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Quantitative impacts of meteorology and emissions on the long-term trend of O3 in the Yangtze River Delta(YRD),China from 2015 to 2022

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Journal of Environmental Sciences 2025年第3期149卷 314-329页

作者： Lingxia Wu Junlin An Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science and TechnologyNanjing 210044China

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta(YRD)region and itsmeteorology-related and emission-related have not been systematically *** this study,by using 8-year-long(2015–2022)surface ozone observation data,we attempted to reveal the variation ofmultiple timescale components using the Kolmogorov–Zurbenko filter,and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological *** results showed that the short-term,seasonal,and long-term components accounted for daily maximum 8-hr average O_(3)(O_(3–8)hr)concentration,46.4%,45.9%,and 1.0%,*** meteorological impacts account for an average of 71.8%of O_(3–8)hr,and the YRD’s eastern and northern sections aremeteorology-sensitive *** on statistical analysis technology with empirical orthogonal function,the contribution of meteorology,local emission,and transport in the long-term component of O_(3–8)hr were 0.21%,0.12%,and 0.6%,*** spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest,influenced by the monsoon and synoptic *** central urban agglomeration north and south of the YRD was particularly susceptible to local *** the cities studied,Shanghai,Anqing,and Xuancheng,located at similar latitudes,were significantly impacted by atmospheric transmission—the contribution of Shanghai,the maximum accounting for 3.6%.

关键词： O_(3)Yangtze River Delta(YRD)Kolmogorov-Zurbenko filter Empirical orthogonal function Long-term trend

A Correntropy-Based Echo State Network With Application to Time Series Prediction

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 425-435页

作者： Xiufang Chen Zhenming Su Long Jin Shuai Li the School of information Science and Engineering Lanzhou University IEEE the Hangzhou Institute for Advanced Study University of Chinese Academy of Science

As a category of recurrent neural networks, echo state networks(ESNs) have been the topic of in-depth investigations and extensive applications in a diverse array of fields, with spectacular triumphs achieved. Nevertheless, the traditional ESN and the majority of its variants are devised in the light of the second-order statistical information of data(e.g., variance and covariance), while more information is neglected. In the context of information theoretic learning, correntropy demonstrates the capacity to grab more information from data. Therefore, under the guidelines of the maximum correntropy criterion, this paper proposes a correntropy-based echo state network(CESN) in which the first-order and higher-order information of data is captured, promoting robustness to noise. Furthermore, an incremental learning algorithm for the CESN is presented, which has the expertise to update the CESN when new data arrives, eliminating the need to retrain the network from scratch. Finally, experiments on benchmark problems and comparisons with existing works are provided to verify the effectiveness and superiority of the proposed CESN.

关键词： Correntropy echo state network (ESN) noise time series prediction

A Support Vector Machine(SVM)Model for Privacy Recommending Data Processing Model(PRDPM)in Internet of Vehicles

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Computers, Materials & Continua 2025年第1期82卷 389-406页

作者： Ali Alqarni Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Open networks and heterogeneous services in the Internet of Vehicles(IoV)can lead to security and privacy *** key requirement for such systems is the preservation of user privacy,ensuring a seamless experience in driving,navigation,and *** privacy needs are influenced by various factors,such as data collected at different intervals,trip durations,and user *** address this,the paper proposes a Support Vector Machine(SVM)model designed to process large amounts of aggregated data and recommend privacy preserving *** model analyzes data based on user demands and interactions with service providers or neighboring *** aims to minimize privacy risks while ensuring service continuity and *** SVMmodel helps validate the system’s reliability by creating a hyperplane that distinguishes between maximum and minimum privacy *** results demonstrate the effectiveness of the proposed SVM model in enhancing both privacy and service performance.

关键词： Support vector machine big data IoV privacy-preserving

Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

Antenna Selection Method for Distributed Dual-Function Radar Communication in MIMO System

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Chinese Journal of Electronics 2025年第1期34卷 165-175页

作者： Haitao Zhao Zhongzheng Ding Qin Wang Wenchao Xia Bo Xu Hongbo Zhu College of Communication and information Engineering Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless Communications and Internet of Things Nanjing University of Posts and Telecommunications

Distributed dual-function radar system is an emerging trend in next-generation wireless systems, offering the possibility of improved parameter estimation for target localization as well as improved communication performance. With sufficient resource allocation, the achievable minimum estimated mean square error(MSE) and maximum total communication rate of localization may exceed the intended performance metrics of the system, which may consume an excessive number of antennas as well as antenna costs. In order to avoid resource wastage, this paper proposes a distributed dual-function radar communication multiple-input multiple-output(MIMO) system capable of performing radar and communication tasks simultaneously. The distributed system achieves the desired MSE performance metrics and communication performance metrics by efficiently selecting a subset of antennas, and minimizing the number of transmitting antennas and receiving antennas used in the system as well as the cost. In this paper, the problem is modeled as a knapsack problem where the objective is to obtain the maximal MSE performance and the maximal total communication rate performance at the lowest cost, for which we design a heuristic antenna selection algorithm. The designed algorithm is effective in reducing the time complexity as well as reducing the cost of antenna, and minimizing the number of antennas required.

关键词： Measurement Location awareness Costs Transmitting antennas Receiving antennas Radar Radar antennas MIMO Time complexity Antenna arrays

D-DeepOCSORT: multi-object tracking algorithm based on LiDAR and monocular camera

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Optoelectronics Letters 2025年

作者： HE Xiao REN Shuai LIU Chang SHI Lei School of information Engineering， Chang'an University School of Control of Robotic and Autonomous Systems， University of California Berkeley

Multi-object tracking is a fundamental problem in computer vision， and DeepOCSORT， due to its reliance on the 2D image position information of targets， tends to exhibit prediction drift. To enhance the tracking stability of DeepOCSORT， this paper proposes a novel multi-sensor data fusion-based multi-object tracking method. Specifically， we build upon the DeepOCSORT foundation and additionally integrate target velocity information directly measured by LiDAR. The introduction of this velocity information is conducted from three perspectives: firstly， during data association， a penalty term is constructed based on the differences in target velocities to constrain generating matches with consistent velocities; secondly， using LiDAR velocity for initialization and online updating of the velocity state within the tracker， making tracking predictions more stable; thirdly， controlling the degree of dependence on velocity information by adjusting the process noise covariance matrix. Evaluation results on the KITTI dataset demonstrate that compared to the original DeepOCSORT， the proposed improved multi-source heterogeneous information fusion method significantly enhances tracking performance， with maximum improvements of 3.35， 3.26， and 3.71 on the HOTA， MOTA， and IDF1 metrics， respectively. This study provides an effective approach to building a more stable and accurate multi-object tracking system.

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Variety classification and identification of maize seeds based on hyperspectral imaging method

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Optoelectronics Letters 2025年第4期21卷 234-241页

作者： XUE Hang XU Xiping MENG Xiang College of Optoelectronic Engineering Changchun University of Science and Technology College of Electronic and information Engineering Beihua University

In this study, eight different varieties of maize seeds were used as the research objects. Conduct 81 types of combined preprocessing on the original spectra. Through comparison, Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN) was identified as the optimal preprocessing technique. The competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), and their combined methods were employed to extract feature wavelengths.

关键词： A

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Biisoindolylidene solvatochromic fluorophores: Synthesis and photophysical properties

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Chinese Chemical Letters 2025年第2期36卷 394-399页

作者： Xiaoyu Chen Jiahao Hu Jingyi Lin Haiyang Huang Changqing Ye Hongli Bao College of Chemistry Fuzhou University State Key Laboratory of Structural Chemistry Key Laboratory of Coal to Ethylene Glycol and Its Related TechnologyCenter for Excellence in Molecular SynthesisFujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fujian College University of Chinese Academy of SciencesFuzhou 350002China dUniversity of Chinese Academy of Sciences

Environment-sensitive fluorescent probes are commonly utilized in various fields, including fluorescence sensing and imaging. This paper describes the synthesis and photophysical properties of a novel class of solvatochromic fluorophores that incorporate biisoindolylidene as the core backbone. This study investigates the structure-property relationships of these newly developed fluorophores. The central biisoindolylidene acts as an efficient electron acceptor, and by modifying the aryl ring substituent at the 3,3 position, the photophysical properties of the fluorophores can be significantly enhanced, particularly in terms of photoluminescence quantum efficiency. Furthermore, when an electron-donor group replaces the aryl ring at the 3,3 position, intriguing solvatochromic behavior is observed. This leads to a red-shift in the maximum emission wavelength and an increase in the Stokes shift with increasing solvent polarity. In solvent dimethyl sulfoxide(DMSO), the maximum emission wavelength can reach up to 750 nm,with a Stokes shift of approximately 150 nm. Finally, the potential application of the fluorophore in the detection of volatile acids is explored in a preliminary manner.

关键词： Acid sensitive Biisoindolylidene Electron receptor New fluorophores Solvatochromic