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Smart fiber-optic masks: real-time respiratory monitoring and health analysis

science China(information sciences) 2025年第4期68卷 216-227页

作者： Qi YU Ya-Nan ZHANG Jiaqi ZHANG Shuang YANG Lingxiao JIANG Xuegang LI College of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Affiliated Hospital of North Sichuan Medical College

In this study, we design a smart mask based on an ultrathin retractable flexible fiber optic sensor with high sensitivity(0.56 V/m-1), ultra-light mass（0.24 g）, and excellent tensile properties. The sensor was integrated with a medical mask to recognize multiple breathing patterns（standard, fast, slow, shallow, deep, breath-holding）, coughing, and speaking,as well as to study gender characteristics and physiological differences in the respiratory system. By comparing the nasal-oral respiratory waveforms and frequencies, guidance for respiratory correction was provided. In addition, affixing flexible fiber optic sensors to the outside of the mask reduces the risk of cross-infection and significantly reduces temperature and humidity disturbances. Studies have shown that nine sensor locations placed on the outside of the mask responded significantly to respiratory waveforms. For personalized health management, the system is also equipped with a communication module,web and mobile apps to support data downloads, real-time monitoring, and exception alerts.

关键词： smart mask respiratory monitoring fiber optic sensor health management anti-interference

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Radio Environment Map Reconstruction Via Tensor Completion: Bayesian and Semantic Approaches

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7897-7913页

作者： Wang, Xuegang Wang, Fanggang He, Boxiang Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Frontiers Science Center for Smart High-Speed Railway System School of Electronics and Information Engineering Beijing100044 China

The radio environment map (REM) is one of the representations of the wireless environments, which consists of the spectrum data and enables the users to understand the electromagnetic situation in temporal, spectral and spatial domains. Generally, the observations of the spectrum data are incomplete due to the insufficient acquisition capability, and even the observed ones could be corrupted by some interferences and white noises. In this paper, we model the REM in all domains using the tensor notation, and propose a Bayesian and a deep-learning approaches to complete the spectrum map from the incomplete and corrupted observed spectrum data. In the first approach, by using the Tucker decomposition on the spectrum tensor, a hierarchical Bayesian framework is modeled to characterize the core tensor, the factor matrices, and the other nuisances. These nodes and their distribution parameters serve as the latent variables in the model. The variational Bayesian method is adopted to compute the posterior probabilities in an iterative manner. Regarding the low-rank property and the correlation of the spectrum, an adaptive compressed tensor decomposition algorithm is proposed to denoise the recovered spectral map in each iteration. In the second approach, the spectrum blanks are initialized by the linear interpolation to obtain the initial complete spectrum tensor. We use the Vision Transformer to solve a semantic segmentation problem in order to identify the semantic regions of the spectrum map in which the power of one emitter dominates. Then, the tensor completion is performed in the individual semantic tensor using the proposed compression algorithm. At last, the simulation results show that both the proposed approaches outperform the existing ones. We further observe that the semantic approach outperforms the Bayesian one for the sparse emitter scenarios while the Bayesian approach exhibits better recovery accuracy as the density of the emitters increases in the normali

关键词： Bayesian networks

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A Novel Nectarine Fruit Maturity Detection and Classification Counting Model Based on YOLOv8n

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 144-155页

作者： Ji, Baofeng Zhao, Jingming Tao, Fazhan Zhang, Ji Zhang, Gaoyuan Wang, Nan Zhang, Ping Fan, Huitao Henan University of Science and Technology College of Information Engineering Luoyang471023 China Longmen Laboratory Luoyang471000 China Henan Academy of Sciences Zhengzhou450046 China College of Information Engineering Henan University of Science and Technology Luoyang471023 China Henan University of Science and Technology School of Mathematics and Statistics Luoyang471023 China

Fruit yield assessment is an important aspect of orchard management. In this context, target detection of fruit is of paramount importance. However, due to complex factors in real orchard environments, such as fruit occlusion, insufficient lighting, and overlapping fruits, traditional detection and counting methods often suffer from low detection accuracy and inadequate classification precision, failing to meet the requirements of practical applications. To address this issue, we focus on nectarine fruit and propose an improved YOLOv8n-based object detection algorithm model, YOLOv8n-global feature extraction enhancement (GFE). We integrate the effective squeeze-and-excitation attention mechanism into the YOLOv8n model. This integration allows our approach to adaptively adjust the weight of each channel, which enhances both detection efficiency and target recognition accuracy. Then, we introduce focal distance-intersection over union loss to address the misjudgment of hard samples. This further contributes to improving detection accuracy. In addition, we incorporate the gather-and-distribute mechanism from GOLD-YOLO, replacing the traditional feature pyramid network structure. This enhancement improves the information fusion capability in the neck of the model, leading to a higher mean average precision (mAP@0.5). In addition, the output of the improved model can be used as an input to DEEPSORT to classify and count nectarine fruit. This functionality can be used for estimating fruit maturity and yield in orchards. Experimental results demonstrate that the YOLOv8n-GFE model achieves a mAP@0.5 of 92.5%, which is an improvement of 3.2% over the original YOLOv8n model, meeting the required accuracy for recognizing nectarine fruit maturity in practical applications. © 2023 IEEE.

关键词： YOLO Lighting Feature extraction Attention mechanisms Shape Technological innovation Neck Head Detection algorithms Data models

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Appointed-Time Fuzzy Fault-Tolerant Control of Hypersonic Flight Vehicles With Flexible Predefined Behaviors

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IEEE Transactions on Automation science and engineering 2025年 22卷 13995-14007页

作者： Luo, Ruining He, Guangjun Li, Yulun Bu, Xiangwei Li, Qiuni Air Force Engineering University Air Defense and Antimissile School Xi’an710051 China Chinese Academy of Sciences Key Laboratory of Electronics and Information Technology for Complex Aerospace System National Space Science Center Beijing101499 China Air Force Engineering University Aviation Engineering School Xi’an710051 China

This paper explores a novel fuzzy fault-tolerant control scheme for hypersonic flight vehicles (HFVs) that accounts for parameter perturbations and system disturbances, thereby achieving flexible prescribed properties and designated-time convergence. In contrast to existing studies, this framework incorporates the more detrimental elevator stuck fault within the context of prescribed performance control (PPC). To mitigate the fragility issues associated with PPC in fault-tolerant control, we propose an innovative approach that integrates a fault sensing system along with a readjustment prescribed envelope. This is accomplished by transforming the original HFVs model into an imprecise pure feedback model, allowing for the design of low-complexity fuzzy controllers with minimal model dependence through the utilization of higher-order error functions and fuzzy logic systems. Finally, numerical simulations validate both the effectiveness and superiority of the proposed method. © 2004-2012 IEEE.

关键词： Hypersonic vehicles

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A survey on textual emotion cause extraction in social networks

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Digital Communications and Networks 2025年第2期11卷 524-536页

作者： Sancheng Peng Lihong Cao Guojun Wang Zhouhao Ouyang Yongmei Zhou Shui Yu Laboratory of Language Engineering and Computing Center for Linguistics and Applied Linguistics Guangdong University of Foreign Studies School of English Education Guangdong University of Foreign Studies School of Computer Science and Cyber Engineering Guangzhou University South China University of Technology School of Information Science and Technology Guangdong University of Foreign Studies School of Computer Science University of Technology Sydney

With the rapid development of web technology, Social Networks(SNs) have become one of the most popular platforms for users to exchange views and to express their emotions. More and more people are used to commenting on a certain hot spot in SNs, resulting in a large amount of texts containing emotions. Textual Emotion Cause Extraction(TECE) aims to automatically extract causes for a certain emotion in texts, which is an important research issue in natural language processing. It is different from the previous tasks of emotion recognition and emotion classification. In addition, it is not limited to the shallow-level emotion classification of text, but to trace the emotion source. In this paper, we provide a survey for TECE. First, we introduce the development process and classification of TECE. Then, we discuss the existing methods and key factors for TECE. Finally, we enumerate the challenges and developing trend for TECE.

关键词： Text Emotion Emotion cause Machine learning Deep learning

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Mode transitions in Hall effect thrusters by Varying duty ratio under pulsating operation

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Advances in Space Research 2025年第10期75卷 7466-7472页

作者： Ma, Haochen Zheng, He Liang, Tiance Li, Jiapeng Wei, Liqiu Han, Liang Li, Hong Ding, Yongjie School of Energy Science and Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China Key Laboratory of Aerospace Plasma Propulsion Ministry of Industry and Information Technology Harbin150001 China Beijing Institute of Control Engineering China Aerospace Science and Technology Corporation Beijing100089 China

During the operation of a Hall effect thruster, small changes in discharge voltage, mass flow, or magnetic field cause significant changes in the discharge mode of the thruster. Keeping other working conditions unchanged, the discharge mode of the Hall effect thruster can be triggered by changing the duty ratio. The experimental results show that at different frequencies, a small change in the duty ratio caused a significant increase in the discharge current and discharge oscillation amplitude. When the duty ratio changed from 70 % to 68 % at 90 kHz, the discharge mode changed from high- to low-oscillation mode. The discharge current oscillation decreased from 1.03 to 0.66, and the anode efficiency increased from 24.5 % to 25.8 %. When the duty ratio was changed from 64 % to 58 % at a pulse frequency of 70 kHz, the discharge current oscillation decreased from 1.26 to 0.85, and the anode efficiency increased from 23.5 % to 24.8 %. In the low-oscillation mode, the discharge current and anode voltage of the thruster were at the same frequency, and the discharge oscillation of the thruster was significantly reduced. Furthermore, the Faraday probe measurement results showed that the ion current density distribution of the thruster was more focused. The match between the supply of the working medium and the ionization rate improved the degree of ionization, leading to an improvement in thrust performance. Maintaining the Hall effect thruster in low-oscillation mode is of great significance for improving the reliability of the thruster. © 2025 COSPAR

关键词： Hall thrusters

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Enhanced Neutrosophic Set and Machine Learning Approach for Kidney Disease Prediction

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Neutrosophic Sets and systems 2025年 80卷 465-477页

作者： Al-Doori, Humam M. Alkellezli, Tareef S. Abdelhafeez, Ahmed Eassaa, Mohamed Sawah, Mohamed S. El-Douh, Ahmed A. Cybersecurity Sciences Department College of Science Ashur University Baghdad Iraq Cybersecurity Engineering Department College of Engineering Ashur University Baghdad Iraq Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science Faculty of Information Technology Ajloun National University P.O.43 Ajloun26810 Jordan Cybersecurity Technology Engineering Department College of Engineering Technology Ashur University Baghdad Iraq

Kidney disease (KD) is a gradually increasing global health concern. It is a chronic illness linked to higher rates of morbidity and mortality, a higher risk of cardiovascular disease and numerous other illnesses, and expensive medical expenses. The machine learning (ML) models are applied for KD prediction with higher accuracy and precision. The KD dataset has uncertainty and vague information, so, we used the neutrosophic set (NS) to deal with vague and uncertainty information in the KD dataset. The KD dataset is converted into the N-KD dataset with three membership functions: truth, indeterminacy, and falsity. Three ML models are used in this study such as logistic regression (LR), support vector machine (SVM), and k-nearest neighbor (KNN). These ML models are applied to the N-KD dataset. The results show the LR has higher accuracy and precision on the N-KD dataset than the original KD dataset. © 2025, University of New Mexico. All rights reserved.

关键词： Logistic regression

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Chirp-free hundred-picosecond pulse fiber laser based on carbon nanotubes mode-locker

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Optics Express 2025年第7期33卷 14850-14857页

作者： Li, Weixi Jiang, Kailin Dai, Lilong Huang, Qianqian Zou, Meng Luo, Siyu Chen, Siyu Song, Yingxiong Liu, Yunqi Yan, Zhijun Mou, Chengbo Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute for Advanced Communication and Data Science Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai200444 China School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access System Huazhong University of Science and Technology Wuhan430074 China

We demonstrate a narrow bandwidth passively erbium-doped mode-locked fiber laser based on single-wall carbon nanotubes (SWCNTs). The center wavelength is 1546.61 nm. The strong filtering effect and low saturable absorber (SA) modulation depth provide advantages for a long pulse duration of 323 ps. An overall spectral bandwidth of 1.3 GHz (0.01 nm) is measured by the optical heterodyne method, representing the narrowest spectral width based on SWCNT under a single filter structure. The obtained spectral width is very close to the transform-limited bandwidth of 8 pm, indicating that the pulse is chirp-free. Meanwhile, the generation of beat signals reveals the strong coherence between pulses. The repetition frequency of the laser is 7.8 MHz, and the number of longitudinal mode locks is only 166, which is the minimum number of longitudinal mode-locking in passively mode-locked laser based on material SA. At the same time, numerical simulations further support our experimental results and reveal the pulse evolution, providing evidence that SA and filter are the key factors in the generation of chirp-free long pulse. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Saturable absorbers

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Three-dimensional interconnected carbon nanoreactors with CoP nanocrystals to enhance performance in solar cells

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CrystEngComm 2025年第20期27卷 3257-3266页

作者： Wang, Wen Li, Dan Li, Weidong Fang, Yuanjie Wang, Xiuying Xu, Mingkun Ye, Song Li, Guang School of Electronic Engineering Chaohu University Chaohu238024 China Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511370 China School of Materials Science and Engineering School of Physics and Optoelectronic Engineering Key Laboratory of Structure and Functional Regulation of Hybrid Materials Ministry of Education Anhui Key Laboratory of Information Materials and Devices Institute of Physical Science and Information Technology Anhui University Hefei230601 China

Failure to fully utilize the catalytic activity of electrode materials is a crucial bottleneck under the harsh operating conditions of a high concentration of iodine. Herein, we design an optimized counter electrode (CE) material with a large number of highly dispersed CoP ultrafine nanoparticles (∼10 nm in size) throughout P-doped multi-aperture honeycomb carbon as three-dimensional interconnected nanoreactors. The established 3D porous conductive honeycomb architecture offers a "highway" for accelerating charge and mass transfer, which facilitates the homogeneous distribution of infiltrated iodine and the close interaction between infiltrated iodine and CoP nanoparticles. This constructed structure not only provides a high surface-to-volume ratio to increase the number of exposed catalytic sites but also prevents nanoparticles from aggregating during cycling owing to the pore spatial confinement effect, ensuring the uniform dispersion of CoP, maximum catalytic effect and enhanced iodide ion diffusion. Additionally, the synergistic coupling effects between rich defect interfaces and chemical bonding derived from heteroatom-doping increase the catalytic activity. As a result, the developed CoP@PC catalyst presents superior power conversion efficiency (8.88%), outperforming all the known noble-metal Pt materials (7.82%). Such an unconventional material design offers an attractive and instructive model of high-performance nanomaterial engineering for application in various fields. © 2025 The Royal Society of Chemistry.

关键词： Covalent bonds

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