interconnect delay in circuit timing is also increasing. This makes the importance of layer assignment algorithms increasingly prominent in circuit design. However, most previous layer assignment algorithms prioritize optimizing timing exclusively from the perspective of interconnect delay, thereby disregarding the impact of slew violations on circuits. Therefore, this paper proposes a slew-driven layer assignment algorithm, which considers the timing of different routing layers and introduces non-default-rule wires to design a layer assignment algorithm that can significantly optimize delay, congestion, and slew violations. This algorithm mainly includes three key technologies: 1) Introducing non-default-rule wires technology to optimize timing and adopting a negotiation based approach to ensure that the final routing scheme does not have overflow;2) Proposing a slew prioritization strategy that comprehensively considers slew and interconnect delay during the routing process;3) Proposing a timing critical awareness strategy to further optimize the slew and interconnect delay without worsening the overflow. The experimental results show that the proposed algorithm has significant effects on optimizing delay and reducing slew violations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wire

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A prompt-based approach to adversarial example generation and robustness enhancement

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Frontiers of Computer Science 2024年第4期18卷 85-96页

作者： Yuting YANG Pei HUANG Juan CAO Jintao LI Yun LIN Feifei MA Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing 100190China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Department of Computer Science Stanford UniversityCA 94305USA School of Computing National University of SingaporeSingapore 119077Singapore Laboratory of Parallel Software and Computational Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Recent years have seen the wide application of natural language processing(NLP)models in crucial areas such as finance,medical treatment,and news media,raising concerns about the model robustness and *** find that prompt paradigm can probe special robust defects of pre-trained language *** prompt texts are first constructed for inputs and a pre-trained language model can generate adversarial examples for victim models via *** results show that prompt paradigm can efficiently generate more diverse adversarial examples besides synonym ***,we propose a novel robust training approach based on prompt paradigm which incorporates prompt texts as the alternatives to adversarial examples and enhances robustness under a lightweight minimax-style optimization *** on three real-world tasks and two deep neural models show that our approach can significantly improve the robustness of models to resist adversarial attacks.

关键词： robustness adversarial example prompt learning pre-trained language model

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