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arXiv 2024年

作者： Lin, Jiuheng Lai, Yuxuan Feng, Yansong Wangxuan Institute of Computer Technology Peking University China State Key Laboratory of General Artificial Intelligence Peking University China Department of Computer Science The Open University of China China Engineering Research Center of Integration and Application of Digital Learning Technology Ministry of Education China

Conditional question answering (CQA) is an important task that aims to find probable answers and identify missing conditions. Existing approaches struggle with CQA due to two challenges: (1) precisely identifying necessary conditions and the logical relationship, and (2) verifying conditions to detect any that are missing. In this paper, we propose a novel prompting approach, Chain of condition, by first identifying all conditions and constructing their logical relationships explicitly according to the document, then verifying whether these conditions are satisfied, finally solving the logical expression to indicate any missing conditions and generating the answer accordingly. Experiments on two CQA benchmark datasets show our chain of condition outperforms existing prompting baselines, establishing a new state of the art. Furthermore, with only a few examples, our method can facilitate GPT-3.5-Turbo or GPT-4 to outperform all existing supervised models. © 2024, CC BY.

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Orthogonal matrix of polarization combinations:concept and application to multichannel holographic recording

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Opto-Electronic Advances 2024年第10期7卷 4-13页

作者： Shujun Zheng Jiaren Tan Hongjie Liu Xiao Lin Yusuke Saita Takanori Nomura Xiaodi Tan Information Photonics Research Center College of Photonic and Electronic EngineeringFujian Normal UniversityFuzhou 350117China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA College of Photonic and Electronic Engineering Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of EducationFujian Provincial Key Laboratory of Photonics TechnologyFujian Provincial Engineering Technology Research Center of Photoelectric Sensing ApplicationFujian Normal UniversityFuzhou 350117China Faculty of Systems Engineering Wakayama University930 SakaedaniWakayama640-8510Japan.

Orthogonal matrices have become a vital means for coding and signal processing owing to their unique distributional *** orthogonal matrices based on amplitude or phase combinations have been extensively explored,the orthogonal matrix of polarization combinations(OMPC)is a novel,relatively unexplored ***,we propose a method for constructing OMPCs of any dimension encompassing 4n(where n is 1,2,4,8,…)mutually orthogonal 2ncomponent polarization *** the field of holography,the integration of polarization multiplexing techniques with polarization-sensitive materials is expected to emerge as a groundbreaking approach for multichannel hologram multiplexing,offering considerable enhancements in data storage capacity and security.A multidimensional OMPC enables the realization of multichannel multiplexing and dynamical modulation of information in polarization holographic *** consolidating all information into a single position within the material,we effectively avoided extraneous crosstalk during the reconstruction *** results show that achieving four distinct holographic images individually and simultaneously depends on the polarization combination represented by the incident *** discovery opens up a new avenue for achieving highly holographic information storage and dynamically displayed information,harnessing the potential of OMPC to expand the heretofore limited dimensionality of orthogonal polarization.

关键词： orthogonal matrix of polarization combinations polarization-modulated multiplexing multichannel recording polarization holography dynamical information modulation

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Continuous-variable measurement-device-independent quantum key distribution with passive state in oceanic turbulence 21

Continuous-variable measurement-device-independent quantum k...

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21st International Symposium on Distributed Computing and applications for Business Engineering and Science, DCABES 2022

作者： Chen, Guojun Yi, Jianmin Guo, Ying Wuxi Taihu University Jiangsu Key Laboratory of IoT Application Technology Wuxi214064 China College of Computer Internet of Tings Engineering Wuxi Taihu University Wuxi214064 China School of Automation Central South University Changsha410083 China

ISBN: (纸本)9781665454629

Quantum communication, as an absolutely secure communication method, has been widely studied in recent years. While CVQKD is easier to realize and has efficient information transmission, has attracted more attention than DVQKD. And there is another kind of detection strategy which places the detector on a third party called continuous-variable measurement device independent quantum key distribution(CV -MDI), can lower the cost of implementation because it don't need such a high precision Gaussian modulator and thus can be commercialized easily. We apply a CV -MDI with passive-state preparation protocol to a oceanic turbulence model, and then we analyze the secret key rate and other performance of the protocol in the particular scenario. © 2022 IEEE.

关键词： Turbulence models

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Passive Detection for Multiple Underwater Targets with Linear Frequency Modulation Signals 17

Passive Detection for Multiple Underwater Targets with Linea...

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17th IEEE International Conference on Signal Processing, ICSP 2024

作者： Wang, Junfeng Cui, Yue Zhou, Mingzhang Sun, Haixin Liu, Lanjun Zhang, Ailing Tianjin University of Technology School of Integrated Circuit Science and Engineering Tianjin300384 China Mnr Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application China Tianjin Normal University College of Computer and Information Engineering Tianjin300387 China Xiamen University School of Information Science and Engineering Xiamen361005 China Ocean University of China College of Engineering Qingdao266100 China

ISBN: (纸本)9798350387384

Detecting the status of autonomous underwater vehicle, referred to hereinafter as an underwater target, is fundamental for successfully fulfilling cognition tasks or improving communication quality. In this article, we present a thorough study over the passive detection issue for multiple underwater targets emitting the linear frequency modulation signals. Specifically, hypothesis testing model, which comprises the signals received at the underwater detection node including periodic emission signals from the targets and additive noise, is firstly proposed for the practical scenarios. Then, the detection scheme has been investigated. Among this scheme, the behavior of the signals emitted by the underwater targets has been analyzed;and the primary aiming of the detection procedure, i.e., decision rule and its performance, has also been discussed and derived for the aforementioned scenarios. Towards the end, to confirm the advantages of our proposed studies, numerical simulation examples are carried out to examine the performance under different conditions. © 2024 IEEE.

关键词： Signal modulation

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A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-Resolution

arXiv

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arXiv 2023年

作者： Mei, Xiaoyong Yang, Yi Li, Ming Huang, Changqin Zhang, Kai Lió, Pietro The Key Laboratory of Intelligent Education Technology Application of Zhejiang Province Zhejiang Normal University Jinhua China The Computer Vision Lab. ETH Zurich Switzerland The Department of Computer Science and Technology University of Cambridge United Kingdom

Reference-based super-resolution (RefSR) has gained considerable success in the field of super-resolution with the addition of high-resolution reference images to reconstruct low-resolution (LR) inputs with more high-frequency details, thereby overcoming some limitations of single image super-resolution (SISR). Previous research in the field of RefSR has mostly focused on two crucial aspects. The first is accurate correspondence matching between the LR and the reference (Ref) image. The second is the effective transfer and aggregation of similar texture information from the Ref images. Nonetheless, an important detail of perceptual loss and adversarial loss has been underestimated, which has a certain adverse effect on texture transfer and reconstruction. In this study, we propose a feature reuse framework that guides the step-by-step texture reconstruction process through different stages, reducing the negative impacts of perceptual and adversarial loss. The feature reuse framework can be used for any RefSR model, and several RefSR approaches have improved their performance after being retrained using our framework. Additionally, we introduce a single image feature embedding module and a texture-adaptive aggregation module. The single image feature embedding module assists in reconstructing the features of the LR inputs itself and effectively lowers the possibility of including irrelevant textures. The texture-adaptive aggregation module dynamically perceives and aggregates texture information between the LR inputs and the Ref images using dynamic filters. This enhances the utilization of the reference texture while reducing reference misuse. The source code is available at https://***/Yi-Yang355/FRFSR. © 2023, CC BY.

关键词： Textures

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Fake the Real: Backdoor Attack on Deep Speech Classification via Voice Conversion

arXiv

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arXiv 2023年

作者： Ye, Zhe Mao, Terui Dong, Li Yan, Diqun Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology China Ningbo City College of Vocational Technology Ningbo China

Deep speech classification has achieved tremendous success and greatly promoted the emergence of many real-world applications. However, backdoor attacks present a new security threat to it, particularly with untrustworthy third-party platforms, as pre-defined triggers set by the attacker can activate the backdoor. Most of the triggers in existing speech backdoor attacks are sample-agnostic, and even if the triggers are designed to be unnoticeable, they can still be audible. This work explores a backdoor attack that utilizes sample-specific triggers based on voice conversion. Specifically, we adopt a pre-trained voice conversion model to generate the trigger, ensuring that the poisoned samples does not introduce any additional audible noise. Extensive experiments on two speech classification tasks demonstrate the effectiveness of our attack. Furthermore, we analyzed the specific scenarios that activated the proposed backdoor and verified its resistance against fine-tuning. Copyright © 2023, The Authors. All rights reserved.

关键词： Speech recognition

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Space-Air-Ground Integrated Network (SAGIN) for 6G: Requirements, Architecture and Challenges

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China Communications 2022年第2期19卷 90-108页

作者： Huanxi Cui Jun Zhang Yuhui Geng Zhenyu Xiao Tao Sun Ning Zhang Jiajia Liu Qihui Wu Xianbin Cao School of Electronic and Information Engineering Beijing Key Laboratory for Network-Based Cooperative Air application ManagementBeihang UniversityBeijing 100191China Advanced Research Institute of Multidisciplinary Science Beijing Institute of TechnologyBeijing 100081China China Mobile Research Institute Beijing 100053China Department of Electrical and Computer Engineering University of WindsorONCanadaN9B 3P4 National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology the School of CybersecurityNorthwestern Polytechnical UniversityXi’anShaanxi710072China College of Electronics and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210007China

As the fifth-generation(5G)mobile communication network may not meet the requirements of emerging technologies and applications,including ubiquitous coverage,industrial internet of things(IIoT),ubiquitous artificial intelligence(AI),digital twins(DT),etc.,this paper aims to explore a novel space-air-ground integrated network(SAGIN)architecture to support these new requirements for the sixth-generation(6G)mobile communication network in a flexible,low-latency and efficient ***,we first review the evolution of the mobile communication network,followed by the application and technology requirements of *** the current 5G non-terrestrial network(NTN)architecture in supporting the new requirements is deeply *** that,we proposes a new flexible,low-latency and flat SAGIN architecture,and presents corresponding use ***,the future research directions are discussed.

关键词： 6G AI DT SAGIN NTN Network architecture

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Unsharp Mask Sharpening Detection via Global Analysis

Unsharp Mask Sharpening Detection via Global Analysis

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Irish Signals and Systems Conference (ISSC)

作者： Rong-Hui Lu Tzong-Jer Chen Junhong Pan Information Technology and Laboratory Management Center Wuyi University Wuyishan Fujian China School of Mathematics & Computer Science Wuyi University Wuyishan Fujian China Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry Wuyi University

ISBN: (数字)9798350352986

ISBN: (纸本)9798350352993

Image sharpening prediction plays a significant role in image restoration, forensics, and computer vision. This work proposes a new method for detecting sharpening and indexing in digital images. Images initially undergo manipulation using Gaussian filters and Unsharp Masking (UM) with various degrees of intensity. This is followed by transformation into the frequency domain using Fourier transform. The resulting amplitude values are calculated, and their absolute values are summed along the frequency axis to produce a profile curve. These data curves are subsequently smoothed. The UM curves exhibit concavity and symmetry relative to the curve of the original image. The values of these curves at the concave positions, corresponding to various UM intensities, can be utilized as a sharpness index by comparing them to the curve values of the original image at the same positions. These sharpness indices are dependent on the UM amplification factors. This methodology finds utility in medical image processing and computer vision systems for sharpness detection and indexing. The features identified in this study, based on Fourier power spectrum analysis, can be input into a machine learning classifier for classification.

关键词： computer vision Filters Fourier transforms Frequency-domain analysis Forensics Machine learning Image restoration

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Design of Three Components for the Mobile application Supporting Software

Design of Three Components for the Mobile Application Suppor...

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International Conference on Network and Information Systems for computers (ICNISC)

作者： Tingting Shi Wenjie Du Xiyu Xu Beijing Institute of Computer Technology and Application Beijing China The Key Laboratory of Microwave Remote Sensing National Space Science Center Chinese Academy of Sciences Beijing China

The technology of mobile application supporting software design has been an increasingly field in the past decade. It is benefic to establish a generalized methodology to better direct the software engineering practice. After a brief description of architecture of the mobile application supporting software, this paper focuses on the design of three core components: integration network, development support environment, geographic information support. In each of the components several innovative techniques are introduced to commit the requirement specifications. The methodology of this paper can make solid contribute to the community.

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Deep Hypergraph Neural Networks with Tight Framelets 39

Deep Hypergraph Neural Networks with Tight Framelets

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Li, Ming Fang, Yujie Wang, Yi Feng, Han Gu, Yongchun Bai, Lu Lio, Pietro Zhejiang Key Laboratory of Intelligent Education Technology and Application Zhejiang Normal University China Zhejiang Institute of Optoelectronics China School of Computer Science and Technology Zhejiang Normal University China Department of Mathematics City University of Hong Kong Hong Kong School of Artificial Intelligence Engineering Research Center of Intelligent Technology and Educational Application Ministry of Education Beijing Normal University China Department of Computer Science and Technology Cambridge University United Kingdom

ISBN: (纸本)157735897X

Hypergraphs provide a flexible framework for modeling high-order (complex) interactions among multiple entities, extending beyond traditional pairwise correlations in graph structures. However, deep hypergraph neural networks (HGNNs) often face the challenge of oversmoothing with increasing depth, similar to issues in graph neural networks (GNNs). While oversmoothing in GNNs has been extensively studied, its implications in relation to hypergraphs are less explored. This paper addresses this gap by first theoretically exploring the reasons behind oversmoothing in deep HGNNs. Our novel insights suggest that a spectral-based hypergraph convolution, equipped with both low-pass and high-pass filters, can potentially mitigate these effects. Motivated by these findings, we introduce FrameHGNN, a framework that utilizes framelet-based hypergraph convolutions integrating tight framelet transforms with both low-pass and high-pass components, as well as the commonly used strategies in designing deep GNN architecture: initial residual and identity mappings. The experiment results on diverse benchmark datasets demonstrate that FrameHGNN outperforms several state-of-the-art models, effectively reducing oversmoothing while improving predictive accuracy. Our contributions not only advance the theoretical understanding of deep hypergraph learning but also provide a practical spectral-based approach for HGNNs, emphasizing the design of multifrequency channels. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Graph neural networks

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