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Recent progress of in‑fber WGM microsphere resonator

Frontiers of Optoelectronics 2023年第2期16卷 25-62页

作者： Yong Yang Zijie Wang Xiaobei Zhang Qi Zhang Tingyun Wang Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai Institute for Advanced Communication and Data ScienceShanghai UniversityShanghai 200444China

In-fber whispering gallery mode(WGM)microsphere resonators have received remarkable attention due to the superiorities of compact structure,high stability and *** an in-fber structure,WGM microsphere resonators have been demonstrated in various applications,such as sensors,flters and lasers,which have signifcant impacts on modern ***,we review recent progress of in-fber WGM microsphere resonators,which involve fbers of diverse structures and microspheres of diferent ***,a brief introduction is given to in-fber WGM microsphere resonators,from structures to ***,we focus on recent progresses in this feld,including in-fber couplers based on conventional fbers,capillaries and micro-structure hollow fbers,and passive/active ***,future developments of the in-fber WGM microsphere resonators are envisioned.

关键词： Whispering gallery mode Microsphere resonator In-fber device Sensor

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Using analytic hierarchy process to evaluate deep learning for infrared target recognition

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Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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Improving physical properties of poly(vinyl alcohol)/montmorillonite nanocomposite hydrogels via the Hofmeister effect

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Chinese Physics B 2023年第8期32卷 6-14页

作者：郭蓉蓉余德帅黄一帆王森付聪朱水洪易佳王涵淇林友辉 Department of Physics Research Institute for Biomimetics and Soft MatterFujian Provincial Key Laboratory for Soft Functional Materials ResearchXiamen UniversityXiamen 361005China National Institute for Data Science in Health and Medicine Xiamen UniversityXiamen 361102China

Hydrogel is a kind of three-dimensional crosslinked polymer material with high moisture ***,due to the network defects of polymer gels,traditional hydrogels are usually brittle and fragile,which limits their practical ***,we present a Hofmeister effect-aided facile strategy to prepare high-performance poly(vinyl alcohol)/montmorillonite nanocomposite *** montmorillonite nanosheets can not only serve as crosslinking agents to enhance the mechanical properties of the hydrogel but also promote the ion *** importantly,based on the Hofmeister effect,the presence of(NH_(4))_(2)SO_(4)can endow nanocomposite hydrogels with excellent mechanical properties by affecting PVA chains'aggregation state and *** a result,the as-prepared nanocomposite hydrogels possess unique physical properties,including robust mechanical and electrical *** as-prepared hydrogels can be further assembled into a high-performance flexible sensor,which can sensitively detect large-scale and small-scale human *** simple design concept of this work is believed to provide a new prospect for developing robust nanocomposite hydrogels and flexible devices in the future.

关键词： nanocomposite hydrogels Hofmeister effect network structure poly(vinyl alcohol) montmorillonite

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Quantification and Validation for Degree of Understanding in M2M Semantic Communications 24

Quantification and Validation for Degree of Understanding in...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Xia, Linhan Cai, Jiaxin Hou, Ricky Yuen-Tan Jeong, Seon-Phil BNU-HKBU United International College Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science Zhuhai China

ISBN: (纸本)9798350363760

With the development of Artificial Intelligence (AI) and Internet of Things (IoT) technologies, network communications based on the Shannon-Nyquist theorem gradually reveal their limitations due to the neglect of semantic information in the transmitted content. Semantic communication (SemCom) provides a solution for extracting information meanings from the transmitted content. The semantic information can be successfully interpreted by a receiver with the help of a shared knowledge base (KB). This paper proposes a two-stage hierarchical qualification and validation model for natural language-based machine-to-machine (M2M) SemCom. The approach can be applied in various applications, such as autonomous driving and edge computing. In the proposed model, we quantitatively measure the degree of understanding (DoU) between two communication parties at the word and sentence levels. The DoU is validated and ensured at each level before moving to the next step. The model's effectiveness is verified through a series of experiments, and the results show that the quantification and validation method proposed in this paper can significantly improve the DoU of inter-machine SemCom. © 2024 IEEE.

关键词： Latent semantic analysis

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Can bidirectional encoder become the ultimate winner for downstream applications of foundation models? 2

Can bidirectional encoder become the ultimate winner for dow...

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2nd International Conference on Foundation and Large Language Models, FLLM 2024

作者： Yang, Lewen Zhou, Xuanyu Fan, Juao Xie, Xinyi Zhu, Shengxin BNU-HKBU United International College Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science Zhuhai China

ISBN: (纸本)9798350354799

Over the past few decades, Artificial Intelligence(AI) has progressed from the initial machine learning stage to the deep learning stage, and now to the stage of foundational models. Foundational models have the characteristics of pre-training, transfer learning, and self-supervised learning, and pre-trained models can be fine-tuned and applied to various downstream tasks. Under the framework of foundational models, models such as Bidirectional Encoder Representations from Transformers(BERT) and Generative Pre-trained Transformer(GPT) have greatly advanced the development of natural language processing(NLP), especially the emergence of many models based on BERT. BERT broke through the limitation of only using one-way methods for language modeling in pre-training by using a masked language model. It can capture bidirectional context information to predict the masked words in the sequence, this can improve the feature extraction ability of the model. This makes the model very useful for downstream tasks, especially for specialized applications. The model using the bidirectional encoder can better understand the domain knowledge and be better applied to these downstream tasks. So we hope to help understand how this technology has evolved and improved model performance in various natural language processing tasks under the background of foundational models and reveal its importance in capturing context information and improving the model's performance on downstream *** article analyzes one-way and bidirectional models based on GPT and BERT and compares their differences based on the purpose of the model. It also briefly analyzes BERT and the improvements of some models based on BERT. The model's performance on the Stanford Question Answering dataset(SQuAD) and General Language Understanding Evaluation(GLUE) was compared. © 2024 IEEE.

关键词： Self-supervised learning

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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

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science China(Information sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG Shenzhen Research Institute of Big Data Future Network of Intelligence Institute (FNii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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A reposition algorithm for e-hailing based on quantum annealing and intuitive reasoning

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Intelligent and Converged Networks 2024年第4期5卷 317-335页

作者： Chao Wang Yiyun Shi Sumin Wang Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Information Engineering Ganzhou Key Laboratory of Cloud Computing and Big Data ResearchGannan University of Science and TechnologyGanzhou 341000China

Currently,the challenge lies in the traditional intelligent algorithm’s ability to effectively address the e-hailing repositioning *** identifying the underlying characteristics in extensive traffic data within a limited timeframe is difficult,ultimately preventing the achievement of the most optimal *** paper suggests a hybrid computing architecture involving reinforcement learning and quantum annealing based on intuitive *** reasoning aims to enhance performance in scenarios with poor system robustness,complex tasks,and diverse goals.A deep learning model is constructed,trained to extract scene features,and combined with expert knowledge,then transformed into a quantum annealable *** final strategy is obtained using a D-wave quantum computer with quantum tunneling effect,which helps in finding optimal solutions by jumping out of local suboptimal *** on 400000 real data,four algorithms are compared:minimum-cost flow,sequential markov decision process,hot-dot strategy,and driver-prefer *** average total revenue increases by about 10%and vehicle utilization by about 15%in various *** summary,the proposed architecture effectively solves the e-hailing reposition problem,offering new directions for robust artificial intelligence in big data decision problems.

关键词： intuitive reasoning reinforcement learning quantum annealing

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research on Pricing of data Based on Bi-level Programming Model

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Annals of data science 2024年第4期11卷 1391-1419页

作者： Ding, Yurong Tian, Yingjie School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation at UCAS Beijing100190 China

Effective value measurement and pricing methods can greatly promote the healthy development of data sharing, exchange and reuse. However, the uncertainty of data value and neglect of interactivity lead to information asymmetry in the transaction process. A perfect pricing system and well-designed data trading market (hereafter called data market) can widely promote data transactions. We take the three-agents data market as an example to construct a sound data trading process. The data owner who provides data records, the model buyer who is interested in buying machine learning (ML) model instances, and the data broker who interacts between the data owner and the model buyer. Based on the characteristics of data market, like truthfulness, revenue maximization, version control, fairness and non-arbitrage, we propose a data pricing methods based on different model versions. Firstly, we utilize market research and construct a revenue maximization (RM) problem to price the different versions of ML models and solve it with the RM-ILP process. However, the RM model based on market research has two major problems: one is that the model buyer has no incentive to tell the truth, that is, the model buyer will lie in the market research to obtain a lower model price;the other is that it asks the data broker to release version menu in advance, resulting in an inefficient operation of the data market. In view of the defects of the RM transaction model, we propose a model buyers behavior analysis, establish the revenue maximization function based on different data versions to establish a bi-level linear programming model. We further add the incentive compatibility constraint and the individual rationality constraint, taking the utility of the model buyer and the revenue of the data broker into account. This reflects the consumer driven model in the data transaction mode. Finally, the RM-BLP process is proposed to transform RM problem into an equivalent single-level integer program

关键词： Costs

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Eigen microstate analysis unveils climate dynamics

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science China(Physics,Mechanics & Astronomy) 2025年第4期68卷 91-100页

作者： Hua Tu Shang Wang Jun Meng Yongwen Zhang Xiaosong Chen Deliang Chen Jingfang Fan School of Systems Science/Institute of Nonequilibrium Systems Beijing Normal UniversityBeijing 100875China Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Data Science Research Center Faculty of ScienceKunming University of Science and TechnologyKunming 650500China Department of Earth System Science Tsinghua UniversityBeijing 100084China Department of Earth Sciences University of GothenburgGothenburg 40530Sweden Potsdam Institute for Climate Impact Research Potsdam 14412Germany

The Earth's climate operates as a complex,dynamically interconnected system,driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback *** study employs a theoretical framework and the Eigen Microstate(EM)approach of statistical physics to examine global surface temperature variations since 1948,as revealed by a global *** identified EMs significantly correlated with key climate phenomena such as the global monsoon system,tropical climates,and El Niñ*** analysis reveals that these EMs have increasingly influenced global surface temperature variations over recent decades,highlighting the critical roles of hemispheric differences,land-sea contrasts,and tropical climate fluctuations in a warming ***,we used model simulations from more than 10 Coupled Model Intercomparison Project Phase 6(CMIP6)under three future climate scenarios to perform a comparative analysis of the changes in each EM *** results indicate that under future warming scenarios,tropical climate fluctuations will become increasingly dominant,while traditional hemispheric and monsoonal patterns may *** shift underscores the importance of understanding tropical dynamics and their impact on global climate from a physics-based *** study provides a new perspective on understanding and addressing global climate change,enhancing the theoretical foundation of this critical field,and yielding findings with significant practical implications for improving climate models and developing effective mitigation and adaptation strategies.

关键词： statistical physics nonlinear dynamics complex systems climate change

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Application of meta-learning in cyberspace security:a survey

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Digital Communications and Networks 2023年第1期9卷 67-78页

作者： Aimin Yang Chaomeng Lu Jie Li Xiangdong Huang Tianhao Ji Xichang Li Yichao Sheng Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshan063000China Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and TechnologyTangshan063000China The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and TechnologyTangshan063000China

In recent years,machine learning has made great progress in intrusion detection,network protection,anomaly detection,and other issues in ***,these traditional machine learning algorithms usually require a lot of data to learn and have a low recognition rate for unknown *** them,“one-shot learning”,“few-shot learning”,and“zero-shot learning”are challenges that cannot be ignored for traditional machine *** more intractable problem in cyberspace security is the changeable attack *** a new attack mode appears,there are few or even zero samples that can be ***-learning comes from imitating human problem-solving methods as humans can quickly learn unknown things based on their existing knowledge when *** purpose is to quickly obtain a model with high accuracy and strong generalization through less data *** article first divides the meta-learning model into five research directions based on different principles of *** are model-based,metric-based,optimization-based,online-learning-based,or stacked ***,the current problems in the field of cyberspace security are categorized into three branches:cyber security,information security,and artificial intelligence security according to different ***,the application research results of various meta-learning models on these three branches are *** the same time,based on the characteristics of strong generalization,evolution,and scalability of meta-learning,we contrast and summarize its advantages in solving ***,the prospect of future deep application of meta-learning in the field of cyberspace security is summarized.

关键词： Meta-learning Cyberspace security Machine learning Few-shot learning

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