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arXiv 2023年

作者： Gu, Jiaming Mou, Yicheng Ma, Jianwen Chen, Haonan Zhang, Chuanxin Wang, Yuxiang Wang, Jiayu Guo, Hangwen Shi, Wu Yuan, Xiang Jiang, Xue Ta, Dean Shen, Jian Zhang, Cheng State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Center for Biomedical Engineering School of Information Science and Technology Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China Shanghai Qi Zhi Institute Shanghai200232 China State Key Laboratory of Precision Spectroscopy East China Normal University Shanghai200241 China School of Physics and Electronic Science East China Normal University Shanghai200241 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China

Light-to-electricity conversion is crucial for energy harvesting and photodetection, requesting efficient electron-hole pair separation to prevent recombination. Traditional junction-based mechanisms using built-in electric fields fail in non-barrier regions. Homogeneous material harvesting under photovoltaic effect is appealing but only realized in non-centrosymmetric systems via bulk photovoltaic effect. Here we report the realization of photovoltaic effect by employing surface acoustic waves (SAW) to generate zero-bias photocurrent in a conventional layered semiconductor MoSe2. SAW induces periodic modulation to electronic bands and drags the photoexcited pairs toward the travelling direction. The photocurrent is extracted by a local barrier. The separation of generation and extraction processes suppresses recombination and yields large nonlocal photoresponse. We distinguish acousto-electric drag and electron-hole pair separation effect by fabricating devices of different configurations. The acousto-drag photovoltaic effect, enabled by piezoelectric integration, offers an efficient light-to-electricity conversion method, independent of semiconductor crystal symmetry. © 2023, CC BY.

关键词： Energy harvesting

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Semi-vortex solitons and their excited states in spin-orbit-coupled binary bosonic condensates

arXiv

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arXiv 2024年

作者： Deng, Haiming Li, Jinqing Chen, Zhaopin Liu, Yaohui Liu, Dong Jiang, Chunzhi Kong, Chao Malomed, Boris A. School of Physics and Electronic-Electrical Engineering Xiangnan University Chenzhou423000 China Microelectronics and Optoelectronics Technology Key Laboratory of Hunan Higher Education Xiangnan University Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University Chenzhou423000 China Physics Department Solid-State Institute Technion Haifa32000 Israel Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

It is known that two-dimensional two-component fundamental solitons of the semi-vortex (SV) type, with vorticities (s+, s−) = (0, 1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binary Bose-Einstein condensate with the contact self-attraction acting in both components, in spite of the possibility of the critical collapse in the system. However, excited states (ESs) of the SV solitons, with the vorticity set (s+, s−) = (S+, S+ + 1) and S+ = 1, 2, 3, ..., are unstable in the same system. We construct ESs of SV solitons in the SOC system with opposite signs of the self-interaction in the two components. The main finding is stability of the ES-SV solitons, with the extra vorticity (at least) up to S+ = 6. The threshold value of the norm for the onset of the critical collapse, Nthr, in these excited states is higher than the commonly known critical value, Nc ≈ 5.85, associated with the single-component Townes solitons, Nthr increasing with the growth of S+. A velocity interval for stable motion of the GS-SV solitons is found too. The results suggest a solution for the challenging problem of the creation of stable vortex solitons with high topological charges. Copyright © 2024, The Authors. All rights reserved.

关键词： Excited states

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Collision Attack Framework on RIPEMD-128

Collision Attack Framework on RIPEMD-128

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International Conference on Artificial Intelligence and advanced Manufacturing (AIAM)

作者： Jingyu Li Guang Zeng Yang Yang State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Force Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Information Engineering University Zhengzhou China Trusted Computing and Information Assurance Laboratory Institute of Software Chinese Academy of Sciences Beijing China

In the last few years, the hash functions are the very common and essential primitives implemented in lots of fields. RIPEMD-128, a member of MD-family hash function, has been found collisions on the full round. In this paper, we further analyze the property about the security against collision attack of RIPEMD-128. The collision attack framework for RIPEMD-128 is proposed in order to provide ideas for other hash functions. The framework consists of three parts namely choosing a message word difference insertion, constructing differential characteristics and collision search phase. Cryptographic techniques including message modification is also introduced to reduce the complexity.

关键词： Hash functions Complexity theory Cryptography Artificial intelligence

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SURE-based Stopping Strategy for Fine-tunable Supervised PET Image Denoising

SURE-based Stopping Strategy for Fine-tunable Supervised PET...

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2021 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Cui, Jianan Gong, Kuang Guo, Ning Wollenweber, Scott Jansen, Floris Liu, Huafeng Li, Quanzheng Zhejiang University State Key Laboratory of Modern Optical Instrumentation College of Optical Science and Engineering Hangzhou China Massachusetts General Hospital Harvard Medical School Center for Advanced Medical Computing and Analysis BostonMA United States Massachusetts General Hospital Harvard Medical School Gordon Center for Medical Imaging BostonMA United States Ge Healthcare Waukesha United States

ISBN: (纸本)9781665421133

Previously, based on the unsupervised deep learning method, conditional deep image prior (CDIP), we showed the possibility of finetuning during the testing phase after supervised learning. However, one barrier for CDIP finetuning is that it needs early stopping before the network output converges to the noise which is hard to determine. In this work, we proposed to construct the finetuning loss based on Stein's unbiased risk estimator (SURE), which can provide an unbiased estimation of the true mean square error (MSE). We demonstrated that using SURE-based finetuning loss, the network output can be close to the ground truth while not converging to the noise. Quantification results based on seven real patient datasets show that the proposed method is more stable during finetuning than CDIP. © 2021 IEEE.

关键词： Image denoising

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An landmark evaluation algorithm based on router identification and delay measurement 5th

An landmark evaluation algorithm based on router identificat...

引用

5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Ma, Te Liu, Fenlin Zhang, Fan Luo, Xiangyang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Science and Technology Institute Zhengzhou China

ISBN: (纸本)9783030242701

City-level landmarks serve as an important foundation for achieving city-level and higher-precision IP geolocation. On the basis of the feature that router host names in network-developed areas often imply geographical location information, this paper proposes a city-level landmark evaluation algorithm based on router identification. Firstly, router host name matching rules are formulated by using plenty of network topology information obtained through probing. Secondly, the matching rules are used to extract router host names;the geographical locations corresponding to routers are queried through the established geographical location dictionary;and the nearest router that can obtain a city-level location in the probing path is reserved. Finally, candidate landmarks are evaluated based on the rule that the physical distance between network entities is less than the delay conversion distance. The experimental results show that the proposed algorithm can effectively evaluate the reliability of landmarks: among the experimental results on 8000 network landmarks in 4 cities in the United states, compared with the typical database query-based landmark obtaining, the city-level accuracy rates of landmarks are increased by 4.4%, 6.85%, 4.35% and 7.05% respectively. © Springer Nature Switzerland AG 2019.

关键词： Location

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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CCA-Net: Zero-shot SSVEP classification via an integration of canonical correlation analysis and deep neural network

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Deng, Yang Ji, Zhiwei Wang, Yijun Zhou, S. Kevin Harbin Institute of Technology School of Life Science and Technology Heilongjiang Harbin150001 China University of Science and Technology of China Division of Life Sciences and Medicine School of Biomedical Engineering Anhui Hefei230026 China Suzhou Institute for Advanced Research Jiangsu Suzhou215123 China Nanjing Agricultural University College of Artificial Intelligence Jiangsu Nanjing210095 China Chinese Academy of Sciences State Key Laboratory on Integrated Optoelectronics Institute of Semiconductors Beijing100083 China University of Science and Technology of China Key Laboratory of Precision and Intelligent Chemistry Anhui Hefei230026 China Chinese Academy of Sciences Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology Beijing100190 China

Accurate decoding of electroencephalographic (EEG) signals is a crucial foundation for brain-computer interface (BCI) applications. Among various decoding approaches, those that do not require calibration are particularly significant for advancing BCI technologies into everyday life, as they alleviate user fatigue by eliminating the need for user-specific training. In this study, we integrate a deep neural network with canonical correlation analysis (CCA) to form the CCA-Net approach for decoding steady-state visually evoked potential (SSVEP) based BCI without user-specific calibration, i.e., at the zero-shot scenario. The CCA-Net aims to reduce the cross-subject domain gap for better transfer learning and make full use of the testing signal itself. Specifically, it adapts the cross-subject dual-domain fusion network (CSDuDoFN) by transferring the global multi-reference least-squares transformation coefficient from source subjects to both source and target data to reduce the cross-subject domain gap. In addition, CCA-Net enhances the transfer template-based canonical correlation analysis (tt-CCA) by introducing a subject-specific template to replace the sine-cosine reference template and adding an extra CCA coefficient to make full use of the testing signal itself, resulting in the Modified tt-CCA. Finally, the features extracted by CSDuDoFN and Modified tt-CCA are integrated to produce the final decoding result. Our approach leverages the strengths of both data-driven and model-driven methods and achieves state-of-the-art performance on three publicly available datasets, thus holding the potential to facilitate everyday BCI applications based on SSVEP. The reproducibility code is available at: https://***/Sungden/Zero-shot-SSVEP-classification. © 1963-2012 IEEE.

关键词： Deep neural networks

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Unveiling Hidden Vulnerabilities in Digital Human Generation via Adversarial Attacks

arXiv

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arXiv 2025年

作者： Li, Zhiying Jin, Yeying Shen, Fan Liu, Zhi Chen, Weibin Zhang, Pengju Zhang, Xiaomei Chen, Boyu Shen, Michael Wu, Kejian Fan, Zhaoxin Dong, Jin College of Cyber Security Jinan University China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing School of Artificial Intelligence Beihang University China Hangzhou International Innovation Institute Beihang University China Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Electrical and Computer Science University of Pittsburgh United States State Key Laboratory of Multimodal Artificial Intelligence Institute of Automation Chinese Academy of Science China Institute of Automation Chinese Academy of Science China University College London United Kingdom Mingdu Tech China Xreal Beijing Academy of Blockchain and Edge Computing China

Expressive human pose and shape estimation (EHPS) is crucial for digital human generation, especially in applications like live streaming. While existing research primarily focuses on reducing estimation errors, it largely neglects robustness and security aspects, leaving these systems vulnerable to adversarial attacks. To address this significant challenge, we propose the Tangible Attack (TBA), a novel framework designed to generate adversarial examples capable of effectively compromising any digital human generation model. Our approach introduces a Dual Heterogeneous Noise Generator (DHNG), which leverages Variational Autoencoders (VAE) and ControlNet to produce diverse, targeted noise tailored to the original image features. Additionally, we design a custom adversarial loss function to optimize the noise, ensuring both high controllability and potent disruption. By iteratively refining the adversarial sample through multi-gradient signals from both the noise and the state-of-the-art EHPS model, TBA substantially improves the effectiveness of adversarial attacks. Extensive experiments demonstrate TBA’s superiority, achieving a remarkable 41.0% increase in estimation error, with an average improvement of approximately 17.0%. These findings expose significant security vulnerabilities in current EHPS models and highlight the need for stronger defenses in digital human generation systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Man machine systems

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Cascaded adaptive aberration-eliminating multimode fiber imaging

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advanced Photonics 2025年第2期 135-143页

作者： Zhong Wen Qilin Deng Quanzhi Li Yizhou Tan Jingshan Zhong Chiming Zhang Jiahe Zhang Clemens F.Kaminski Ying Gu Xu Liu Qing Yang Zhejiang University College of Optical Science and Engineering State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University International Research Center for Advanced Photonics Zhejiang University ZJU-Hangzhou Global Scientific and Technological Innovation Center Chinese PLA General Hospital The First Medical Center Department of Laser Medicine Chinese PLA General Hospital Hainan HospitalLaser Medicine Center Zhejiang Laboratory Research Center for Intelligent Manufacturing Computing University of Cambridge Department of Chemical Engineering and Biotechnology

In vivo microscopic imaging inside a biological lumen such as the gastrointestinal tract, respiratory airways, or within blood vessels has faced significant technological challenges for decades. A promising candidate technology is the multimode fiber(MMF) endoscope, which enables minimally invasive diagnostics at a resolution reaching the cellular level. However, for in vivo imaging applications deep inside a biological lumen, sample-induced aberrations and the dynamic dispersion in the MMF make the MMF endoscope a chaotic system with many unknowns, where multiple minor fluctuations can couple and compound into intractable problems. We introduce a dynamically encoding, cascaded, optical, and ultrathin polychromatic light-field endoscopy(DECOUPLE) to tackle this challenge. DECOUPLE includes an adaptive aberration correction that can accurately track and control MMF behavior in the spatial-frequency domain to compensate for chaos introduced during complex dynamic imaging processes. We demonstrate the flexibility and practicality of DECOUPLE for noninvasive volumetric imaging in two colors for light passing through various highly aberrating samples including 120-μm-thick onion epidermal slices and 80-μm-thick layers of fat emulsions. To summarize, we represent a significant step toward practical in vivo imaging deep within biological tissue.

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Applications of nanogenerators for biomedical engineering and healthcare systems

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InfoMat 2022年第2期4卷 53-109页

作者： Wanli Wang Jinbo Pang Jie Su Fujiang Li Qiang Li Xiaoxiong Wang Jingang Wang Bergoi Ibarlucea Xiaoyan Liu Yufen Li Weijia Zhou Kai Wang Qingfang Han Lei Liu Ruohan Zang Mark HRümmeli Yang Li Hong Liu Han Hu Gianaurelio Cuniberti College of Electrical Engineering Qingdao UniversityQingdaoChina Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong Institute for Advanced Interdisciplinary Research(iAIR)University of JinanJinanChina College of Electronic Information Qingdao UniversityQingdaoChina Department of Pediatric Surgery The Affiliated Hospital of Qingdao UniversityQingdaoChina College of Physics Qingdao UniversityQingdaoChina Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresdenGermany Center for Advancing Electronics Dresden Technische Universität DresdenDresdenGermany College of Biological Science and Technology University of JinanJinanChina School of Chemistry and Chemical Engineering University of JinanShandongJinanChina College of Energy Soochow Institute for Energy and Materials InnovationsSoochow UniversitySuzhouChina Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhouChina Centre of Polymer and Carbon Materials Polish Academy of SciencesZabrzePoland Institute for Complex Materials IFW DresdenDresdenGermany Institute of Environmental Technology VŠB-Technical University of OstravaOstravaCzech Republic School of Information Science and Engineering University of JinanJinanChina Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of JinanJinanChina State Key Laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong UniversityJinanChina College of Chemical Engineering China University of Petroleum(East China)QingdaoChina Dresden Center for Computational Materials Science Technische Universität DresdenDresdenGermany The Dresden Center for Intelligent Materials(DCIM) Technische Universität DresdenDresdenGermany

The dream of human beings for long living has stimulated the rapid development of biomedical and healthcare ***,conventional biomedical and healthcare devices have shortcomings such as short service life,large equipment size,and high potential safety ***,the power supply for conventional implantable device remains predominantly *** emerging nanogenerators,which harvest micro/nanomechanical energy and thermal energy from human beings and convert into electrical energy,provide an ideal solution for self-powering of biomedical *** combination of nanogenerators and biomedicine has been accelerating the development of self-powered biomedical *** article first introduces the operating principle of nanogenerators and then reviews the progress of nanogenerators in biomedical applications,including power supply,smart sensing,and effective ***,the microbial disinfection and biodegradation performances of nanogenerators have been ***,the protection devices have been discussed such as face mask with air filtering function together with real-time monitoring of human health from the respiration and heat ***,the nanogenerator devices have been categorized by the types of mechanical energy from human beings,such as the body movement,tissue and organ activities,energy from chemical reactions,and gravitational potential ***,the challenges and future opportunities in the applications of nanogenerators are delivered in the conclusive remarks.

关键词： biomedical engineering healthcare implantable devices nanogenerators self-powered devices sensors

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