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Highly efficient acousto-optic modulation using nonsuspended thin-fil1m lithium niobate-chalcogenide hybrid waveguides

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Light(Science & Applications) 2022年第6期11卷 1285-1295页

作者： Lei Wan Zhiqiang Yang Wenfeng Zhou Meixun Wen Tianhua Feng Siqing Zeng Dong Liu Huan Li Jingshun Ppan Ning Zhu Weiping Liu Zhaohui Li Department of Electronic Engineering College of Information Science and TechnologyJinan University510632 GuangzhouChina Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University510275 GuangzhouChina State Key Laboratory for Modern Optical Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZhejiang UniversityZijingang Campus310058 HangzhouChina Institute of Semiconductor Science and Technology Guangdong Engineering Technology Research Center of Low Carbon and New Energy MaterialsSouth China Normal University510631 GuangzhouChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) 519000 ZhuhaiChina

A highly efficient on-chip acousto-optic modulator is as a key component and occupies an exceptional position in microwave-to-optical *** thin-film lithium niobate is preferentially employed to build the suspended configuration for the acoustic resonant cavity,with the aim of improving the modulation efficiency of the ***,the limited cavity length and complex fabrication recipe of the suspended prototype restrain further breakthroughs in modulation efficiency and impose challenges for waveguide *** this work,based on a nonsuspended thin-film lithium niobate-chalcogenide glass hybrid Mach-Zehnder interferometer waveguide platform,we propose and demonstrate a built-in push-pull acousto-optic modulator with a half-wave-voltage-length product VnL as low as 0.03 V cm that presents a modulation efficiency comparable to that of a state-of-the-art suspended counterpart.A microwave modulation link is demonstrated using our developed built-in push-pull acousto-optic modulator,which has the advantage of low power *** nontrivial acousto-optic modulation performance benefits from the superior photoelastic property of the chalcogenide membrane and the completely bidirectional participation of the antisymmetric Rayleigh surface acoustic wave mode excited by the impedance-matched interdigital transducer,overcoming the issue of low modulation efficiency induced by the incoordinate energy attenuation of acoustic waves applied to the Mach-Zehnder interferometer with two arms in traditional push-pull acousto-optic modulators.

关键词： modulator waveguide interferometer

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Rotation-DPeak: Improving Density Peaks Selection for Imbalanced Data 1

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8th China computer Federation International Conference on Big Data, CCF BIGDATA 2020

作者： Hu, Xiaoliang Yan, Ming Chen, Yewang Yang, Lijie Du, Jixiang The College of Computer Science and Technology Huaqiao University Xiamen China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Soochow China Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao University Xiamen China

ISBN: (数字)9789811607059

ISBN: (纸本)9789811607042

Density Peak (DPeak) is an effective clustering algorithm. It maps arbitrary dimensional data onto a 2-dimensional space, which yields cluster centers and outliers automatically distribute on upper right and upper left corner, respectively. However, DPeak is not suitable for imbalanced data set with large difference in density, where sparse clusters are usually not identified. Hence, an improved DPeak, namely Rotation-DPeak, is proposed to overcome this drawback according to an simple idea: the higher density of a point p, the larger δ it should have such that p can be picked as a density peak, where δ is the distance from p to its nearest neighbor with higher density. Then, we use a quadratic curve to select points with the largest decision gap as density peaks, instead of choosing points with the largest γ, where γ= ρ× δ. Experiments shows that the proposed algorithm obtains better performance on imbalanced data set, which proves that it is promising. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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A Simple Decoupling Method for Millimeter-Wave Aperture-Coupled Patch Antenna Arrays

A Simple Decoupling Method for Millimeter-Wave Aperture-Coup...

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International Workshop on Antenna technology: Small Antennas and Novel Metamaterials, iWAT

作者： Yi-Ming Zhang Xu Li Shao-Qiu Xiao Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Sun Yat-Sen University Guangzhou China

This work presents a decoupling method for aperture-coupled patch antenna arrays, especially for millimeter-wave applications since the method is simple in both principle and structure. There is no additional decoupling structure, and the decoupling is achieved by constructing a decoupling path between the feeding line of an element and the feeding aperture of the adjacent element to cancel the original mutual coupling. Although no decoupling operation is utilized between non-adjacent elements, the coupling between them is also reduced. Full-wave simulated results of an example working at 27.5 GHz are provided to verify the effectivity of the decoupling method, from impedance matching, coupling suppression, and radiation performance point of view.

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Class Constraint-based Discriminative Features Learning Algorithm for Palm Print and Palm Vein Fusion Recognition 7

Class Constraint-based Discriminative Features Learning Algo...

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7th International Conference on Signal and Image processing, ICSIP 2022

作者： Zhang, Kunyan Wang, Huabin Yu, Chengnian Du, Mengli Tao, Liang Anhui University Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Hefei China Chaohu University School of Information Engineering Hefei China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

In recent years, hand-based multimodal biometrics has received a lot of attention in the field of pattern recognition due to its convenience, stability and inclusion of a wider range of recognition features. However, Some existing multimodal hand feature extraction methods extract the features of different modalities separately and then fuse them directly, mostly ignoring the correlation between the different modalities. In this paper, a multimodal biometric feature learning algorithm combining palm vein and palm print is proposed. The pixel difference vectors in multiple directions are first extracted by calculating the difference between each pixel in both modalities and its linear neighbour pixels. Then a simple and efficient feature learning algorithm is used, and the pixel difference vectors are projected into a low-dimensional binary code in a supervised manner. Finally, we perform a feature-level fusion of the learned binary features of palm veins and palm prints for multimodal hand feature recognition. The experimental results show that the method performs better than existing finger recognition methods. © 2022 IEEE.

关键词： Pixels

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Standing on the Shoulders of Giants: Reprogramming Visual-Language Model for General Deepfake Detection 39

Standing on the Shoulders of Giants: Reprogramming Visual-La...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Lin, Kaiqing Lin, Yuzhen Li, Weixiang Yao, Taiping Li, Bin Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security SZU-AFS Joint Innovation Center for AI Technology Shenzhen University Shenzhen518060 China Tencent Youtu Lab China

ISBN: (纸本)157735897X

The proliferation of deepfake faces poses huge potential negative impacts on our daily lives. Despite substantial advancements in deepfake detection over these years, the generalizability of existing methods against forgeries from unseen datasets or created by emerging generative models remains constrained. In this paper, inspired by the zero-shot advantages of Vision-Language Models (VLMs), we propose a novel approach that repurposes a well-trained VLM for general deepfake detection. Motivated by the model reprogramming paradigm that manipulates the model prediction via input perturbations, our method can reprogram a pre-trained VLM model (e.g., CLIP) solely based on manipulating its input without tuning the inner parameters. First, learnable visual perturbations are used to refine feature extraction for deepfake detection. Then, we exploit information of face embedding to create sample-level adaptative text prompts, improving the performance. Extensive experiments on several popular benchmark datasets demonstrate that (1) the cross-dataset and cross-manipulation performances of deepfake detection can be significantly and consistently improved (e.g., over 88% AUC in cross-dataset setting from FF++ to WildDeepfake);(2) the superior performances are achieved with fewer trainable parameters, making it a promising approach for real-world applications. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Suppression of Two Stopbands and Grating Lobe in Periodic Leaky-Wave Antenna

Suppression of Two Stopbands and Grating Lobe in Periodic Le...

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Juhua Liu The Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems The School of Electronics and Information Technology Sun Yat-sen University Guangzhou China

A periodic leaky-wave antenna (PLWA) can usually produce a narrow beam scanning in the backward and in the forward quadrants with frequency. However, a PLWA with a low permittivity may suffer from some stopbands (e.g., open stopband and the next coming stopband) and unwanted grating lobe, as the main beam scans through broadside and in the forward quadrant. Besides, it may also suffer from an unwanted grating lobe, which limits its single-beam scanning range. This talk discusses recent advances in the research on the suppression of two stopbands (the open stopband and the next coming stopband) and unwanted grating lobe in PLWA.

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3-D Printed Cylindrical Luneburg Lens Antenna Based on Concentric Dielectric Shells with Same Thickness

3-D Printed Cylindrical Luneburg Lens Antenna Based on Conce...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Ning Zhang Kai Lu Nan Yang School of Electronics and Information Technology and Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University Guangzhou China

A millimeter-wave dielectric cylindrical Luneburg Lens antenna is proposed, which is comprised of multiple concentric dielectric shells of the same thickness. The dielectric-constant distribution of the cylinder is controlled by the volume fraction of air between dielectric shells. The measured gain of the proposed antenna varies from 9.86 to 11.80 dBi from 30 GHz to 40 GHz. A low side-lobe level of −18.35 dB is obtained from measured radiation patterns at 35 GHz.

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EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for Edge Devices

EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Fuquan Wu, Yu Xu, Xinxin Wang, Chuansheng Ma, Minjia Grau, Antoni Huang, Jiayan School of Computer and Big Data Minjiang University Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of New Engineering Industry Putian University Putian China Department of Automatic Control Polytechnic University of Catalonia Barcelona Spain School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China College of New Engineering Industry Putian University Fujian Ruituo Information Technology Limited Company Putian China

ISBN: (纸本)9798350386226

Fatigue driving is a common potential traffic safety hazard. To detect and analysis the driver Fatigue degree in real-time, more attention have been increasing paid to application research of EEG fatigue detection device. However, existing methods suffer from complex model structure or large-scale model parameters. In the other words, they requires high computational consumption and large memory footprint, which creates a contradiction between model and portable EEG machine with limited hardware resources. In this work, we take both time and frequency domains of EEG signal into account and design an lightweight and efficient driver fatigue detection network based on GCN (EEG-GNet), which is available edge-end device application. Experiments on 4th Raspberry Pi on a public baseline dataset show that our EEG-GNet outperforms the state-of-the-art methods and takes good tradeoff between detection accuracy and resource consumption. Our EEG-GNet provides a new potential opportunity for future applications in practical portable/wearable (P/W) devices. © 2024 IEEE.

关键词： Electrocardiography

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Sketch-based Point Cloud Generation with Diffusion Model and Pre-training Enhancement

Sketch-based Point Cloud Generation with Diffusion Model and...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yangdong Chen Mohan Chen Yuejie Zhang Rui Feng Tao Zhang Shang Gao School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China School of Information Management and Engineering Shanghai Key Laboratory of Financial Information Technology Shanghai University of Finance and Economics Shanghai China School of Information Technology Deakin University Victoria Australia

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Diffusion models, known for their success in various generative tasks like image generation and super-resolution, are applied in this study for point cloud generation, a field that has not been extensively explored due to the complexity of point clouds. We propose a novel method using a diffusion model to generate high-quality 3D point clouds from 2D sketches. This method employs a self-supervised contrastive learning scheme to align sketch and point cloud modalities. Additionally, it incorporates a specific partition mixing strategy to integrate edge information during pre-training. Evaluated on two benchmark datasets, our method outperforms existing state-of-the-art approaches, showcasing the potential of diffusion models in point cloud generation and setting a new direction for future research.

关键词： Point cloud compression Three-dimensional displays Image synthesis Superresolution Contrastive learning Benchmark testing Signal processing Diffusion models Stability analysis Speech processing

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3D hierarchical porous Cr2O3 nanomaterials for high performance dimethyl disulfide gas sensor

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Ceramics International 2025年第16期51卷 22067-22074页

作者： Guo, Wen Deng, Zanhong Zhang, Ruofan Klamchuen, Annop Horprathum, Mati Wang, Shimao Fang, Xiaodong You, Libing Meng, Gang Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Anhui Provincial Key Laboratory of Photonic Devices and Materials Anhui Institute of Optics and Fine Mechanics And Key Lab of Photovoltaic and Energy Conservation Materials Chinese Academy of Sciences Hefei230031 China Advanced Laser Technology Laboratory of Anhui Province Hefei230037 China Wan Jiang Emerging Industry Technology Development Center Tongling244000 China National Nanotechnology Center National Science and Technology Development Agency Pathum Thani12120 Thailand Opto-Electrochemical Sensing Research Team Spectroscopic and Sensing Devices Research Group National Electronics and Computer Technology Center Pathum Thani12120 Thailand College of New Materials and New Energies Shenzhen Technology University Shenzhen518118 China Shenzhen Shengfang Technology Company Limited Shenzheng518116 China

Dimethyl disulfide (DMDS) is one of the malodorous gases mandatorily monitored by the government. Developing highly sensitive and selective DMDS sensors based on metal oxide semiconductor (MOS) is an urgent requirement and remains a challenge. In this study, 3D hierarchical mesoporous Cr2O3 nanoparticles were successfully synthesized by a time- and cost-efficient solution combustion synthesis method. The sensing performances of the as-synthesized mesoporous Cr2O3 nanoparticles have been thoroughly investigated. The sensor demonstrated a high response of 102 to 10 ppm DMDS at working temperature of 140 °C, along with satisfactory selectivity and long-term stability, indicating a promising future in DMDS detection. © 2025

关键词： Combustion synthesis

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