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A learnable self-supervised task for unsupervised domain adaptation on point cloud classification and segmentation

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Frontiers of Computer Science 2023年第6期17卷 147-149页

作者： Shaolei LIU Xiaoyuan LUO kexue fu Manning WANG Zhijian SONG Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai 200032China Digital Medical Research Center School of Basic Medical ScienceFudan UniversityShanghai 200032China

1 Introduction Deep neural networks have exhibited excellent performance in supervised tasks on point clouds,such as classification,segmentation[1]and registration[2].In supervised learning schemes,manual labeling of massive point clouds is needed for model ***,point clouds captured from different scenarios exist inevitable distribution discrepancy,and model trained from one domain always generalize badly in another *** reduce the doamin distribution discrepancy,many studies[3–6]have emerged for point cloud unsupervised domain adaptation(UDA)by learning domain-invariant features,where[5]proposed using adaptive nodes to align the local features between the source and the target domains[3,4],and[6]proposed utilizing self-supervised tasks to help capture highly transferable feature representations.

关键词： point cloud utilizing

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Reducing the measurement errors in nonadiabatic holonomic quantum computers

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 64-70页

作者： Guo-fu Xu Department of Physics Shandong University

Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum *** quantum computation has entered the noisy intermediate-scale era, building accurate intermediate-scale nonadiabatic holonomic quantum computers is clearly necessary. Given that measurements are the sole means of extracting information, they play an indispensable role in nonadiabatic holonomic quantum computers. Accordingly, developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance. However, while much attention has been given to the research on nonadiabatic holonomic gates, the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking. In this study, we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers. The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates. Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.

关键词： quantum holonomy quantum computation measurement errors

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基于改进KNN算法的手写数字识别研究

武汉理工大学学报（信息与管理工程版） 2019年第1期41卷 22-26页

作者：胡君萍傅科学武汉理工大学信息工程学院湖北武汉430070

针对传统KNN算法手写数字识别速度和精度都不高的问题,提出了一种改进的KNN手写数字识别方案。改进的KNN算法利用PCA方法对手写数字进行降维,降低传统KNN算法在距离计算过程中的时间和空间复杂度;并采用距离权重统计改善手写数字识别错... 详细信息

针对传统KNN算法手写数字识别速度和精度都不高的问题,提出了一种改进的KNN手写数字识别方案。改进的KNN算法利用PCA方法对手写数字进行降维,降低传统KNN算法在距离计算过程中的时间和空间复杂度;并采用距离权重统计改善手写数字识别错误问题。在手写数据集MNIST上验证改进的KNN算法,结果显示识别速度有显著提升,识别准确度有一定提高。

关键词：手写数字识别 KNN算法 PCA 距离权重统计人工智能

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Loss Aware Feature Attention Mechanism for Class and Feature Imbalance Issue

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Computers, Materials & Continua 2025年第1期82卷 751-775页

作者： Yuewei Wu Ruiling fu Tongtong Xing fulian Yin College of Information and Communication Engineering Communication University of ChinaBeijing100024China State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing100024China

In the Internet era,recommendation systems play a crucial role in helping users find relevant information from large *** imbalance is known to severely affect data quality,and therefore reduce the performance of recommendation *** to the imbalance,machine learning algorithms tend to classify inputs into the positive(majority)class every time to achieve high prediction *** can be categorized such as by features and classes,but most studies consider only class *** this paper,we propose a recommendation system that can integrate multiple networks to adapt to a large number of imbalanced features and can deal with highly skewed and imbalanced datasets through a loss *** propose a loss aware feature attention mechanism(LAFAM)to solve the issue of feature *** network incorporates an attention mechanism and uses multiple sub-networks to classify and learn *** better results,the network can learn the weights of sub-networks and assign higher weights to important *** propose suppression loss to address class imbalance,which favors negative loss by penalizing positive loss,and pays more attention to sample points near the decision *** on two large-scale datasets verify that the performance of the proposed system is greatly improved compared to baseline methods.

关键词： Imbalanced data deep learning e-commerce recommendation loss function big data analysis

Enhancing weather predictions:Initial condition sensitivity and error dynamics in data assimilation

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Science China Earth Sciences 2025年

作者： Weiwei fu Department of Atmospheric and Oceanic Sciences Fudan University Key Laboratory of Polar Atmosphere-ocean-ice System for Weather and Climate Ministry of Education Fudan University IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather Fudan University

Data Assimilation (DA) plays a crucial role in modern numerical forecasting (Kalnay, 2002). It has been demonstrated that incorporating real-time observational data into forecast models significantly enhances the accuracy of both shortterm weather forecasts (Bauer et al., 2015; Bannister, 2017)and long-term climate predictions (Karspeck et al., 2013;Mochizuki et al., 2016).

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Energy injection,transport,and dissipation in Earth's magnetosphere

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Science China Earth Sciences 2025年

作者： Huishan fu Jinbin CAO School of Space and Earth Sciences Beihang University Key Laboratory of Space Environment Monitoring and Information Processing Ministry of Industry and Information Technology

The Earth's magnetosphere is a region occupied by many artificial satellites, and also is a region that spacecraft must cruise during the deep-space exploration. In this sense, the Earth's magnetosphere is closely related to human activity and is a candidate for us to expand our living space. Generally, the Earth's magnetosphere can preclude most energetic particles from the Sun and the interstellar space, effectively protecting human beings on the Earth from being attacked and thus making the Earth to be a habitable planet. However, in some conditions, the Earth's magnetosphere becomes dynamic and energetic, and consequently may damage the artificial satellites, threaten the astronauts' health, and disrupt the ground infrastructure, which leads to a decline in the national economy. Therefore, investigating how energy is injected into the magnetosphere, how it is transported in the magnetosphere, and how it is ultimately dissipated in the magnetosphere are the key issues in space physics. Targeting these key issues, in this paper, we review the recent progress on them. Particularly, we introduce the relevant scientific questions,models, methods, and spacecraft missions, for better building a physical link among the energy injection, transport, and dissipation in the magnetosphere, present an energy chain of the magnetosphere, reveal the relationship between such energy chain and the space weather events, and discuss the forecasting and warning methods for energetic-particle events in the magnetosphere. The magnetospheric energy chain discussed in this paper will help us reveal the mechanisms of space weather events, establish the models of space environment, and forecast the disastrous space weather events.

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PS-CoT-Adapter: adapting plan-and-solve chain-of-thought for ScienceQA

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Science China(Information Sciences) 2025年第1期68卷 392-393页

作者： Qun LI Haixin SUN fu XIAO Yiming WANG Xinping GAO Bir BHANU School of Computer Science Nanjing University of Posts and Telecommunications Purple Mountain Laboratories Department of Electrical and Computer Engineering University of California at Riverside

Large language models (LLMs) have recently shown remarkable performance in a variety of natural language processing (NLP) *** further explore LLMs'reasoning abilities in solving complex problems,recent research [1-3]has investigated chain-of-thought (CoT) reasoning in complex multimodal scenarios,such as science question answering (ScienceQA) tasks [4],by fine-tuning multimodal models through human-annotated CoT ***,collected CoT rationales often miss the necessary rea-soning steps and specific expertise.

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Advancements and Challenges in Organic–Inorganic Composite Solid Electrolytes for All‑Solid‑State Lithium Batteries

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Nano-Micro Letters 2025年第1期17卷 46-97页

作者： Xueyan Zhang Shichao Cheng Chuankai fu Geping Yin Liguang Wang Yongmin Wu Hua Huo State Key Laboratory of Space Power‑Sources School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin 150001People’s Republic of China College of Chemical and Biological Engineering Zhejiang UniversityHangzhou 310058People’s Republic of China State Key Laboratory of Space Power-Sources 2965 Dongchuan RoadMinhang DistrictShanghai 200240People’s Republic of China

To address the limitations of contemporary lithium-ion batteries,particularly their low energy density and safety concerns,all-solid-state lithium batteries equipped with solid-state electrolytes have been identified as an up-and-coming *** the various SEs,organic–inorganic composite solid electrolytes(OICSEs)that combine the advantages of both polymer and inorganic materials demonstrate promising potential for large-scale ***,OICSEs still face many challenges in practical applications,such as low ionic conductivity and poor interfacial stability,which severely limit their *** review provides a comprehensive overview of recent research advancements in ***,the influence of inorganic fillers on the main functional parameters of OICSEs,including ionic conductivity,Li+transfer number,mechanical strength,electrochemical stability,electronic conductivity,and thermal stability are systematically *** lithium-ion conduction mechanism of OICSE is thoroughly analyzed and concluded from the microscopic ***,the classic inorganic filler types,including both inert and active fillers,are categorized with special emphasis on the relationship between inorganic filler structure design and the electrochemical performance of ***,the advanced characterization techniques relevant to OICSEs are summarized,and the challenges and perspectives on the future development of OICSEs are also highlighted for constructing superior ASSLBs.

关键词： Composite solid electrolytes Inorganic filler Interfacial stability Li-ion conduction mechanism Characterization techniques

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Quantum public-key crypto via EPR pairs

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 58-63页

作者： Xiang-Qun fu Hong-Wei Li Jian-Hong Shi Tan Li Wan-Su Bao Henan Key Laboratory of Quantum Information and Cryptography Information Engineering University Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China

With the development of quantum computing technology, quantum public-key cryptography is gradually becoming an alternative to the existing classical public-key cryptography. This paper designs a quantum trapdoor one-way function via EPR pairs and quantum measurements. Based on this, a new quantum public-key cryptosystem is presented, which offers forward security,and can resist the chosen-plaintext attack and chosen-ciphertext attack. Compared with the existing quantum public-key cryptos,eavesdropping can be automatically detected in this new quantum public-key cryptosystem under a necessary condition, which is also detailed in the paper.

关键词： quantum public-key crypto trapdoor one-way function EPR pairs