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TechRxiv 2023年

作者： Zheng, Zhiyong Liu, Fengxia Tian, Kun Beihang University China Engineering Research Center of Ministry of Education for Financial Computing and Digital Engineering Renmin University of China Henan Academy of Sciences China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Institute of Artificial Intelligence China Engineering Research Center of Ministry of Education for Financial Computing and Digital Engineering Renmin University of China China

We propose an unbounded fully homomorphic encryption scheme, i.e. a scheme that allows one to compute on encrypted data for any desired functions without needing to decrypt the data or knowing the decryption keys. This is a rational solution to an old problem proposed by Rivest, Adleman, and Dertouzos [42] in 1978, and to some new problems appeared in Peikert [38] as open questions 10 and open questions 11 a few years ago. Our scheme is completely different from the breakthrough work [21, 22] of Gentry in 2009. Gentry’s bootstrapping technique constructs a fully homomorphic encryption (FHE) scheme from a somewhat homomorphic one that is powerful enough to evaluate its own decryption function. To date, it remains the only known way of obtaining unbounded FHE. Our construction of unbounded FHE scheme is straightforward and noise-free that can handle unbounded homomorphic computation on any refreshed ciphertexts without bootstrapping transformation technique. © 2023, CC BY.

关键词： Cryptography

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Data-driven sleep structure deciphering based on cardiorespiratory signals

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Computer Methods and Programs in Biomedicine 2025年 267卷 108769-108769页

作者： Huang, Ming Iwata, Osuke Yokoyama, Kiyoko Tamura, Toshiyo Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Shenzhen China of Science and Technology Nara Institute of Science and Technology Ikoma Japan of Medical Sciences Nagoya City University Japan School of Data Science Nagoya City University Japan Institute for Healthcare Robotics Waseda University Japan

Background and Objective: : Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) and low-frequency (LF) bands, indicating that signal segments of 4–8 min are optimal for analysis. However, the lack of labels tailored to these signals has led to reliance on the American Academy of Sleep Medicine (AASM) definitions, which are primarily designed for electroencephalogram (EEG) and electrooculogram (EOG) data. This study aims to address the challenge of transitioning from AASM-defined labels to cardiorespiratory-oriented ones and to evaluate the feasibility of using these signals for accurate sleep structure recognition. Methods: To align with the physiological characteristics of cardiorespiratory signals, AASM labels were modified by excluding the N2 stage due to its overlap of stable and unstable non-rapid eye movement (NREM) phases, which introduces ambiguity. The modified dataset focused on the wake, N1, deep sleep (N3), and rapid eye movement (REM) stages. A physiologically-inspired deep-learning model (PIDM) was developed to extract features from cardiorespiratory time series and classify sleep stages. Post-analysis assessed the physiological validity of the model's N2 predictions by evaluating the HF-to-LF ratio and respiratory variability. Results: The pipeline, combining the modified labeling scheme with the PIDM model, achieved balanced accuracy scores of 0.83, 0.86, and 0.78 for wake, deep sleep, and REM stages, respectively in the normal group;and 0.92, 0.95, and 0.90 in the mild and moderate sleep apnea groups. Post-analysis revealed that most N2 samples were attributed to stable NREM sleep, characterized by higher HF-to-LF ratios and lower respiratory variability, aligning with physiological understanding. Conclusions: This study highlights the physiological relevance of cardiorespiratory s

关键词： Electroencephalography

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CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understanding

CroPrompt: Cross-task Interactive Prompting for Zero-shot Sp...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Qin, Libo Wei, Fuxuan Chen, Qiguang Zhou, Jingxuan Huang, Shijue Si, Jiasheng Lu, Wenpeng Che, Wanxiang School of Computer Science and Engineering Central South University China Key Laboratory of Data Intelligence and Advanced Computing in Provincial Universities Soochow University China Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China Harbin Institute of Technology Shenzhen China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences China

ISBN: (纸本)9798350368741

Slot filling and intent detection are two highly correlated tasks in spoken language understanding (SLU). Recent SLU research attempts to explore zero-shot prompting techniques in large language models to alleviate the data scarcity problem. Nevertheless, the existing prompting work ignores the cross-task interaction information for SLU, which leads to sub-optimal performance. To solve this problem, we present the pioneering work of Cross-task Interactive Prompting (CroPrompt) for SLU, which enables the model to interactively leverage the information exchange across the correlated tasks in SLU. Additionally, we further introduce a multi-task self-consistency mechanism to mitigate the error propagation caused by the intent information injection. We conduct extensive experiments on the standard SLU benchmark and the results reveal that CroPrompt consistently outperforms the existing prompting approaches. In addition, the multi-task self-consistency mechanism can effectively ease the error propagation issue, thereby enhancing the performance. We hope this work can inspire more research on cross-task prompting for SLU. © 2025 IEEE.

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Multi-photon Fock state generation using a single-pixel ultrafast photon-number-resolving detector

Multi-photon Fock state generation using a single-pixel ultr...

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Quantum 2.0, QUANTUM 2024 in Quantum 2.0 Conference and Exhibition

作者： Sonoyama, Tatsuki Takahashi, Kazuma Nomura, Takefumi Sano, Tomoki China, Fumihiro Yabuno, Masahiro Miki, Shigehito Terai, Hirotaka Takase, Kan Asavanant, Warit Endo, Mamoru Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Hyogo Kobe651-2492 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan

Single-pixel superconducting nanostrip photon detectors (SNSPDs) have both low timing jitter of 50 ps and photon-number-resolving capability. We generate multi-photon Fock states with Wigner negativities using SNSPDs,... 详细信息

ISBN: (纸本)9781557525185

关键词： Timing jitter

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An Automated Penetration Semantic Knowledge Mining Algorithm Based on Bayesian Inference

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Computers, Materials & Continua 2021年第3期66卷 2573-2585页

作者： Yichao Zang Tairan Hu Tianyang Zhou Wanjiang Deng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000China National Engineering Technology Research Center of the Digital Switching System Zhengzhou450000China NUS Business School National University of SingaporeSingapore119077Singapore

Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration *** rule mining,a data mining technique,has been studied and explored for a long ***,few studies have focused on knowledge discovery in the penetration testing *** experimental result reveals that the long-tail distribution of penetration testing data nullifies the effectiveness of associative rule mining algorithms that are based on frequent *** address this problem,a Bayesian inference based penetration semantic knowledge mining algorithm is ***,a directed bipartite graph model,a kind of Bayesian network,is constructed to formalize penetration testing ***,we adopt the maximum likelihood estimate method to optimize the model parameters and decompose a large Bayesian network into smaller networks based on conditional independence of variables for improved solution ***,irrelevant variable elimination is adopted to extract penetration semantic knowledge from the conditional probability distribution of the *** experimental results show that the proposed method can discover penetration semantic knowledge from raw penetration testing data effectively and efficiently.

关键词： Penetration semantic knowledge automated penetration testing Bayesian inference cyber security

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Robustness optimization for rapid prototyping of functional artifacts based on visualized computing digital twins

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Visual computing for Industry,Biomedicine,and Art 2023年第1期6卷 33-50页

作者： Jinghua Xu Kunqian Liu Linxuan Wang Hongshuai Guo Jiangtao Zhan Xiaojian Liu Shuyou Zhang Jianrong Tan State Key Lab of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310058China Key Lab of Advanced Manufacturing Technology of Zhejiang Province Zhejiang UniversityHangzhou 310058China Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province Zhejiang UniversityHangzhou 310058China Zhejiang-Singapore Innovation and AI Joint Research Lab Zhejiang UniversityHangzhou 310058China School of Creative Arts and design Zhejiang Institute of Mechanical and Electrical EngineeringHangzhou 310053China Ningbo Research Institute Zhejiang UniversityNingbo 315100China

This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built,where thermal,structural,and multidisciplinary knowledge could be integrated for *** implement visualized computing,the membership function of fuzzy decision-making was optimized using a genetic *** thermodynamic,structural statics,and flow field analyses were conducted,especially for glass fiber composite materials,which have the characteristics of high strength,corrosion resistance,temperature resistance,dimensional stability,and electrical *** electrothermal experiment was performed by measuring the temperature and changes in temperature during *** thermographs were obtained using thermal field measurements to determine the temperature distribution.A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the ***,manufacturability was verified based on a thermal-solid coupled finite element *** physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.

关键词： Robustness optimization design Rapid prototyping Functional artifacts Fuzzy decision-making Infrared thermographs Visualized computing digital twins

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ROCFL: A Robust Clustered Federated Learning Framework towards Heterogeneous Data

ROCFL: A Robust Clustered Federated Learning Framework towar...

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2023 International Conference on Intelligent Communication and Networking, ICN 2023

作者： Li, Zihan Guan, Zhitao Yuan, Shuai An, Ningyu Liang, Xiao North China Electric Power University School of Control and Computer Engineering Beijing China Canada State Grid Smart Grid Research Institute State Grid Laboratory of Grid Advanced Computing and Applications Beijing China

ISBN: (纸本)9798350357677

As a decentralized machine learning approach, federated learning has become a key solution for numerous applications. However, one primary challenge lies in the data heterogeneity issue when developing effective federated learning algorithms. While many existing frameworks address the concern of non-independent and identically distributed data(non-IID), they have not considered heterogeneity of data quality. Therefore, we propose ROCFL, a robust clustered federated learning method in this study, which can amplify the disparity in weight allocation between models trained on different quality data. We first develop an optimal clustering matching mechanism that groups clients with similar data distributions. This allows the optimal clustering model to be derived without specifying a predetermined number of clusters. Next, we introduce a personalized weight allocation strategy, which assigns a weight benchmark to each cluster based on its cluster importance index. This strategy mitigates the negative impacts of low-quality data during model aggregation. Finally, we design a federated aggregation strategy grounded in a sampling approach. It not only ensures unbiased sampling but also significantly reduces both computational and communication overheads. Experiments have been carried out and the results demonstrate that higher accuracy and robustness can be achieved by ROCFL in scenarios wherein data distribution and quality heterogeneity coexist, in comparison with the benchmarks. © 2023 IEEE.

关键词： Learning algorithms

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Learning from Noisy Crowd Labels with Logics 39

Learning from Noisy Crowd Labels with Logics

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Chen, Zhijun Sun, Hailong He, Haoqian Chen, Pengpeng Beihang University Sklsde Lab Beijing China Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China China's Aviation System Engineering Research Institute Beijing China

ISBN: (纸本)9798350322279

This paper explores the integration of symbolic logic knowledge into deep neural networks for learning from noisy crowd labels. We introduce Logic-guided Learning from Noisy Crowd Labels (Logic-LNCL), an EM-alike iterative logic knowledge distillation framework that learns from both noisy labeled data and logic rules of interest. Unlike traditional EM methods, our framework contains a "pseudo-E-step"that distills from the logic rules a new type of learning target, which is then used in the "pseudo-M-step"for training the classifier. Extensive evaluations on two real-world datasets for text sentiment classification and named entity recognition demonstrate that the proposed framework improves the state-of-the-art and provides a new solution to learning from noisy crowd labels. © 2023 IEEE.

关键词： Crowdsourcing

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Controllable synthesis of argentum decorated CuO_(x)@CeO_(2) catalyst and its highly efficient performance for soot oxidation

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Journal of Rare Earths 2022年第10期40卷 1546-1553页

作者： Jie Wan Yanjun Liu Yuanyuan Zhou Han Liu Gongde Wu Jianfei Kan Min Li Duan Weng Xiaodong Wu Energy Research Institute Nanjing Institute of TechnologyNanjing 211167China Key Laboratory of Advanced Materials of Ministry of Education School of Materials Science and EngineeringTsinghua UniversityBejing 100084China School of Civil Engineering Southeast UniversityNanjing 211189China State Key Laboratory of Digital Household Appliances Haier Group Technique R&D CenterQingdao 266100China

In this paper,CuO_(x)@Ag/CeO_(2) catalysts were synthesized by simple wet-chemical method and equal volume impregnation *** obtained catalysts were subjected to soot temperature programmed oxidation(soot-TPO)activity tests and were further characterized by various techniques such as X-ray diffraction(XRD),transmission electron microscopy/high-resolution transmission electron microscopy(TEM/HR-TEM),N_(2) physisorption,X-ray photoelectron spectroscopy(XPS)and H_(2)-temperature programmed reduction(H_(2)-TPR).The results show that CuO_(x)@Ag/CeO_(2) synthesized presents well controlled core-shell structures,with nano-cube like Cu_(2)O as the core and Ag decorated polycrystalline CeO_(2) grafting layers as the *** core-shell structured CuO_(x)@Ag/CeO_(2) can successfully construct a secondary oxygen delivery channel(CuO_(x)→CeO_(2)→Ag)to effectively transfer bulk oxygen of the catalyst to the soot,resulting in its excellent soot oxidation activity compared to CuO_(x)@CeO_(2).The potential benefiting effect by Ag introduction over Cu@Ag/Ce can be concluded as:(ⅰ)pumping lattice oxygen and accelerating gaseous O_(2) dissociation to generate significantly increased active surface oxygen content;(ⅱ)modulating a moderate surface oxygen vacancies concentration to maintain more highly active O_(2) species.

关键词： Soot oxidation CuO_(x) Ag/CeO_(2) Controllable synthesis Active oxygen species Rare earths

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Memristive structure of Nb/HfOx/Pd with controllable switching mechanisms to perform featured actions in neuromorphic networks

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Nano research 2022年第9期15卷 8410-8418页

作者： Junwei Yu Fei Zeng Qin Wan Yiming Sun Leilei Qiao Tongjin Chen Huaqiang Wu Zhen Zhao Jiangli Cao Feng Pan Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Center for Brain Inspired Computing Research(CBICR) Tsinghua UniversityBeijing 100084China Microelectronics Institute Tsinghua UniversityBeijing 100084China School of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083China

All memristor neuromorphic networks have great potential and advantage in both technology and computational protocols for artificial *** is crucial to find suitable elementary units for both performing featured neuromorphic functions and fabrication in large *** a simple memristive structure,Nb/HfOx/Pd,is proposed for this *** two resistive switching mechanisms,Mott transition of NbO2 and oxygen vacancy(Vo)migration,can be controlled by modulating external bias *** bias activates reversible phase transition and restrains Vo filament formation to allow the memristor to mimic the firing action *** bias activates Vo filament formation and restrains the other to allow the memristor to mimic synaptic plasticity and learning *** system can respond adaptively to naturally generated action potentials and modified synaptic signals from the same memristive *** addition,some special features related to signal encoding and recognition are discovered when the system is settled according to chaos circuit *** study provides a novel approach for designing elementary units for neuromorphic computations.

关键词： memristive system phase transition oxygen vacancy action potential synaptic plasticity

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